Technological, Managerial and Organizational Core Competencies: Dynamic Innovation and Sustainable Development

Technological, Managerial and Organizational Core Competencies: Dynamic Innovation and Sustainable Development Farley Simon Nobre Federal University of Parana, Brazil David Walker The University of Birmingham Business School, UK Robert Harris The University of Wolverhampton Business School, UK

Senior Editorial Director: Director of Book Publications: Editorial Director: Acquisitions Editor: Development Editor: Production Editor: Typesetters: Print Coordinator: Cover Design:

Kristin Klinger Julia Mosemann Lindsay Johnston Erika Carter Joel Gamon Sean Woznicki Adrienne Freeland and Christopher Shearer Jamie Snavely Nick Newcomer

Published in the United States of America by Business Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2012 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark.

Library of Congress Cataloging-in-Publication Data

Technological, managerial and organizational core competencies: dynamic innovation and sustainable development / Farley Simon Nobre, David Walker and Robert Harris, editors. p. cm. Includes bibliographical references and index. Summary: “This book investigates the impact of knowledge management, information systems, finance, organizational networks, internationalization, strategic management, marketing, entrepreneurship, and sustainability on an organization that pursues dynamic innovation and sustainable advantage”--Provided by publisher. ISBN 978-1-61350-165-8 (hardcover) -- ISBN 978-1-61350-166-5 (ebook) -- ISBN 978-1-61350-167-2 (print & perpetual access) 1. Knowledge management. 2. Organizational learning. I. Nobre, Farley Simon, 1971- II. Walker, David, 1947 Sept. 1- III. Harris, Robert, 1961 Apr. 21HD30.2.T4235 2011 658.4’038--dc23 2011027029

British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher.

In memory of my Father (1938-2010), who I love and miss dearly, for his constant family support, warm heart, happiness, and brilliant mind, and to my Mother who struggled to educate me, and to Carolina, for her kindness, patience, and love. Farley S. Nobre

Editorial Advisory Board Neil Anderson, Brunel University, UK Thomas Andersson, Jönköping University, Sweden & the Research Council, Sultanate of Oman Glauco Arbix, University of Sao Paulo, Brazil Michael Brown, Birmingham City University, UK Elias G. Carayannis, George Washington University, USA Steven Cavaleri, Central Connecticut State University, USA Erik G. Hansen, Leuphana University Lüneburg, Germany Colette Henry, University of London, UK Yuya Kajikawa, The University of Tokyo, Japan Valentina Lazzarotti, LIUC University, Italy Enrique Leff, Universidad Nacional Autónoma de México, Mexico Caroline Mothe, Université de Savoie, France David L. Rainey, Rensselaer Polytechnic Institute, USA Pedro López Sáez, Universidad Complutense de Madrid, Spain Joanne L. Scillitoe, New York Institute of Technology, USA William H. Starbuck, University of Oregon & New York University, USA Eric Viardot, EADA Business School, Spain

List of Reviewers Oihana Valmaseda Andia, Universidad del País Vasco, Spain Glauco Arbix, University of Sao Paulo, Brazil Theodora Asimakou, London Metropolitan University, UK Andrea Bikfalvi, Universitat de Girona, Spain Adriana Bin, University of Campinas, Brazil Michael Brown, Birmingham City University, UK Luiz Caseiro, University of Sao Paulo, Brazil María Catalina Ramírez Cajiao, Universidad de los Andes, Colombia Milton de Abreu Campanario, University of Sao Paulo, Brazil Gregorio Martín de Castro, Universidad Complutense de Madrid, Spain Jason G. Caudill, Carson-Newman College, USA Steven Cavaleri, Central Connecticut State University, USA Claudio Cruz Cázares, Autonomous University of Barcelona, Spain

Alok K. Chakrabarti, Thapar University, India Javier Alejandro Carvajal Díaz, Universidad de los Andes, Colombia Pilar Fernández Ferrín, Universidad del País Vasco, Spain Diana A. Filipescu, Autonomous University of Barcelona, Spain Sergio Salles Filho, University of Campinas, Brazil Jonas Gabrielsson, Lund University, Sweden Jorge Cruz González, Universidad Complutense de Madrid, Spain Amir Grinstein, Ben-Gurion University of the Negev, Israel Jerald Hage, University of Maryland, USA Erik G. Hansen, Leuphana University Lüneburg, Germany Robert Harris, University of Wolverhampton, UK Colette Henry, University of London, UK Gretchen Jordan, Sandia National Laboratories, USA Milton de Freitas Chagas Junior, Instituto Tecnológico de Aeronáutica, Brazil Yuya Kajikawa, The University of Tokyo, Japan Jose Carlos Korelo, Federal University of Parana, Brazil Valentina Lazzarotti, LIUC University, Italy José Emilio Navas López, Universidad Complutense de Madrid, Spain Patrizia de Luca, University of Trieste, Italy Caroline Mothe, Université de Savoie, France Jonathon Mote, Southern Illinois University, USA M. Elena Aramendia Muneta, Universidad Pública de Navarra, Spain Hiroko Nakamura, The University of Tokyo, Japan Farley Simon Nobre, Federal University of Parana, Brazil José Tiberio Hernández Peñaloza, Universidad de los Andes, Colombia Diamanto Politis, Halmstad University, Sweden Andrew Pollard, University of Wolverhampton, UK, & Caparo Innovation Centre, UK Paulo Henrique Muller Prado, Federal University of Parana, Brazil David L. Rainey, Rensselaer Polytechnic Institute, USA Renata Lèbre La Rovere, Federal University of Rio de Janeiro, Brazil Pedro López Sáez, Universidad Complutense de Madrid, Spain Horst-Hendrik Scholz, The University of Birmingham, UK Javier Amores Salvadó, Universidad Complutense de Madrid, Spain Joanne L. Scillitoe, New York Institute of Technology, USA Danielle Mantovani Lucena da Silva, Federal University of Parana, Brazil Marcello Muniz da Silva, University of Sao Paulo, Brazil Gavin Smeilus, University of Wolverhampton, UK, & Caparo Innovation Centre, UK William H. Starbuck, University of Oregon & New York University, USA Shinji Suzuki, The University of Tokyo, Japan Adriana Roseli Wunsch Takahashi, Federal University of Parana, Brazil Miriam Delgado Verde, Universidad Complutense de Madrid, Spain Eric Viardot, EADA Business School, Spain Valter A. Vieira, Federal University of Parana, Brazil Belén Bande Vilela, Universidad de Santiago de Compostela, Spain David S. Walker, The University of Birmingham, UK

Table of Contents

Foreword by Alan D. Meyer and William H. Starbuck.................................................................... xii Foreword by Colette Henry................................................................................................................ xv Preface.................................................................................................................................................xvii Acknowledgment............................................................................................................................ xxxvii Section 1 Sustainability and Innovation Chapter 1 Environmental Rationality: Innovation in Thinking for Sustainability................................................... 1 Enrique Leff, Universidad Nacional Autónoma de México, Mexico Chapter 2 A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation....................................................................................................................................... 18 David L. Rainey, Rensselaer Polytechnic Institute, USA Chapter 3 Product-Service Systems as Enabler for Sustainability-Oriented Innovation: The Case of Osram’s Off-Grid Lighting................................................................................................ 40 Friedrich Grosse-Dunker, Dark Horse GmbH, Germany Erik G. Hansen, Leupana University Lüneburg, Germany Chapter 4 Innovation for Sustainability in Aviation: World Challenges and Visions............................................. 55 Hiroko Nakamura, The University of Tokyo, Japan Yuya Kajikawa, The University of Tokyo, Japan Shinji Suzuki, The University of Tokyo, Japan Chapter 5 Diffusion and Adoption of Innovations for Sustainability..................................................................... 73 Helen E. Muga, University of Mount Union, USA Ken D. Thomas, Auburn University, USA

Chapter 6 Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage and Firm Performance......................................................................................................... 89 Javier Amores Salvadó, Universidad Complutense de Madrid, Spain José Emilio Navas López, Universidad Complutense de Madrid, Spain Gregorio Martín de Castro, Universidad Complutense de Madrid, Spain Chapter 7 Observe, Conceive, Design, Implement and Operate: Innovation for Sustainability.......................... 105 Javier Alejandro Carvajal Díaz, Universidad de los Andes, Colombia María Catalina Ramírez Cajiao, Universidad de los Andes, Colombia José Tiberio Hernández Peñaloza, Universidad de los Andes, Colombia Section 2 Organizational Networks and Innovation Chapter 8 The Integration of Independent Inventors in Open Innovation........................................................... 131 Gavin Smeilus, University of Wolverhampton, UK & Caparo Innovation Centre, UK Robert Harris, University of Wolverhampton, UK Andrew Pollard, University of Wolverhampton, UK & Caparo Innovation Centre, UK Chapter 9 An Examination of Independent Inventor Integration in Open Innovation......................................... 146 Gavin Smeilus, University of Wolverhampton, UK & Caparo Innovation Centre, UK Robert Harris, University of Wolverhampton, UK Andrew Pollard, University of Wolverhampton, UK & Caparo Innovation Centre, UK Chapter 10 Firm-Specific Factors and the Degree of Innovation Openness.......................................................... 167 Valentina Lazzarotti, Carlo Cattaneo University, Italy Raffaella Manzini, Carlo Cattaneo University, Italy Luisa Pellegrini, University of Pisa, Italy Chapter 11 Effects of Product Development Phases on Innovation Network Relationships................................. 191 Christina Öberg, Lund University, Sweden Chapter 12 Maturity in Innovation Network Management.................................................................................... 203 Caspar Van Rijnbach, TerraForum Consulting, Brazil Gustavo de Boer Endo, TerraForum Consulting, Brazil Suzana Monteiro Leonardi, TerraForum Consulting, Brazil

Chapter 13 Science Parks and their Role in the Innovation Process: A Literature Review for the Analysis of Science Parks as Catalysts of Organizational Networks.................................................. 230 Renata Lèbre La Rovere, Federal University of Rio de Janeiro, Brazil Leonardo de Jesus Melo, Federal University of Rio de Janeiro, Brazil Section 3 Entrepreneurship and Innovation Chapter 14 Entrepreneurial Learning and Innovation: Building Entrepreneurial Knowledge from Career Experience for the Creation of New Ventures..................................................................................... 245 Jonas Gabrielsson, Lund University, Sweden Diamanto Politis, Halmstad University, Sweden Chapter 15 Innovation and Corporate Reputation: Britain’s Most Admired Company Surveys 1990-2009......... 264 Michael Brown, Birmingham City University, UK Paul Turner, Anglia Ruskin University, UK Chapter 16 Natural Resource Dependency and Innovation in the GCC Countries................................................ 278 Thomas Andersson, Jönköping University, Sweden, & The Research Council, Sultanate of Oman Chapter 17 Innovation in Scenario Building: Methodological Advancements and a Foresight Study of the Automotive Industry in Brazil................................................................................................... 302 Ariane Hinça Schneider, Industry Federation of Parana, Brazil Laila Del Bem Seleme, Industry Federation of Parana, Brazil Felipe Fontes Rodrigues, Federal University of Parana, Brazil Marilia de Souza, Industry Federation of Paraná, Brazil Helio Gomes de Carvalho, Federal Technological University of Parana, Brazil Section 4 Knowledge Management and Innovation Chapter 18 Toward a More Pragmatic Knowledge Management: Toyota’s Experiences in Advancing Innovation...................................................................................................................... 327 Steven Cavaleri, Central Connecticut State University, USA Chapter 19 Knowledge and the Politics of Innovation: Insights from a R&D Company...................................... 347 Theodora Asimakou, London Metropolitan University, UK

Chapter 20 Innovation and Knowledge Management for Sustainability: Theoretical Perspectives...................... 365 René J. Jorna, Frisian Academy (KNAW), The Netherlands & University of Groningen, The Netherlands Niels R. Faber, Frisian Academy (KNAW), The Netherlands & University of Groningen, The Netherlands Chapter 21 Dynamic Capabilities and Innovation Radicalness: Review and Analysis.......................................... 384 Jorge Cruz-González, Universidad Complutense de Madrid, Spain José Emilio Navas-López, Universidad Complutense de Madrid, Spain Pedro López-Sáez, Universidad Complutense de Madrid, Spain Miriam Delgado-Verde, Universidad Complutense de Madrid, Spain Section 5 R&D&T Management and Innovation Chapter 22 Research Profiles: Prolegomena to a New Perspective on Innovation Management.......................... 408 Gretchen Jordan, Sandia National Laboratories, USA Jonathon Mote, Southern Illinois University, USA Jerald Hage, University of Maryland, USA Chapter 23 Determinants and Consequences of R&D Strategy Selection............................................................. 428 Diana A. Filipescu, Autonomous University of Barcelona, Spain Claudio Cruz Cázares, Autonomous University of Barcelona, Spain Chapter 24 Institutional Innovation Practices in Technopoles: An Example in France......................................... 450 Anne Berthinier-Poncet, Université de Savoie, France Rachel Bocquet, Université de Savoie, France Sébastien Brion, Université de Savoie, France Caroline Mothe, Université de Savoie, France Chapter 25 Choosing Locations for Technology and Innovation Support Centers: Methodological Proposal and Brazilian Studies.................................................................................. 474 Mário Otávio Batalha, Federal University of São Carlos, Brazil Daniela Tatiane dos Santos, Federal University of São Carlos, Brazil Nelson Guedes de Alcântara, Federal University of São Carlos, Brazil Sérgio Ronaldo Granemann, University of Brasília, Brazil

Section 6 Marketing and Innovation Chapter 26 Taxonomy of Marketing Core Competencies for Innovation.............................................................. 491 Eric Viardot, EADA Business School, Spain Chapter 27 Self Regulation on Innovative Products Choice.................................................................................. 508 Paulo Henrique Muller Prado, Federal University of Parana, Brazil Danielle Mantovani Lucena da Silva, Federal University of Parana, Brazil Jose Carlos Korelo, Federal University of Parana, Brazil Chapter 28 The New Product Development Process as a Communication Web Part I: Introduction, Concepts and Spanish Context....................................................................................... 526 Pilar Fernández Ferrín, Universidad del País Vasco, Spain José Antonio Varela González, University of Santiago de Compostela, Spain Belén Bande Vilela, University of Santiago de Compostela, Spain Oihana Valmaseda Andia, Universidad del País Vasco, Spain Chapter 29 The New Product Development Process as a Communication Web Part II: Analysis of Spanish Firms................................................................................................................... 540 Pilar Fernández Ferrín, Universidad del País Vasco, Spain José Antonio Varela González, University of Santiago de Compostela, Spain Belén Bande Vilela, University of Santiago de Compostela, Spain Oihana Valmaseda Andia, Universidad del País Vasco, Spain Section 7 Finance and Innovation Chapter 30 Innovations and Financing of SMEs Part I: SME Financing and Credit Rationing: The Availability of Funds..................................................................................................................... 555 David S. Walker, The University of Birmingham, UK Horst-Hendrik Scholz, The University of Birmingham, UK Chapter 31 Innovations and Financing of SMEs Part II: Case Study of German SMEs in 2010.......................... 574 David S. Walker, The University of Birmingham, UK Horst-Hendrik Scholz, The University of Birmingham, UK

Section 8 Internationalization and Innovation Chapter 32 The Recent Internationalization of Brazilian Companies.................................................................... 590 Glauco Arbix, University of Sao Paulo, Brazil Luiz Caseiro, University of Sao Paulo, Brazil Chapter 33 R&D Internationalization as Mechanism of Innovation in Global Enterprises: A Brazilian Case Study........................................................................................................................ 619 Simone Vasconcelos Ribeiro Galina, University of Sao Paulo, Brazil Section 9 Information Systems and Innovation Chapter 34 Tools That Drive Innovation: The Role of Information Systems in Innovative Organizations........... 640 Jason G. Caudill, Carson-Newman College, USA Chapter 35 The Roles of Cognitive Machines in Customer-Centric Organizations: Towards Innovations in Computational Organizational Management Networks....................................................................... 653 Farley Simon Nobre, Federal University of Parana, Brazil About the Contributors..................................................................................................................... 675 Index.................................................................................................................................................... 688

xii

Foreword

The editors have assembled this book around the topic of innovation, which they define very broadly. As a happy result of this broad definition, the book comingles the themes of technological innovation, entrepreneurship, and organizing. Usually, scholars have discussed these themes separately, and this separation has probably concealed opportunities for fruitful interdependence among the themes. These are vital themes in economies and in societies more generally, and the themes intertwine. Technological innovation fosters the emergence of new ways of organizing. Advances in Information Technology, for instance, have transformed hierarchical, co-located business organizations into geographically distributed virtual networks. Yesterday’s organizations are turning into “dense spots in networks of contracts between sovereign individuals” (Davis & Marquis, 2005). People can break supply chains apart and distribute work to the most efficient producers wherever they are, and can assemble components wherever customers happen to be located today. The three themes of technological innovation, entrepreneurship, and organizing share a concern with the emergence of new things – new concepts, new forms, new viewpoints. Emergence remains one of the persistent mysteries of science. An irony of Darwinian evolutionary theory is that despite the title of his book, Darwin did not attempt to explain “the origin of species.” His analyses began with established populations, and examined how differential survival led to gradual adaptation within these populations. Contemporary scientists – physicists, chemists, biologists, and social scientists alike – have generally followed Darwin’s example. Scientists avoid studying or even thinking about emergent processes, consigning them to the realms of philosophy and spirituality along with other phenomena evoking faith and magic. However, innovation, entrepreneurship, and organizing are inherently emergent, so scholars who study these topics find it hard to ignore emergence and the interactions that foster emergence. The book itself emerged through an evolutionary process that broke through national and disciplinary boundaries, and drew energy from entrepreneurial editorial activities that extended around the world. The editors and reviewers subjected manuscripts to careful selection processes and the successful manuscripts reflect repeated revisions that improved their clarity and relevance. The editors’ efforts to enlist diverse authors enhance the book’s usefulness. The authors come from many countries. People in different parts of the world see different issues and participate in different discussions, so distinct research topics and findings emerge all around the globe. A book that embraces a wide range of societies and perceptions helps readers to distinguish between observations that are more general and those that are more idiosyncratic. New technologies and organizational forms develop differently, and with experimental adventures over time, so their characteristics are disorderly. Efforts to understand very new technologies and organizational forms have to confront both the heterogeneity of the systems themselves and the researchers’ lack of effective filters for distinguishing important stimuli.

xiii

Observations that are more general are possible because some social trends have been widespread. For instance, throughout the 20th century, the so-called developed countries evolved from agriculture and manufacture toward services, and the latter part of the 20th century brought mounting emphasis on services requiring higher education. A large amount of global dispersion of expert services has been occurring. Companies have not only placed call centers for technical support around the world, they have located research laboratories and engineering design centers around the world. Knowledge-based activities have been at least as mobile as physical work. In the short run, this geographic dispersion increases the relative advantage of social skills over technical expertise. In the longer run, such dispersion undercuts the competitive advantage of knowledge-based activities by making expertise less esoteric. In addition to intermingling technological innovation, entrepreneurship, and organizing, Professors Nobre, Walker and Harris have introduced another more contemporary theme – sustainability. In the book’s Preface, Nobre makes an important distinction between “competitive advantage” and “sustainable development”. “Competitive advantage” is a concept based in economic theories about competitive markets; it stresses the value to individual business firms of distinguishing themselves from their competitors by offering valuable and unusual products or services. However, economists and business scholars have defined competitive advantages solely in terms of the benefits to individual business firms and without concern for effects on consumers, communities, nations, societies, or humanity in general. Nobre introduces the term “sustainable development” to describe a kind of business development that maintains a balance between economic and societal goals and between short-run and long-run goals. This is a timely distinction, since the modern global corporation, a brilliant social innovation that extended benefits of commerce around the globe, has become the world’s dominant social institution – and is helping to drive every living system on the earth into decline. We live in a time when humans are at the very peak of our technological power. We are making changes in the earth that will echo through the centuries. Sustainable development would seek to benefit not only individual firms but also their societies and the future of humanity. Alan D. Meyer University of Oregon, USA William H. Starbuck University of Oregon, USA

REFERENCE Davis, G. F., & Marquis, C. (2005). Prospects for organization theory in the early 21st century: institutional fields and mechanisms. Organization Science, 16(4), 332–343.

Alan Meyer is the Charles H. Lundquist Professor of Entrepreneurial Management at the University of Oregon. Using organizational theory and sociology as theoretical frames, he studies industry emergence, corporate venturing, and technology entrepreneurship. He is a field researcher who triangulates between archival data and primary data gathered through interviews and naturalistic observation. Alan has been a continuous National Science Foundation grantee since 1999. He is a Fellow of

xiv

the Academy of Management, he served as the founding chair of the Managerial and Organizational Cognition Division, and he chaired the Organization and Management Theory Division. Alan has served as Consulting Editor for AMJ and as Associate Editor-in-Chief for Organization Science, and on the editorial boards of Administrative Science Quarterly, the Academy of Management Journal, and Strategic Management Journal. William H. Starbuck is Professor-in-Residence at University of Oregon and professor emeritus at New York University. He has held faculty positions in economics, sociology, or management at Purdue University, Johns Hopkins University, Cornell University, University of Wisconsin-Milwaukee, and New York University, as well as visiting positions in England, France, New Zealand, Norway, Sweden, and the United States. He was also Senior Research Fellow at the International Institute of Management in Berlin. He edited Administrative Science Quarterly, chaired the screening committee for Fulbright awards in business management, directed the doctoral program in business administration at New York University, and was President of the Academy of Management. He has published over 150 articles on accounting, bargaining, business strategy, computer programming, computer simulation, forecasting, decision making, human-computer interaction, learning, organizational design, organizational growth and development, perception, scientific methods, and social revolutions. He has also authored two books and edited 17 books. His latest book, The Production of Knowledge, reflects on lessons from his own academic journey and on the challenges associated with management and social science research.

xv

Foreword

It is now widely acknowledged that innovation drives the knowledge economy, fuelling productivity and growth. It is innovation that essentially underpins successful entrepreneurship, creates jobs and contributes to the sustainable development of economies around the globe. It is not surprising therefore, that the topic of innovation continues to attract increased attention from academics and politicians alike. While earlier literatures depict innovation as ‘creative destruction’ that erodes existing markets and industries (Schumpeter, 1934), more recent commentators refer to innovation in the form of ‘disruptive, radical technologies’ that allow entire markets and industries to emerge, transform or even disappear (Christensen, et el; 1997). Research has also been growing with regard to innovation in the workplace, its link to human resource management and how innovation relates to organizational structures (Scott and Bruce, 2008; West, 2002, as discussed in Foss and Henry, 2010). However, there remains a gap in the literature with regard to the study of innovation in the context of organizational competence building and the identification of key creative areas that can create and drive sustainable innovation processes. In this book the editors have brought together a range of important topics under the heading of Technological, Managerial and Organizational Core Competencies. Nobre, Walker and Harris discuss knowledge management, networks, sustainability, marketing, R&D, Information Systems and internationalization across a range of geographical contexts and organizational settings. Strategically organized in nine sections, the editors combine empirically and theoretically based research contributions from leading commentators around the globe. The diversity of authors providing insights on innovation in different economies highlights the strong international dimension of the book. However, the unique contribution of the book undoubtedly lies in its identification of key creative and typically untapped areas within an organization that can build competencies towards dynamic innovation and sustainable development. Essentially, this book enhances current understanding of the innovation process and platforms its importance as a driver of 21st century entrepreneurship. The book will be of value to those studying and researching the broad field of innovation, particularly as it relates to dynamic organizational processes. The contributions will also be of interest to innovation educators, R&D managers and those working within the general innovation support system. This timely edited text offers a multidisciplinary perspective on innovation, reminding us that innovation is dynamic in nature and highly creative in its origins. Colette Henry University of London, UK

xvi

REFERENCES Christensen, C. (1997). ‘The innovator’s dilemma: When new technologies cause great firms to fail. Boston, MA: Harvard Business School Press. Foss, L., & Henry, C. (2010). ‘Gender and innovation: Exploring the hegemonic voice’, paper presented at the Gender Work and Organization (GWO) Conference, Keele University, 20-23 June. Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press. Scott, S. G., & Bruce, R. A. (2008). ‘Determinants of innovative behavior: A path model of individual innovation in the workplace . Academy of Management, 37(3), 580–607. West, M. A. (2002). Sparkling fountains or stagnant ponds? An integrative model of innovation implementation groups, Applied Psychology: An International Review, 51 (p. 3).

Colette Henry (BA; MBA; PhD; FRSA; FISBE) is the Norbrook Professor of Business & Enterprise at the Royal Veterinary College (RVC), University of London. She also holds visiting professorships at the Universities of Tromsø (Norway) and Birmingham City (UK). A Fellow of the Royal Society for the encouragement of Arts, Manufactures & Commerce (RSA), Colette is also the former President of the Institute for Small Business & Entrepreneurship (ISBE), and was recently awarded a fellowship in recognition of her work. She has been published widely on the topics of entrepreneurship education & training, programme evaluation, women’s entrepreneurship and the creative industries. Her publications include books, edited collections and articles in a range of leading academic journals. Her more recent research focuses on entrepreneurship education and women in veterinary medicine. Colette is also the editor of the International Journal of Gender & Entrepreneurship (IJGE).

xvii

Preface

THE ROLE OF ORGANIZATIONAL CREATIVE AREAS (OCA) IN DYNAMIC INNOVATION: FROM COMPETITIVE ADVANTAGE OF INDIVIDUAL RATIONAL ECONOMICS TOWARDS DEVELOPMENT OF COLLECTIVE SUSTAINABILITY Genesis and Overview: The Organization as Mediator between Entrepreneurs and Innovations This book represents the culmination of an international project to compile multi and inter-disciplinary research that most contributes to innovation. The book’s unifying constructs are innovation and the organization. The organization mediates between entrepreneurs and innovations. This preface presents a brief overview of developments concerning the organization and innovation. Organizations have gradually grown in importance throughout human history. They matured after the Industrial Revolution began in Europe in the 18th century and later spread to the United States of America in the 19th century. The gradual transition from a non-industrial to an industrial society has marked the frontiers between periods of evolution and industrial development of organizations. Here, the term evolution assumes that changes in society are relatively unpredictable, whereas industrial development denotes a more predictable sequence of planned modernization (Richter, 1982). Evolution characterizes processes of organizing in ancient and the Middle Ages civilizations, and the Renaissance supported development of the Industrial Revolution in Europe. Many modern principles of organizing emerged during ancient civilizations (5.000 B.C. - 500 A.C). It is probable that organizing processes began in the family, later extending to the tribe, and finally reaching formalized political units (Wren, 1987). After the fall of the Roman Empire and the emergence of Feudalism in Europe, new principles of organizing evolved as solutions to economic and political crises. An increasing record of writings about organizing characterized the Middle Ages. Nevertheless, economies and societies were essentially static, management practices were still largely antihuman, science was only a philosophical rather than a technological concern, and political values involved unilateral decisions by central authorities. These conditions were unfavorable for developing an industrialized society. Crises in Europe during the 14th and 16th centuries brought a revolution in thinking and culture, together with religious, social, economic and political strife, giving genesis to the Renaissance (Delouche, 2001). The Renaissance brought a new focus on reason, discovery, exploration and science. Overseas expansion of Europe between the 15th and 18th centuries strengthened the confrontation and integration of cultures on different continents and gave birth to Mercantilism. Globalization and a worldwide economy evoked new technologies and more complex principles of organizing. Additionally, there was increasing need and call for practices that could bring ethics to individual liberty and to markets. Political philosophers

xviii

began to disseminate new ideas about equality, reason, justice, the rights of citizens, governance by consent of the people, and decentralized of political power. In the 18th century, new economic theories challenged Mercantilism and the controlling power of the landed aristocracy and initiated the Industrial Revolution. In his Wealth of Nations, Adam Smith (1723-1790) established the classical school of liberal economics and he proposed that only markets and competition should be the regulators of economic activity. The transition from pre to post-industrial organizations was gradual. The transition created new social, economic, technological and political conditions and brought new societal challenges. Continuous advances in science and technology, especially in electricity, energy and information, made possible large combinations of humans and machines, giving origin to new kinds of organizations. Principles of organization and management had to be improved and extended to a new and increasingly dynamic environment. Theories of organizations have developed systematically since the beginning of the 20th century. Organization theorists have advanced in knowledge through the 20th century (Grusky & Miller, 1981; March, 1965; March & Simon, 1958; Pugh, 1997; Nobre, Tobias & Walker, 2009: 236-289; Scott, 1998; Simon, 1997). With advances in capitalism and liberal economics, philosophers, historians, political economists and sociologists proposed opposing ideologies and models of political, economic and social thought. Perhaps, Marxism was the most revolutionary political ideology. Marx and Engels supported the idea that capitalism inevitably produces internal tensions that lead to its collapse or destruction.i This Marxist process has been called Creative Destruction (Reinert & Reinert, 2006: Chapter 4). Later, the concept of Creative Destruction was revisited and popularized by Joseph Schumpeter (McCraw, 2007), and became most associated with his economic development and innovation theory, particularly from his books The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle (1912/1934) and Capitalism, Socialism and Democracy (1942/1950). Despite being sympathetic to Marxian Doctrines, Schumpeter placed entrepreneurship and innovation at the center of his economic development theory. He said destruction, transformation, and renewal of a social-economic system are rooted in entrepreneurs’ decisions and actions that introduce innovations. Therefore, entrepreneurs, and innovations, are core elements that can disturb the equilibrium of any social-economic system and that accelerate economic growth (Schumpeter, 1939). However, to think about innovation, and especially technological innovation, only as synonymous with economic growth is to overlook its broad significance for humanity. While innovation and technology can benefit humans with artifacts that raise living standards (Easterlin, 2000; Johnson, 2000; Tidd, 2006; Tidd, Bessant & Pavitt, 2005), innovation and technology can also have negative results.ii Innovation and technology affect political power (Kipnis, 1990; Scarbrough & Corbett, 1992) and power-holders of innovation and technology can control resources and decisions (Suarez-Villa, 2009). Strongly influenced by the Corporation (Drucker, 1993) and by the hegemonic power of 20th century neo-Corporatism (Hagger, 2004; Suarez-Villa, 2009; Wiarda, 1996), society has entered the 21st century with the strongest desires for capital accumulation ever seen in history. These desires have accelerated environmental degradation and the destruction of natural resources (Leff, 1995). Egocentrism, individualism, and consumerism characterize contemporary society, and a political and economic model of maximization of production and consumption is generating cultural alienation and intense materialism. These have, in turn, destroyed environmental resources and eroded the values and social conditions of humanity (Nobre, Lourenço & Fagundes, 2010). Education and innovation stand out as processes that should be changing human behavior to develop a sustainable future (Dunne & Martin, 2006; Wals, 2009),

xix

and innovation offers a key to sustainability by contributing new alternatives (Hart & Milstein, 2003; Nidumolu, Prahalad & Rangaswami, 2009; Rainey, 2006). One day, organizations, nations and executives may be able to perceive and act based on models grounded in systemic sustainability. These new models will have to reconcile environmental, social and economic demands (Gladwin, Kennelly & Krause, 1995; Korten, 2006) - the “three pillars” of sustainability defined by The United Nations General Assembly during the World Summit Outcome, in 2005. Organizations and their participants, especially entrepreneurs, will have to create dynamic innovation and competitive advantages without disrupting the balance needed for survival of the human species (Nobre, Tobias & Walker, 2010:391).

Objectives: What the Book is About Chapters in this book address many recent theories and practices on innovation. The book contemplates economic, social, political, educational and environmental facets of innovation through technological, managerial and organizational perspectives. More specifically, this book is about innovation in firms, industries, nations and society. It speaks to professionals and researchers who want to improve their understanding of dynamic innovation and sustainable development. Chapters contribute answers to questions on: • • • • • • • • •

What are the roles (and contributions) of Sustainability in (for) Innovation? What are the roles (and contributions) of Organizational Networks in (for) Innovation? What are the roles (and contributions) of Entrepreneurship in (for) Innovation? What are the roles (and contributions) of Knowledge Management in (for) Innovation? What are the roles (and contributions) of R&D&T (Research, Development and Technology) Management in (for) Innovation? What are the roles (and contributions) of Marketing in (for) Innovation? What are the roles (and contributions) of Finance in (for) Innovation? What are the roles (and contributions) of Internationalization in (for) Innovation? What are the roles (and contributions) of Information Systems in (for) Innovation?

Key Concepts of the Book In this book, innovation involves processes, organizational elements (or resourcesiii), and Organizational Abilities (OA)iv that support the production and transformation of knowledge into new knowledge, processes, structures, technologies and products, goods and services. At the firm and industry levels of analysis, innovation can provide organizations with strengths relative to other firms, clusters, and nations and it is a key source of customer benefits and sustainable development. At the collective and societal levels of analysis, innovation can provide humanity with economic, social and environmental wealth through sustainable development. The uniqueness of this book lies in the participants’ efforts to identify Organizations’ Creative Areas (OCA) that can provide core competencies for the organization in pursuit of dynamic innovation and sustainable development. In this perspective, innovation is a dynamic system and it is contingent upon a set of core competencies that couple to each other. Therefore, changing of even one competence can affect the organization’s ability to innovate.

xx

Core competencies develop within Organizations’ Creative Areas (OCA) that include Sustainability, Organizational Networks, Entrepreneurship, Knowledge Management, R&D&T (Research, Development and Technology) Management, Marketing, Finance, Internationalization, and Information Systems. Core competencies are valuable and unique from a customer’s point of view, and also inimitable and non-substitutable from a competitor’s point of view (Prahalad & Hamel, 1990). Core competencies can represent collective knowledge that develops through learning and that provide strengths relative to other organizations (Nobre, Tobias & Walker, 2010; Nobre & Walker, 2011). The term dynamic refers to capacity of the organization to create new competencies and to adapt to the changing business environment (Teece, 2007). The concept of competitive advantage refers both to the position that a firm occupies in its competitive environment and the firm’s ability to create superior value for its customers and superior profits for itself (Porter, 1998). The organization can sustain competitive advantage by developing strategic resources and core competencies (Lei, Hitt & Bettis, 1996). Although some chapters in this book support this economic concept of competitive advantage, that concept makes assumptions about economic supremacy that separate humanity from ecological and social developments. Therefore, this Preface avoids the term competitive advantage and adopts a more fruitful perspective of sustainable development–“the process of achieving human development … in an inclusive, connected, equitable, prudent, and secure manner” (Gladwin, Kennelly & Krause, 1995). An inclusive perspective sees traditional competitive advantage as occupying one extreme, whereas truly sustainable development occupies the opposite extreme. Sustainable development must benefit not only the organization and its customers, but also the whole society and the future of humanity through sustainability.v Most chapters of this book fall between these extremes.

The Dynamic Model Figure 1 portrays innovation as interacting with the Organization’s Creative Areas (OCA). In this Figure, the Organization’s Creative Areas [OCA-(1…9)] include Sustainability (Sus.), Organizational Networks (ON), Entrepreneurship (Ent.), Knowledge Management (KM), Research, Development and Technology (R&D&T) Management, Marketing (Mar.), Finance (Fin), Internationalization (Int.), and Information Systems (IS). Figure 2, adapted from (Nobre & Walker, 2011), portrays the organization in pursuit of dynamic innovation and sustainable development. This model’s functional processes can be summarized as follows: •

•

•

First, the organization interacts with the environment through its Organization’s Creative Areas (OCA) and Organizational Abilities (OA) for acquisition, exchange, processing, creation, storage, renewal, distribution and employment of resources. By these processes, the organization evolves and improves its own abilities of cognition, intelligence, autonomy, learning and knowledge management. Second, the Organization’s Creative Areas (OCA) and Organizational Abilities (OA) manage strategic resources, and, consequently, develop the organization’s core competencies. Improvements in strategic resources as well as in core competencies can feed back and provide improvements in the Organization’s Creative Areas (OCA) and Organizational Abilities (OA). Third, internal and external stimuli can affect the Organization’s Dynamic Innovation and Sustainable Development (ODISD), and, consequently, changes in ODISD activate the

xxi

Figure 1. Organization’s Creative Areas (OCA)

Figure 2. Dynamic Innovation Model

Organization’s Creative Areas (OCA) and Organizational Abilities (OA), thus starting new cycles of sustainable development. Processes (1) to (3) repeat continuously to reduce environmental uncertainty and to improve the Organization’s Creative Areas (OCA), Organizational Abilities (OA), strategic resources, core competencies and the Organization’s Dynamic Innovation and Sustainable Development (ODISD).

xxii

Target Audience This book is most relevant to researchers, students and executives interested in future organizations that pursue dynamic innovation and sustainable development. The technological, managerial and organizational background addressed in this book can be applied in different levels of academic and industrial research, including: • • •

Research programs of undergraduate and post-graduate levels. Lectures of undergraduate and post-graduate courses. Industrial and business research projects of firms of any size.

Due to the multidisciplinary scope of this book, the editors are suggesting some schools and courses where the book can be useful. These are: • •

Schools of: Business Administration, Management, Information Systems, Organization Theory, Social Sciences, Economics, Sociology, Philosophy, Education, Technology, and Engineering. Courses on: Innovation; Organizational, Managerial and Technological Innovation; R&D and Technology Management; Organizational Theory, Organizational Learning; Knowledge Management, Information Systems, Finance, Organizational Networks, Internationalization, Strategic Management, Marketing, Entrepreneurship, and Sustainability.

The book offers readers a multidisciplinary perspective on dynamic innovation, and most importantly, challenges readers to explore new frontiers between innovation and Sustainability, Organizational Networks, Entrepreneurship, Knowledge Management, R&D&T (Research, Development and Technology) Management, Marketing, Finance, Internationalization, and Information Systems. Organizations of today confront increasing levels of environmental complexity and uncertainty (Nobre, Tobias & Walker, 2010) that demand new processes of organizing. Sustainable development, at the firm, industry, nation and societal levels, depends on new economic, social and environmental analyses. This book contributes by presenting theoretical and empirical findings for mastering, analyzing and integrating technological, managerial and organizational perspectives that identify core competencies of future organizations. The subject of dynamic innovation raises new challenges for researchers. Organizational, managerial and technological principles of the past and present have contributed successful applications in many areas of organizations and society. However, the world is changing, new processes of organizing are continuously emerging, and methods that proved successful in the past may not provide the right tools for addressing problems of the future. Participants in this book hope to provide readers with very exciting insights about how innovation can create a better future.

Book Structure and Chapters Synopsis The Editors’ goal is to foster cross-pollination among researchers. To this aim, the Editors have selected and assembled chapters that illustrate multidisciplinary theoretical perspectives and empiric results on innovation and the roles of Sustainability, Organizational Networks, Entrepreneurship, Knowledge Management, R&D&T (Research, Development and Technology) Management, Marketing, Finance,

xxiii

Internationalization, and Information Systems in the organization that pursues dynamic innovation and sustainable development. The book’s structure involves these major sections: • • • • • • • • •

Section 1: Sustainability and Innovation Section 2: Organizational Networks and Innovation Section 3: Entrepreneurship and Innovation Section 4: Knowledge Management and Innovation Section 5: R&D&T Management and Innovation Section 6: Marketing and Innovation Section 7: Finance and Innovation Section 8: Internationalization and Innovation Section 9: Information Systems and Innovation

Section 1 on Sustainability and Innovation Subsumes Seven Chapters In Chapter 1, “Environmental Rationality: Innovation in Thinking for Sustainability”, Leff proposes perspectives and concepts for a model of environmental rationality for the construction of a sustainable society. He argues that “rationality of modernity has limited capacities to reestablish the ecological balance of the planet, while environmental rationality opens new perspectives to sustainability: the construction of a new economic paradigm based on neguentropic productivity, a politics of difference and an ethic of otherness. The problem to be approached is that of understanding the unsustainability of the established, dominant and hegemonic ways of constructing the world we live in: that of economic, scientific and technological rationality which organizes the actual world order. Humanity needs to think about the possibilities of deconstructing this dominant rationality, constructing and putting into social action a new social order: a new agreement with nature based on environmental rationality”. In this prominent treatise, Leff concludes that innovation in thinking is a need, if not a must, for sustainability. In Chapter 2, “A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation”, Rainey presents the foundations of a conceptual model for connecting the key elements necessary for corporations to adopt sustainability in the context of the global economy and strategic innovation. He explains “while sustainability involves many perspectives, strategies, actions, and management constructs, the chapter focuses on how global corporations employ strategic innovations in response to the driving forces in the global economy and how they can improve their level of management sophistication in a turbulent business environment”. One of the Rainey’s conclusions is that the model provides a framework for creating win-win outcomes that are balanced in terms of the social, political, economic, technological, environmental and ethical forces. In Chapter 3, “Product-Service Systems as Enabler for Sustainability-Oriented Innovation: The Case of Osram’s Off-Grid Lighting”, Große-Dunker and Hansen emphasize the role of innovation for addressing sustainability as well as the role of sustainability as a source for innovation, whereas they propose that Product-Service System (PSS) represents an important approach for both perspectives. Große-Dunker and Hansen start by presenting an exploratory research strategy to further investigate the links between Sustainability-Oriented Innovation (SOI) and Product-Service System (PSS); and they go through a case study on off-grid lighting in Kenya and analyze the sustainability effects on the product and Product-Service System (PSS) level.

xxiv

In Chapter 4, “Innovation for Sustainability in Aviation: World Challenges and Visions”, Nakamura, Kajikawa, and Suzuki collect and analyze the latest experts’ talks from four international meetings on Aviation and the Environment in the period between September 2009 and May 2010. The talks in the international meetings were led by experts and researchers from Japan, Europe, and North America; and they had the aim of discussing technological innovation, policies, and economic measures that could contribute to mitigate the global aviation impact to climate change, such as the adoption of low-carbon technologies. The authors explain that only 1% of the world population has flown yet and that there will be a great increasing rate of this percentage in the next years, which makes it very difficult to suppress the impact of aviation on climate change. Moreover, they suggest future research directions. In Chapter 5, “Diffusion and Adoption of Innovations for Sustainability”, Muga and Thomas primarily investigate theory and concepts of sustainability and why they are important to innovation and vice-versa. They discuss in detail some key reductionist approaches to assessing sustainability such as Life Cycle Assessment (LCA), Life Cycle Cost Analysis (LCCA), and sustainability indicators and they also apply these approaches to an engineering infrastructure scenario. The authors explain “the integrated sustainability methods of LCA and LCCA enable a business to assess alternative products or processes at the planning and design stages. These methods may also be used during the production stages to assess whether a business needs to use a different raw material to make their products”. The chapter also contributes by explaining the roles of management, social network analysis, and mental models of individuals in the diffusion and adoption of innovations. In Chapter 6, “Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage and Firm Performance”, Salvadó, Navas-López, and Castro provide special emphasis on the relationship between businesses and natural environment. They argue that the inclusion of environmental criteria into business activities can promote the creation of new core competencies, offering a creative and innovative perspective to the organization that can lead to the achievement of competitive advantages. In this investigation, the authors analyze the existence of a direct relationship between Environmental Innovation and Firm Performance and the existence of an indirect relationship between the two, which highlights the mediating role of the kind of competitive advantage generated. Among the chapter’s main findings: 1) the authors explain the nature of Environmental Innovation through the Social Innovation perspective and therefore they contribute by considering some key aspects of administrative and technological innovations that have not been taken into account in the academic literature; 2) they analyze the different types of environmental innovations in order to understand and describe the strategic options in the environmental field; 3) and they conclude that Environmental Innovation is related to business performance. Finally, they explain that the practical implications of this previous relation are of great importance, since it directly influence the choice of the type of environmental strategy, allowing the company to choose from innovative strategies (based on pollution prevention) or more conservative strategies (emissions control). In Chapter 7, “Observe, Conceive, Design, Implement and Operate: Innovation for Sustainability”, Carvajal Díaz, Ramírez Cajiao, and Hernández Peñaloza present a learning model that can be applied by academics and professionals in the development of innovations. The model draws upon the engineering education cycle of Observe, Conceive, Design, Implement and Operate (OCDIO). The authors start their chapter by reviewing curricula and learning activities in some world-class universities in order to understand the contribution of state-of-the-art education models for the creation of competences for innovation. Afterwards, they introduce the Observe, Conceive, Design, Implement and Operate (OCDIO) model and explain that sustainability comes from following the OCDIO cycle continuously. In such a

xxv

proposal, the authors argue that the OCDIO model contributes for the sustainability of the innovation, but not specifically for the creation of solutions and promotion of innovations that subsume the three pillars of economic, social and environmental sustainability. Nevertheless, the OCDIO model as well as other leaning cycles such as Problem-Based Learning (PBL) can be followed to reach innovations which attend such sustainability triple-constraints. Furthermore, the authors use the OCDIO framework to analyze innovations in Colombia as well as case studies in the Universidad de los Andes.

Section 2 on Organizational Networks and Innovation Subsumes Six Chapters In Chapter 8, “The Integration of Independent Inventors in Open Innovation”, Smeilus, Harris, and Pollard explain that “whilst current academic literature points to the growing importance of Open Innovation as a means of companies capturing new products from sources other than internal R&D facilities; the integration of independent inventors, a source of innovative new products, within Open Innovation has proven challenging”. The authors present a series of preliminary Critical Success Factors, driven by current academic literature, that are intended to contribute to independent inventors becoming more successful suppliers of new product ideas to businesses, with the intention that adherence to such factors may have a positive influence on the effectiveness of open innovation. The chapter also provides the necessary introduction and background to the understanding of the next chapter. In Chapter 9, “An Examination of Independent Inventor Integration in Open Innovation”, Smeilus, Harris, and Pollard take the preliminary critical success factors proposed in the previous chapter and utilize them as priori constructs as evidence is sought through case study for their presence or nonpresence in a practical context. A case study on the Caparo RightFuel, an automotive device originating from an independent inventor and commercialized through an Open Innovation model, forms the basis of the chapter. In Chapter 10, “Firm-Specific Factors and the Degree of Innovation Openness”, Lazzarotti, Manzini, and Pellegrini investigate the topic of how open innovation is actually implemented by companies, according to a conceptual approach in which open and closed models of innovation represent the two extremes of a continuum of different openness degrees; whereas, these are not the only two possible models. By means of a survey conducted among Italian manufacturing companies, this chapter sheds light on the many different ways in which companies open their innovation processes. Four main models emerge from the empirical study and they are investigated in depth in order to understand the relationship between a set of firm-specific factors (such as size, R&D intensity, sector of activity, company organization) and the specific open innovation model adopted by a company. In Chapter 11, “Effects of Product Development Phases on Innovation Network Relationships”, Öberg starts by explaining that “in the research literature, product development has frequently been associated with four distinct phases: introduction, growth, maturity, and decline. While these phases have been related to and used for the study of product life cycle, market strategies and competition, less or no attention has been given to the subject of Innovation Network Relationships (INRs), and more specifically, to whether and how INRs are affected by these Product Development Phases (PDPs)”. Based on a literature review of Resource Dependence Theory (RDT) and four case studies, this chapter contributes by discussing how various INRs are affected by PDPs of an innovative firm. Findings include: (i) the specific needs and resource dependence by the innovative firm during different PDPs affect the status of the firm’s INRs, whereas new relationships are built and old ones are finished; (ii) during product development, the INRs become increasingly complex where network parties become negative resources

xxvi

of the innovative firm through increased uncertainty being introduced into previous relationships; and (iii) the development of INRs cannot be captured on a dyadic level, but various parties’ relationships with one another need to be considered. In Chapter 12, “Maturity in Innovation Network Management”, Van Rijnbach, de Boer Endo, and Leonardi aim to contribute to a better understanding of how innovation networks work and how to develop them. They start by reviewing the concept of network management and by explaining the principal attributes that impact the formation and optimization of innovation networks, based on the network’s objectives, the combination of the characteristics of the network’s participants as well as the network’s organizational format to attract and maintain the partnership. To reach the chapter’s aim, the authors present the results of a benchmark study undertaken in Brazil, the United States of America and Europe between March and June 2009. In this study, they interviewed executives at 24 leading companies known as innovators in their industry. Findings by the authors showed that some common good practices exist among companies when it comes to open innovation management. They concluded that, although some practices partly depend on the company’s industry or Research, Development and Innovation (R&D&I) investment levels, many practices are common and their use depends on the company’s level of maturity regarding open innovation networks. As a result of their investigation, the authors derive and propose a maturity model for open innovation, based on four dimensions: strategic, relational, support and organization. In Chapter 13, “Science Parks and their Role in the Innovation Process: A Literature Review for the Analysis of Science Parks as Catalysts of Organizational Networks”, La Rovere and Melo investigate the contributions of Science Parks (SPs) to innovation. In particular, the authors discuss whether the literature on innovation and SPs considers the fact that SPs can be catalysts of Organizational Networks (ONs). The authors consider that ONs are elements of knowledge production and can contribute to the development of core competencies to pursue dynamic innovation and competitive advantage. The chapter is based on literature review of scientific papers and theses on SPs and their contributions to innovation, which are included in indexed databases. Preliminary analysis of the literature shows that SPs have been mostly studied as part of innovation systems, and that less attention has been given to the role of ONs and SPs in the processes of technological learning and innovation.

Section 3 on Entrepreneurship and Innovation Subsumes Four Chapters In Chapter 14, “Entrepreneurial Learning and Innovation: Building Entrepreneurial Knowledge from Career Experience for the Creation of New Ventures”, Gabrielsson and Politis explain that the relation between entrepreneurial learning and innovation has been poorly understood, especially with respect to how entrepreneurs build up their capability to create new ventures. In this chapter, the authors employ arguments from theories of experiential learning to examine the extent to which entrepreneurs’ prior career experience is associated with entrepreneurial knowledge that can be productively used in the new venture creation process. They relate entrepreneurial knowledge to two distinct learning outcomes: the ability to (i) recognize new venture opportunities, and (ii) cope with liabilities of newness. Based on analysis of data from 291 Swedish entrepreneurs, they provide novel insights into how and why entrepreneurs differ in their experientially acquired abilities in different phases of the new venture creation process. In Chapter 15, “Innovation and Corporate Reputation: Britain’s Most Admired Company surveys 1990-2009”, Brown and Turner explain that The Britain’s Most Admired Company surveys into cor-

xxvii

porate reputation includes nine characteristics, one of these is a company’s capacity to innovate. They also explain that, “surveys between 1990 and 2009 show that a good reputation for innovation does not guarantee a good overall reputation; nor does a reputation for innovation lead to business success. However, where a company has a reputation for innovation and is able to manage other characteristics, there is a better chance that this company will develop its innovation capability into long-term competitive advantage and profitability. Central to this conclusion is converting innovation into enhanced processes, products or services through effective implementation”. The chapter also contributes by identifying key attributes of companies that combine a reputation for innovation, with a good corporate reputation overall and business success. In Chapter 16, “Natural Resource Dependency and Innovation in the GCC Countries”, Andersson explains that, “whether the current strong performance displayed by the Gulf Cooperation Council (GCC) countries proves sustainable for the long term will cast new light on the extent to which natural resource abundance can be turned into a blessing, rather than a curse, and then the requirements for that”. Andersson’s chapter synthesizes new evidence on the conditions for innovation in these economies, including through examination of innovative performances at firm level, collected through the first Community Innovation Survey (CIS) carried out in the GCC countries. Whereas strengths are recorded in some respects, e.g., Information and Communication Technology (ICT), education and some conditions for start-up activity, challenges remain in others, including with regard to governance. The chapter ends with recommendations what further action is required to enable better conditions for innovation both in the natural resource sector itself, and broadly in the economy. In Chapter 17, “Innovation in Scenario Building: Methodological Advancements and a Foresight Study of the Automotive Industry in Brazil”, Schneider, Seleme, Rodrigues, de Souza, and de Carvalho extend and apply a prospective scenario building methodology over a long-range forecasting (up to 2020) for the analysis of market and innovation potentials of the automotive industry of the Metropolitan Region of Curitiba (MRC); whereas the MRC is located in the state of Paraná in southern Brazil and is home to an automotive sector, which plays a major role in the local and national economy. The sources of data in the study include literature review, document analysis, direct observation, semi-structured interviews and two rounds of questionnaires. Results of the study provided the players, stakeholders and entrepreneurs with a clearer managerial view of the industry’s future and also suggested that the proposed methodology can be applied to other industries in future studies.

Section 4 on Knowledge Management and Innovation Subsumes Four Chapters In Chapter 18, “Toward a More Pragmatic Knowledge Management: Toyota’s Experiences in Advancing Innovation”, Cavaleri contributes by examining how pragmatic principles used by Toyota can achieve superior innovation results. The chapter concludes by explaining why the pragmatic approach delivers superior performance at lower cost than conventional knowledge management methods. In Chapter 19, “Knowledge and the Politics of Innovation: Insights from a R&D Company”, Asimakou discusses the relationship between knowledge management and innovation; and specifically, she examines how knowledge in organizations affects the creation of new knowledge and what the implications are for innovation management. The chapter’s core argument is that in a knowledge-based company, where competition is assessed at the edge of rare expertise and the development of innovations, knowledge, which is always interwoven with power, becomes a precious resource, on the grounds of which struggles are inevitably enacted over its control. To support such an argument, the chapter

xxviii

discusses two innovation mechanisms in two business groups of a major oil company. The study uses a set of qualitative techniques for data collection (in-depth interview, participant observation, documentary analysis) and a sample of 41 employees that represent the groups participating in the innovation game (manager, scientists, assistant scientists, administration staff and students). From the results, the author concludes that two mainstream innovation management approaches (the rational planning and the cultural approach) have shaped the understanding and actions of the Business Groups in setting up the innovation mechanisms; however, power struggles at the individual, group and organizational level impacted upon the innovation processes to the extent that the latter became passive technical solutions. In Chapter 20, “Innovation and Knowledge Management for Sustainability: Theoretical Perspectives”, Jorna and Faber explain that “innovation is a special case of knowledge management; it is about knowledge creation. With economic profit as its driving force, innovation is mostly short term and commercial, feeding the question whether innovation really can be applied to ecological and social systems. The problem concerns the goal of innovation: what does it suppose to realize?” From such constraints, the authors propose the study of a combination of Knowledge Management (KM) and innovation concepts with sustainability and they argue that as long as the emphasis in innovation is on ‘profit’ and not on ‘people’ and ‘planet’ (the three P’s of sustainability) there is no guiding mechanism for innovation, namely the existence of a sustainable future. They also explain that “in a sustainable perspective, innovation becomes an instrument that benefits society at large”. Based on these perspectives and literature review, the authors contribute along three lines of thinking: (i) by demonstrating that innovation is knowledge creation at an individual and collective level; (ii) by explaining that innovation should be a means and not a goal; (iii) and by offering a perspective to define the relationship between knowledge, innovation and sustainability. The authors conclude the chapter by introducing concepts on Knowledge of Sustainability (KoS) and Sustainability of Knowledge (SoK), and they set the outline of a framework for sustainable innovation. In Chapter 21, “Dynamic Capabilities and Innovation Radicalness: Review and Analysis”, CruzGonzález, Navas-López, López-Sáez, and Delgado-Verde provide theoretical analyses on the determinants of firm’s innovation radicalness (the degree of novelty incorporated in an innovation) from a dynamic capabilities-based view of competitive advantage. The authors start by reviewing the many literature facets and concepts of dynamic capabilities. From such a review, they argue that dynamic capabilities (or second order capabilities) arise from the firm’s orientation or ability for knowledge exploration that can result in the creation of new organizational capabilities (first order capabilities). By deepening on this exploratory learning argument, they also suggest that external knowledge acquisition and internal knowledge combination are key components of dynamic capabilities.

Section 5 on R&D&T (Research, Development and Technology) Management and Innovation Subsumes Four Chapters In Chapter 22, “Research Profiles: Prolegomena to a New Perspective on Innovation Management”, Jordan, Mote, and Hage explain that “despite the increasing importance of the management of research for innovation, the range of differences among types of research, as well as projects and programs, are not adequately captured in current theories of either project or organizational innovation”. In this chapter, the authors offer preliminary discussions for a new perspective about alternative styles of management for different types of research, whether basic, applied, product development, manufacturing, quality control or marketing. Based on these discussions, the chapter proposes a framework for a new perspec-

xxix

tive of innovation management, called Research Profiles, which is derived from a literature review and extensive field research. This new perspective delineates four research profiles on the basis of two dimensions of research objectives and two dimensions of research tasks. In matching the research objectives and tasks, the authors identify inherent dilemmas that managers must address and this developing perspective suggests appropriate some research management approaches. In Chapter 23, “Determinants and Consequences of R&D Strategy Selection”, Filipescu and Cázares explain that “nowadays firms are not able to achieve all innovation in-house due to the specific set of technologies required by most products and processes, obliging firms to access external knowledge”. In this chapter, the authors contribute to the knowledge on firm innovating behavior by: (i) analyzing the determinants of the selection of the “Research and Development (R&D) Strategy” (all abbreviated by RDS), considering the make, buy and make-buy as the three RDS types; (ii) and also analyzing the consequences that each of the RDS types has on firm innovativeness. Results show that commercial and organizational resources, jointly with the information sources, influence the selection of the strategy. As for the second part of the analysis, the authors see that all RDS types have positive effects on firm innovative performance but these effects are not straightforward and simple since they vary depending on firm’s type and on the radicalness of the innovation. In Chapter 24, “Institutional Innovation Practices in Technopoles: An Example in France”, BerthinierPoncet, Bocquet, Brion, and Mothe contribute by filling a void in the literature on the question on whether organizational proximity can be fostered within clusters. With the objective to gain new insights into institutional practices and to evaluate their effects on firms’ innovation performance, the authors address a dimension that has received little attention until recently, which is named the local governance structures of technopoles. They explain that by identifying how geographical and organizational (cognitive and relational) proximity interrelate in the analysis of cluster forms, the chapter seeks to contribute to the burgeoning literature on the different types of proximity. For such a purpose, the authors performed an empirical research that was based on a representative sample of 88 firms implanted within the Savoie Technolac technopole, in the French Rhône-Alpes region. The results suggest that, even though local governance contributes to territorial anchoring, only the local labor market has a direct significant impact on the firms’ innovation performance. Additionally, it was found that territorial anchoring combined with the roles played by governance in terms of ‘matchmaking’ and support for technology transfer significantly increased the number of innovation projects. The authors emphasize that “these results suggest that governance has a decisive role in the creation of communication and interaction structures between firms, which are essential for firm innovation”; and that, “this research may have important implications for governance modes, not only in technopoles, but also more generally in clusters”. In Chapter 25, “Choosing Locations for Technology and Innovation Support Centers: Methodological Proposal and Brazilian Studies”, Batalha, Santos, Alcântara, and Granemann discuss problem-solving issues of location of Technology and Innovation Support Centers (TISC) through multi-criteria analyses in order to identify demand and supply factors of these services. The authors use quantitative and qualitative methods to establish a sequence of steps that include a variety of aspects ranging from criteria preferences to global valuation of the model. Multi-criteria analysis is applied to the choice of geographic locations for Brazilian Technology Centers; this analysis contributes to identify the most suitable or preferable regions for the creation of technology centers as well as to reveal particular characteristics of the dynamics of such services in the regions in question.

xxx

Section 6 on Marketing and Innovation Subsumes Four Chapters In Chapter 26, “Taxonomy of Marketing Core Competencies for Innovation”, Viardot argues “there is a lack of taxonomy of the various marketing capabilities that are necessary to achieve the market success of innovation”. Therefore, the author tries to fill this gap by proposing a model that subsumes two classes of Marketing Core Competencies (MCC) for successful innovative companies. The first category of core competencies is related to a superior ability of the firm to identify and to connect the actual market needs with the innovation during the preparation of the new product launching phase. Once the innovation is on the market, a second group of core competencies is associated with the capacity of the firm to ease the customers’ tensions in order to facilitate the acceptance of the innovation and turn it into a market success through adoption and diffusion. In conclusion, the chapter underlines the importance of the place of these two categories of Marketing Core Competencies (MCC) in innovative firms. In Chapter 27, “Self Regulation on Innovative Products Choice”, Prado, Lucena da Silva, and Korelo explore how choice goals influence consumers’ innovativeness in a product category domain. They explain that “intentions to adopt new products are guided by promotion and prevention self-regulation systems”. Therefore, in the investigation of the chapter, two of the choice goals were classified as promotion goals – justifiability and choice confidence – and two were classified as prevention goals – anticipated regret and evaluation costs. Two groups emerged from the analysis: one named “most innovative” and another called “less innovative”. The authors explain that “when comparing the groups, the results show that the most innovative cluster demonstrated higher choice confidence, higher justifiability and was more capable of avoiding a possible choice regret. The differences found in the group analysis highlight the need of understanding in further detail how consumers behave during the choice process of innovative products. Therefore, the Regulatory Focus Theory has been shown to be very important for understanding the choice process, especially for the innovation adoption”. In Chapter 28, “The New Product Development Process as a Communication Web – Part I: Introduction, Concepts and Spanish Context”, Fernández, Varela, Bande and Valmaseda contribute with the existing literature by analyzing the innovation activities of Spanish companies and by proposing New Product Development (NPD) as a communication Web. Based on literature reviews, the authors propose a model that relates the external communication of cross-functional teams to the performance of NPD programs. The composition of NPD teams and the external communication activities form the core competencies for companies and they can provide them with major competitive advantages. The chapter also provides the necessary introduction and background to the understanding of next chapter. In Chapter 29, “The New Product Development Process as a Communication Web – Part II: Analysis of Spanish Firms”, Fernández, Varela, Bande and Valmaseda extend the investigation in the previous chapter by applying structural equations analysis in order to compare the model to a sample of 136 managers from different functional areas at 121 innovative Spanish firms. The authors explain that “the results indicate that the impact of explanatory variables on new product programme performance differs according to the measure of performance considered. The cross-functional nature of NPD teams, the presence of product champions in NPD teams and the gathering of information by all NPD team members were all shown to positively influence new product performance. Firms should be aware of the importance of the aforementioned variables”.

xxxi

Section 7 on Finance and Innovation Subsumes Two Chapters In Chapter 30, “Innovations and Financing of SMEs - Part I: SME Financing and Credit Rationing [The Availability of Funds]”, Walker and Scholz describe various financing options and give rationales for the credit rating process and credit conditions building the base for financing decisions. Furthermore, by discussing the topic of ‘Credit Rationing’, the authors demonstrate the impact of credit conditions on management decisions in order to justify the rationing of credits. This chapter also provides the necessary introduction and background to the understanding of next chapter. In Chapter 31, “Innovations and Financing of SMEs - Part II: Case Study of German SMEs in 2010”, Walker and Scholz describe traditional and non-traditional financing opportunities for SMEs in Germany by focusing on its applicability. They explain that “the disclosure of financial business information and giving a say to an equity financier is a difficult topic for owners of Small and Medium-sized Enterprises (SMEs), because these companies are often run as a ‘one-man-show’ (by a single manager) and this person identifies itself with the company. The request for external funds is in that perspective still regarded as a disability of a business to be self-financed. A comparison of the organizational structure of a SME and that of a Large Scale Enterprise (LSE) reveals the structural weaknesses in terms of research and development (R&D) activities. While LSE have an extra department, budget and procedures to develop product and process innovations similarly to a knowledge push, in SMEs, innovations are often originated from customers - similarly to a need pull process. Furthermore, CEOs and customer contribute to a great extend to innovations in SMEs (BDI, 2010). The results of an online-based survey presented in the BDI-Mittelstandspanel 2010, show that less than 13% of innovations are originated by external scientists, R&D organizations and consultants. This proves that external R&D sources (to compensate missing internal resources and structures) are rarely employed; impeding or slowing down the development of innovations”.

Section 8 on Internationalization and Innovation Subsumes Two Chapters In Chapter 32, “The Recent Internationalization of Brazilian Companies”, Arbix and Caseiro explain that “the recent wave of internationalization among Brazilian companies differs from past experiences, in terms of volume, reach, destination and quality. Brazilian multinationals are not restricting their activities solely to regional markets, nor are their first steps entirely directed towards South America. In amount of investment and number of subsidiaries there are signs they prefer assets and activities in advanced markets – including Europe and North America - where they compete on an equal footing with major conglomerates for a share of these markets. Some Brazilian companies have previous internationalization experience, and a significant portion had been prepared and initiated outward growth in the 1990s, after the economy opened up. However, the boom of internationalization that began in 2004 took place in such unusual conditions as to deserve highlight and special analysis”. The authors contribute by discussing the recent expansion of Brazilian multinationals as a result of: (i) the functioning of a more responsive and targeted system of financing, (ii) transformation of the Brazilian productive structure, which led to the emergence of a group of companies seeking internationalization as a strategy, (iii) preference for seeking more advanced economies as a means to expand access to new markets and suppliers, as well as to absorb innovations and technology, (iv) the State’s performance in several dimensions, especially in financing the implementation of policies that support the creation of large national groups with a presence in the globalized market.

xxxii

In Chapter 33, “R&D Internationalization as Mechanism of Innovation in Global Enterprises: A Brazilian Case Study”, Galina explains that “internationalization of Research and Development (R&D) allows transnational companies (TNC) to access different and important resources overseas, which may lead to the improvement of their technological innovation. The literature in this field was mostly created from studies of TNCs coming from developed countries”. In this chapter, Galina contributes by presenting some of the main topics the literature addresses on R&D internationalization, and which are used to explore and to verify how companies in developing countries internationalize their R&D activities. In order to do so, the author conducted a bibliographic review about strategies of internationalization of TNC operations, as well as motivating factors and management of R&D internationalization. The chapter finishes presenting a case study about international R&D conducted in a Brazilian TNC. The results enabled to evidence that, like developed countries TNCs, developing coutries companies also seem to perform internationalization of R&D activities with very similar characteristics.

Section 9 on Information Systems and Innovation Subsumes Two Chapters In Chapter 34, “Tools That Drive Innovation: The Role of Information Systems in Innovative Organizations”, Caudill examines computer technology as a tool to support innovation and innovative processes. The author explains that the primary problem addressed in the chapter is the multitude of widely held misconceptions that seem to exist regarding technology and innovation; whereas technology is not innovative in and of itself. The chapter contributes by examining how technology is being successfully integrated into innovative processes in industry through literature review and case study methods. Specifically, this chapter focuses on the role of technology in communication and creativity, two of the many activities found in an innovative process. Findings indicate that while directly connecting technology use to innovation is difficult, technology can play a substantial role in facilitating the innovative process. Thus, the author concludes that “technology is a qualifier for many innovative processes, a resource that is necessary for the work of innovation to take place”. In Chapter 35, “The Roles of Cognitive Machines in Customer-Centric Organizations: Towards Innovations in Computational Organizational Management Networks”, Nobre proposes innovative features of future industrial organizations in order to provide them with the capabilities to manage high levels of environmental complexity in the 21st century. For such a purpose the author introduces the concept of Computational Organization Management Networks (COMN), which represents new organizations whose principles of operation are based on the concepts of Hierarchic Cognitive Systems (HCS) along with those of Telecommunications Management Networks (TMN). Structured with functional layers and cognitive roles that range from technical and managerial to institutional levels of analysis, and also equipped with operational, managerial and strategic processes, the concept of Computational Organization Management Networks (COMN) plays an important part in the developments of future organizations where cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise. It is in such a context that the new organization COMN will provide customers and the whole environment with innovations such as immersiveness for the production of services and goods that are most customer-centric.

xxxiii

REFERENCES Baird, F. E. (2010). Philosophic Classics: From Plato to Derrida (6th ed.). Upper Saddle River, NJ: Prentice Hall. Delouche, F. (2001). Illustrated history of Europe. Cassell Paperbacks, Cassell & Co. Drucker, P. (1993). Concept of the corporation. Transaction Publishers. Dunne, D., & Martin, R. (2006). Design thinking and how it will change management education: An interview and discussion. Academy of Management Learning & Education, 5(4), 512–523. doi:10.5465/ AMLE.2006.23473212 Easterlin, R. A. (2000). The worldwide standard of living since 1800. The Journal of Economic Perspectives, 14(1), 7–26. doi:10.1257/jep.14.1.7 Gladwin, T., Kennelly, J., & Krause, T. (1995). Shifting paradigms for sustainable development: Implications for management theory and research. Academy of Management Review, 20(4), 878–907. Grusky, O., & Miller, G. (1981). The sociology of organizations: Basic studies. The Free Press. Hagger, N. (2004). The syndicate: The story of the coming world government. O Books. Hart, S. L., & Milstein, M. B. (2003). Creating sustainable value. The Academy of Management Executive, 17(2), 56–67. doi:10.5465/AME.2003.10025194 Hitt, M. A., Ireland, R. D., & Hoskisson, R. E. (2008). Strategic management: Competitiveness and globalization, Concepts and cases. South-Western College Pub. Johnson, D. G. (2000). Population, food, and knowledge. The American Economic Review, 90(1), 1–14. doi:10.1257/aer.90.1.1 Kipnis, D. (1990). Technology and power. New York, Berlin: Springer-Verlag New York Inc. Korten, D. C. (2006). The great turning: From empire to earth community. San Francisco, USA: BerrettKoehler Publishers. Leff, H. (1995). Green production: Toward an environmental rationality. New York, NY: Guilford Press. Lei, D., Hitt, M. A., & Bettis, R. (1996). Dynamic core competences through meta-learning and strategic context. Journal of Management, 22(4), 549–569. doi:10.1177/014920639602200402 March, J. G. (1965). Handbook of organizations. Rand McNally & Company. March, J. G., & Simon, H. A. (1958). Organizations (1st ed.). John Wiley & Sons, Inc. McCraw, T. K. (2007). Prophet of innovation: Joseph Schumpeter and creative destruction. Cambridge, London: Belknap Press of Harvard University Press. Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation. Harvard Business Review, (September): 57–64.

xxxiv

Nobre, F. S., Lourenço, M., & Fagundes, G. (2010). Education for sustainable management: A perspective of constructivism. International Conference on Education for Sustainable Development (EDS-2010). May 18-20th. Curitiba-PR, Brazil: FIEP-PR. Nobre, F. S., Tobias, A. M., & Walker, D. (2009). Organizational and technological implications of cognitive machines: Designing future Information Management Systems. New York/Hershey, USA: Information Science Reference, IGI Global. Nobre, F. S., Tobias, A. M., & Walker, D. (2010). A new contingency view of the organization: Managing complexity and uncertainty through cognition. Brazilian Administration Review, 7(4), 379–396. doi:10.1590/S1807-76922010000400005 Nobre, F. S. & Walker, D. (2011). A dynamic ability-based view of the organization. International Journal of Knowledge Management, 7(2), (to appear in March 2011). Porter, M. E. (1998). Competitive advantage: Creating and sustaining superior performance. Free Press. Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91. Pugh, D. S. (1997). Organization theory: Selected readings. Penguin Books. Reinert, H., & Reinert, E. S. (2006: Chapter4). Creative destruction in economics: Nietzsche, Sombart, Schumpeter. In J. G. Backhaus & W. Drechsler (Eds.), Friedrich Nietzsche (1844-1900) Economy and Society. Berlin/Heidleberg, Germany: Springer Science+Business Media, LLC. Ribeiro, D. (1970). The culture – Historical configurations of the American peoples. Current Anthropology, 11(4-5), 403–434. doi:10.1086/201144 Ribeiro, D. (2000). The Brazilian people: The formation and meaning of Brazil. University Press of Florida. Richter, M. N. (1982). Technology and social complexity. State University of New York. Scarbrough, H., & Corbett, J. M. (1992). Technology and organization - Power, meaning and design. Routledge. Schumpeter, J. A. (1912/1934). The theory of economic development: An inquiry into profits, capital, credit, interest and the business cycle. London, UK: Oxford University Press. Schumpeter, J. A. (1939). Business cycles: A theoretical, historical, and statistical analysis of the capitalist process. New York, London: McGraw-Hill. Schumpeter, J. A. (1942/1950). Capitalism, socialism and democracy. London, UK: Unwin. Scott, W. R. (1998). Organizations: Rational, natural, and open systems. Upper Saddle River, NJ: Prentice Hall. Simon, H. A. (1997). Administrative behavior: A study of decision-making processes in administrative organizations. The Free Press.

xxxv

Suarez-Villa, L. (2009). Technocapitalism: A critical perspective on technological innovation and corporatism. Philadelphia, PA: Temple University Press. Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. doi:10.1002/smj.640 Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. doi:10.1002/(SICI)1097-0266(199708)18:7<509::AIDSMJ882>3.0.CO;2-Z Tidd, J. (2006). From knowledge management to strategic competence – Measuring technological, market and organizational innovation (2nd ed.). Imperial College Press. Tidd, J., Bessant, J., & Pavitt, K. (2005). Managing innovation: Integrating technological, market and organizational change (3rd ed.). John Wiley & Sons, Ltd. Wals, A. (2009). Review of Contexts and Structures for Education for Sustainable Development Learning for a Sustainable World 2009 - Learning for a Sustainable World. United Nations Decade of Education for Sustainable Development (DESD, 2005-2014). UNESCO: www.unesco.org/education/desd. WCED. (1987). World commission on environment and development. Our common future. Oxford, UK: Oxford University Press. Wernerfelt, B. (1995). The resource-based view of the firm: Then years after. Strategic Management Journal, 16(3), 171–174. doi:10.1002/smj.4250160303 Wiarda, H. J. (1996). Corporatism and comparative politics: The other great “ism”. Armonk, NY: M. E. Sharpe. Wren, D. A. (1987). The evolution of management thought (3rd ed.). John Wiley and Sons.

ENDNOTES

i

ii



iii



Just as capitalism replaced feudalism, Marx and Engels believed socialism would, in its turn, replace capitalism, and lead to a stateless, classless society called pure communism (Baird, 2010). Consider for instance the expansion of Europe between the 15th and 18th centuries, which was empowered by the dominance of the colonizers in navigation and army technologies. Their overseas discoveries and actions brought about a revolution in the history of humanity, resulting in good, but also negative and controversial results of political, economic, religious, and social facets for the new world (Delouche, 2001; Ribeiro, 1970, 2000). Resources can be associated with tangible and intangible assets that contribute to the production system in the organization (Hitt, Ireland & Hoskisson, 2008). This book expands this definition to the perspective that resources are organizational elements that involve social structure, goals, technology and participants (Scott, 1998: 17-22). These resources can be employed at the technical, managerial, institutional and worldwide levels (Nobre, Tobias & Walker, 2009: 47-49) by the organization through the use of the organizational abilities for the development of the core competencies, and, consequently, for the creation of dynamic innovation and sustenance of the

xxxvi

iv

v





organization’s development. In such a perspective, the organization manages its resources with basis on its strategy. Moreover, the organization interacts with the environment for the acquisition, processing, creation, distribution, employment and management of new strategic resources. Cognition, intelligence, autonomy, learning and knowledge management represent the set of organizational abilities (Nobre, Tobias & Walker, 2010). These abilities have an important role in the deployment and management of the organization’s strategic resources and they also represent sources of development of the organization’s core competencies (Nobre & Walker, 2011); whereas this perspective is based on the strategic context of the resource-based view (Wernerfelt, 1995) along with dynamic capabilities of the firm (Teece, 2007; Teece, Pisano & Shuen, 1997). Sustainability means the ability to meet the needs of the present without compromising the ability of future generations to meet their needs (WCED, 1987).

xxxvii

Acknowledgment

In the role of Editors (Farley S. Nobre, David S. Walker, and Robert J. Harris), we would like to thank all the participants in this international book. The process of invitation and selection of the participants started in January of 2010 and finished in February of 2011, resulting 35 accepted chapters. We could account about five hundred invitations approximately! We sent Calls for Proposals and Full Chapters directly to Professors and Graduate Students of well-known worldwide Universities, Firms and Institutions as well as to researchers who are the authors of recent published papers by well-known international journals on the subjects of the book. The selection process of chapters was characterized as vast and strictly competitive since it was based on a system of blind-reviews and technical criteria of evaluation. Therefore, we are very pleased to thank the Authors, the Editorial Advisory Board (EAB) Members, the Reviewers, and the Publisher for their interest, diligent work and contribution in this international project. In particular, we are indebted to Professor William H. Starbuck (University of Oregon and New York University, USA), Alan Meyer (University of Oregon, USA), and Colette Henry (The Royal Veterinary College, University of London, UK) due to their contribution in the writing of the Forewords. We also express an inestimable gratitude for Professor William H. Starbuck who supported Farley S. Nobre in the constructive discussion and writing of Preface. We are pleased to acknowledge the authors and EAB members of the book, and in particular to whom has served this book with distinguished blind-reviews and important recommendations which most contributed to improve the overall quality of the project. We also would not forget to acknowledge all the IGI Global staff due to their attention and services provided in this publication, and specially, we are very grateful to Mr. Joel Gamon who continuously supported our questions and advised on this publication. Finally, we are grateful to our affiliation institutions: Federal University of Parana (Brazil), The University of Birmingham (UK), and The University of Wolverhampton (UK). Farley Simon Nobre Federal University of Parana, Brazil David Walker The University of Birmingham Business School, UK Robert Harris The University of Wolverhampton Business School, UK

Section 1

Sustainability and Innovation

1

Chapter 1

Environmental Rationality:

Innovation in Thinking for Sustainability Enrique Leff Universidad Nacional Autónoma de México, Mexico

ABSTRACT Renovating our thinking as humankind (rethinking nature, culture and development) is an imperative to approach the challenges of environmental crisis and to orient the social construction of a sustainable world. If environmental crisis is a predicament of knowledge, beyond the task of reinventing science, innovating technology and managing information, we must face the challenge of inventing new ways of thinking, organizing and acting in the world; of reorienting our ethical principles, modes of production and social practices for the construction of a sustainable civilization. Innovation for sustainability is drawn by alternative rationalities. I will argue that rationality of modernity has limited capacities to reestablish the ecological balance of the planet, while environmental rationality opens new perspectives to sustainability: the construction of a new economic paradigm based on neguentropic productivity, a politics of difference and an ethic of otherness. Paramount to this purpose is the contribution of Latin American Environmental Thinking.

INTRODUCTION Since Antiquity, the cosmic, natural, biological and social order, have been conceived as an ongoing process of “emergence”. Thus, metaphysics thought ontology as the “generativity of physis” DOI: 10.4018/978-1-61350-165-8.ch001

and Darwinian biology thought nature as the evolution of life forms. Innovation became the core concept of such emergence in the modern social order, as a result of the Enlightenment of Reason that intended to brighten the darkness of the Middle Ages, to bring transparency to reality through true knowledge, to make conscious the unconscious and to enlighten the human soul. In-

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Environmental Rationality

novation is in the heart and at the roots of modern rationality; it is what mobilizes progress as a self-contained process within the rationality that produced it. Thus, innovation became a mecanism inbuilt in economic rationality for the continuous renovation of the conditions of production and the unlimited expansion of the economy with the purpose of granting to humanity the well being promissed by modernity. Modernity is thus defined as the era of progress, of development, of novelty that ages and is renewed in unprescedented forms, in an infinite process that demands unendless creativity and that gears the rationalization of social organization towards its ends through unlimited growth. Thus unquestionned, innovation was inscribed and institutionalized in economic rationality; it was embodied in our mode of thinking and imbedded in our mode of production, until it reached the limits of nature and of human life. The environmental crisis unveiled the unsustainable trends of the economic process: the entropic death of the planet, the erosion of living forms, the degradation of life supporting ecosystems and the fading out of the meaning of life. Can this crisis of modernity be solved by the “reflexion of modernity” over its theoretical and scientific foundations, over its technological and instrumental means: by revolutions of science and management of positive knowledge; by innovations in technology and developments in social organization? Is ecological and complex thinking an emergence that can innovate and ecologysze a new world order? Is environmental rationality a new conception of human life on Earth that can guide the social construction of a sustainable future? The purpose of this chapter is to reflect on the key importance of innovating in the ways of thinking our place as human beings in our living planet (our thinking on nature, culture and development) to be able to face the challenges of environmental crisis and to orient the social construction of a sustainable world. If environmental crisis is at its origins and its basis a crisis of knowledge, we 2

should not only promote innovations in science, knowledge management, technological change and behavioural shifts, but we must derive new ways of thinking the world, new ethical principles and new forms of knowing to orient new modes of production and social practices for the construction of a sustainable civilization. That is what environmental rationality intends to offer to the world in crisis (Leff, 2001, 2006). Innovation of knowledge has been established in the economic world order and in the social system as an already in-set mechanism that produces novelties triggered by a mode of thinking that is “developed” in the way that science is finalized by technology as the maturing of its theoretical principles leading to their technical applications for the solution of socio-economic problems (Böhme et al., 1976); or the wy in which Bachelard thought of the new rationalism as the incorporation of the conditions of the application of a concept in the sense of the concept itself (Bachelard, 1949). Thus the real economy is the expression of economic rationality: a world system revolving in its same axis and closed in itself. If knowledge is thus geared and oriented by its internal motives and the inertia of its trends towards the growth of the economic system, then, to what extent can scientific revolutions and technological innovation readapt to the ecological conditions imposed by the laws of nature and cultural meanings to open civilization to a truly sustainable world order? This impasse in the self-reflection of modernity over its own matrix of rationality leads us to inquire if a change of rationality is needed and if such a novelty in human history is possible. We should ask ourselves if a sustainable future can be contained in the dialectical trascendance of the present world already inscribed in in the becoming of Being drawn by the destiny of the techno-economic rationality that organizes the present world order challenged by environmental crisis and unsustainanbility, or if new thinking can bring about and open new paths towards the construction of a sustainable world order.

Environmental Rationality

The problem to be approached is that of understanding the unsustainability of the established, dominant and hegemonic ways of constructing the world we live in: that of economic, scientific and technological rationality that organizes the actual world order; to think the possibilities of deconstructing this dominant rationality and of thinking, putting into social action and constructing a new social order: a new agreement with nature based on environmental rationality.

SUSTAINABILITY, RATIONALITY AND THE SELF-REFLECTION OF MODERNITY The transition to sustainability is a social challenge demanding “innovative thinking”. However, tackling innovation for sustainability implies a clarification of concepts. Sustainability has irrupted as an unexpected emergence in our consciousness, our discoursiveness and our ethics; our social organization and dayly practices. Sustainability has become an imperative for survival –for the reconstruction of the relations of nature with culture– and as a search of new meanings for life. But, how is innovation embedded in rationality? We may define rationality as the complex order of social procceses, as a system of rules of thought and behaviour established within economic, political and ideological structures that legitimize and orient social actions and give meaning to society as a whole. These rules and structures guide social practices and processes towards certain ends, through socially constructed means, which in turn reflect in moral norms, cultural beliefs, institutional arrangements and modes of production. Rationality is thus organized in 3 main orders of rationality: 1. Formal and theoretical rationality that organizes the conscious control of reality through the construction of abstract concepts that constitute rational orders and cosmo-

visions that rule the modes of production and juridical rules that rationalize de World lives of the people. 2. Instrumental and practical rationality (zweckrationalität), that organizes the methodical pursue of certain practical and predetermined ends through the precise calculation of efficient means. 3. Substantive rationality, that organizes social actions based on value principles, which vary in their internal content, comprehensiveness and consistence; these values are irreducible to a scheme of relations between ends and efficient means. Substantive rationality internalizes cultural diversity, axiological relativity and social conflict in the face of different values and interests (Weber, 1978). The challenges of sustainability call for many different areas of innovation: innovation in theory and science from where new paradigms are emerging: environmental and ecological economics, the science of climate change, systems theories, energy saving systems and clean production technologies, etc. Dematerialization of production calls for innovation in production processes through eco-efficiency to optimize the amount of matter that enters the productive process and is degraded in its “throughput”; to minimize the entropic degradation of energy in the extraction, industrial transformation, agricultural production, recycling of waste, and in the consumption processes involved in the overall metabolism of nature. Thus, new areas of innovation are emerging within the prevailing rationality of modernity, in what mainstream sociology denominates “reflective modernity” (Beck, Giddens & Lash, 1997). Reflective modernity calls for a reorganization of the social system in order to ensure its stability and sustainability: that is for the ecological reestructuring and refunctioning. However, a difference must be established between the various theoretical and practical areas of innovation activated by “reflective modernity” for the transi-

3

Environmental Rationality

tion towards sustainability. Here different forms of creativity are involved, from novelty in live forms emerging from the technological intervention in biological organization and anthropogenically induced environmental changes, to creativity in the realm of thought: from scientific paradigm shifts and methodological innovations to cultural changes and social reorganization. Reflective modernity intends to activate and make use of different philosophical sources and scientific and technological resources to solve the socio-environmental problems generated by modernity, by the cultural imprint and the ecological footprint generated by the application of knowledge within its prevalent rationality. This “reflective” process certainly has generated an enormous outburst of innovations: for conservation ecology, energy saving technologies, green production systems, economic instruments for environmental management. These innovations are currently inscribed in a new geopolitics of sustainable development (Kyoto Protocol, Clean Development Mechanism, economic valuation of environmental goods and services, including carbon sinks). In the academic litterature, the term innovation has arisen from the entrepreneural and managerial world, as the creative application of knowledge to production. Novelties in thinking (schools of thought or philosophical traditions) are seldom conceived as “innovations”. In the field of science, changes of paradigms are refered to as scientific revolutions, rather than innovations in knowledge (Kuhn, 1962). It would seem even more awkward to refer to cultural changes as innovations –even those induced by the technoeconomic intervention on nature, such as cultural changes from forced adaptations to climate change; the emergence of new entities (cyborgs), hibrids of organic, technological and symbolic orders in the “reinvention of nature” (Haraway, 1991); or the reinvention of identities resulting from cultural strategies to readapt to the processes of globalization.

4

Innovation most clearly refers to the application of knowledge to new ways of reorganizing an already objectified and rationalized world, from the application of its scientific principles and technological developments, to process management and product design, rather than to the breakthrough of ideas of new modes of thinking, of understanding the creativeness of nature and the reinvention of cultural identities. Innovation can be defined as the purposeful organization of knowledge for the production of new means for the efficient management of processes, guided by the principles of instrumental rationality. Thus, sustainable development, as an emergent social goal, has triggered a broad array of innovative processes in science and technology. Innovation is by essence and definition technological, managerial and organizational novelties brought about by applying knowledge through creative thinking to new problem-solving areas, to make processes more efficient, to use new materials, to apply new methods. In this sense, sustainable development is a global goal that involves and activates changes in scientific and technological paradigms, in patterns of production and consumption behaviours. Knowledge has become a tradable good and as such, subject to innovation drawn by economic purposes and not by a pure epistemophilic drive. Innovation of knowledge became the objective of managing the optimal harmonization of the productive factors, of guiding entrepreneurship for financing and marketing tradable goods where knowledge and information systems have become strategic means of production. Thus, the management of knowledge has become the “basis of the technological, managerial and organizational core competencies of the organization in the pursuit of dynamic innovation and sustainable competitive advantage.” Innovation is the creative processes involved in producing something new, especially something useful and with economic value. Innovation brings emergent and even radical and revolutionary

Environmental Rationality

changes in production organization: a new good, a new technology, new production systems and commercialization methods. However, following Schumpeter (1934), the scholarly literature on innovation distinguishes between invention –an idea made manifest– and innovation –ideas applied successfully in practice. Innovation in the field of economics implies the production of new organizing methods and technologies that increase economic value. Innovation leading to increased productivity, through research and development, is the fundamental source of wealth in an economy. Invention is the embodiment of a new idea. It is the outcome of research or practical inventiveness that can be embodied in a paradigm shift that reorganizes knowledge, or a new prototype or design that is patentable. Inventions become innovations when they are “developed” and put to use effectively in a new social, economic or commercial reorganization. Innovation involves creativity, but not all outputs of human creativity are innovations. Innovation involves acting on the creative ideas to make some specific and tangible difference in the objectified reality, resulting in new or altered processes within the economic organization, or changes in the products and services provided. Through these varieties of viewpoints, creativity is seen as the basis for innovation, and innovation as the successful implementation of creative ideas within an organization. An innovation can be distinguished from an invention or a scientific discovery by the fact that an innovation is defined by an applicative perspective. The scientific enterprise intends to discover the internal workings of reality; theory uncovers the organization of the real. Through theoretical models and empiric experimentation, science constructs the laws that rule the functioning of the world: reality. Innovation in the economy and in technology is not an act of discovery, but of application and reordering of available knowledge of the World to generate a novelty. From the generativity of matter, to epigenesis in the evolution of nature, to ordering from chaos (Prigogine

& Stengers, 1984), the novelties emerging from Nature can be distinguished from the discoveries of science and the inventiveness of culture; from the creativeness of art, the productiveness of economy, the innovations of technology and the originality of design. Innovations are productions that because of their novelty can be registered as property rights. Although creative thinking is claimed to be universal knowledge, with the progress of technoscientific knowledge and its application to the workings of the economy, these innovations have become patented and tradable knowledge, thus distinguishable from scientific and philosophical knowledge, as well as other forms of knowledge and wisdom which have a more intrinsic value. However, with the over-economization of the modern world these traditional or non-marketable forms of knowledge are becoming targets of an extended ecological global economy. Thus the emergence of tradable knowledge over environmental goods and services, or the appropriation of indigenous knowledge by ethno-bio-prospecting carried out by biotechnological enterprises (Bellmann, Dutfield & Meléndez-Ortiz, 2003).

INNOVATION FOR DEMATERIALIZATION Undoubtedly, the main driving force that orients innovation processes towards sustainability goals, is the geopolitics of economic globalizaton and sustainable development that has been set-up since the UN World Conference on the Human Environment in 1972, to the Johanesbourg Summit on Environment and Sustainable Development in 2002, through the Eco-Rio Conference in 1992 and all their outcomes (Agenda 21, MEAs, Conventions on Biodiversity and Climate Change, Kyoto protocol, Clean Development Mechanism, etc.) that configure today the dominant vision, strategy that rules the World and national environmental policies.

5

Environmental Rationality

Within that scope, one major project that has set in motion more specific actions towards technoeconomic and managerial innovations has been the one to dematerialize production, set in motion by the Wuppertal Institute in 1993, and followed by the Factor 10 Institute founded in 1997 followed by the International Factor 10 Innovation Network in 1998. Ernst Ulrich von Weizsäcker (1997) published his idea of dematerializing by a Factor 4, advocating a resource strategy founded on reducing resource use by means of what he called “efficiency revolution”. This idea was challenged and further developed by Friedrich Smidt-Bleek, who proposed a tenfold dematerialization of western technologies on average as a conditio sine qua non for approaching economic sustainability. To achieve that goal, by 2050, the worldwide average per capita consumption shall not exceed 8 tons of material per year; a per capita ecological footprint of 1.8 has, a per capita consumption of 5-6 yearly tons of non-renewable material resources and an emission of CO2 not exceeding 2 tons per year per person. These sustainable economic conditions could only be reached by increasing the resource productivity of the industrialized countries (Schmidt-Bleek, 2008). If the worldwide consumption of nature had to be reduced by a factor of 2, but up to 8 million people had to “grow” in order to satisfy their basic needs intended by the market economy in place, then the industrialized countries had to make the extra effort to dematerialize by a factor of 10. If the advanced economies are the societies of knowledge of our times, how could they doubt their capacities to trigger the innovations necessary to reach the desired sustainable economy? Thus, within the prevalent rationality, and with the intent of reestablishing the ecological balance in the economy, a campaign for eco-innovation was launched1. The basic assumptions and imperatives upon which this intended dematerialization was based on were no other than the wishful thinking principles of some of the first and main proponents of

6

ecological economics: (a) The human economy must be constrained to function within the limits of the environment and its resources and in such a way that it works with the grain of, rather than against, natural laws and processes; (b) We must adjust our wealth and prosperity-generating machine to operate within the guardrails of the laws of nature; (c) “if too much environmentally dangerous material escapes at the back-end of an economy, one should curb the input streams of natural resources at the front end of the wealth machine.” Schmidt-Bleek thinks it is “the rucksack of finished products rather than the process of manufacturing what determines the overall resource intensity of the economy”; he recognizes that “lifesustaining services of the environment cannot be generated by technology at any cost”, and that “the present price situation allows only rather limited dematerialization moves under profitable conditions”. Yet he affirms that “Sustainability is won on the market or not at all.” (Schmidt-Bleek, p.3). In practice, dematerialization implied the calculation of the limited materials that the Earth can offer and the overdose of nature that enters and is consumed by the economic machine. Measured as Material Input per Service rendered at the micro level (MIPS), total yearly material flows (TAPS) and cost per unit service or utility (COPS), the Factor 10 project intends to reduce material flows and increase resource productivity in a service oriented economy. And the work to do was delivered to faith in the workings of the market economy and technological innovation. There is no hint at deconstructing, but only mending and reshaping the established wealth machine. From the fact that the economy will not listen and adjust to the imperatives of nature, that it will not reach by consciousness and planning a steady state that would allow for ecological balance, then the next step has been to call for de-growth and de-coupling the economy from nature, a step back again to the false pretention of having an economy working delinked

Environmental Rationality

away from nature. And with more arrogance than critical spirit and openness to other thinking, experiences and practices, he pontificates with Eurocentric pride that “Europe may be the only region in the world where the necessary experiences, both shameful and brilliant, have sprung from its history, and where the human and technical genius exists to lead humankind toward a more sustainable future.” (Ibid.) As we will see in what follows, there is something more to expect of alternative knowledge, thinking, experiences and practices from other corners and latitudes of the planet that are opening new perspectives for the social construction of sustainability. From the standpoint of environmental rationality and the perspectives to sustainability conceived in the South, eco-innovation appears more as a will to de-grow the economy than to refurnish and remodel it with ecological balances and energy flow calculations, with ecological footprints and economic valuation instruments. The proposal to de-grow the economy is based not only on an increase of resources productivity, efficiency of “throughput” and recycling and restriction in consumption, but on the innovation of new production processes and consumption patterns (Latouche, 2006, 2009). Notwithstanding this broad program of de-growing, it remains a fatuous will if it is not based on a new productive paradigm. As in order to de-grow, the economy has to deactivate the inbuilt mechanism that triggers growth. And this implies the deconstruction of the established economic rationality in the global world order and the construction and legitimization of a new sustainable paradigm of production based on the negentropic productivity of ecosystem local economies, and of an environmental rationality based on a culture of diversity, a politics of difference and an ethic of otherness (Leff, 2008).

SUSTAINABILITY AND INNOVATION: ENVIRONMENTAL RATIONALITY AND REVOLUTION OF KNOWLEDGE Innovation is the inbuilt mechanism that mobilizes processes within a structured system and drives it towards its prescribed and embodied ends. In economics, innovation occurs as a technological change or reorganization of processes that renews the productive capacities of the system and expands them for the use of new materials, the implementation of new instruments, the design of new products, the creation of new needs and the management of the productive forces. But innovation within the rationality that has cradled and triggered its potency, does not lead to sustainable development. By ignoring and neglecting the ecological limits and the environmental conditions for a sustainable economic process, the innovation of productive forces under the prevalent economic rationality has driven an environmental crisis (Leff, 1995, 2009a; Benton, 1996). Thus, the question of the contribution of sustainability to innovation or innovation for sustainability should be inquired in its twofold relationships but in a new perspective. It is not sustainability, as an emergent objective, which reorients innovation as an end prescribed in the tendencies and possibilities of the workings of modern rationality, those that were set at the insept of its driving mechanism towards unsustainable growth, as a way of dialectical transcendence in the reflexivity of modernity. Thus, beyond viewing sustainability as a new objective towards which dynamic innovation should be oriented to reconstruct an ecologized world order subject to the constraints of the dominant economic order, it should be viewed as a new condition of human life that reorients innovation toward the purposes and goals of a sustainable social order founded in a new environmental rationality. The construction of such environmental rationality implies new thinking and a shift in scientific theories. In this context, sustainability

7

Environmental Rationality

has become the main attractor in the emergence of interdsiciplinary paradigms of environmental sciences. These innovations in knowledge imply new methods of complex thinking, as well as the articulation and hibridization of different disciplines and areas of knowledge, the application of new interdisciplinary methods to complex socioenvironmental problems and the elaboration of new interscientific objects of science. Thus, environmental economics has evolved as a new branch of mainstream economics for the crematistic valuation of nature, extending its arms to embrace environmental goods and services (Fisher, 1918; Pearce, 2002); ecological economics has emerged as a new interdisciplinary paradigm that intends to subsume economics as a subsystem in a more embracing ecological system, where population processes, technological innovation and changes in human behaviour merge in the remodeling of economics (Costanza et al., 1991). In a more critical approach, Nicholas Georgescu-Roegen (1971) intended to innovate a new economic paradigm –that of bioeconomics–, establishing the intrinsic link between the law of entropy and the economic process. From the limits of biospheric resources and the ineluctability of the law of entropy, sustainability has reflected as an imperative to lessen the amount of matter and energy entering the global economic system and its metabolic “throughput” along the transformation of nature and its entropic degradation, today reflected as the threat of global warming and climate change. Thus, an imperative of technological innovation has triggered new efforts towards ecoefficiency, the increase in resource productivity, a shift to renewable sources of energy and the recycling of waste (Hinterberger & Seifert, 1995). The configuration of environmental knowledge has lead to the development of new scientific fields and environmental branches within the established scientific paradigms; of new hybrid and interdisciplinary domains of scientific research and new horizons of philosophical inquiry. Thus, we have seen a display of novel approaches to problem-

8

solving knowledge that imply the articulation of a variety of theoretical paradigms and practical forms of knowledge. These efforts have brought about novelties in the management and application of available knowledge and induced innovations in research methodologies as those of complex environmental systems (García, 1986, 1994). But seldom do they imply a shift in scientific paradigms, a revolution in knowledge or the invention of a new rationality by reflective thinking. The emergence of the ecological era in our times carries with it and is rooted in a new episteme; this is not only the rearrangement of already existing disciplines, but the eruption of a novelty in philosophy, methodology and science that can be conceived as a breakthrough in knowledge and in human thinking. In similar ways as the development of knowledge in social sciences in modern times led to structuralism (Foucault, 1970), post-structural knowledge is being codified and reordered by an ecological understanding of the world order. This emergent ecological episteme influenced the new approaches to the Ecology of the Mind (Bateson, 1972), complex thinking (Morin, 1980, 1993), Gaia Theory –life as a self-regulatory systems in equilibrium with its environment– (Lovelock, 1979), the Web of Life (Capra, 1999), and autopoiesis governing selforganizing processes (Maturana & Varela, 1994). These inquiries have led to new paradigms of complex thinking on the interrelatedness of ontological and epistemological orders and the creation of new ecological and environmental disciplines: human ecology, ecological economics, ecological and environmental anthropology, deep ecology, political ecology, environmental sociology, environmental law, etc. These scientific disciplines, discourses and bodies of philosophical thinking involve novelties arising from the convergence, articulation, hybridization of traditional paradigms while being “ecologized” and problematized by an emergent environmental knowledge (Leff, 2001). In this process, the differentiation of concepts referred to as “novelties in thinking” is becom-

Environmental Rationality

ing somewhat blurred, once innovations in the different areas of human being, thinking, creativity and intervention on nature have become increasingly intertwined. Sustainability emerges in the crossroads of different forms of rationality, in the hibridization of nature, culture, economy and technology, of the real and the symbolic, where nature and culture are increasingly being intervened by technological and economic rationality. Thus, creativity in nature through natural evolution has yielded to biotechnology, where new forms of biological artifacts are being produced by scientific-technological innovations drawn by the global market economy. This outcome of modern civilization is not the result of the evolution of nature towards an ecologyzed and complex world order. Environmental complexity (Leff, 2003) has emerged from the intervention of knowledge in nature, as a process of rationalization based on the axis of modern rationality that, by ignoring and externalizing nature from the social system, has fueled the economic system towards unsustainable growth, environmental degradation and the entropic death of the planet. Thus, sustainability demands new thinking and the reorientation of the innovation processes. Here is where environmental rationality emerges planting its roots in new life territories and viewing new horizons to guide social creativity towards the construction of a sustainable future.

REENCOUNTERING NATURE AND CULTURE: THE ENVIRONMENTAL EPISTEMOLOGICAL CHALLENGE Environmental rationality opens new perspectives for the social construction of sustainability; it changes gears for the innovation process towards other purposes that depart from the inertial tendencies of modernity. Rationality, organized in its main orders of rationality –formal and theoretical rationality; instrumental and practical; substantive and cultural–, change their meaning and priorities.

In modern rationality, substantive, cultural and scientific rationality have been subordinated to the imperatives of formal logic, economic value and instrumental rationality that project the potentialities of the Real and the creativeness of the Symbolic towards the objectification of the World and an unsustainable techno-economic process of unsustainable growth. Environmental rationality is constructed from critical theory and ethical principles that reorient the civilization process towards sustainability. When environmental problems emerged and economic growth and the World economic order were questioned for their impact on environmental degradation, back in the late 60s, the economy responded by asserting that the environment is an externality of the economic system. In its selfjustifying eagerness, the economy confessed its fundamental flaw in building the economic process in a divorce from the natural, ecological, geophysical, and thermodynamic order within which it operates; that is to say, by ignoring its conditions of sustainability. In this way, an initial idea of the environment emerged as an epistemological space for the reencountering between society and nature, to solve the disjunction between the object and the subject of knowledge and the split between natural and social sciences. A more careful investigation of the constitution of the sciences as conceptual structures built around a nucleus-object of knowledge led us to understand the exclusion of the environment in the universe of the “centred formations” of modern sciences. From George Canguilhem and Jacques Derrida, an epistemological inquiry unfolded that was particularly fruitful in forging the epistemological basis of environmental rationality. Following the perspectives of French critical rationalism –from Gaston Bachelard to Louis Althusser and Michel Foucault–, an epistemological inquiry led to the positing of the environment not only as a factual territory inhabited by living beings, but actually as the epistemic space bordering and surrounding the logocentric spaces of science.

9

Environmental Rationality

Thus, the environment was defined as otherness to dominant scientific rationality, beyond the holistic perspectives that were shaping theoretical systems and emerging ecological thought. In this way, it was possible to transcend a merely empirical and functional conception of the environment, as the milieu surrounding a population, the economy and society. Beyond identifying economic, political, and social causes tied to an array of socio-environmental problems –pollution, deforestation, ecological degradation, soil erosion, global warming–, this epistemological view transcended the stance of systems theory and the holistic visions that led to a will for interdisciplinary integration of existing sciences as a method to solve the fragmentation of knowledge associated to the environmental crisis (Leff, 2001). The environment was not, then, the junction of fragmented disciplines, focused on their own autonomous objectives of knowledge; it was not a simple “environmental dimension,” that could be internalized within the systemic approaches and planning practices based on the principles of ecology, cybernetics and general systems theories, that could be extended to other paradigms of knowledge or serve as the unifying thread capable of weaving the transversality of environmental through into the dispersed and dismembered body of knowledge, as suggested and posited by diverse authors (i.e., Sachs, 1972; von Bertalanffy, 1976; Morin, 1980, 1993). The environment was formed as a field of externality to the logocentrism of science, outside the system of established scientific theories. From that position, emerging environmental savoir problematizes the “normal” paradigms of science and promotes their transformation in order to generate environmental branches of knowledge. In this sense, environmental epistemology goes beyond those proposals that pretend to integrate natural and social disciplines to generate the much desired environmental sciences, interdisciplinary fields and transdisciplinary methods capable of ap-

10

proaching complex emerging socio-environmental problems (Leff, 2001). In the realm of theory, from the standpoint of environmental rationality, a new approach to interdisciplinarity emerged. Beyond the methodological purpose of articulating the actual paradigms of science, the construction of new objects of knowledge was proposed. From a critical epistemological perspective that derived from systems theory conception of the environment as an externality of the system, the environment was defined as the lack of knowledge of existing sciences, as the unknown to the logocentric organization of science, as the “external” processes that influence, condition and even determine the processes that sciences are concerned with, but that have been erradicated from their field of knowledge. An exemplary case of this “externalization” of material and symbolic processes impringing on a scientific paradigm is that of economic theory, where nature as a condition of sustainable production has been simply ignored. The response to this fact in the history of science, is the reaction of economics to construct a new discipline of environmental economics by extending its traditional and mainsteram paradigm to embrace nature –ecological systems, environmental goods and services– by recodifying nature as natural capital instead of integrating nature as nature’s Being: the ecological organization of nature; the laws of entropy that determine the flows and degradation of matter and energy in the economic process. In the perspective of environmental rationality, a new economics was proposed. Following the epistemological indagatories of George Canguilhem (1970, 1977) derived from critical rationalism, interdisciplinarity is thought, not as the intended articulation, hibridization and blending of existing paradigms (that carry within themselves their own epistemological obstacles), but as the conjunction of different ontological orders and disciplines in the construction of a new scientific object. Thus, instead of recodifying nature in economic terms, or trying to subsume the

Environmental Rationality

established economic order within the limits and conditions of the biospheric ecological system, a paradigm of sustainable production can be thought of as the articulation of ecological, technological and cultural productivity: as an economic process based on the potency of nature, –of the negentropic productivity of photosynthesis and the ecological organization of nature– signified and embedded in culture (Leff, 1995, 2009a). This new productive paradigm carries within itself a complex array of innovative processes: In the level of theoretical rationality, it implies the deconstruction of the theories (economic, juridical, social) that became the pilars of modern rationality. In the field of economics and law, it carries the deconstruction of economic value and positive law based on the individual as the principle of economic and juridical actions, of intellectual property rights, etc., to construct new paradigms based on common property rights over the common patrimony of nature and culture. In the level of instrumental and practical rationality, the technological innovation process is subordinated to the preservation of the productive potentialities of nature supported by the organization of ecosystems, neguentropic productivity derived from photosynthesis and the ecological management of the metabolism of material and energy flows in agricultural and industrial, urban and rural, domestic and social systems. Technological innovation is not restricted to “ecoefficiency” in the production system –dematerialization of production end recycling of waste–; ecolabelling and the compliance to environmental rules of trade; new technologies for clean production –energy derived from renewable sources: solar, eolic, biofuels–; it promotes important shifts in agronomic production systems –agroecology and agroforestry– and new strategies for the collective and sustainable management of water and forests beyond the economic valuation of environmental goods and services under the geopolitics of sustainable development.

Substantive rationality becomes fundamental to environmental rationality. Environmental rationality is not a model, nor a paradigm to guide a “new deal” State planification for sustainable development, nor the scientific management of nature, but rather the “governance of the commons” based on cultural institutions (Orstrom, 1990). Environmental rationality is rooted and embodied in different matrixes of cultural rationality. It is from cultural rationality that nature is revalued. Culture is the source of meaning and inventiveness that resignifies the potency of nature, the creativeness that orients the construction of sustainability through a dialogue of knowledges imbedded in social imaginaries, beyond the scientific management of nature (Leff, 2006, 2010).

BUILDING ENVIRONMENTAL RATIONALITY FOR SUSTAINABILITY: CREATIVITY IN THINKING, INNOVATIVE KNOWLEDGE AND SOCIOLOGICAL IMAGINATION Environmental rationality does not only reorient innovation towards sustainability but re-signifies the concept of production. Ideas have always fed the economy and forged innovations as they entered into the productive processes in what Piero Sraffa (1973) named the “production of commodities by means of commodities”. But even though knowledge has become a commodity, the “innovations” of environmental rationality are novelties brought about in the “production of ideas by means of ideas”, of thinking by means of thinking. Following Heidegger (1957/1988), it is only though thinking that we can reflect on what has previously be thought, to bring about what there is still to be thought. If innovation is the process of purposely reorganizing what there is –re-setting reality, rearranging objective reality in the present world, applying available knowledge to produce a practical novelty–, to what extent

11

Environmental Rationality

does thinking that implies an act of no-thingness –thinking on Being and Becoming beyond the present reality of things; thinking that guides the deconstruction of the objectified world as to let the Being of nature and of culture be–, can be called an innovation? That is the predicament of environmental rationality, of an idea that reorients creativeness, inventiveness and innovation towards sustainability. If environmental decay is caused by the counter-ecological workings of modern rationality, then sustainability cannot be constructed by the self-reflection of modernity over its own rationality. Innovation for sustainability demands new thinking that transcends any innovation of knowledge within the paradigms of normal science and leads to the creation of a new rationality. Environmental rationality as philosophical thinking emerges from a critical point and moment in the evolution of modern civilization: that of an environmental crisis conceived as a turning point in history, triggered by a limiting frontier in the expansion and development of the established rationality. The environmental crisis is conceived as a crisis of knowledge, that is to say, a crisis brought about by the ways of thinking and the forms of knowledge that guided the constitution of prevalent economic rationality and the technological developments brought about by scientific and instrumental rationality –together with the ethical principles and values imbedded in such configurations of rationality–, that theorized, legalized and legitimized human actions in the building of an unsustainable world. As a crisis in knowledge, environmentalism has launched innovative thinking that has impinged in several different domains of philosophy and science. However, environmental rationality is not ecologysed thinking; it goes beyond the articulation of disciplines and the blending of actual current knowledge developed by normal science. As a political philosophy, it goes beyond the simple adoption or application of philosophical traditions or post-modern philosophy to the

12

understanding of present problems and situations in our societies. Environmental rationality does not emerge as “thinking within normal science”, as the reflection of knowledge on social structure, or as the refinement of an already established logic (the reworking of what is at hand in the thinking principles and instruments of modern rationality). Environmental rationality is born from the standpoint of its transcendence of metaphysical thinking, its externality to logocentrism of science and delinking from hegemonic dominant rationality. Thus, the construction of sustainability, viewed in the perspective of environmental rationality implies the creation of new ways of thinking. Counter-hegemonic globalization demands the deconstruction of the one-dimensional oppressive force against diversity, difference and otherness. The unifying force born from the power of the One, the Universal, the General, the Absolute Idea, and Systemic Totality, today globalized under the dominance of economic rationality, demands an epistemological decentralization, a Copernican revolution away from logocentric science –the centrality of thought that insists on placing modern rationality at the center of the universe of human life. This external anchor point is the environment: environment as an epistemological concept. If environmental rationality must be thought of as other to the prevailing social rationality, it cannot emerge from any ontological or epistemological order –a cultural territory–, untouched by the prevalent world order. Environmental rationality is forged in the deconstruction of metaphysical, scientific, and postmodern thought –in the territorialization of diversity, difference and otherness– on the basis of ecological potentialities and cultural knowledges that inhabit these unknown regions of the Real that are emerging from the South. Environmental rationality impinges in knowledge but is rooted in the field of political ecology and environmental politics. It is expressed in the demands and struggles of peasant and indigenous peoples like the seringueiros (rubber tapers) movement of Chico Mendes and the network

Environmental Rationality

of community based river and land extractive reserves of the Amazon region in Brazil; it becomes the mobilizing force of many indigenous peoples throughout the Latin American region, from the Seris in the Northern arid lands of Sonora, Mexico, to the Mapuches of Argentine and Chile, including the Coordination of Indigenous Peoples Organizations of the Amazonian Basin (COICA) and the Black communities of the Pacific Coast in Colombia, that are reaffirming their identities and reorganizing their productive practices for the management of their natural and cultural heritage, including their forests and genetic resources. These social environmental movements go beyond claims against biopiracy, ecological damages and the distribution of benefits from bioprospecting and ecotourism in the new geopolitics of economic-ecologic globalization, to demand their rights to re-establish their livelihoods and modes of production with nature (Porto Goncalves, 2001; Leff, 2002; Escobar, 2008). The field of political ecology is becoming an emancipation force slowly extending to large peasant organizations like the landless movement in Brazil and to peaceful unarmed popular movements, as the Zapatistas in Chiapas Mexico and the Green Army of the Indigenous Peoples of the Ecuadorian Amazonia, that struggle for the preservation of their ecosystems and for a sustainable development based on the harmonious coexistence of cultural diversity in a globalized world. It is a struggle for reappropriation of their patrimony of natural and cultural resources and for the territorialization of an environmental rationality (Leff, 2009a). From a critical perspective of the oppression and dependence of Latin America and the Third World, in relation to the hegemonic power of the globalized economy as the organizing centre of the world, environmental rationality emerges from a reflection on the Coloniality of Knowledge (Lander, 2000), to the construction of Knowledge from the South (Santos, 2008) as an epistemological struggle that accompanies social processes of

emancipation in the perspectives of constructing alternative sustainable worlds for its peoples. These reflections stem from a critique to Eurocentrist ideas (from the foundation of metaphysics in Greek philosophy through postmodern thought), as well as dominant paradigms of scientific knowledge and modern technologies continue to be imposed to our societies, from the times of the colonial period, to the era of globalization. The ideas of Enlightenment that colonized our ways of thinking, our modes of production and our life-worlds, and have led –as a reaction– to the emergence of an emancipatory knowledge and political culture. Environmental rationality as strategic knowledge, in its purpose to liberate the potentialities of nature and culture from the determinations infringed by the relationships of domination, exploitation, extermination, inequality and unsustainability, turns to the recognition of social imaginaries, alternative forms of knowledge and traditional life-worlds denied and subjugated by dominant paradigms (Leff, 2010). However, this does not necessarily imply the possibility of delinking and abandoning once and for all Western thinking. In order for the globalized World-system to be deconstructed and for other possible worlds to be constructed, the reconstruction of knowledges and of “other rationalities” emerging from “knowledge from the South” –from cultural knowledge and ecological potentials– encounter the established hegemonic economic and epistemic world order. The emergent environmental rationality is constructed through a dialogue of knowledges with the critical Western thinking now underway in science, philosophy and ethics. Environmental rationality emerges not only from a spirit of emancipation, but from its epistemological standpoint in the margins and the externality to logocentric knowledge. Above all, it emerges, outside the realm of thought, from the ecological and cultural roots of a social movement for survival and resignification of human life. It is from this situated critical knowledge that Latin American

13

Environmental Rationality

Environmental Thought contributes an original outlook to sustainability (Leff, 2011). The epistemological inquiry set forth by that critical concept of the environment sowed a seed that fertilized the field of Latin American environmentalism. This led to a new theoretical path that stimulated a critical revision of many of the most important theorists of modernity, from Karl Marx (1965) and Max Weber (1978), to Martin Heidegger (1927/1951), Emmanuel Levinas (1977) and Jacques Derrida (1989), in order to attract their thoughts and transform them from the roots of the ecology and the cultures of Latin American territories. This epistemological odyssey –from eco-Marxism to political ecology and existential ontology rooted in ecology and culture– did not merely imply the influence of European thought on American lands. The theories forged in Europe were transformed from a critical perspective that was born from the sources of ecological potentials and the cultural diversity of our continent, that are fertilizing new fields of political ecology in Latin America. The concept of environment as potential; the concepts of difference and otherness as cultural diversity rights, are typically Latin American. From this epistemological field, unique proposals about environmental complexity arose –beyond complex thought and the sciences of complexity– that displaced the critique of interdisciplinary methodologies and systems theories toward the dialogue of knowledge as an epistemological strategy to construct sustainable societies (Leff, 2003, 2006). The pending debt of environmental rationality is that of building a more plural, direct and close dialogue with the indigenous savoirs and cultural knowledges imbedded in the social imaginaries, habitus and practices of the people of the region. Only by setting this dialogue into practice can a political ethic of difference emerge, one that orients the cultural re-appropriation of the common heritage of humanity; a democratic and participatory management of the commons that challenges the totalitarian regime of meaning on nature and

14

the dominance of the World economic order: a political ethics for diverse sustainable societies which neither submits to the merchandizing of nature, nor to an ecological order, nor to a general sense of Being, pretending to unify the views and interests of the people, that are differentiated by nature and culture. Apart from a hegemonic or dominant rationality that forces a consensus in a unified knowledge, the solidarities that must be forged to construct a sustainable future for all peoples in our living planet, must recognize their differences, their irreducible otherness to a “common sense”, their being and becoming led by the heterogenesis of a new world order generated by coevolution of biocultural diversity and guided by a new environmental rationality.

FUTURE RESEARCH DIRECTION AND BRIEF CONCLUSION Theoretical inquiry on environmental rationality is an open ongoing process for the construction of a sustainable future. Most important for this goal will be research on the social appropriation of the categories of environmental rationality in the building of a new economy, the dialogue of knowledges among all social factors involved and environmental education for the training of new forms of reasoning, modes of thinking and ways of being, to open the paths for a sustainable future. Several research routes are open for further theoretical and practical reasearch regarding the concept of environmental rationality and its application for innovation in social organization oriented towards the construction of a sustainable world order. A synthetic list of inquiries and applications can organize a research programme include the following issues: 1. Further research on the theoretical consistency of the category of environmental rationality following its epistemological,

Environmental Rationality

theoretical and ethical principles, and contrasting this “paradigm” with other innovations in thinking –in science, philosophy, economy, politics and ethics oriented towards the construction of sustainability 2. Further research and action for the construction and implementation of a paradigm of negentropic productivity, conceived as an alternative mode of production based on an integrated system of ecological-technological-cultural productivity. This research is not only theoretical –ie defining an heuristic concept of a negentropic society facing the entropic condition of the techno-economic order—but should focus on actual practices for territorializing environmental rationality as innovative forms of productive and social organization. This will open new research on the ecological and cultural potentials for local sustainability based on interdisciplinary ethno-ecological research. 3. Further research on socio-environmental movements and groups that are “innovating” their strategies for sustainability inspired by, and in dialogue with, the ideas and proposals emerging from environmental rationality.

REFERENCES Bachelard, G. (1938). La formation de l’esprit scientifique. Paris, France: Librairie Philosophique J. Vrin. Bateson, G. (1972). Steps to an ecology of mind: Collected essays in anthropology, psychiatry, evolution, and epistemology. Chicago, IL: University of Chicago Press. Beck, U., Giddens, A., & Lash, S. (1997). Modernização reflexiva. São Paulo, Brazil: Editora UNESP.

Bellmann, C., Dutfield, G., & Meléndez-Ortiz, R. (2003). Trading in knowledge. Development perspectives on TRIPS, trade and sustainability. London, UK: ICTSD/Earthscan. Benton, T. (1996). Marxism and natural limits: An ecological critique and reconstruction. In Benton, T. (Ed.), The greening of Marxism. New York, NY: Guilford. Böhme, G. (1976). Finalisation in science. Social Sciences Information. Information Sur les Sciences Sociales, 15, 307–330. doi:10.1177/053901847601500205 Canguilhem, G. (1971). La connaissance de la vie. Paris, France: Librairie Philosophique J. Vrin. Canguilhem, G. (1977). Idéologie et rationalité dans l’histoire des sciences de la vie. Paris, France: Librairie Philosophique J. Vrin. Capra, F. (1996). The Web of life. A new scientific understanding of living systems. New York, NY: Anchor Books/Random House. Costanza, R. (Ed.). (1991). Ecological economics: The science and management of sustainability. New York, NY: Columbia University Press. Derrida, J. (1989). Márgenes de la filosofía. Madrid, Spain: Cátedra. Escobar, A. (2008). Territories of difference. Place, movements, life, redes. Durham, London: Duke University Press. Fisher, A. C. (1981). Resource and environmental economics. Cambridge, New York: Cambridge University Press. doi:10.1017/ CBO9780511572081 Foucault, M. (1970). The order of things: An archaeology of the human sciences. New York, NY: Pantheon Books.

15

Environmental Rationality

García, R. (1986/2000). Conceptos básicos para el estudio de sistemas complejos. In E. Leff (coord.), Los problemas del conocimiento y la perspectiva ambiental del desarrollo. México: Siglo XXI Editores. García, R. (1994). Interdisciplinariedad y sistemas complejos. In E. Leff (coord.), Ciencias sociales y formación ambiental. Barcelona, Spain: GEDISA. Georgescu-Roegen, N. (1971). The economic process and the entropy law. Cambridge, MA: Harvard University Press.

Leff, E. (2001). Epistemologia ambiental. São Paulo, Brazil: Cortez Editora. Leff, E. (2002). A geopolítica da biodiversidade e do desenvolvimento sustentável: Economização do mundo, racionalidade ambiental e reapropriação social da natureza, In Ceceña, A. E. & Sader, E. (Eds.), A guerra infinita. Hegemonia e terror mundial (pp. 253-288). Petrópolis, RJ:VozesClacso-LPP. Leff, E. (2003). A complexidade ambiental. São Paulo, Brazil: Cortez/Edifurb/PNUMA.

Haraway, D. (1991). Simians, cyborgs and women. The reinvention of nature. New York, NY: Routledge.

Leff, E. (2006). Racionalidade ambiental: A reapropriação social da natureza. Rio de Janeiro, Brazil: Civilização Brasileira.

Heidegger, M. (1927/1951). El ser y el tiempo. México: Fondo de Cultura Económica.

Leff, E. (2009a). Ecologia, capital e cultura: A territorialização da racionalidade ambiental. Petrópolis, Brasil: Editora Vozes.

Heidegger, M. (1957/1988). Identidad y diferencia. Barcelona: Editorial Anthropos. Hinterberger, F., & Seifert, E. (1995). Reducing material throughput: A contribution to the measurement of dematerialization and sustainable human development. In van der Straaten, J., & Tylecote, A. (Eds.), Environment, technology and economic growth: The challenge to sustainable development. Aldershot, UK: Edward Elgar Publishing. Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago, IL: The University of Chicago Press. Lander, E. (Ed.). (2000). La colonialidad del saber. Buenos Aires, Argentina: CLACSO/UNESCO. Latouche, S. (2006). Le pari de la décroissance. Paris, France: Fayard. Latouche, S. (2009). Farewell to growth. New York, NY: Wiley. Leff, E. (1995). Green production. Towards an environmental rationality. New York, NY: Guilford Press.

16

Leff, E. (2009b). De-growth or deconstruction of the economy: Towards a sustainable world. In U. Brand, N. Bullard, E. Lander & T. Mueller (Eds.), Contours of climate justice: Ideas for shaping new climate and energy politics, in Critical currents (Occasional Paper Series, No. 6) (pp. 101-107). Upsala, Sweden: Dag Hammarskjöld Foundation. Leff, E. (2010). Imaginarios sociales y sustentabilidad, Cultura y representaciones sociales (Num. 9, pp. 42-121), México. Retrieved from www. culturayrs.org.mx Levinas, E. (1977). Totalidad e infinito. Ensayo sobre la exterioridad. Salamanca, Spain: Sígueme. Lovelock, J. (1979). Gaia. A new look at life on earth. Oxford, UK: Oxford University Press. Marx, K. (1965). Œuvres. Paris, France: Gallimard. Maturana, H., & Varela, F. (1994). De máquinas y seres vivos. Autopoiesis: La organización de lo vivo. Buenos Aires, Argentina: Lumen.

Environmental Rationality

Morin, E. (1980). La méthode. La vie de la vie. Paris, France: Éditions du Seuil. Morin, E. (1993). Introducción al pensamiento de la complejidad. Barcelona, Spain: GEDISA. Orstrom, E. (1990). Governing the commons. The evolution of institutions for collective action. Cambridge, UK: Cambridge University Press. Pearce, D. (2002). An intellectual history of environmental economics. Annual Review of Energy and the Environment, 27, 57–81. doi:10.1146/ annurev.energy.27.122001.083429 Porto-Gonçalves, C. W. (2001). Geo-grafías. Movimientos sociales, nuevas territorialidades y sustentabilidad. México: Siglo XXI Editores. Prigogine, I., & Stengers, I. (1984). Order out of chaos: Man’s new dialogue with nature. New York, NY: Bantam Books. Rees, W. E. (1992). Ecological footprints and appropriated carrying capacity: What urban economics leaves out. Environment and Urbanization, 4(2), 121–130. doi:10.1177/095624789200400212 Sachs, I. (1982). Ecodesarrollo. Desarrollo sin destrucción. México: El Colegio de México. Santos, B. de Sousa (2008). Conocer desde el Sur. Para una cultura política emancipatoria. Buenos Aires, Argentina: CLACSO/CIDES-UMSA/ Plural Editores. Schmidt-Bleek, F. (2008). Future. Beyond climate change (Position paper 08/01). Provence, France: Factor 10 Institute.

Schumpeter, J. (1934). The theory of economic development. Boston, MA: Harvard University Press. Sraffa, P. (1973). Production of commodities by means of commodities. Cambridge, UK: Cambridge University Press. von Bertalanffy, L. (1976). Teoría general de los sistemas. México-Madrid-Buenos Aires: FCE. von Weiszsäcker, E. U., Lovins, A. B., & Lovins, L. H. (1997). Factor four. Doubling wealth halving resource use. A report to the Club of Rome. London, UK: Earthscan. Wackernagel, M. (1994). Ecological footprint and appropriated carrying capacity: A tool for planning toward sustainability (PhD thesis). Vancouver, Canada: School of Community and Regional Planning, The University of British Columbia. Weber, M. (1978). Economy and society. An outline of interpretive sociology. Berkeley, Los Angeles, London: University of California Press.

ENDNOTE 1



In terms of the EU Eco-innovation panel, eco-innovation means “the creation of novel and competitively priced goods, processes, systems, services and procedures, that can satisfy human needs and bring quality of life to all people with a life-cycle-wide minimal use of natural resources (material including energy and surface area) per unit output, and a minimal release of toxic substances.”

17

18

Chapter 2

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation David L. Rainey Rensselaer Polytechnic Institute, USA

ABSTRACT This chapter presents the foundations of a conceptual model for connecting the key elements necessary for corporations to adopt sustainability in the context of the global economy and strategic innovation. While there are numerous theories and practical methods for managing in a national or even regional markets, most of them lack the sophistication necessary for leading change in a global business environment. With the advent of globalization, the complexities of doing business on a global basis have increased dramatically over the last two decades. While sustainability involves many perspectives, strategies, actions, and management constructs, the chapter focuses on how global corporations employ strategic innovations in response to the driving forces in the global economy and how they can improve their level of management sophistication in a turbulent business environment. The model incorporates the concepts of sustainability and sustainable development in creating the solutions, systems and structures for doing business in the global economy. It focuses on strategic innovations that provide more positive aspects and fewer negative ones. Sustainability and sustainable development are based on proactive strategies and actions that exceed expectations and outperform peers and competitors alike. Strategic innovations are dramatic changes that have the potential to create dramatic new solutions that create exceptional value and eliminate or reduce negative effects and impacts. Strategic innovations include radical technological innovations, business model innovations, product developments, and organizational developments that are game changers. DOI: 10.4018/978-1-61350-165-8.ch002

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

INTRODUCTION This chapter presents a model for adopting sustainability and sustainable development (SD) in business organizations based on the perspectives of globalization and the management constructs associated with strategic innovation. Globalization involves the development of an integrated global economic system. It is based on fewer time and distance constraints, the reduction in the costs of global communications and logistics, the removal of trade restrictions, and enhancements in information flows and currency exchanges. Today, advanced technologies and sophisticated management methods and practices have dramatically improved the efficiency, effectiveness, and benefits of international trade. While incredible improvements have been made over the last decade, there are many more changes necessary to ensure that globalization is a positive force resulting in sustainable outcomes for all of the participants. Given that globalization is still far from a true reality, sustainability and SD are essential constructs for achieving positive gains and reducing negative effects and impacts. Sustainability involves the quest toward more ideal solutions and sustainable success over time. It necessitates more inclusive and innovative approaches for collaboration, cooperation, integration, and innovativeness in developing and deploying the best possible solutions for enhancing the well being of people, preserving the natural environment, and ensuring social and economic stability. It requires creating newto-the-world solutions that are based on clean technologies and innovative products and more efficient, effective, and less polluting systems; ones that provide mostly positive benefits with few defects, burdens, problems, and significantly less pollution and waste. Sustainability involves a transformation to higher levels of sophistication in how business leaders and government officials

formulate and implement strategies, policies, and actions plans to achieve such outcomes. SD is a critical element of sustainability that focuses on developing and deploying strategic innovations that exceed the expectations customers, stakeholders, and people. SD focuses on protecting the natural environment and enhancing the social and economic world as well as achieving superior strategic, market, and financial results by the corporations. SD involves obtaining the best outcomes possible for the present generation and ensuring that future generations can realize their aspirations for social and economic well being in harmony with the natural world. SD originated in 1987 by the World Commission Environment and Development for the General Assembly of the United Nations that prepared the Brundtland Report, entitled Our Common Future. In the report, SD refers to the notion “that it [humankind] meets the needs of the present without compromising the ability of future generations to meet their own needs.” (The World Commission of Environment and Development, 1987, p8) Strategic innovation refers to technological innovations and high-level product developments that have the potential to change the global competitive landscape based on advancements in the benefits provided to customers and stakeholders, and significant reductions in the negative effects and impacts associated with existing technologies and products. Creating, developing and deploying strategic innovations offer bright prospects for an enhanced global business environment with the greater possibilities for more people worldwide to enjoy the solutions provided by businesses. Specifying precisely what strategic leaders must do to achieve sustainability, SD and strategic innovation is an arduous task. Given that an all-compassing model linking globalization, sustainability, SD and strategic innovation may not be possible in the short term, developing and gaining acceptance of a general model that fits multinational enterprises (MNEs), transnational

19

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

corporations, and small and medium sized enterprises (SMEs) may take years to realize. Moreover, as more companies from the developing countries play significant roles in the global business environment, such a model or models have to accommodate the social, economic, cultural, environmental, technological and ethical realities that exist across the globe. Most importantly, a holistic model pertaining to sustainability and SD has to recognize and incorporate the differences in resources, capabilities and sophistication between the MNEs and the SMEs, between the companies from the developed countries and those from the developing ones, and the between the old line corporations and the emerging companies. The objective of the chapter is to articulate the basic elements of a holistic model for improving the adoption of sustainability in the context of globalization. The model provides broad guidelines for what is necessary and beneficial from a global perspective. Such guidelines are intended to provide insights and assistance in developing and implementing the requisite methods and mechanisms. The adoption of the model would be voluntary and offer benefits to corporations, governments, business leaders, political officials, and practitioners alike, since they would have a sense of the underlying specifications so that they can more easily determine what needs to be done going forward. Sustainability and SD involve a continuum in the formulation and implementation of strategies, solutions, actions and innovations that unfold over decades. The chapter does not provide all of the answers. The discussions herein do not include all of the requisite details to fully articulate how to develop and implement the model. Trying to prescribe a single pathway to sustainability and SD would require a model that is so intricate and detailed that it would take several books to spell out all of the variations. The intent herein is to offer insights about what can be done to become more sustainable in a world full of opportunities and challenges.

20

BACKGROUND The business world has changed dramatically over the last two decades as the scope of the social, economic, political and environmental forces impacting businesses has broadened to include not just those pertaining to the developed countries, but those affecting developing countries as well. While there has been much discussion about a shrinking world due to the incredible innovations in new technologies and the linkages between businesses and people, it can also be said that the business world has expanded multifold with the inclusion of all people living in the developed and developing countries. This profound change has been supported by numerous strategic innovations including the expansion of the internet, the interconnectivity of telecommunications, the digitization of many products, and the improvements in affordability. The lowering of the costs of manufactured parts, final products and the related logistical requirements has made the integration of the global economy possible, especially from an economic perspective. Prior to the fall of the Iron Curtain, global corporations generally served approximately one billion people, those living in the developed countries. Today, the business world is not only global, but it is richer in scope, scale, and diversity. Worldwide, there are approximately 6.9 billion people who play a role in the global economy. While some are active participants in the served markets, most are bystanders who might be considered latent customers waiting for the right solutions to meet their needs and circumstances. Globalization is a complex term that has many meanings from a limited view focusing mainly on the economic exchanges of the global economy to the multi-dimensional perspective involving an interrelated, interactive, innovative and more sustainable business world. Regardless, globalization includes interconnections and interrelationships between business enterprises, national governments, and non-governmental organizations (NGOs) among many others. Most

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

importantly, it is based on the context of all of the social, political, economic, technological, environmental and ethical forces. The limited view of globalization is often stated in terms of the merging of national economies into a regional economy and ultimately into a global economy. The European Union (EU) is an example of a regional economy that includes 27 nation states that have linked their economic interests and activities to enjoy economies of scale and more open associations. The intent is to enhance free trade based on a transnational economic system. On a global basis, the limited view pertains to economic exchanges and activities as the primary forces that drive international trade, business investments, and the global economic system. In the limited perspective, global corporations vie to satisfy customer demand and meet stakeholder expectations based strategic positions and global resources and capabilities. The key factors for achieving success are perceived to be cost-effectiveness, high quality products, and tailored products and services; ones that generate advantages and financial rewards for the entities involved. Economics is perceived to be the overarching factor and markets and customers are viewed as the main driving forces. The underpinnings of the limited view are based on free enterprise and market capitalism. The multi-dimensional perspective of globalization involves sophisticated management systems, proactive strategies, cutting-edge solutions, and innovative methods that are developed and deployed to enhance the positive aspects and eliminate the negative aspects of the social, political, economic, technological, environmental and ethical forces. It is based on advanced information and communications technologies, more costeffective means and mechanisms for producing and transporting goods from remote locations to the markets across the world, sophisticated management constructs for decision making, and newto-the-world technologies and products. It is also based on the realization that enduring economic success depends on satisfying all entities and

individuals engaged in or impacted by business transactions, not just customers and stakeholders. It implies that participants and non-participants have to be included in the analysis of what is necessary and appropriate and in the creation of sustainable outcomes. It involves creating, developing, producing and providing innovative solutions for people based on their context and not just the objectives, strategies, and actions of the global corporations. The multi-dimensional perspective also includes a longer time horizon. While most business leaders, economists, and government officials view five to ten years out to be the long term, the long term in the context of the multi-dimensional perspective is measured in decades. The multi-dimensional perspective includes considerations about future generations of people as well. Such considerations are an integral part of true globalization that has yet to be fully developed. Globalization without sustainability, SD and strategic innovations may be viewed as a continuation of the “business usual” mindset that has dominated strategic management thinking over the last half century. The “business as usual” mindset represents the line of strategic thinking, in which the main focus is on growing and expanding businesses without significant concerns about their social and environmental underpinnings, effects and impacts. It presumes that such corporations and their strategic leaders comply with the existing laws and regulations and take due care of their specified environmental responsibilities, but they are not compelled to go beyond such mandates and requirements. The “business as usual” mindset has positives from an economic perspective, but it is generally limited in terms of the social, environmental and ethical aspects. The time horizon is relatively short, usually five years or so. Historically, such perspectives resulted in reasonable outcomes in the developed countries, especially if the social and economic forces were stable and enduring. However, difficulties and discontinuities often arise in the long term. For instance, if the effects of oil depletion are the 21

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

most profound in latter stages of the life cycle of petroleum, then the next ten years may be relatively stable in terms of conventional energy sources, but chaotic thereafter. Moreover, with the addition of many new participants in the global economy and expanding global energy consumption, the business world may become less stable and secure as conflicts arise over obtaining the necessary resources. Under such conditions, there is a significant possibility that the economic and social forces may be overwhelmed by increasing demand for energy; thus, affecting the costs of all materials and goods and leading to significant competition for resources and unsustainable outcomes. Indeed, the current economic recession may be a harbinger of more challenging times ahead, especially if strategic leaders maintain the “business as usual” mindset. True globalization has to incorporate the concepts of sustainability, SD and strategic innovation. They are essential elements in achieving broadbased globalization and providing successful outcomes for all people. Globalization based on sustainability, SD and strategic innovation necessitates a mindset shift in strategic thinking from exploiting the prevailing situations and selling the existing products to customers who have the financial wherewithal to developing innovative solutions that fit the needs, expectations and circumstances of people on their basis. Today, many of the strategic leaders focus their efforts on the developed countries because people in those countries have money and can afford to buy the branded products and services. Moreover, many of the same strategic leaders pay little attention to people in the least developed countries because most of the people are poor and seemingly do not have the necessary disposable income to buy the existing products. However, such strategic leaders should view the creation of solutions based on the needs and perspectives of people, especially those in the developing countries, as enormous opportunities for translating non-customers into customers.

22

Daniel Esty (2006) and Andrew S. Winston in their book, Green to Gold, articulate that “successful, long-lasting companies regularly redefine themselves. Environmental-inspired innovations offer companies new and exciting way to find fresh expressions for their capabilities” (p301). In support of sustainability, Bob Willard (2005) in his book, The Next Sustainability Wave, suggests that “sustainability strategies give corporations the choice of getting ahead of the curve, defining the new rules, and being rewarded by their stakeholders for behaving responsibly” (p1). Sustainability is about leading change to create better outcomes and more enduring business value.

UNDERPINNINGS AND GLOBAL REALITIES Prevailing Business Situation The current economic crisis, the so-called Great Recession, has shed new light on the many difficulties and problems facing business leaders, politicians, government officials and NGO leaders as they try to right the global economy and develop new mechanisms for dealing with the related challenges. All leaders are being challenged to make dramatic improvements in the ways they manage their responsibilities and achieve desired outcomes. Politicians and government officials focus on setting new policies, providing stimulus, and allocating resources. Business leaders across the spectrum of industries and markets try to develop and implement the most effective programs to maximize benefits and outcomes and minimize the risks and vulnerabilities. Today, strategic leaders and senior management of all persuasions have to expand their capabilities and knowledge and adopt innovative management approaches that are in line with the realities of the world. As evidenced by the current economic crisis with its myriad of causes, effects, impacts, and consequences, the underpinnings and

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

key elements of the global economy are too complicated and intertwined for “old school” approaches to succeed. A major untangling of the turbulence and new understandings of the global economy are necessary for creating the requisite solutions. C.K. Prahalad (2005) in his book, The Fortune at the Bottom of the Pyramid, talked about how to handle the global challenges: “What is needed is a better approach to help the poor, an approach that involves partnering with them to innovate and achieve sustainable win-win scenarios where the poor are actively engaged, and at the same time, the companies providing products and service to them that are profitable” (pp3-4). With all of the uncertainty, there are incredible opportunities for companies to succeed. The great challenge for strategic leaders is not just to “right the mistakes” of the past or cut through the turbulence, but to invent a more sustainable future by creating wonderful new solutions for people everywhere and by eliminating the problems and the underlying risks and difficulties. Strategic leaders have to recognize that they are responsible for assuring that the best solutions possible are devised and implemented. Unfortunately, most of today’s management models are not in synch with the new realities of globalization and the twenty-first century business world. The world has changed significantly over the past two decades, yet many strategic leaders still follow the theories and practices that were developed during the 1980s and 1990s. While such management constructs were innovative methods during the later years of the twentieth century, they are based on the realities of the times. Most of the models viewed the business world in the context of the developed countries and Western business philosophies. They were underpinned by many assumptions that were relevant for the major markets like those in the US, UK, Germany, France, Japan, etc. The underlying perspectives were based on political stability, economic freedom, open exchanges, linear increases in market demand, affluent populations with significant disposable

income, and well-established infrastructures. Today, many of those assumptions and perspectives are questionable, especially on a global basis. The economic, social and environmental conditions and trends are now less predictable and more volatile. Many factors and phenomena play out on a global scale. The global economy with its numerous interconnections and interrelationships brings with it many risks and uncertainties. With all of the improvements in management science, managing global corporations is still an extremely risky venture. Globalization requires global corporations to recognize new responsibilities, if they plan to create value and enjoy success. Paul Hawken (2007) in Blessed Unrest discusses the challenges of globalization (p135): One of the failures of the arguments opposing market globalization is the visible lack of an alternative economic model that might address the plight of the world’s poor. The failure of those making the case for globalized free trade is their inability to adequately address the results of rapid economic change in human and ecological degradation, roughly in equal measure, incomparable through they may seem. Hawken clearly points out the problems with the prevailing business situation. The present form of globalization is not inclusive. It does not provide the necessary support for the poor of the world nor does it include a scope wide enough to assure that solutions are complete.

Insights about Global Realities and Possibilities The global economy includes all of the existing, emerging and potential markets and customers in the world. One of the most significant underlying approaches in the drive to be more successful is to make products and services more affordable through design innovations and incorporating

23

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

customers’ needs and expectations in the solutions. Such methods have been in play for several decades in the developed countries as companies like Walmart and Toyota have become global giants and great financial successes through innovations to make their products and services both more affordable and their systems more productive and cost-effective. Globalization requires that businesses and governments become key participants in developing, supporting and advancing the social, economic, technological, market, and environmental underpinnings of the global community of nations and people. The underpinnings include assuring that the recipients of the solutions, especially the customers, stakeholders, and societies of the world, are provided with right products and services that have been designed and delivered from an external perspective, not just those of business leaders and/or high-level government officials, and that everyone’s well being is positively enhanced and not exploited. The multi-dimensional perspective of globalization includes the effects and impacts on a much larger scale, including all of the driving forces of change. The resulting management constructs are more complicated because reality and future requirements have to be examined from multiple views involving more intensive analysis of the salient forces and more in-depth understandings of the interactions and interrelationships between the forces. Moreover, the analyses require exploring the possibilities as well as the realities, i.e. what could be or should be not just what is. Thus, it is not just a simply matter of obtaining information and data and discerning what is happening; it also involves getting to the underpinnings of reality and trying to ascertain what could be done instead of just trying to understand what is being done. It involves a mindset shift from exploring “what is” to “what could be.” Strategic leaders have to view human developments and the elimination of poverty in the least developed countries as enormous opportunities

24

for transforming non-customers into customers. Moreover, strategic leaders in rapidly industrializing countries have to create positive outcomes without overwhelming the social world and the natural environment with pollution and wastes. For instance, strategic leaders in China are expanding their industrial outcomes at incredible rates, but in doing so they are creating wastes streams that may become impossible to mitigate in just a few years. Air and water pollution may be the limiting factor in China’s quest to be a global economic power. Such difficulties are much easier to correct before the industrial facilities and power plants are built. Once the plants have been designed and constructed, it is often close to impossible to retrofit pollution abatement on a cost-effective basis. With positive actions, strategic leaders have the opportunity to solve future problems at low investments that in the long-term are inconsequential to overall economics of the processes. Failure to do so may result in significant long-term costs, expenditures, and possible failures. In Globalization: A Critical Introduction, J. A. Scholte (2000) identifies five categories that help to articulate what globalization is as follows (p15-17): •

•

•

•

•

Internationalization-the growth of international trade and interdependence among countries and participants. Liberalization-reducing government imposed trade restrictions on the movement of goods between countries. “Universalization”-spreading of concepts and experiences to people around the world in harmonizing aspirations and outcomes. Modernization- spreading social structures around the world affecting local self-determination and destroying local cultures. “Deterritorialization”-reconfiguring geography so that social space is mapped out in terms of territorial places, territorial distances, and territorial borders.

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

Scholte’s perspective provides a sense of the complexities involved in globalization. Clearly, globalization involves moving away from just economic theories about international trade and exchanges to the more integrated business world, in which all of the driving forces are considered and acted upon from a unified perspective. Moreover, there are many positive aspects, but as indicated by Scholte, there are many concerns and issues that have to be dealt with, especially those impacting social institutions like the destructions of ingenious cultures and languages. Globalization today is more than economic forces, political decisions and geography. The expanding physical and informational links between distance markets have spawned a better understanding of cultural and regional similarities and differences among people. Public policy directives in the developed countries to eliminate historic barriers to trade and commerce contribute to common markets and more open communications and travel. However, the evidence about whether globalization is real does not provide a compelling answer. Globalization can be viewed as part of the evolutionary track of expanding opportunities for economic and social activities and interactions. It may be viewed as simply a linear expansion of the economic power that has migrated from the Western countries, principally the G7, to a few new players who are vying for the share in the economic riches. This perspective is not a new paradigm for achieving growth and improvements for all people, but one of simply adding new players to the world elites. The new powerhouses are China, India, Brazil, and Russia (BRIC countries). The current form of globalization may lead to more intense competition among the key players without regard for the broader social, economic, and environmental factors. New companies in the BRIC countries may focus extensively on economic outcomes and try to gain superior positions against the old line corporations like BMW, DuPont, Ford, IBM, Pfizer, Proctor & Gamble,

Shell Oil, Unilever, and thousands of others. Emerging companies may use their strategic advantages of low-cost labor and positive cash flow to grow rapidly. They may quickly become global players. In this scenario, globalization is really a different manifestation of the old world of the economic models of the twentieth century. The main competitors not only seek to dominate customers and markets, they try to monopolize the essential resources for production through whatever means available. For instance, companies in China are trying to secure sources of raw materials around the world from aluminum to zirconium. Moreover, with the numerous examples of toxic substances being used in producing products or incorporated in the products, there are great concerns that Chinese companies in particular are not following prescribed protocols or generally accepted practices for ensuring safeguards, consumer protection, proper work standards, and environmental protection. Globalization must include the whole context of reality (inclusiveness), involve providing the best solutions possible (innovativeness), build enduring and trust-based relationships with customers, stakeholders, partners and people around the world (connectedness), provide the requisite information about products, processes and services to all customers and constituencies (openness), and ultimately, ensure that people are successful and that success is enduring over time (effectiveness). To do this, strategic leaders must embrace the importance of the social underpinnings, recognize and respect cultural differences between societies, protect and preserve the natural environment, create and deploy the best technologies and products possible, contemplate non-traditional and countervailing perspectives that reveal ways of doing business more efficiently and effectively, and understand the needs of the future as well as the expectations of the present. Adil Najam, David Runnalls, and Mark Halle (2005) of the International Institute of Sustainable Development in their article, “Environment

25

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

and Globalization: Five Propositions”, identify several challenges and opportunities associated with globalization (P10): 1. The rapid acceleration in global economic activity and our dramatically increased demand for critical natural resources undermine our pursuit of continued economic prosperity. 2. The linked processes of globalization and environmental degradation pose new security threats to an already insecure world. They impact the vulnerability of ecosystems and societies. And the least resilient ecosystems. The livelihoods of the poorest communities are most at risk. 3. The newly prosperous and the established wealthy will have to come to terms with the limitations of the ecological space in which both must operate, and also with the needs and rights of those who have not been as lucky. 4. Consumption-in both the North and Southwill define the future of globalization as well as the global environment. 5. Concerns about the global market and global environment will become even more intertwined and each will become increasingly dependent on the other. These perceptions are very useful when exploring the meaning and future aspects of globalization. It is crucial to realize that globalization is accelerating and that the availability of resources is a significant strategic factor for the sustainable success of global corporations. For most the twentieth century, competition played out in the domain of the markets and the drive for revenue and profits. Today, the availability of natural resources, especially metal ores, petroleum and water, is among the most critical factors for achieving strategic success. Resource vulnerabilities are becoming worrisome. Such vulnerabilities are multifaceted. They include being unable to handle all of the wastes being

26

generated and lacking the capabilities to mitigate, if not eliminate, pollution and hazardous wastes. Failures to resolve such difficulties may limit the overall economic and market potential. As more people around the world expect and demand products and service, the economic realities have to be improved dramatically to satisfy all of the needs and at the same time keep the negative effects and impacts under control and mitigated to the extent possible. The world is more complex and is expected to become more interdependent as emerging markets take their place in the business world of the twenty-first century.

A MULTI-DIMENSIONAL MODEL FOR THE ADOPTION OF SUSTAINABILITY The Strategic Logic for the Adoption of the Model External context in the long term drives change and the opportunities and challenges facing global corporations. In the days when most corporations primarily focused on their home markets, the scope of their enterprises was relatively small even in the case of MNEs. For most of the early twentieth century, corporations obtained most of their revenues and profits from their national markets. Most MNEs participated in exporting and licensing and the large ones often had subsidiaries and operations in the other major economies. As such corporations expanded internationally during the last century, their external context did become more complicated with a greater geographic scope. They did adapt their business models to recognize the additional forces and factors that required attention and actions. However, the complexities of the situations were mitigated to a large extent because there were many similarities between the most advanced national economies. For instance, all of the G7 countries had relatively stable political, social, and economic systems and structures. The markets were generally expanding and custom-

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

ers demanded fairly similar products. Variations in demand usually were easily accommodated through product innovations and modifications in marketing methods. While there were major differences and culturally based requirements like the French preferences for their own wines and American preferences for fast food, most MNEs accommodated the market-related expectations. As discussed earlier, the business world changed dramatically in the 1990s. Free trade was expanded with the formalization of the EU and the North American Free Trade Agreement (NAFTA). The EU enhanced economic exchanges throughout most of Western Europe and NAFTA eliminated many of the trade restrictions between Canada, Mexico and the US. While the underpinnings and implications of the EU and NAFTA are profound and beyond the scope of this discussion, such changes expanded the prospects for trade and business growth by integrating national economies into regional ones. The changes were more compelling in the EU than in North America. The difference might be explained by that fact that the national economies of the leading European countries (Germany, France, UK and Italy) were more or less coequal, whereas the US economy overwhelmed the economies of Canada and Mexico. Moreover, US economy was already interconnected with many other national economies on a global basis. Regionalization introduces many more variables to the scope of the business environment. As the scope expands, strategic leaders of global corporations have to modify their perspectives of what is necessary for achieving success and adopt new models for including the essential elements. Most importantly, strategic leaders have to shift their strategic thinking from what the company has to do to serve its home market to how it can meet the needs and expectations of more complicated market situations. In a nutshell, they have to become market-centric instead of company-centric. They have to transition from basic constructs like improving their competitiveness in markets, building a large portfolio of products and services,

obtaining efficient and effective operations, and maximizing profits to more advanced approaches like achieving market leadership, creating cuttingedge brands that are unique, establishing strategic direction for exceeding expectations, and obtaining desirable market shares. The logic behind the transition is not based on an “either-or” situation, but a realization that the scope and scale have to become much greater as a corporation moves from national markets to regional ones. It means that the basic requirements in serving national markets are still important, except that additional perspectives are also critical for achieving success in a much large business environment. It is important to point out that these discussions only cover some of the most salient aspects and that in both cases the requisite models are much more complicated than outlined herein. In most cases, global corporations have made the transition from focusing on national markets to regional or more broadly based markets, especially considering the phenomena in the developed countries. Obviously, some corporations are more successful than others and that outcomes are dependent on circumstances and the capabilities of the organizations involved. Gary Hamel in The Future of Management (2007) suggests the “there’s little that can be said with certainty about the future except this; sometimes over the next decade your company will be challenged to change in a way for which it has no precedent (p41). More recently, many global corporations are struggling with the complexities of the global business environment. Globalization has taken root, but the means and mechanisms for achieving success in the global economy are not well established. Most strategic leaders are still using management constructs that were developed for managing in national or regional economies. While some of the approaches may be useful in the global business environment, many lack the scope and sophistication for assessing, understanding, and managing the realities impacting global corporations.

27

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

Managing in the global economy necessitates more comprehensive and sophisticated management constructs and models for realizing extraordinary performance and achieving longterm success. Globalization requires that strategic leaders consider, analyze, engage, strategize and execute from the very broad perspectives. While it is impossible to know and manage everything in the world, sophisticated strategic leaders have to be holistic in their thinking and have inclusive strategies, actions and decision making, if they except to realize success in a complex and turbulent reality. In a global setting, global corporations have to become enterprise-centric, not just market-centric. They have to recognize that success depends on more than addressing markets and satisfying customers and stakeholders. It involves incorporating all of the driving forces and facets of the global business environment into the strategic logic of the corporation and the models used for decision making. Globalization necessitates a transformation in management constructs and models from marketbased approaches to inclusive and innovative ways of realizing sustainable success. The transformation to a broader scope using more sophisticated constructs and models does not mean that the traditional constructs and models are no longer appropriate or useful. Some may be embedded within the systems and structures of the more contemporary models; others can be applied in special cases, in which the underpinnings and forces are less complicated. For instance, Southwest Airlines (SWA) is a specialized US airline that successfully serves small markets. Its model is fine-tuned to the US and its business environment is national in scope and nature. While global forces impinge on all corporations, SWA’s strategic leaders have chosen to focus on a narrow perspective. Most strategic leaders realize that their corporations must be more capable, innovative and responsive. They have made improvements; however, in many cases the improvements are simply not good enough to stay ahead of the changes

28

and expectations in the business environment. For instance, for more than a decade many strategic leaders in the developed countries viewed globalization in terms of outsourcing processes and activities to lower their cost structures. They were company-centric focused on improving the sales and profits of their products and services. While strategic leaders believed that such strategies and actions would lead to profound outcomes and financial success, such theories were sound in the short term but over time have become less powerful as competitors followed the same line of thinking. Such methods have helped consumers in the developed countries obtain more affordable products and services and allowed governments to keep inflation low. However, the hoped for gains in profitability became less and less viable as outsourcing evolved into a global phenomenon. Ultimately, management constructs that can be easily copied are subject to being generic approaches with limited advantages, if any at all. Simple methods have the allure of being easy to understand and implement, but they also have the risk of being quickly duplicated by competitors. Table 1 provides some of the salient factors involving the transformation from national market to regional one and then to global perspectives. The higher level of sophistication identified under “global” in Table 1 provides strategic leaders with the prospects of realizing more enduring performance and success. While very little in the business world lasts forever, the broader the scope, the more inclusive the model and the more sophisticated the elements, the more difficult it is for others to emulate the strategies and actions. Sustainability is the imperative of the twentyfirst century. It implies exactly what the term means, i.e. to support from the foundation, to strengthen the framework, to endure over the course of time, to keep going regardless of the challenges, etc. For instance, it is fool-hardy to create new products, invest in new capital equipment, and develop new ventures among numerous other business initiatives unless they are sustain-

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

Table 1. Salient factors pertaining to national, regional and global markets Scope

National

Regional

Global

Focus

Company

Market

Business Environment

Imperative Means Mechanisms Measures Strategies

Competitiveness Products & Services Operations & Marketing Process Innovations Profitability Competitive Strategies

Market Leadership Cutting Edge Brands Strategic Planning Product Innovations Market Share Market Strategies

Sustainability Sustainable Solutions Sustainable Development Strategic Innovations Sustainable Success Preemptive Strategies

Dimensions

Salient Factors of the External Context

Market

Customers Competitors National Stakeholders

Customers Allies & Partners Regional Stakeholders

Customers & Non-customers Contributors & Recipients All Stakeholders

Social

Communities Employees Shareholders

Civil Society National Identity Social systems

All people Cultural Diversity Social Structure

Economic

Production / Consumption Competitive Positions Revenue & Profits

Value Proposition Market Positions Economic Performance

Value Creation Value Maximization Sustainable Success

Technological

Products/Services Dominant Technologies Incremental Innovation

Innovative Products Advanced Technologies Radical Innovation

Cutting Edge Solutions Clean Technologies Strategic Innovation

Environmental

Regulatory Compliance Pollution Prevention Waste Management

Beyond Compliance Green Management Waste Minimization

Openness & Transparency Sustainable Enterprise Zero Defects & Wastes

Political

Legal System Political Structure Regulatory Mandates

Political Economy Governmental Structures Directives

International Laws and Policies International Organizations International Treaties

Ethical

Values and ethics Accepted Principles Established Behaviors

World Class Standards Axiomatic Principles Proper Behaviors

Universal Standards Global Compact Profound Respect

able over the long term. Sustainability is about realizing ongoing success from every dimension, not just the economic or environmental ones. While there are strategic leaders, practitioners and scholars who discuss concepts like “environmental sustainability,” sustainability is really about integrating the social, economic, environmental, technological, ethical, political, and market forces and considerations into a holistic perspective (model), in which success is obtained in every dimension. For instance, outsourcing of jobs from developed countries to developing countries may result in improved cost structures, but in the long term the consumers in the developed countries may not be able to afford the products, if they

do have sufficient disposable income; therefore, such approaches may not be sustainable. Sustainability requires an integrated model for decisions, strategies, solutions and actions. Sustainability is facilitated through sustainable solutions. It is based on the realization that customers and stakeholders really want and desire solutions. A sustainable solution is the complete package of everything that is necessary to provide the customers and stakeholders with their own successfully outcomes. It includes the products and services, the support mechanisms, the complementary products, and all of the short-term and long-term requirements to make the solution succeed and endure. 29

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

SD involves the mechanisms that are employed to create sustainable solutions, sustain success, and advance sustainability. It is underpinned by strategic innovations. Strategic innovations are particularly powerful when they create extraordinary value for all contributors and recipients and eliminate difficulties and challenges across the business environment. SD requires preemptive strategies for leading change. From a sustainability perspective, strategic leaders have to have the confidence and courage to develop new solutions that offer extraordinary value and new-to-the-world outcomes. In my book, Enterprise-wide Strategic Management: Achieving Sustainable Success through Leadership, Strategies, and Value Creation, the construct of preemptive strategies is developed and discussed in detail. Preemptive strategies are cutting-edge methods for leapfrogging expectations and competitors and achieving sustainable success. The following excerpts provide the main perspectives (Rainey, 2010, pp373-376): Preemptive strategies are proactive approaches for leading change and taking the initiative to aggressively move on opportunities and challenges in the business environment before such actions are expected or become obvious. Preemptive strategies necessitate changing and even disrupting industry or market space norms through fast-paced, hard to duplicate strategic actions that provide distinctive and sustainable advantages for first mover, fast follower, or strategic change leaders. Preemptive strategies eschew the notions of reacting to change or anticipating changes only slightly ahead of a necessity for action. Preemptive strategies imply that strategic leaders seek out every opportunity to forge positive changes and exploit new opportunities before customers or competitors understand the implications. Preemptive strategies require extremely assertive actions in making dramatic or radical improvements to the external and internal dimensions of

30

[the company and/or] business units… Aggressive does not mean increasing the rivalry among competitors; it does mean taking every opportunity to make profound changes that advance the well being of customers, the extended enterprise, the organization, and all of the key contributors. Preemptive strategies usually involve the full integration of the whole enterprise into a seamless and highly assertive value delivery system (holistic management system) that is fully capable of planning and executing every action at the highest level of quality and performance. Most importantly, preemptive strategies involve strategic innovations that significantly or radically improve underlying technologies, products and servicesthe solutions. Such innovations include inventing and validating clean technologies, developing and delivering more valuable solutions, enriching and exploiting improved process capabilities, and reinventing the strategic management system and value delivery system with outstanding intellectual capital, capabilities and resources. Preemptive strategies involve transitions and transformations to the next higher levels of achievements and sustainable outcomes… [Preemptive strategies] involve out-of-the-box thinking about how to move closer toward perfection and obtain the best solutions for customers and stakeholders, and to build enduring relationships with all of the essential contributors and recipients. Strategic thinking shifts from the competitive spaces of the past to preempting the market spaces and creating the business enterprise of the future. This includes integrating the extended enterprise into a complete system, leading change to secure sustainable advantages, and using all of the capabilities and resources in the most effective and least damaging ways. Sustainability involves applying the most sophisticated management constructs possible to attain market leadership and value creation. In the

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

context of globalization, it provides the underlying elements and perspectives that make the concept of globalization truly global. Sustainability integrates of all of the external driving forces into a coherent model for creating value and sustainable solutions for the present and future. Sustainability is more than the “triple bottom line” articulated by John Elkington (1997, P2). The “triple-bottom line” includes social, economic, and environmental considerations in managing businesses. While Elkington’s concept is an important contribution to management theories, preemptive strategies and sustainable solutions necessitate dynamic actions to produce sustainable success, especially from the development and deployment of new-to-theworld technologies and products.

The Model: Sustainability in the Context of Globalization and Strategic Innovation Sustainability and SD fit well in the context of globalization. They are essential for true globalization. However, sustainability is a preeminent management construct in its own right with or without globalization. Moreover, sustainability and SD are inextirpable linked with strategic innovations. Given the current state of affairs in the business world, global corporations are a long way from achieving the level of sophistication that is necessary to achieve a modicum of sustainability within a decade or two. In my book, Sustainable Business Development: Inventing the Future through Strategy, Innovation and Leadership, the important factors for realizing sustainable are detailed. Some of the key underlying concepts include (Rainey, 2006, pp678-680): Management across the world is engaged in the relentless struggle to keep pace with technological, social, economic and environmental changes that seem to accelerate as time moves forward. Great strides in competitive advantages are marginalized by the gains of peers and competitors, and the changing business environment.

Where past breakthroughs led to competitive advantages that lasted for decades, the effects of such achievements today are often measured in months. However, with all of the challenges, there are also enormous opportunities, opportunities to lead change and move beyond the social, economic and environmental mandates. Across the world people want solutions to the problems they face. The opportunities for providing these solutions range from finding ways to expand health care and obliterate hunger to protecting natural resources and eliminating waste streams. The penultimate objective is the quest for greatness, the quest for perfection, not perfection itself. It is akin to the building of the great cathedrals of Europe. The architects and builders recognized the daunting nature of such projects. They knew that it would take many generations of skilled and dedicated people to realize the dreams. Nevertheless, they were willing to invest their time and efforts in the process because they believed in the vision. They understood that laying the foundation and building solid walls would provide the means for others to continue building. Moreover, they realized that the succeeding generations of their relatives and compatriots would enjoy the fruits of their labor and that the structures would provide humankind a lasting testimonial of their contributions and achievements. Sustainability requires dedication and ongoing development. While continuous improvement was one of the main management themes of the late twentieth century, the pursuit of sustainability and SD are the critical perspectives driving global corporation in this century. Sustainability is the relentless pursuit toward perfection through innovativeness, inclusiveness, and connectedness. The requisite model includes the key elements for leading change through innovation, managing the systems and structures across the organization and the extended enterprise, and building enduring relationships with people through social responsibility. The model provides a framework pertaining to how the key elements interrelate. The

31

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

Figure 1. Model for improving the adoption of sustainability in the context of globalization and innovation

model is depicted in Figure 1; it is an adaptation of the model presented in my book, Enterprisewide Strategic Management: Achieving Sustainable Success through Leadership, Strategies and Value Creation (Rainey, 2010, p160). While the framework maps out the essential elements, it is impossible to articulate all of the details. The model offers several exciting perspectives: •

•

32

The model provides an inclusive, sophisticated, and broader framework for leading change in complex business situations, in which strategic leaders create extraordinary value for all. The focus is on the global business environment and market spaces. Market spaces

•

include existing markets, emerging ones, customers, and non-customers. While many existing models are either company-centric based on core competencies or competition-centric based on rivalry, sustainable success focuses on making people the center of strategies and actions and making them successful. The underlying aspirations include creating sustainable solutions and achieving sustainable outcomes through SD and strategic innovations, not just making shortterm profits at the expense of long-term success. Given that people are central to sustainable success, building enduring re-

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

•

lationships is essential for realizing the expected outcomes on an ongoing basis. The model has holistic connections with strategic management and operational constructs. It focuses on integrating the corporation’s strategies and actions with the external contributions of the extended enterprise and the needs and expectations of the market spaces. This represents a quantum leap forward in connecting the systems, structures, processes, and practices that facilitate developing and deploying the best solutions possible.

The model addresses perspectives and constructs that are in line with 21st century dynamics. It examines the business environment in the context of the whole global landscape, and strategic leadership and management in the context of sustainability and sustainable development. Indeed, it examines the whole perspective rather than focusing on the parts, which is often the prevailing methodology. For instance, the model integrates concepts for dealing with customers and stakeholders and building relationships rather than just focusing on marketing and selling. It recognizes that customers want solutions that exceed their needs and expectations. It discusses solutions in the context of social, economic, technological, ethical, environmental, and market space considerations. It explores not only the prevailing situation but how innovative solutions taken from the market perspective can create new opportunities. It includes the systems, structures, and processes required for obtaining results. These perspectives are reinforced by the contributions of C. K. Prahalad and M. S. Krishnan (2007) in the new age of innovation, in which they state that building relationships with external contributors are a main source of competitive advantage (p46).

The Means: Sustainability and Sustainable Development Sustainability is the overarching constructs that includes the philosophical perspectives, theoretical constructs and practical approaches for leading change in global corporations and managing their businesses, enterprises, and organizations. The intellectual challenges include determining the vision and strategic direction and the strategic leadership philosophies and constructs for leading change. The simple yet most compelling philosophical perspective is putting the business environment or external context first before thinking about internal context. This fits the concept of “people, planet and profit,” (Bergmans, 2006, pp117-119). It is based on the recognition that people and the natural environment are the overarching considerations and that profit is important for sustaining companies, but profit is really a derivative of good analysis, decision making, strategies and actions. Sustainability is a continuum of strategic thinking and actions that is internally driven by visionary strategic leadership. Strategic leaders have to have the courage and dedication to take on incredible challenges, to think about radical ways of providing solutions, and to use preemptive strategies for realizing extraordinary outcomes. Without direction from strategic leaders, sustainability and SD do not get traction. They require concerted efforts and significant investments. Strategic leaders have to provide the resources and commitments to implement the revolutionary ways to do more good and less bad as Peter Senge discussed in his book, The Necessary Revolution (Senge, 2008, pp33-41)) SD is often conceptually accepted by global corporations. While the underpinnings and aspirations are often clear, it involves a complex array of solutions, systems, structures, processes and techniques. Unlike most of the major initiatives of the last century like strategic planning and total quality management, SD cannot be implemented

33

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

on a project basis, in which significant efforts and funds are allocated to create the systems and then one can enjoy the results at completion. SD involves a long-term approach for transforming the corporation and its enterprise(s) into an integrated and innovative entity. SD requires an embedded structure that is parallel to the salient factors associated with the transition from national and regional markets to global ones as portrayed in Table 1. The key elements for being successful in national markets are also necessary for success in the global economy. As depicted in Figure 1, strategic leaders have to provide the key elements for establishing the basic foundation and the strategic direction. They define the values, principles and ethics of the organization based on the broader social, legal, ethical, and environmental responsibilities. Strategic leaders and the directors of the corporation determine the governance structure and company policies. They must set strategic direction, the missions and the objectives. These elements are translated into strategies and action plans that are implemented by the organization and its enterprise. Strategic leaders ensure that the capabilities and resources of the organization are aligned with the strategic direction. Moreover, strategic leaders allocate the resources and provide learning opportunities for employees and contributors across the enterprise. Operational management engages in the implementation and execution. It includes a myriad of the critical systems and processes that a used to realize outcomes and achieve success. They include, but are not limited to, marketing, finance, quality management, supply chain management, environmental management, health and safety management and waste management. Results are accomplished through support systems and structures, programs, protocols, and tactics. While most global corporations have well-functioning operating systems and reasonably effective processes, the management constructs are often based on twentieth century requirements rather than on the current realities or future ones. Like many of the

34

military situations and organizations of the past, strategic leaders are often well prepared to fight the battles of the past, instead of being proactive and contemplating what is necessary for the future. Strategic leaders too often think about what their organizations are instead of what they must be. Understanding the past is important because it gives us insights about the social and economic dimensions, but transforming the corporation and organization to lead change and being ahead of mandates and expectations is the essence of SD.

The Mechanism: Strategic Innovations The transformation to highly levels of achievement is predicated on strategic innovations. Strategic innovations are radical changes to the corporation, its business units, the extended enterprise, the organization, the leadership, relationships, and the technologies, products and processes. Strategic innovations involve high-level investments into employees, learning, intellectual property, know-how, business portfolios, technological underpinnings, brands, and product lines. They also involve the tangibles of developing and commercializing new products and creating and building new business ventures and the intangibles of enhancing one’s reputation and acquiring new knowledge. Strategic innovations make sustainability and SD real for the people who are task with carrying out the actions. Strategic innovations are a global corporation’s answers to how to develop a unique place in today’s turbulent and complex business world. Global corporations seek practical approaches to their quests to be competitive and achieve ongoing success. While strategic innovations do not always result in significant advancements in competitiveness and market success, they do offer a greater probability of achieving game changing outcomes that are more difficult for competitors and would be rivals to emulate. However, strategic leaders often view strategic innovations, i.e.

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

Table 2. Types of strategic innovations Categories

Main Types

Salient Aspects

Solutions

Radical technological innovation (RTI)

RTI involves developing new or dramatically improved technologies that change the basis for delivering value. Creating a new-to-the-world solution starts with insights and innovativeness. It incorporates the full spectrum of internal and external ingredients to create exceptional value and realize sustainable success.

Systems

Business model innovation (BMI)

BMI involves a conceptual combination of all of the entities and the patterns of interrelationships and interfaces that are linked together in formal and informal arrangements to create and deliver value-producing outcomes that are guided by strategies and actions. It also involves starting new business units that have superior solutions with new technologies.

Structures

Leadership and organizational development (LOD)

LOD is critical for realizing sustainable success. It involves the development of new competencies and capabilities and the transfer of know-how and management wherewithal within the corporation and enterprise and between the generations of leaders and practitioners. Leadership and talent development are crucial for assuring the going commitment to sustainable success.

radical innovations, as risky and subject to many perils. While it is clear that strategic innovations are more challenging, they are not necessarily more risky than incremental innovations or doing nothing when all factors are considered. While the potential results of incremental innovations are usually more predictable and successful from a product or process point of view, the actual business outcomes are often less fruitful and enduring. For instance, improving obsolete products may result in additional sales and revenues in the short term, but the resultant business performance and financial outcomes are often unchanged and the products are eventually replaced or eliminated. The investment in incremental innovations may be positive, but the business may lose valuable time and money pursuing marginal outcomes. Strategic innovations are necessary to assure that global corporations stay ahead of the driving forces and expectations in the business environment. Among the most crucial are strategic innovations that create unique advantages for the corporation through innovative solutions, systems, and structures and build enduring relationships. Table 2 lists some types of strategic innovations. Innovative solutions engender outstanding combinations of value creation, value innovation, and value delivery expressed and supported using

the value systems and extended enterprise. Radical technological innovation is a primary mechanism for effecting strategic innovation. The strategic leaders initiate the development of new technologies using the research and development (R&D) programs and projects. While there are many variations, the corporate R&D generally involves developing new-to-the-world technologies and/or products with potentially exceptional business value. Radical technological innovations depend on external context. Exploring the global business environment and the market spaces and determining how the corporation and its enterprise(s) fit the needs and requirements for the future are effective ways for initiating the long process of creating new technologies. Radical technological innovations are based on insights from the business environment and the organization’s imagination about what can be accomplished. Global corporations can take a proactive approach and invest into transforming their businesses by developing new technologies that are cleaner and more efficient and effective. Some of the best opportunities are those involving eliminating the negative side of existing technologies. This results in new-to-theworld products that have superior attributes and value. Strategic leaders must allow for risk taking

35

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

and even failures to occur as the R&D people find new ways of achieving success. Moreover, creating radical innovations that solve problems for people in emerging markets are also great opportunities. Antoine van Agtmael (2007) in his book, The Emerging Markets Century, details how many of the emerging companies in BRIC countries, Taiwan, South Korea and Mexico are gaining footholds as world-class competitors through brainpower and innovation. He cites the incredible progress made by companies like Embraer of Brazil, Lenovo of China, Samsung of South Korea, and TSMC of Taiwan. These companies are vying for their place in the world. Historically, global corporations used simple business models for managing their businesses. The general methodology employed a de-coupled, hierarchical approach that included operations management of the value system on the bottom and strategic business management at the top. Traditional business models limited the scope of the analytical framework to facilitate decisionmaking and simplify the interactions. Due to the lack of integration at the operating level, strategic leaders had to play a significant role in resolving difficulties within the system. The strength of the approach became the weakness. During the mid-1980s Michael Porter’s models of the value chain and the value system dramatically shifted the management constructs from a vertical organizational approach to a system approach with horizontal processes (Porter, 1985, pp33-35). A higher level of sophistication is necessary for incorporating all of the forces impinging on the entire organization and its linkages, partners, stakeholders, and customers. An effective business model is a comprehensive management construct that forms the basis for analysis, understanding, decision-making, continuous improvement, as well as radical innovation. It is a unifying approach that integrates the people, the processes, the practices and the programs into a comprehensive management system. Today, fully integrated business models are pivotal for success as more

36

corporations depend on supply networks, strategic alliances, and external relationships for sustaining success. Business model innovation encompasses the whole, both internal and external, and the present and the future. It is inclusive of all of the essential dimensions in managing and leading an organization. Business model innovation involves the convergence of the solution, systems and the structure. In Leading the Revolution, Gary Hamel (2000) discusses the ‘age of revolution’. He suggests that “it is not knowledge that produces wealth, but insights into opportunities for discontinuous innovation” (p14). Hamel’s business model includes “four major components: core strategy, strategic resources, customer interfaces, value networks” (p70). He incorporates into the “new innovation” model the concept of a solution (pp283-313). He views innovation as an essential element for achieving strategic success. Given the diversity of the global competitive landscape and the expectations of people and society, the most important part of strategic innovation is the development of talent. Unlike the business world of the early twentieth century that was based on machine-driven methods, twentyfirst century corporations are based on intellectual capital. The core competencies and capabilities of the corporations are its true strategic assets. From strategic management and strategic innovation perspectives, people are the innovative force. They create the solutions and the systems. Leadership and organizational development address the needs of the people in the organization and how to enhance their knowledge and capabilities through learning and experience. Leadership and organizational development invoke a spirit to become the best and to build new capabilities and competencies for the emerging technologies and practices of the 21st century. It provides the means and mechanisms for the organization to acquire the new knowledge and skills to perform to the highest standards.

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

CONCLUDING COMMENTS Rapid changes in the business world over the last two decades have made most of the prevailing management constructs obsolete. In a global business environment of limited time and scarce resources, strategic leaders have to seek and develop innovative ways to keep ahead of change. This necessity is especially important for global corporations. Global corporations have to expand their reach and sophistication to create sustainable solutions, integrated systems, and robust structures that are proactive and unique. Good is no longer good enough. Global corporations have to lead change and become sustainable enterprises. They have to incorporate sustainability and SD in their models and ensure that they can exceed customer and stakeholder expectations and outperform competitors. Strategic leaders have to preemptive the market and competitive situations through strategic innovations that open the doors to new possibilities and success. They have to think about the whole enterprise and ensure that solutions and systems are fully aligned and providing successful outcomes for all contributors and recipients. Globalization without a multi-dimensional perspective is a prescription for enduring ongoing problems, challenges, and instability. Solutions have to be multifaceted and holistic. They have to produce win-win outcomes. They must avoid creating tensions and conflicts among people across the world. For instance, simply shifting jobs to low-wage countries to obtain low-cost products may result in cost-effective products that people in the developed countries cannot afford to buy because they lack employment opportunities and personal income. The model discussed in the chapter provides a framework for creating win-win outcomes that are balanced in terms of the social, political, economic, technological, environmental and ethical forces. Good solutions require an integrated approach with strategic leaders and contributors working together using strategic innovations. For most

global corporations, the focus shifts from “business as usual” approaches to creating sustainable solutions and developing holistic systems and structures to deploy the solutions. From a strategic perspective, the decision making methodology for strategic innovations has to become more comprehensive and farsighted. Decision makers have to be proactive. They have to use learning and acquire new knowledge to obtain a more comprehensive understanding of the realities. They must be thorough in their assessments of context to obtain insights about what the solutions have to be. Ultimately, they need to use their imaginations to envisions how to create the best strategies, solutions, and outcomes and to use the judgments of all of the participants in the decision making process. Great decisions are based on the collective wisdom and intellectual capital of the people involved. True globalization may only be possible in the context of sustainability, SD and strategic innovation. Otherwise, short-term successes may turn into complex challenges and difficulties that limit long-term performance and outcomes. For instance, pollution and wastes are critical factors that have to be eliminated via clean technologies and new-to-the-world products, if solutions are to endure. Future developments may be stymied because resources have to be allocated for cleaning up the messes created due to poor decision making or simply not available because of resource depletion. It is critical that business leaders, government officials and people understand, develop, produce and deploy sustainable solutions and achieve sustainable success. With true globalization, global corporations have to adopt a more inclusive and comprehensive model of their external and internal context, if they aspire to obtain competitive advantages, achieve outstanding business performance, and enjoy sustainable success. The underpinnings must focus on protecting future generations of people, preserving the natural environment, ensuring that the economic, social, environmental and financial interests of businesses and society continue well into the future. 37

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

REFERENCES Bergmans, F. (2006). Integrating people, planet and profit. In J. Jonker & Marco de Witte (Eds.), Management models for corporate social responsibility (pp. 117-125). Berlin, Germany: Springer. Elkington, J. (1997). Cannibals with forks: The triple bottom line of sustainable development. Oxford, UK: Chapstone Publishing. Esty, D., & Winston, A. (2006). Green to gold: How smart companies use environmental strategy to innovate, create value, and build competitive advantage. New Haven, CT: Yale University Press.

Rainey, D. L. (2006). Sustainable business development: Inventing the future through strategy, innovation and leadership. Cambridge, UK: Cambridge University Press. doi:10.1017/ CBO9780511617607 Rainey, D. L. (2010). Enterprise-wide strategic management: Achieving sustainable success through leadership, strategies and value creation. Cambridge, UK: Cambridge University Press. Scholte, J. A. (2000). Globalization: The critical introduction. New York, NY: Palgrave.

Hamel, G. (2000). Leading the revolution. Boston, MA: Harvard Business School Press.

Senge, P. (2008). The necessary revolution: How individuals and organizations are working together to create a sustainable world. New York, NY: Doubleday Publishing Group.

Hamel, G., & Breen, B. (2007). The future of management. Boston, MA: Harvard Business School Press.

The World Commission of Environment and Development. (1987). Our common future. Oxford, UK: Oxford University Press.

Hawken, P. (2007). Blessed unrest: How the largest movement in the world came into being and why no one saw it coming. New York, NY: Viking/Penguin Group.

van Agtmael, A. (2007). The emerging markets century: How a new breed of world-class companies is overtaking the world. New York, NY: Free Press.

Najam, A., Runnalls, D., & Halle, M. (2007). Environment and globalization: Five propositions (p. 10). Winnipeg, Canada: International Institute of Sustainable Development.

Willard, B. (2005). The next sustainability wave: Building boardroom buy-. Gabriola Island, BC: New Society Publishers.

Porter, M. (1985). Competitive advantage: Creating and sustaining superior performance. New York, NY: Free Press.

KEY TERMS AND DEFINITIONS

Prahalad, C. (2005). The fortune at the bottom of the pyramid: Eradicating poverty through profits. Upper Saddle River, NJ: Wharton School Publishing. Prahalad, C., & Krishnan, M. (2007). The new age of innovation: Driving co-created value through global networks. New York, NY: McGraw-Hill.

38

Business Environment: The business environment includes the external forces impinging upon the corporation. It includes the social, economic, political, technological, environmental, and market forces. It also includes the external dimensions of markets, stakeholders, and competition. Clean Technology: Clean technology involves advanced technological designs that maximize the positive benefits and minimize the negative defects, burdens, and impacts. It includes sys-

A Model for Improving the Adoption of Sustainability in the Context of Globalization and Innovation

tems, processes, equipment and know-how that eliminates, reduces or controls pollution and waste streams better than alternates. Construct: A construct is a theoretical framework or model used to analyze and determine strategies, systems, structures, and solutions. A construct is intended to be a representation of the dimensions and elements of business situations. It combines information, data and experience with theoretical thinking about how to view the business situation in light of its opportunities, challenges, and constraints. Context: Context provides the basis for analysis, understanding and decision making. It includes the business environment and the management systems of the organization. Context is framed based on defining the scope of the analysis and the inclusion or exclusion of variables. The context includes both time and space considerations. Extended Enterprise: The extended enterprise includes the contributors to the solutions and recipients who use the solutions. It includes customers, stakeholders, supply networks, strategic partners, related industries, competition, and infrastructure. It provides a framework for a descriptive, analytical, and structural understanding of the needs, opportunities, challenges, requirements, specifications, and the strategies and action plans. Globalization: The notion that the world economies are shifting toward a borderless economic structure, in which global corporations vie to satisfy customer demand on a global basis. Space and time are compressed and geography becomes less of a critical factor. Preemptive Strategies: Preemptive strategies are intended to gain sustainable advantages by

significantly improving the solutions, systems and structures. The focus is primarily on leading change and value creation. Product Innovation: Product innovation includes the initiatives, methods, techniques, and processes for making incremental improvements to existing products and services. It involves making evolutionary changes to the products employing the prevailing technologies and organizational capabilities. Radical Technological Innovation: Radical technological innovation involves creating new-to-the-world technology that brings about revolutionary changes. It often creates new industry or market structures or involves dramatic changes to the existing ones. It also involve making substantial changes to the existing strategic management system including developing new customers, new markets, new supply networks, and other related entities. Sustainability: Sustainability implies that all human and business activities are carried out rates equal to or less than the Earth’s natural carrying capacity to renew the resources used and naturally mitigate the waste streams generated. Sustainable Development: Sustainable development is a holistic management construct that includes the entire management business system from the origins of the raw materials to production processes and the customer applications and to the end-of-life solutions. Sustainable development involves making dramatic improves and positive changes to the full scope of relationships and linkages of the supply networks, customers and stakeholders, and support service providers for handling wastes, residuals and impacts.

39

40

Chapter 3

Product-Service Systems as Enabler for SustainabilityOriented Innovation:

The Case of Osram’s Off-Grid Lighting Friedrich Grosse-Dunker Dark Horse GmbH, Germany Erik G. Hansen Leupana University Lüneburg, Germany

ABSTRACT Corporations increasingly subscribe to the principles of corporate sustainability, which is generally described as the integration of economic, environmental, and social dimensions. As sustainability presents a new source of ideas and visions leading to new business opportunities and competitive advantage, the role of Sustainability-Oriented Innovation (SOI) is ever more emphasized. However, developing products under the paradigm of SOI is risky: both the product’s market success and (non-economic) sustainability effects are uncertain. Product-Service System (PSS) – i.e. a combination of products and services –constitutes a significant approach to overcome some of the limitations of SOI and, additionally, can spur the diffusion of SOI. In this chapter, we use an exploratory research strategy to further investigate the links between SOI and PSS. We present a case study on off-grid lighting in Kenya and analyze the sustainability effects on the product and PSS level. The complexity of SOI and the sustainability potentials of PSS are illustrated. Moreover, we also emphasize the role of a joint achievement of sustainability-oriented product innovations and PSS innovations.

DOI: 10.4018/978-1-61350-165-8.ch003

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

INTRODUCTION For the last decade, the prevailing form of doing business has been increasingly challenged by a number of problems such as climate change, environmental degradation, and social inequalities. These challenges culminate in the view that to only focus on economic aspects of business is ever more difficult or even impossible as it is essentially unsustainable (Hart & Milstein, 2003). From a business perspective, corporate sustainability seeks to address these issues by transcending the conventional responsibilities of businesses (i.e. to make profits) to also include non-economic aspects such as ecological and social responsibilities (Sharma, 2002; Schaltegger & Burritt, 2005). Scholars have lately emphasized to put sustainability at the core of the corporation, i.e. its products and services (Hart, 1997; Schaltegger & Wagner, 2010). New regulations, but also raising consumer demand for socially and environmental benign products drive the need for more sustainable products and services. The notion of sustainability-oriented innovations (SOI) thus embraces concepts, criteria, and processes to develop more sustainable products and services (Hansen et al., 2009). One important lever for SOI is the concept of product-service systems (PSS) or servitization (Baines et al., 2007; Mont 2001, 2004; Hansen et al., 2009). Generally, PSS approach represents a spectrum between pure products and pure services (Baines et al., 2007; Pawar et al., 2009). PSS where the manufacturer remains with the ownership of the products are especially interesting. In this case, PSS follows the idea that the environmental burden is dramatically decreased when switching from selling products to providing solutions through product-service combinations. In contrast to mid to long-term leasing and performance contracting in the business to business context (Williams, 2006), this chapter focuses on systems of shared use in business to consumer markets. Current empirical studies on shared use in business to consumer markets are usually case

studies (Baines et al., 2007) and focus on such as car sharing (Huwer, 2004; Engelhardt et al., 2003), ride sharing (Hansen et al., 2010), and on washing machine and power tools service centers (Mont, 2004). Besides few others (Devisscher & Mont, 2008; Manzini & Vezzoli, 2000), existing cases predominantly focus on developed nations. The cases often evaluate the sustainability impacts of PSS (Pawar et al., 2009, Devisscher & Mont, 2008). PSS is said to be a concept that “aims to improve overall system efficiency, along with improving efficiency of each system element” (Mont, 2001, 13). However, most of the case studies are limited to studies where existing products and technologies are integrated into a PSS, i.e. the innovation considers only the servitization of the unchanged product or technology. There is virtually no research on cases where the product innovation joins the introduction of the PSS. Our research question is thus twofold: (1) how can the mechanism of PSS help to introduce a sustainability-oriented product innovation? (2) Which sustainability effects materialize on the product level, which ones at the service level? This chapter addresses this gap with a case study approach (Yin, 2003) about a multinational corporation based in Germany that offers a product-service system in a developing nation. By concurrently addressing economic, environmental, as well as social impacts, the case highlights the multi-dimensionality of SOIs. We furthermore emphasize the importance of PSS as being an innovation enabler on a (technological) product level and therefore underline the importance of product-service offers in the context of sustainability. The remainder of this chapter is structured as follows: first, a literature review introduces the concepts of SOI, life-cycle assessments, and PSS. Building on this framework, a case study on off-grid lighting in Kenya is presented and its sustainability effects are analyzed. The results and implications of the case study are then discussed and future research directions are given.

41

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

BACKGROUND Sustainability-Oriented Innovation (SOI) There is wide agreement that the challenges of sustainability offer significant potential for product and service innovations and related business opportunities. Two arguments support this view. First, new social and environmental regulations and laws increase the pressure for innovativeness (“regulatory push”) (Fichter, 2006; Hockerts, 2008; Preuss, 2007). Second, sustainability presents a new source of ideas and visions leading to new business opportunities through new markets and customer segments (“market pull” or “vision pull”) (Hart, 1997; Day, 1998). Based on these insights, the importance of SOIs has generally been acknowledged (e.g. Hansen et al., 2009; Hart, 1997; Schaltegger & Wagner, 2010). However, recent studies show that only a minority of businesses consider sustainability as a source of innovation (Hockerts & Morsing, 2008). The reluctance in advancing SOIs can arguably be attributed to the high risks involved in this kind of innovation (Hall, 2002). These risks include not only the product’s economic success (Cooper, 2001), but also the direction of environmental and social sustainability effects of innovations, i.e. whether they contribute positively or negatively to sustainability. The latter type of risk is also termed directional risk (Paech, 2005). For instance, environmental innovations can lead to negative societal impacts, i.e. to a problem of “eco justice” (Schaltegger & Burritt, 2005), as the case of bio-fuels demonstrates (Kölsch & Saling, 2008; Rennings & Zwick, 2002). On the other hand, conventional innovation projects sometimes result in innovations with positive sustainability effects (Fichter & Arnold, 2003). Due to the multi-dimensionality of sustainability targets (social, environmental, and economic targets) and the dispersion of innovation sustainability effects, the assessment of innovations with respect

42

to sustainability is considered highly complex (Fichter, 2005). Beyond the triple bottom line reflecting economic, social, and environmental considerations (Elkington, 1998), also referred to as the target dimension of innovation, two other dimensions – life-cycle and innovation type– are important for assessing sustainability effects of product innovations. Both dimensions are addressed in the subsequent sections.

Life-Cycle Assessment and SOI The life cycle dimension refers to the physical life cycle of a product from resources extraction to end-of-life treatment. Life-cycle assessment (LCA) has become a major research field in literature (Kloeppfer, 2008; Mont, 2004; Spillemaeckers & Vanhoutte, 2006), though it also has some limitations (Schaltegger, 1997). Whilst the emphasis in life-cycle assessment has been on environmental considerations, integrated sustainability analysis has gained research attention as well (Spillemaeckers & Vanhoutte, 2006). Table 1 shows a matrix based on the life-cycle dimension and the triple-bottom line.

From Products to Product-Service Systems (PSS) Innovations are commonly classified into the categories of product, process, organizational, or market innovations (Hausschildt & Salomo, 2007). The current chapter focuses on product innovations, and thus on new product development. Within the latter understanding of innovation, people are usually concerned about the technological dimension of products (and – from a life-cycle perspective – of processes related to manufacturing the product). For instance, products can be manufactured with improved eco-efficiency (e.g. they consume less energy; Schaltegger & Burritt, 2005) or companies shift the product portfolio towards addressing environmental challenges

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Table 1. Sustainability of products/technologies related to the physical life-cycle (Hansen et al., 2009) Target dimension

Life-cycle phases Manufacturing

Packaging/ distribution

Use/ maintenance

End of life

Economic

Production efficiency

Efficient packaging; efficient logistics

(Technical) quality

Costs of take-back/ disposal/ landfill

Environmental

Use of environmental friendly materials and processes

Reduce packaging resources; minimized transports

Durability; energy consumption

Dangerous materials; recycling, re-make, or re-use

Social

Occupational health & safety; child work; wages; benefits

Customer health & safety; complaint handling

Health threads of landfills

(e.g. clean technologies) or social challenges (e.g. adapted products for people from poor communities/developing countries) (Hart, 1997). Whilst these efforts are very important, they alone cannot solve some of the overarching sustainability challenges. At least three reasons should be mentioned: first, the increased aggregated resource consumption related to product manufacturing and ownership, i.e. there mere number of products. Second, though product eco-efficiency can be strongly increased, rebound effects (Dyllick & Hockerts, 2002) are responsible for that the overall consumption increases might exist. For example, lower maintenance costs entail more intense use (e.g. when switching to a more fuelefficient car, more kilometres might be driven). Third, more sustainable products may be difficult to introduce and diffuse, simply because the additional environmental and social characteristics make the products too expensive for consumers. For all three reasons mentioned, it is important to go beyond the technological level to also consider the level of the PSSs. A PSS is defined as “[…] a system of products, services, networks of players and supporting infrastructure that continuously strives to be competitive, satisfy customers needs and have a lower environmental impact than traditional business models” (Goedkoop, 1999). This definition shows that the traditional distinction of products and services is nowadays becoming less clear (Wise & Baumgartner, 1999). In general, three degrees of product-service combinations can

be distinguished (e.g. Baines et al., 2007; Mont, 2001): Product-oriented PSS add a service to the conventional product. For example, the product take-back service (end-of-life phase) allows the producer to recycle or remake the product and thus contribute to environmental (but also to economic) value. In an extreme case, product service bundles may turn into pure product-based services based on product leasing and contracting rather than selling. A good example is the case of Interface Inc. which originally focused on selling carpets, but later became involved in leasing carpets. Instead of replacing entire carpets, the company only replaces worn tiles. Third, a further increase of the service factor leads to product-service systems in a narrower sense (Mont, 2006). These are systems of shared use, i.e. consumers (or users) use the same products either subsequently (e.g. car sharing; public washing machines) or simultaneously (e.g. ride sharing instead of a private car; Hansen et al., 2010). The current chapter focuses on such systems of shared use. The benefits of PSSs are very thoroughly analyzed in the literature. Pawar et al. (2009) differentiates three major streams of literature: the first stream of “product service systems” highlights the environmental benefits of PSS. The second stream “integrated solutions” analyses financial effects of PSS and the third stream of “experience services” highlights benefits created by consumer interactions and co-created values. In general, benefits of PSSs result from a shift of 43

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

risks, responsibilities, and costs to the manufacturer, which are associated with the ownership of products (Baines et al., 2007, Pawar et al., 2009). This chapter is especially interested in the environmental (and more broadly, sustainability) benefits of PSS, which are described in the following. By increasing the service content of offers, value creation and resource consumption can be decoupled with the effect of creating sustainability effects (Baines et al., 2007; Mont, 2001). For instance, Interface Inc. is now responsible for the maintaining, recycling, and disposal of its carpets and has therefore a high interest in, for instance, prolonging the life cycle of its carpets and recycling old carpets. As a result, providers of PSSs have strong incentives to consider the total life cycle and to optimize their offers and value chain over the complete PSS life cycle (Aurich et al., 2006). This kind of analysis is also referred to as system thinking (Manzini et al., 2001). Furthermore, by retaining the ownership of products, providers of PSS have strong incentives of minimizing their resource input to reduce costs and capital expenditures, while keeping the value proposition of their offer on a constant level (Baines et al., 2007, Manzini & Velozzi, 2002) or to even increase the value proposition. In systems of shared use, fewer products are sold and thus the number of products in the end-of-life phase is reduced (Aurich et al., 2006; Mont, 2004). For instance, car sharing services need less cars “in action”, leading to a significant increase of overall resource efficiency of the service system. Hence, PSSs offer the opportunity of dematerializing the value creation (Mont, 2006; Ehrenfeld, 2001). Bearing those findings in mind, we may state that the higher the service part of a SOI, the higher the consideration of the products’ life cycle and, consequently, its positive sustainability effects. Hence, PSS offer a promising innovation strategy for SOIs. However, sustainability effects have to be assessed carefully, as contradictory effects may arise through PSSs (Manzini & Velozzi, 2002).

44

CASE STUDY: OFF-GRID LIGHTING Research Method In order to gain a better understanding of the relation between SOI and PSS, we subsequently analyze specific sustainability effects within a case study research strategy. We conducted a single case study about OSRAM, a company providing off-grid lighting in Kenya. OSRAM is a company fully owned by Siemens AG, one of the largest multinational corporation based in Germany. Case study research is a strategy for the “systematic production of exemplars” (Flyvbjerg, 2006). It does not follow a strategy of statistical sampling and thus the number of case studies is not a measure for the quality of this approach. Rather, even a single in-depth case study can contribute to theory (Flyvbjerg, 2006; Yin, 2003). We carefully considered trustworthiness criteria of credibility, transferability, dependability, and conformability (Lincoln and Guba, 1985; Shah and Corley, 2006) in our methodology, as will be further explained in the following paragraphs. When selecting the case, we followed a strategy of extreme cases (Flyvbjerg, 2006), as this is one alley for a purposeful theoretical sampling and thus contributes the trustworthiness criteria of dependability (Shah and Corley, 2006). OSRAM provides a very unique approach for introducing a new PSS, embedding a highly innovative and sustainability-oriented technology. The example is also one of the flag ship programs within the area of Siemens’s corporate sustainability advances, and thus it is also well documented. Access to data was another reason for selecting the case (Yin, 2003). With regard to data collection, we drew on multiple sources of data in order to analyze the case from multiple perspectives and, hence, to increase credibility (Shah and Corley, 2006; Yin, 2003). Data collection covered public corporate reports and websites, documents from the public domain, and media reports. The documents were

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

collected between 2009 and mid 2010 (Table 2). As we solely relied on secondary data from explicit documents and reports, risks with regard to data recording and management – as they are expressed in the trustworthiness criteria of conformability (Shah and Corley, 2006) – were reduced. The data analysis can be considered abductive (Dubois & Gadde, 2002) relying both on an initial (deductive) conceptual framework (life-cycle; levels of innovation) and, at the same time, letting inductive findings emerge from the data. We used a content analysis to investigate the various documents presented earlier. The triangulation of data from different sources led to the emergence of the overall picture (Yin, 2003). In the sense of transferability (Shah and Corley, 2006), the research findings contain “thick” descriptions of empirical data related to the abductive categories, concepts, and overall structures. We further controlled the criteria of dependability by a critical audit of data: whereas the first author collected the first-order data (mere data) and proposed a first draft of the second-order findings (theorizing), the second author served as a critical reviewer of these processes. The following findings section provides some background information on the case setting. Then the off-grid lighting PSS is presented and its effects on both the technological and overall PSS level analyzed. Table 2. Data collection for case study Type of data

Documents studied

Public corporate reports/data

Siemens (2009). Sustainability Report 2008. Munich, Germany. OSRAM website: http://www.osram.com Global Nature Fund website: http://www. globalnature.org

Reports from public domain

Esch et al. (2008) Loew et al. (2009) Mills (2008)

Media

Rybak, A. (2009) Zeug, K. (2009)

Background to Off-Grid Lighting Lighting is of fundamental value for human beings and greatly influences everyday life. For instance, lighting substantially impacts on security issues, production (lighting can considerably prolong working hours), education (lighting enables studying in the evening) and poverty reduction, to name only a few. However, around 1.6 billion people in sub-Saharan Africa do not have access to power grids (Mills, 2008). Thus, fuel-based (primarily kerosene) lamps are often the only viable lighting source in vast areas within developing countries to this date. After all, kerosene is an affordable energy carrier, and is available even in remote rural areas. However, lighting costs can account for up to 10% of household incomes (Mills, 2008). In addition, fuel-based lamps are highly inefficient for lighting purposes and therefore burden excessive costs on its users. Moreover, the practice of kerosene lamps implies additional fundamental negative impacts, both ecologically and socially. Fuel-based lighting leads to the emission of roughly 190 million tonnes of CO2 per year. Kerosene lamps also emit several toxic gases, which can cause severe health damages in the population, especially when used inside buildings. Furthermore, kerosene often causes pollution of potable water, especially when used for fishing purposes. The use of kerosene lamps is extremely widespread in the Lake Victoria region of Kenya. This area is inhabited by 30 million people and is characterized by the use of local fishing vessels, which mainly fish at night. The fishermen use swimming kerosene lamps as lures for fish and are therefore highly dependent on lighting. Approximately 75% of their income accounts for lighting only.

45

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Company Background Osram GmbH was established in 1906 and is a fully-owned subsidiary of Siemens AG. Today, Osram is one of the two leading lighting manufacturer worldwide, being active in numerous markets, e.g. general lighting, automotive lighting, ballasts and luminaries. Osram perceives climate protection and sustainability issues as one of the major drivers in the lighting industry. Hence, Osram is heavily engaging in the development of energy-efficient products, which in 2008 already generated 66% of its total revenues. Furthermore, Osram’s product portfolio was recently acknowledged with the German Sustainability Award. To sustain its growth potential, Osram is increasingly seeking market opportunities in emerging markets, especially in Africa. In 2009, 88% of its revenues were generated outside of Germany. The market for off-grid lighting is of peculiar interest, as its size is estimated to amount to €50 billion per annum, which is almost twice as big as Osram’s original lighting market. In order to further expand its revenues in this market, an innovative product-service system was developed in Kenya, which is described below.

Off-Grid Lighting as a Product-Service System In 2004, the Global Nature Fund and a local Kenyan NGO started to work on an alternative to kerosene lamps. Together with OSRAM, a leading manufacturer of lighting solutions, and SolarWorld, a manufacturer of solar panels, they developed a new solution tailored to the needs of developing countries. OSRAM manufactured portable lamps, which consisted of a rechargeable battery (O-Box) unit and a robust and waterproof energy-saving lamp (O-Lamp). Interestingly, OSRAM did not sell those lamps, but created a PSS by lending those products to local residents. In order to do so, an on-site station was established, where lamps are handed out and recharged by using solar

46

panels installed on the rooftop of the building. This service was supported by micro loans to make it affordable to local residents. Hence, this productbased service promised cheaper, more reliable and ecologically beneficial off-grid lighting. In the following, the sustainability effects of this solution in the use and end-of-life phases of the physical life-cycle are analyzed. A simplified version of the earlier presented Table 1 serves as evaluation matrix. The analysis is limited to major and well-known effects of the PSS, as they already provide a good indication of the overall value and effects of the proposed offer. Basic sustainability effects (resource consumption, etc.) and in-depth analyses (cost structures, eco-balances, working conditions, etc.) are – for reasons of clarity – not explicitly mentioned. Firstly, we focus on the effects of the product (i.e. the technological level) itself. Then the impacts derived from introducing the PSS are discussed.

Analysis of Technology Level From a technological viewpoint, the introduction of O-Lamps with energy saving lamps results in several advantages in comparison to the earlier used kerosene lamps. However, it also poses some disadvantages and new economic, environmental, and social risks, which are described in Table 3: Economic effects: The assessment of effects within the lifecycle of production is generally undertaken from a company’s point of view. At this point, we resign an in-depth comparison of different cost structures of O-Lamps and kerosene lamps. Generally speaking, if we assume costcovering business practices of OSRAM, negative effects for production and recycling exist, but are not higher than accumulated lending revenues per lamp. However, considering the maintenance phase from a user’s point of view, we can analyze the economic effects of the O-Lamp. By capturing solar energy, the price of charging the batteries is around 20% lower than the price of kerosene for the same amount of lighting. The costs of recycling

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Table 3. Sustainability effects on the technological level Target dimension

Life-cycle phases Use/ maintenance

End of life

Economic

20% lower energy costs

n/a

Environmental

Zero emissions Fewer pollution from kerosene

Fewer pollution from kerosene Risk of mercury Risk of battery disposal

Social

Zero air pollution Zero accidents from kerosene lamps Improved living standards and education

Risk of mercury Risk of battery disposal

O-Lamps were not known at this point of time, but can be considered as negative and moderate. Environmental effects: Considering the use phase, the introduction of off-grid lighting leads to a maximum reduction of CO2 and other toxic emissions while the lamps are used. It has to be noted that the reduction of CO2 is possible due to solar energy collected on the roofs of the recharging stations. Furthermore, environmental pollution from spilled or dumped kerosene is removed entirely. However, O-Lamps pose some environmental risks in the end-of-life phase, as some hazardous materials are part of the energy saving lamps (e.g. mercury) and batteries (e.g. plumb). Hence, these products carry certain risks, if not recycled properly. Social effects: Regarding the use phase, the reduction of toxic emissions in houses of the local users leads to healthier living environments and less air pollution. Furthermore, accidents with kerosene lamps, which may lead to severe burns or deaths, can be avoided. Another indirect, but noteworthy, effect is the improvement of living and, foremost, learning conditions. Generally, young children may only be able to study in the evening, when home from school or work. However, kerosene lamps are rather improper due to the poor quality of light. By having access to better and longer lighting, children have improved opportunities for education. From an end-of-life perspective, the use of mercury within the O-Lamps and the use of batteries cause health risks, when not recycled properly.

Analysis of the PSS level The off-grid lighting solution depicts an illustrative example of a PSS: by lending rechargeable battery packs, these packs can be used more often and can be maintained more easily. Therefore, the assessment of sustainability effects on a PSS level is of particular interest (Table 4): Economic effects: As mentioned above, the assessment of the production phase is very company-specific and carried out in this case study rather generically. The analysis of the use phase, however, reveals remarkable effects. By offering a lending service of its product, the product is much more affordable to local residents. This is due to the fact that the actual usage of a product can be split up in single value-adding packages and then sold separately. In contrast, the sales based on transfer of ownership do not allow such separation and can only be sold once. Accordingly, while a classical approach of selling lamps and transferring ownership would impose a very high economical entry barrier, lending out lamps leads to a lower price level per „utility unit“ and therefore significantly increases the market reach of this product. In fact, in this case study, the introduction of a lending service enables the access to technological innovations and SOIs in the first place. The support of micro loans adds to this fact that lower economical entry barriers can be considered as a key achievement of PSS innovations in developing countries. Consequently, in developing countries PSS can be re47

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Table 4. Sustainability effects on the PSS level Target dimension

Life-cycle phases Use/ maintenance

End of life

Economic

Lower economical entry barriers

-

Environmental

Access to clean and renewable energy sources

Recycling and disposal of lamps and batteries, which include toxic materials

Social

Access to improved lighting New job possibilities

-

garded as enabler for SOIs on a technological level. Environmental effects: Major environmental effects of the overall PSS can be determined in the use and end-of-life phase. By collecting solar power at the recharging stations, clean and renewable energy sources can be guaranteed in the use phase. Regarding the end-of-life phase, the collection of battery packs and their recycling and disposal is more feasible. Social effects: Noteworthy social effects on the level of the PSS are created mostly during the use phase. By lowering the economical entry barriers, the PSS discloses the accessibility of technology to the poor and can hence lead to improved living standards of the population. The operation of energy hubs as charging station is an investment in local infrastructure and thus may also add job opportunities to local communities. Still, it may also be considered that such new infrastructure and offerings put previous job opportunities (e.g. kerosene trading) at risk – the positive job effect thus might be outweighed. In summary, Table 5 gives an overview of all effects on the technological level and the PSS level.

DISCUSSION AND FUTURE RESEARCH DIRECTIONS The case study exemplifies the multi-dimensionality of SOIs and demonstrates the importance of structuring sustainability effects along the target

48

and life-cycle dimensions of SOIs. Furthermore, our findings lead to several implications which are discussed in the following.

PSS and its Effects on Sustainability The effects of PSS on sustainability have been generally discussed elsewhere with regard to developed countries (e.g. Mont, 2004). We could identify those effects within this case study again to support the following findings: firstly, by introducing a PSS (instead of mere product sales), the resource efficiency could be significantly increased (by using the batteries more often). Secondly, the PSS leads to an extension of the responsibilities of the manufacturer. The company now owns batteries and lamps and is hence responsible for their recycling and disposal. This is extremely important in the presented case, as both components incorporate toxic and environmentally harmful materials. The case illustrates an additional positive effect resulting from the shift of responsibility: as OSRAM is responsible for the recharging of the batteries, it adds to the positive sustainability impacts by integrating solar power to its system. The use of solar panels is only feasible by taking advantage from economies of scale at the recharging stations. This finding supports research on PSS, in which the generation of synergies is explicitly mentioned as a major benefit of PSS (Manzini & Velozzi, 2002). More generally, Pawar et al. (2009) identified the challenge of “designing value” in order

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Table 5. Overall assessment of sustainability effects Target dimension Economic

Environmental

Social

Innovation level

Life-cycle phases Use/ maintenance

End of life

Product

~20% lower energy costs

-

PSS

Company: lower economical entry barriers through rental and thus creation of new markets

-

Product

Zero emissions Fewer pollution from kerosene

Fewer pollution from kerosene Risk of mercury disposal Risk of battery disposal

PSS

Access to clean and renewable energy sources

Recycling and disposal of lamps and batteries

Product

Zero air pollution Zero accidents from kerosene lamps Improved living standards and education

Risk of mercury Risk of battery disposal

PSS

Access to improved lighting (long-term: new job possibilities)

-

to successfully implement PSS. Furthermore, the need of being able “to model” a PSS was identified (Baines et al., 2007). The presented approach – especially the separate evaluation of technological and PSS levels – may add value by providing an in-depth understanding on how and where value is created and where additional value might be created. Hence, the taken approach may add to the further understanding of a PSS’s sustainability effects.

PSS as Enabler for SOIs This case study emphasizes another profound effect of PSS, which is unveiled in our findings: PSS can function as economic enabler for SOIs – and more generally, for product innovations (Manzini & Velozzi, 2002). By selling the utility of products, rather than transferring ownership, the price of using a product for the first time drops significantly, hence minimizing economic entry barriers to using products and/or services (Mont, 2001, 20). This is extremely important in developing countries where relatively high purchasing prices constitute significant barriers to the diffusion of products. Introducing sustainability-

oriented product innovations through a PSS can thus be a good strategy to maximize positive sustainability effects (Figure 1). Future research should thus analyze the role of PSS for successfully introducing radical SOIs, either in niche markets or at transition into mass markets.

The Role of SOIs for the Development of PSS Pawar et al. (2009) highlighted the importance of simultaneously designing the product, service, and organization in order to successfully establish a PSS. Our case study underlines this finding by illustrating a rather different product design of OSRAM: by integrating batteries and recharging stations, OSRAM designed its offering different to its traditional products of mere selling of bulbs. The product itself was adapted to fit in the newly developed PSS. This notion emphasizes the interdependencies of the technological and PSS levels of innovation. Hence, when advancing to the layer of PSS, companies have to review their product innovations and may design them differently (Pawar et al., 2009).

49

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Figure 1. Simultaneous innovation at the technological level and PSS (or functional) level

Success Factors for the Introduction of PSS General barriers and design features for the introduction of PSS are discussed in literature (Baines et al., 2007, Manzini & Velozzi, 2002). For instance, the need of incorporating a multi-stakeholder approach is highlighted, when introducing PSS (Pawar et al., 2009, Huiten et al., 2001, Mazini & Velozzi, 2002). Additionally, being sensitive to the cultural context can be regarded as one of the key success factors for the integration of PSSs (Wong, 2004). By integrating local and international NGOs in the development of its offering, OSRAM pursued this notion fairly well. However, arguably, OSRAM failed to fully integrate its customer into the development process. One of the reasons, why the solution is not adopted by the local population in Kenya so far, can be traced back to its pricing system: OSRAM charges deposit fees to be able to use the system. However, those deposit fees are considerably high, thereby impeding most of the potential customers from purchasing the service. Additionally, the income of local fishermen is highly volatile and thus their need for electricity is equally varying. However, OSRAM’s offer is rather inflexible, as only fully charged batteries

50

are lent at full cost which does not correspond with the fluctuation of local demand for off-grid lighting. This invalidates the general flexibility benefit of the PSS which would allow for a better adjustment to customer needs (Cook et al. 2006). Ultimately, OSRAM’s PSS is not fully suited to the needs and usage patterns of its target group and, hence, could not fully unveil its sustainability potentials. This emphasizes the importance of integrating customers into the development of PSS as early as possible (Hansen et al., 2009, Manzini et al., 2001, Huiten et al., 2001). The case may further stress the requirement of new methodologies for the design and development of user-tailored PSS (Morelli, 2002, Baines et al., 2007, Manzini & Velozzi, 2002). Further research should look at processes of open innovation and customer integration (e.g. Halila & Horte, 2006; von Hippel, 1988) in order to build more successful PSS.

CONCLUSION This chapter emphasized the role of innovation for addressing sustainability as well as the role of sustainability as a source for innovation. Product-

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Service System (PSS) represents an important approach for both perspectives. However, as PSSs are combinations of products and services and, as they go beyond product ownership, multiple new hurdles and opportunities emerge. The presented case study showed an example of simultaneous product and PSS innovations and revealed how to assess the various sustainability effects on both levels. Beyond established effects of PSS of saving materials due to fewer products in the market (as the same product is used more often by various customers) the PSS could also be a beneficial innovation strategy for introducing new products/technologies in the market. Future research should emphasize this role of PSS in market entry strategies also in developed nations.

ACKNOWLEDGMENT We thank Prof. Stefan Schaltegger, head of the Centre for Sustainability Management (CSM), for providing us with valuable feedback. Furthermore, we thank one unknown reviewer for his/ her constructive suggestions.

REFERENCES Aurich, J., Fuchs, C., & Wagenknecht, C. (2006). Life cycle oriented design of technical product service-systems. Journal of Cleaner Production, 14(17), 1480–1494. doi:10.1016/j. jclepro.2006.01.019 Baines, T., Lightfoot, H., Evans, S., Neely, A. D., Greenough, R., Peppard, J., & Wilson, H. (2007). State-of-the-art in product servicesystems. Proceedings of the Institution of Mechanical Engineers. Part B, Journal of Engineering Manufacture, 221(10), 1543–1552. doi:10.1243/09544054JEM858

Cook, M., Bhamra, T., & Lemon, M. (2006). The transfer and application of product servicesystems: From academia to UK manufacturing firms. Journal of Cleaner Production, 14(17), 1455–1465. doi:10.1016/j.jclepro.2006.01.018 Devisscher, T., & Mont, O. (2008). An analysis of a product service system in Bolivia: Coffee in Yungas. International Journal of Innovation and Sustainable Development, 3(3/4), 262–284. doi:10.1504/IJISD.2008.022229 Dubois, A., & Gadde, L.-E. (2002). Systematic combining: An abductive approach to case research. Journal of Business Research, 55(7), 553–560. doi:10.1016/S0148-2963(00)00195-8 Dyllick, T., & Hockerts, K. (2002). Beyond the business case for corporate sustainability. Business Strategy and the Environment, 11(2), 130–141. doi:10.1002/bse.323 Ehrenfeld, J. (2001). Designing sustainable product service systems. In Proceedings of the 2nd International Symposium on Environmentally Conscious Design and Inverse Manufacturing (pp. 12-23). Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. Elkington, J. (1998). Cannibals with forks. The triple bottom line of 21st century business. Gabriola Island, BC, Canada-Stony Creek, CT: New Society Publishers (Conscientious commerce). Engelhardt, G., Griessler, E., Hammerl, B., Hinterberger, F., Mesicek, R., Omann, I., & Vorbach, S. (2003). Nachhaltige Produkte und Dienstleistungen – Leitfaden zur Entwicklung zukunftsfähiger Geschäftsfelder (co-authorship by C. Jasch). Leitfaden.

51

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Esch, S., Fähling, J., Köbler, F., & Langer, P. (2008). Developing hybrid products: Integrating products and services. In Krcmar, H., Böhmann, T., Leimeister, J. M., Wolf, P., & Wittges, H. (Eds.), Studien (pp. 41–56). München, Germany: Lehrstuhl für Wirtschaftsinformatik. Fichter, K. (2005). Interpreneurship: Nachhaltigkeitsinnovationen in interaktiven Perspektiven eines vernetzenden Unternehmertums. Professorial dissertation. Marburg, Germany: Metropolis. Goedkoop, M. J., van Halen, C. J. G., te Riele, H. R. M., & Rommens, P. J. M. (1999). Product service systems, ecological and economic basics. Report for Dutch Ministries of Environment (VROM) and Economic Affairs (EZ). Halila, F., & Horte, S. A. (2006). Innovations that combine environmental and business aspects. International Journal of Innovation and Sustainable Development, 1(4), 371–388. doi:10.1504/ IJISD.2006.013736 Hall, J., & Vredenburg, H. (2003). The challenges for innovating for sustainable development. MIT Sloan Management Review, 45(1), 61–68. Hansen, E. G., Gomm, M. L., Bullinger, A. C., & Möslein, K. M. (2010). A community-based toolkit for designing ride-sharing services: The case of a virtual network of ride access points in Germany. International Journal of Innovation and Sustainable Development, 5(1), 80–99. doi:10.1504/IJISD.2010.034559 Hansen, E. G., Große-Dunker, F., & Reichwald, R. (2009). Sustainability innovation cube - A framework to evaluate sustainability-oriented innovations. International Journal of Innovation Management, 13(4), 683–713. doi:10.1142/ S1363919609002479 Hart, S. L. (1997). Beyond greening: Strategies for a sustainable world. Harvard Business Review, 75(1), 66–76.

52

Hart, S. L., & Milstein, M. (2003). Creating sustainable value. The Academy of Management Executive, 17(2), 56–67. doi:10.5465/ AME.2003.10025194 Hauschildt, J., & Salomo, S. (2007). Innovationsmanagement. Munich, Germany: Vahlen. Hockerts, K., & Morsing, M. (2008). A literature review on corporate social responsibility in the innovation process. Copenhagen, Denmark: Copenhagen Business School. Huwer, U. (2004). Public transport and car-sharing—Benefits and effects of combined services. Transport Policy, 11, 77–87. doi:10.1016/j.tranpol.2003.08.002 Kloepffer, W. (2008). Life cycle sustainability assessment of products. International Journal of Life Cycle Assessment, 13(2), 89–95. doi:10.1065/ lca2008.02.376 Loew, T., Clausen, J., Hall, M., Loft, L., & Braun, S. (2009). Case studies on CSR and innovation: Company cases from Germany and the USA. Berlin; Münster, Germany. Luiten, H., Knot, M., & van der Horst, T. (2001). Sustainable product service-systems: The Kathalys method. In Proceedings of the 2nd International Symposium on Environmentally Conscious Design and Inverse Manfacturing (pp. 190-197). Manzini, E., & Vezzoli, C. (2002). Product service systems and sustainability. Paris, France: United Nations Environment Program. Manzini, E., Vezzoli, C., & Clark, G. (2001). Product service-systems: Using an existing concept as a new approach to sustainability. Journal of Desert Research, 1(2). Mills, E. (2008). Product quality assurance for off-grid lighting in Africa. In Conference Proceedings from the Lighting Africa Product Quality Assurance Workshop, Arlie, VA.

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Mont, O. (2001). Introducing and developing a Product-Service System (PSS) concept in Sweden. IIIEE Reports (Vol. 6). Lund, Sweden: IIIEE, Lund University. Mont, O. (2004). Reducing life-cycle environmental impacts through systems of joint use. Greener Management International, 45, 63–77. Mont, O. (2006). Product-Service Systems: Reviewing achievements and refining the research agenda. Journal of Cleaner Production, 14(17), 1451–1454. doi:10.1016/j.jclepro.2006.01.017 Morelli, N. (2002). Designing product/service systems:A methodological exploration. Design Issues, 18(3), 3–17. doi:10.1162/074793602320223253 Olivia, R., & Quinn, J. (2003). Interface’s evergreen services agreement. Harvard Business School Case 603112. Paech, N. (2005). Richtungssicherheit im nachhaltigkeitsorientierten Innovationsmanagement. In Fichter, K., Paech, N., & Pfriem, R. (Eds.), Nachhaltige Zukunftsmärkte. Orientierungen für unternehmerische Innovationsprozesse im 21. Jahrhundert (pp. 327–352). Marburg, Germany: Metropolis. Pawar, K. S., Beltagui, A., & Riedel, J. C. K. H. (2009). The PSO triangle: Designing product, service and organisation to create value. International Journal of Operations & Production Management, 29(5), 469–493. doi:10.1108/01443570910953595

Rybak, A. (2009). Osram - Kundenfang in Afrika. Financial Times Deutschland, 1.12.2009. Schaltegger, S. (1997). Economics of life cycle assessment: Inefficiency of the present approach. Business Strategy and the Environment, 6, 1–8. doi:10.1002/(SICI)10990836(199702)6:1<1::AID-BSE84>3.0.CO;2-D Schaltegger, S., & Burritt, R. L. (2005). Corporate Sustainability. In Folmer, H., & Tietenberg, T. (Eds.), The International Yearbook of Environmental And Resource Economics 2005/2006: A Survey of Current Issues (pp. 185–222). Cheltenham, UK: Edward Elgar. Schaltegger, S., & Wagner, M. (forthcoming). Sustainable entrepreneurship and sustainability innovation: Categories and interactions. Business Strategy and the Environment. doi:.doi:10.1002/ bse.682 Spillemaeckers, S., & Vanhoutte, G. (2006). A product sustainability assessment. In Jonker, J., & de Witte, M. (Eds.), Management models for corporate social responsibility (pp. 257–264). Berlin, Heidelberg, Germany: Springer. doi:10.1007/3540-33247-2_31 Tukker, A. (Ed.). (2008). System innovation for sustainability 1: Perspectives on radical changes to sustainable consumption and production. Sheffield, UK: Greenleaf. von Hippel, E. (1988). The sources of innovation. Oxford, UK: Oxford Univ. Press.

Pohl, H., Styhre, A., & Elmquist, M. (2009). The concept of interessement: The story of a powersplit technology for hybrid electric vehicles. International Journal of Innovation Management, 13(1), 47–64. doi:10.1142/S1363919609002236

Wagner, M., & Llerena, P. (2008). Drivers for sustainability-related innovation: A qualitative analysis of renewable resources, industrial products and travel services. Document de Travail n° 2008 - 22. Working paper.

Prahalad, C. K. & Hart, S. L. (2002). The fortune at the bottom of the pyramid. Strategy+Business, 26(First Quarter), 2–14.

Williams, A. (2006). Product-service systems in the automotive industry: The case of micro-factory retailing. Journal of Cleaner Production, 14(2), 172–184. doi:10.1016/j.jclepro.2004.09.003

53

Product-Service Systems as Enabler for Sustainability-Oriented Innovation

Wise, R., & Baumgartner, P. (1999). Go downstream: The new profit imperative in manufacturing. Harvard Business Review, 77(5), 133–141. Wong, M. (2004). Implementation of innovative product service-systems in the consumer goods industry. Doctoral dissertation, Cambridge University, UK. World Commission on Environment and Development. (1987). Our common future. London, UK: Oxford University Press. Yin, R. K. (2003). Case study research: Design and methods (3. ed.). Applied social research methods series: Vol. 5. Thousand Oaks, CA: Sage (Original work published 1984). Zeug, K. (2009). Kein Licht für Afrika. DIE ZEIT, 3, 31, 1.8.2009.

KEY TERMS AND DEFINITIONS Case Study: A case study is a research strategy which focuses on understanding the dynamics present within single settings (Eisenhardt, 1989). Corporate Sustainability: Corporate Sustainability can be defined as meeting the needs of a firm’s direct and indirect stakeholders (such as shareholders, employees, clients, pressure groups, communities etc), without compromising its ability to meet the needs of future stakeholders as well (Dyllick & Hockerts, 2002) - which can be operationalized by the heuristic, multi-criteria triple bottom line perspective aiming at the integration of economic, environmental, and social capital through eco-efficiency and effectiveness,

54

socio-efficiency and effectiveness, and eco justice (Schaltegger & Burritt, 2005). Low-Income Market: Customers with annual purchasing power parity (PPP) of $1500 or less (Prahalad & Hart, 2002). Notably, there is no generally accepted definition of the exact amount of purchasing power yet and the debate on this specific amount is still ongoing. Product Innovation: Gualitatively new products which differ significantly from a comparable condition (Hauschildt & Salomo, 2007). Product-Service System (PSS): A system of products, services, networks of players and supporting infrastructure that continuously strives to be competitive, satisfy customers needs and have a lower environmental impact than traditional business models” (Goedkoop, 1999). Sustainable Development: A development that meets the needs and aspirations of the present generation without compromising the ability of future generations to meet their needs (World Commission on Environment and Development, 1987). Sustainability-Oriented Innovation (SOI): A new development (and commercial introduction) of a product, technology, service, process, or business model which, in comparison to a prior version, has a positive net effect on the overall capital stock (economic, environmental, social), whereby tradeoffs between economic capital on the one hand and environmental and social capitals on the other are possible only when the reduction of either one side is compensated with a sufficiently high increase of the other (Hansen et al., 2010; Wagner and Llerena, 2008).

55

Chapter 4

Innovation for Sustainability in Aviation: World Challenges and Visions Hiroko Nakamura The University of Tokyo, Japan Yuya Kajikawa The University of Tokyo, Japan Shinji Suzuki The University of Tokyo, Japan

ABSTRACT In this chapter, the shared visions and the latest activities for sustainability in the aviation sector are presented and perspectives on the innovations that this sector should achieve are discussed. To do this, the latest experts’ talks are collected from four international meetings for aviation and the environment held around the world between September 2009 and May 2010, which invited experts and researchers from Japan, Europe, and North America. The expansion of networks between agents of the sector, which is considered to be essential for the success of innovation transition, is found in the latest projects for aviation sustainability. To smooth the transition of innovation from sector’s initiatives including radical change such as low-carbon alternative fuels, we emphasize the need for more discussion about new economic measurements. Finally, we discuss directions for future research, using multi-level perspectives for a transition management of aviation innovation for sustainability.

INTRODUCTION Some environmentalists believe that air transportation is evil because it is energy consuming, extravagant, and polluting. Aircrafts fly using fossil fuels, which emits various problems such DOI: 10.4018/978-1-61350-165-8.ch004

as “sustainability”, however air travel also allows people to meet their friends and families living on other continents, and the chance to buy local products of another hemisphere in their own towns. The aviation and a “sustainable” future is very complicated issue socially and economically. Furthermore, aviation connects countries.

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovation for Sustainability in Aviation

No single country has full control of international flights, which indicates that the management of aviation in the future can not be achieved without international negotiations and challenges. In this chapter, we investigate how the sector is going to control the flight for sustainability in such a difficult weather. Over a hundred years after the Wright brothers flights, aviation has achieved countless technological and system innovations in the area of fuel efficiency, noise, air quality, speed and safety. The main agents of the aviation sector are listed as follows: airlines, aircraft manufacturers, engine manufacturers, research institutes, researchers, air control services, airports, and governmental and non-governmental organizations. Geel (2006) pointed out that the networks within the socio-technical system for aviation were one of the keys to success in precedent innovations. With successful experience in innovations, the aviation sector is now tightening and widening the networks between various agents to challenge the climate-change issue. Last year, for example, the sector produced the first globally harmonized agreement on reducing the sector’s impact on climate change (ICAO, 2009), the details of which will be described in the next section. This chapter is organized as follows: the second section explains the theory we use for the analysis of experts’ talks and the background of the aviation and the environment issues. The third section presents the data sources which the analysis is based on, and the sector’s shared visions toward aviation for sustainability. The fourth section discusses the technological and system innovation trends, network expansions of agents of the aviation sector and perspectives for achieving the sector’s responsibility toward a carbon-neutral society. The fifth section proposes future innovation management directions. And the sixth section concludes our findings. Finally, in this chapter, we treat CO2 emission reduction as the main solution for aviation impact reduction for climate change, while the balance

56

of NOx effects to ozone production and methane reduction and the potentially grave effect of contrails are still uncertain (Szodruch, 2009).

BACKGROUND Research into Innovation and Sustainable Development Recent social science research into innovation and sustainable development can be classified into two groups: cleaner technology and systems innovation (Smith, 2006). The latter is important since cleaner technologies are often not adopted without some transformation of socio-technical systems (ex. technology, policy, users, industry structure, markets, culture, infrastructure, science) (Weber et al., 1999). Researchers of systems innovation have been developing many theories and tools to promote the transitions required to make it possible to move innovations from laboratories to market. One prominent school of thought in recent systems innovation debates is called Strategic Niche Management (SNM). Here niche is used to describe an emerging and innovative technology or system, and is vulnerable at the infancy. Studying the history of technology innovations, SNM scholars have analyzed processes to try to determine what is the best for successful development of niche. They have identified some strategic factors; broad and deep social networks, robust expectation shared between actors of a niche, and learning processes at multiple stages where the actors related to the niche learn about the design, user needs, cultural and political acceptability, and other aspects of the niche (Schot & Rip, 1996, Hoogma et al., 2002). SNM researchers have taken a lot of case studies of the transition mechanism of various domains; products such as organic food, ecoefficient house etc., or public services such as biogas energy plant, waste water plants and so on

Innovation for Sustainability in Aviation

(e.g. Smith, 2006; Raven & Geel, 2010; Dries et al., 2007). There are a few studies about aviation (Haan & Mulder, 2002; Kivits et al., 2010). More studies are expected to accelerate both the SNM research and the aviation sustainability, because systems innovation in the aviation sector is very difficult due to the long product lifecycle and huge sunk costs (Kivits et al., 2010). Furthermore, the development requires a lot of investment and government supports, which causes WTO subsidies disputes. How the aviation sector will bring niches up is very interesting to the researchers of SNM.

Aviation for Sustainability The impact of air transport on the atmosphere and the climate was estimated as 3.5%~4.9% of current anthropogenic radioactive forcing (Lee, 2009) with a high uncertainty due to emission at high altitudes (Szodruch, 2009). This number itself doesn’t tell us whether the impact is “small”, “significant” or “fair” (Randles & Bows, 2009) because aviation also brings a number of social and economical benefits. The sector has achieved significant improvements in environmental performance, for example, 90% noise reduction and 70% CO2 reduction (or fuel-efficiency increase) compared to the 1950s (Blackner, 2010). It must be remembered, however, that a stable increase of traffic is forecasted. Boeing estimated an average 5.2% to 5.9% growth of worldwide passenger traffic and cargo traffic, respectively, over the next 20 years (Boeing 2010). The Kyoto Protocol to the United Nations Framework Convention on Climate Change (UNFCCC) asked the International Civil Aviation Organization (ICAO) to pursue limitation or reduction of greenhouse gas (GHG) emissions from international flights (Conference of the Parties, 1997). ICAO formed the Group on International Aviation and Climate Change (GIACC) to develop an ICAO program of Action in January 2008. The ICAO’s discussion on climate change,

however, has been caught between two opposite principals; UNFCCC’s principle on common, but differentiated responsibilities (CBDR), and aviation’s Chicago Convention principle of nondiscrimination and equal and fair opportunities to develop international aviation. In other words, to achieve a consensus in the ICAO, a consensus both of countries which ratified the Kyoto Protocol and those countries which did not. Consideration on the two principles of the CBDR and the Chicago Convention caused very slow progress in the discussions. A continuous increase in world fear about climate change and the absence of a central force in the ICAO consequently called to fore the sector agents’ awareness of their responsibility to work on climate change issues and their ambitious to take leadership in aviation development towards sustainability. A number of activities, which vary from R&D projects in manufacturing to international initiatives for air transport management (ATM) systems are now organized around the world, but especially in North America and Europe.

VISIONS AND TECHNOLOGY DIRECTIONS OF THE AVIATION SECTOR In this section, visions shared widely among the aviation sector and directions of technology development are discussed on the basis of the experts’ talks gathered from four international meetings for aviation and the environment. The meetings were held between September 2009 and May 2010 by 2 major international organizations that are connected strongly with European and North American leading industries and institutes and by authors. The brief summary of each organizations and the meetings are as follows. It is interesting to note that, in each meeting, we can find the increase of the sector’s interest on the environment issue.

57

Innovation for Sustainability in Aviation

The American Institute of Aeronautics and Astronautics (AIAA), which is the world’s largest technical society for aerospace, held “Inside Aerospace”, an annual international forum for aviation and space leaders. While the themes of recent meetings were about the aerospace workforce, the meetings held on the 11th and 12th, May, 2010, at Arlington, in Washington D.C, were dedicated to “a candid discussion of how to make aviation more energy efficient and “green” and how to effectively use aerospace technology to understand and limit climate change” (AIAA homepage). The AIAA invited key speakers from government, airlines, aircraft and engine manufacturers, oil companies, academia, research institutes, non-governmental organizations, and even the Air Forces. Most speakers came from North America, but some speakers were also from Europe. Some of presentation documents can be downloaded from the AIAA homepage. The International Council of the Aeronautical Science (ICAS) is the sole global organization for a free international exchange of information on aeronautical science and engineering. The Council holds an International Congress in the fields of Aeronautical Sciences every two years (ICAS homepage) and receives hundreds of aeronautical researchers and student participants. It also holds an International Workshop biennially for “international experts in the field to exchange views and to identify further areas of potential cooperation”. In 2005, the theme for the international workshop was, “Towards a Global Vision on Aviation Safety and Security”, in 2007, the theme was “UAV-Airworthiness, certification and access to the airspace”, and in 2009, “Aviation and Environment”. It was not until recently that environmental themes were considered important enough to discuss as a main theme. On the 28th of September 2009, in Amsterdam, the Netherlands, the workshop was organized with invited speakers from government, airlines, aircraft manufacturers, academia, and non-governmental organizations.

58

Most speakers came from the Europe, but one speakers was from the U.S. All of the presentation documents from this 2009 meeting in Amsterdam can be downloaded from the ICAS homepage. The Centre for Aviation Innovation Research (CAIR) is an inter-disciplinary organization within the University of Tokyo, established in August, 2009. CAIR’s main objectives are to research aviation innovation from a wide range of views, including aeronautics, aviation policy, and economics, and to help promote and design the aviation industry as one of the leading industries in Japan. One concrete objective is to contribute to realize maximum utilization of airspace by developing a set of policy recommendations. CAIR held an “International Seminar on Aviation and Climate Change” on February 18th, 2010, and an “Aviation Environment Workshop” on May 19th, 2010. The former seminar invited experts and researchers from Japan and Europe to discuss the technological feasibility of attaining emission reduction targets as well as future research directions on the issue. The latter workshop organized by CAIR and the Boeing Company invited experts from the U.S. and Japan to share their knowledge of technologies that have enabled significant reductions in aircraft noise and emissions to date. Technologies being developed for further reduction in aviation’s environmental footprint were discussed. The workshop was initially planned as a workshop for noise issues, but in the course of preparation, the theme was replaced with wider environmental issues, which also included the subject of emissions. This fact implies also the recent increase in the sector’s attention to the climate change. Both meetings invited governments, airlines, aircraft and engine manufacturers, oil companies, academia, and research institutes. Half of the speakers came from Japan and the others from Europe and the U.S. Some of presentation documents can be downloaded from the CAIR homepage.

Innovation for Sustainability in Aviation

Table 1. World aviation goals Organization

Vision Title

CO2 and other aviation environmental performance targets

ICAO

“Programme of Action”

-2% annual fuel efficiency improvement up to 2050 -Further discussion on more ambitious goal

IATA

“Carbon Neutral Growth from 2020”

-1.5% annual fuel efficiency improvement from 2009 until 2020 -Carbon neutral growth from 2020 -50% carbon emission reduction by 2050 compared to 2005 levels

ACARE (Europe)

“A Vision for 2020”

-50% CO2 reduction -80% NOx reduction -50% noise reduction compared with 2000

NASA (USA)

“NASA subsonic transport system level goals”

Conventional configurations relative to 1998 single aisle (N+1=2015***) -32dB below Stage4 for Noise reduction -60% below CAEP6 for LTO NOx emissions reduction -33% aircraft fuel burn reduction** Unconventional configurations relative to 1997 single aisle (N+2=2020***) -42dB below Stage4 for Noise reduction -75% below CAEP6 for LTO NOx emissions reduction -50% aircraft fuel burn reduction** Conventional configurations relative to 1998 single aisle (N+3=2025***) -71dB below Stage4 for Noise reduction -75% below CAEP6 for LTO NOx emissions reduction -Better than 70% aircraft fuel burn reduction** with Exploit metro-plex*concepts ***Technology Readiness Level for key technologies = 4-6 ** Recently Updated. Additional gains may be possible through operational improvements * Concepts that enable optimal use of runways at multiple airports within the metropolitan area

Visions for the Future of Aviation Before discussing the major activities of the aviation sector for sustainability, we would like to present visions and strategies besides the Kyoto Protocol, which serve as a frame for each of the activities. These strategies are summarized in Table 1. The International Air Transport Association (IATA), which “represents some 230 airlines comprising 93% of scheduled international air traffic”, created and have been promoting a fourpillar strategy since 2007 to achieve a vision of “carbon-neutral growth in the mid-term and to build a zero emission commercial aircraft within the next 50 years” (IATA homepage). The fourpillar strategy, ‘Improved technology’, ‘Effective operations’, ‘Efficient infrastructure’ and ‘Positive economic measures’ is comprehensive (Haag, 2009). The IATA, as a representative of the airline industry, set three goals as follows prior to the

ICAO: (1) CO2 efficiency by 1.5 per cent per annum from 2009 until 2020, (2) carbon neutral growth from 2020, and (3) reduction of carbon emissions by 50 per cent by 2050 compared to the 2005 levels in June 2009. The “Next Generation Air Transportation System” (NextGen) is an air transport management concept for the year 2025 and beyond, which meets US future air transportation safety, security, mobility, and environmental needs. The NextGen concept was enacted in 2003 by the Congress of the United States. An important benefit of NextGen is to provide environmental protection (FAA homepage). NextGen uses a five-pillar strategy of ‘advances in science and modeling’, ‘operational improvements’, ‘new technologies’, ‘renewable fuels’ and ‘policy initiatives including the environmental management system (EMS) to address environmental impacts. On the other hand, the National Aeronautics and Space Administration (NASA) in November 2007, presented the tech-

59

Innovation for Sustainability in Aviation

nological goals for future-generation aircraft that should be in service from 2030 to 2035 (NASA homepage). “European Aeronautics: A Vision for 2020” and the Strategic Research Agendas (SRA1, SRA2, Addendum) of the Advisory Council for Aeronautics Research in Europe (ACARE) exist to “better serve societies’ needs while becoming global leaders in the field of aeronautics”. The challenges for the European aviation industry include quality & affordability, the environment, safety, and the efficiency of the air transport system and security. The ambitious environmental goals are 50% CO2 reduction, 80% NOx reduction, and 50% noise reduction compared with 2000 levels (ACARE homepage). Japan does not have a clear shared vision throughout the national aviation industry. A target for domestic aviation, however, has arisen from the national sector-based approach under the Kyoto Protocol Target Attainment plan. The target is 15% improvement in energy efficiency (fuel consumption per pax-km performed). With the UNFCCC Conference of the Parties (COP) 15 close at hand, ICAO finally reached the first globally harmonized agreement on reducing the sector’s impact on climate change at the High-level Meeting on International Aviation and Climate Change in Oct 2009 (ICAO, 2009). The ICAO Programme of Action on International Aviation and Climate Change has a 2% annual fuel efficiency target for improvement up to 2050 and further discussions are expected on even more ambitious goals. These high targets are well shared and stimulate integrated development approaches between agents. There are dozens of technical and operational innovation proposals which include what could not be expected from development approaches by a single agent, such as open rotor engines.

60

Technical Development Directions Through observation of the current sector’s movement toward sustainable aviation, we found that various levels of innovative ideas have been proposed and developed. There are two main directions: One direction of innovation is to reduce fuel use by (1) lighter weight, (2) low air resistance aircraft design, (3) lean combustion and a high bypass engine, (4) an optimized electric system and (5) optimized flight routes Another direction is to replace fossil fuel by 6) biofuels. We discuss each innovation from (1) to (5), while considering (6) as a separate direction below: 1. Light weighting of aircraft: Weight is as critical as cost in aircraft development, and resistance to the severe environments of heat, load, and fire is required aircraft material. Replacement of metal by Carbon Fiber Reinforced Plastics (CFRP) is expected in this sector. According to the panel discussions of the CAIR seminar in Feb 2010, however, simple replacement by CFRP won’t bring enough reduction of weight because a drastic change of structural design is also needed to benefit from the use of CFRP. NASA is currently investigating a “failsafe” structure design instead of “safe-life” for lightweight composite structures in its research project, “Pultruded Rod Stitched Efficient Unitzed Structure” (PRESEUS) (Collier 2010). 2. Lowering air resistance of the aircraft: NASA is now conducting research about a Blended Wing Body (BWB), which can contribute to the reduction of both aircraft weight and air resistance by integrating the wings and the fuselage. In Boeing’s newest product, innovation in aerodynamics is achieved through state-of-the-art Computational Fluid Dynamics (CFD) technology and advanc-

Innovation for Sustainability in Aviation

ing wing technologies like multi-function ailerons and high-aspect ratio wings with CFRP (Blackner, 2010). 3. Improving fuel efficiency of the engine: Improvement of fuel efficiency is pursued in two directions, improvement of propulsive efficiency and thermal efficiency. A higher bypass ratio, of the air that passes around the engine to the air that passes through the engine, is effective in improving the propulsive efficiency by reducing the passed air flow speed. A higher bypass ratio, however, confronts the problem of the hypersonic rotation of blades and engine size. Mitsubishi announced the use of a geared turbo fan (GTF) engine made by Pratt & Whitney in the Mitsubishi Regional Jet (MRJ). Pratt & Whitney has developed a speed reduction gear which can improve propulsive efficiency with very high bypass ratio. The open rotor engine which allows a very high bypass ratio is now under development in many institutes and companies. The development of the open rotor must challenge safety and mounting issues. For thermal efficiency, the main issue has been how to make higher pressure and temperature in a combustion room possible without NOx increase. In Europe, a unique alternative cycle process with an intercooler system is now under investigation on a long-term basis. 4. Optimizing the electric system: The output from jet engines are used not only for propulsive purposes, but also for electric power generation and the power of the hydraulic and heating systems. GE and Boeing have developed a non-engine-bleed system in the 787, which replaces the bleed air heating and de-icing system by changing the engine’s output to an electric signal. The replacement can remove a lot of weight from the hydraulic system. An idea to store electricity, will

cause an increase of aircraft weight due to the weight of the battery. In fact, there is an inbalance of supply and demand in electric power generation. During the take off and climb, the engines generate a lot of power. On the other hand, during the cruise, the cabin requires a lot of electricity for air conditioning, meal preparation, etc. Research is being conducted to minimize the inbalance and to effectively use the engine output by generation and storage of electricity. Furthermore, the Japan Aerospace Exploration Agency (JAXA) is conducting hydrogen and fuel cell hybrid engine research with which an aircraft can cruise with fuel cell power and then use a hydrogen gas turbine engine when the fuel cell power is not enough. 5. Optimizing the flight route: Currently, aircrafts fly to their destination in zigzag for various reasons such as political and technological issues. While many political efforts to encourage effective use of airspace with airlines, military operators, business and general aviations of different countries are being made globally, a new air traffic management system which can optimize the route according to the airports’ particular environments and latest climate reports, are being developed and are under international agreement negotiation. The Federal Aviation Administration’s (FAA’s) PerformanceBased Navigation (PBN) system, which allows aircrafts to take preferred routing and trajectories, is an example of an innovative development. Test flights of PBN conducted and have shown a significant reduction of fuel consumption as well as other benefits like optimal use of air space, reduction of pilot/ controller voice transmission, etc.. The major technological challenge is how to manage plural operations safely without an additional load of works on operators and navigators.

61

Innovation for Sustainability in Aviation

6. Development of Biofuels: Airlines still have few choices when it comes to jet fuels (kerosene) because jet fuels for aircraft are strictly controlled by international standards. Any compound change in fuels, even without combustion characteristics change, need to be approved for safety and reliancy. On the other hand, relying only on kerosene is a menace to the airlines in terms of future energy security and high prices. For energy diversity generally, the fuel candidate must be handled like oil so that XTL such as Gas to Liquid (GTL), Coal to Liquid, and Biomass to Liquid (BLT) have been challenged. For alternative aviation, too, “dropin” fuel which can replace current jet fuels without change to aircrafts has been actively investigated (Okai, 2010). The use of XTL products produced by new industry processes, which have been developed for more than thirty years, have been approved by the American Society For Testing and Materials (ASTM), an international standards for aviation. Synthetic gas from natural gas, coal, or biomass are being processed in the Fisher-Tropsch process to log chain paraffins and are finished in hydroprocessing and separated into final XTL products. ASTM D7566, a standard for Aviation Turbine Fuel Containing Synthesized Hydrocarbons, which was issued in Sep. 2009, accommodates up to 50% blends of conventional aviation turbine fuel with synthesized hydrocarbon blend components produced from coal, natural gas, or biomass using the Fischer-Tropsch process. For low carbon jet fuel, experts say that biofuel is technically feasible. While 1st generation biofuels often produced from seeds or grains such as wheat, are criticized for their strong adverse effects regarding food shortage in developing nations (Hansen et al., 2009, Schaltegger et al., 2005), 3rd generation biofuels derived from algae avoid this criticism since they can be

62

grown on soil or in water that is otherwise unsuitable for food production (Sustainable Aviation, 2010, Ito, 2010). Many test flights have been completed by Boeing, Airbus, and many research institutes (Blackner, 2010, Szodruch, 2009). According to Shell (Ito, 2010, Bauldreay, 2010), the cost of production due to the longer refining routes, and the cost of feedstock and poor yields are the big obstacles when the biofuels try to replace the kerosene.

PERSPECTIVES ON AVIATION FOR SUSTAINABILITY In this section, we are going to investigate, on the basis of SNM findings, whether current aviation sector’s activities toward sustainability can be implemented successfully. According to the findings from SNM research, development of a broad network including actors from dominant “regimes” such as policy makers, users, suppliers, knowledge institutes and also new actors such as small innovative firms, is very important. For the success of the project, SNM also emphasizes the importance of high expectations to the vision by all of the actors and of internal and external learning cycles on technologies, infrastructures, and policies (Van der Laak et al., 2007).

Active Networks Table 2 shows some examples of active networks found among agents in the aviation projects for sustainability. A close relationship among agents has supported a number of innovations since the Wright brothers. Aviation is an integrated multi-technology system. Aircraft development and operation involve thousands of people all over the world. During the development of a new aircraft, such as the Boeing 787, or the Mitsubishi MRJ, the aircraft manufacturer “works together” with not only engine manufacture and other suppliers but

Air Transport Association (ATA) Aerospace Industries Association (AIA)

Boeing

AIA

P&W, R-R, GE

54 industries

P&W, GE, R-R

Contracts

P&W

GE& Rolls-Royce

Engine Manufacturers

15 instit. + 17 univ.

NASA

JAXA

NASA

Research institutes / Academia

Airports

Airports Council International North America (ACI-NA)

€€

Commercial Aviation Alternative Fuels Initiative (CAAFI) - Environmental team - R&D team - Certification-Qualification team - Business & Economics team

JAL, COA, ANZ, VJM

54 industries

EU Clean Sky Programme - 6 integrated technology demonstrators - 40% CO2 reduction

Sustainable biofuel viability

Boeing, Honeywell

FAA Continuous Lower Energy and Noise (CLEEN) Project - Focus on NASA N+1 goal - 33% fuel burn reduction

Mitsubishi

Boeing

Contracts

ANA

ANA

Aircraft/ Avionics Manufacturers

NASA Environmentally Responsible Aviation (ERA) Project - Focus on NASA N+2 goal - 50% fuel burn reduction

Mitsubishi MRJ - 70% lower CO2 emissions from ICAO CAEP6 requirements - Pratt & Whitney PurePower PW1000G: 12~15% fuel efficient

Boeing 787 Dreamliner - 20% reduction in fuel and CO2 (Relative to the 767)

IATA four-pillar strategies; “Improved technology”

Projects, Activities, Technologies

Airlines

Table 2. Landscape of aviation activities for sustainability

FAA

European Commission

Federal Aviation Administration (FAA)

FAA, JCAB

FAA

Governments /Air control services

Shell

Young (ATA) Inside Maurice (CAAFI) Inside Baudreay (Shell) Inside

Blackner (Boeing) CAIRMay

Wetzel (Federal Environmental Agency) CAIR-May

Hanlon (FAA) CAIR-May

Collier (NASA) CAIR-May

Sakura (Mitsubishi) CAIRFeb Parakeh (P&W) Inside

Blackner (Boeing) CAIRMAY

Data Sources*

continued on following page

UOP etc.

20 small and medium enterprises

Others (fuel suppliers)

Innovation for Sustainability in Aviation

63

64 Airlines Aircraft/ Avionics Manufacturers

JAL, ANZ, QFA, UAL, SIA

FAA

Air service of AU, NZ, SG, JP US

Governments /Air control services

EU

US Airports

AU, NZ, SG, JP US Airports

Airports

EU-ETS - All airlines operating in territory of the EU from 2012 - CO2 will be capped at the 97% level of average emissions for 2004-2006 and will be lowered to 95% from 2013

Research institutes / Academia

Japan Civil Aviation Bureau (JCAB)

Engine Manufacturers

JAPAN - Corporation tax and property tax reduction to promote new efficient aircraft - Application of Act on the rational use of energy for large airlines

IATA four-pillar strategies; “Positive economic measures”

Performance Based Navigation (Next Gen) - Radar Navigation (RNAV) - Required Navigation Performance (RNP)

Asia and Pacific Initiative to Reduce Emissions (ASPIRE)

IATA four-pillar strategies; “Effective operations” and “Efficient infrastructure”

Projects, Activities, Technologies

Table 2. Continued Others (fuel suppliers)

Anger-Kraavi (Cambridge Uni) CAIR-Feb

Shimizu (JCAB) CAIRMay

Hanlon, FAA, CAIR-Feb

Funai, JAL, CAIR-Feb Hanlon, FAA, CAIR-May

Data Sources*

Innovation for Sustainability in Aviation

Innovation for Sustainability in Aviation

also with airlines and government agencies. Among various projects, the Asia and Pacific Initiative to Reduce Emissions (ASPIRE) and the Commercial Aviation Alternative Fuels Initiative (CAAFI) are especially interesting because the networks found in the former project are international, and the later project involves more different agents than in most other aviation projects (Table 2). ASPIRE: ASPIRE was created in 2008 as a joint partnership between air navigation service providers – Airservices Australia, Airways New Zealand, and the FAA – to demonstrate optimized operational procedures to reduce fuel burn with current best practices and existing technology. The Japan Civil Aviation Bureau (JCAB) and the Civil Aviation Authority of Singapore (CAAS) joined in the ASPIRE partnership in 2009, and 2010, respectively. To date ASPIRE has conducted five flight demonstrations with Air New Zealand Qantas, United Airlines, Japan Airlines (JAL), and Singapore Airlines on oceanic routes. The oceanic routes have a culture which accepts changes, and has the most modern aircraft fleet, as well as many advanced ocean ground automation systems. The five flights demonstrated the maximum potential for environmental efficiency. For example, JAL flight J077 from Honolulu, U.S. to Kansai, Japan, on the 10th of October 2009 succeeded in a 4,825kg fuel consumption reduction; in other words, a 15,247kg CO2 emission reduction (Funai, 2010). The flight was fueled with the latest on-board loads data, used the closest runway, followed shorter departure routes adjusted by the U.S. Air Force, took a User Preferred Route for the oceanic phase of the flight with a dynamic airborne re-route procedure instead of a route determined by 24-hours old climate data, arrived with Continue Descended Approach, and optimized a flap/ undercarriage/ thrust-reverse operation. CAFFI: CAAFI has been working to lead development and deployment of alternative jet fuels for commercial aviation since 2006 under the leadership and sponsorship of the Federal Aviation

Administration (FAA), Airports Council International – North America (ACI-NA), Aerospace Industries Association (AIA) and the Air Transport Association of America (ATA). “The coalition of airlines, aircraft and engine manufacturers, energy producers, researchers, international participants, and U.S. government agencies” has accelerated preparation for alternative fuel introduction (Maurice, 2010). For example, any slight change to a jet fuel needs a certification approval because of the strict priority to safety in this sector, and this approval is usually a long procedure. ASTM D7566, which is a specification for Aviation Turbine Fuel Containing Synthesized Hydrocarbons accommodates up to 50% blends of conventional aviation turbine fuel with synthesized hydrocarbon blend components produced from coal, natural gas, or biomass using the Fischer-Tropsch process, was approved in 2009 with an exceptionally fast procedural speed because of supports to evaluation and qualification of alternative fuels by CAAFI and other agencies (Rumizen, 2009). In CAAFI, the FAA leads the Environmental team and the Certification-Qualification team, AIA leads the R&D Team, and ATA and ACI-NA comprise the Business & Economic team. Shell, which has contributed to the fuel readiness level of the Fischer-Tropsch process and other alternative fuels, is an active member of CAAFI, as well as various international aviation alternative fuel projects: FAA-PARTNER, ASTM, CRC, IATA & EU programs SWAFEA and Alfa-Bird (Bouldreay, 2010). * Inside stands for “Inside Aerospace” held by AIAA on the 11th and 12th, May, 2010. CAIRFeb and May stand for “International Seminar on Aviation and Climate Change” on February 18th, 2010, and an “Aviation Environment Workshop” on May 19th, 2010 held by Authors. In addition to the projects in the Table 2, there is an interesting initiative within UK, Sustainable Aviation, which brings together the UK’s leading airlines, airports, aerospace manufacturers and air navigation service providers. The sorts of agents

65

Innovation for Sustainability in Aviation

involved in the initiative is typical as for aviation but the aim of this initiative is broad. The initiative sets a series of eight goals and 34 commitments relating to economic, environmental and social aspects of aviation. The initiative is for the long term sustainability of the UK aviation industry but provides interesting and important reports about alternative fuels, CO2 efficient airport operation etc. through its homepage (Sustainable Aviation homepage). The initiative is strong and leads the government (Sunetra, 2010).

A Forked Expectation Governments and other non-profit organizations expect suppression of greenhouse gas effects in the aviation sector for innovations presented in the previous section. On the other hand, in actuality, the expectation from airlines for innovations is heterogeneous. Airlines, which are the main customers and users of new technology and systems, look for cost reduction before reduction of greenhouse gases. However, in many presentation documents of the four meetings, a slide with the equation: “Fuel reduction = CO2 emission reduction” is shown. This equation amplifies the driving force behind innovation. In the new aircraft development phase, fuel efficiency is a critical factor in addition to speed, load capacity, and aircraft range without any trade-offs in safety and security. This priority among fuel efficiency, speed, load capacity and aircraft range changes, however, depending on the business and social environment for operators such as airlines and sometimes airports. Recent soaring fuel prices and the expectation from governments to operators to reduce CO2 emissions raise the need for fuel efficiency in the priority competition. Governments and airlines, manufacturers and research institutes expect technological breakthroughs for technological and operational innovations. Therefore, “Fuel reduction = CO2 emission reduction”, accelerates the sector’s activities on sustainability innova-

66

tion. The expectations of the airlines themselves are especially important because it is the airlines that finally decide whether or not to modernize their fleets (e.g., Lufthansa’s fleet modernization programme of 170 aircrafts with a list-order price of 16 billion euros (Haag, 2009)). Airlines open the window of opportunity for technological and system innovations to spread in actual operations. Nonetheless, the aviation industry still needs more discussions about the stage where CO2 emissions reduction is not equal to cost reduction any more. “Drop in” biofuels, are one of the most feasible candidates for low carbon alternative fuel. In terms of cost, however biofuels are not competitive against current jet fuel (Ito, 2010). Even though many airlines are open to development in various alternative fuel projects such as CAAFI for example, the main expectation of airlines to biofuel programs is energy security and corporate social responsibility. So even if biofuels can be used technically, the positive participation of airlines to the development does not promise the positive use of the low carbon alternative fuels if the current kerosene jet fuel is still available and less expensive than alternatives. In order to introduce technological and system innovations and the use of low carbon fuels to achieve a carbon-neutral environment, we need a new mechanism to keep such different expectations to the same direction. From the discussions in the four meetings, however, a lack of ideas about positive economic measurements, the 4th pillar of IATA strategies, seemed to stand out. The cap-and-trade scheme is considered by many politicians and economists to be one of the most effective methods for realizing a low GHG society (Duval, 2009). The cap-andtrade scheme can add more value to low-carbon technologies so that these technologies can enter the market. In the U.S., which didn’t ratify the Kyoto-protocol, or pass national legislation for cap-and-trade, many regional initiatives have been established with the aim of reducing GHG from particular regions and most initiatives are preparing a cap-and-trade scheme, although the

Innovation for Sustainability in Aviation

aviation industry is not yet included in the scheme (McCann, 2010). The EU emission trading system (EU-ETS) is one of a few propositions made to the aviation sector as a positive economic measure. From 2012, the EU will begin an emissions trading system (EU-ETS) for all airlines operating in the territory of the EU. CO2 will be capped at the 97% level of average emissions for 2004-2006 and will be lowered to 95% from 2013. While the cap-and-trade scheme can be expected to evaluate the cost benefits of low-carbon technology for aircraft, this scheme still has the problem of reducing airline business rather than replacing conventional fleets with innovative low-carbon technology. The reduction of airline business causes a reduction of mobility. Stopping the significant increase of traffic is actually one of the purposes of EU-ETS supporters. However, secure of mobility is also important in a different frame, for example, in the regional economic gap issue. Because when airlines need to reduce the business, they may start the reduction from abandonment of the routes to developing regions. Even though cap-and-trade is a positive mechanism urgently needed in the implementation of aviation for sustainability, long discussions are still necessary before putting such a scheme into effect. For example, the EU-ETS was sued recently by the US Air Transport Association of America (ATA) to halt and is assumed not to be able to start from 2012 (Young, 2010). We need, therefore, other measures to compliment the time gap from now until the introduction of the cap-and-trade scheme to the aviation sector. Daley and Preston (2009) assessed market-based policy options, which is similar to IATA’s 4th piller of, ‘Positive economic measures’, for the mitigation of aviation impact to climate change. The authors listed environmental taxes, emission charges, subsidies and tradable permits as marketbased policy options. The authors assessed that any of these options confront problems of uncertainty in aviation’s impact on climate change, distortions of international airlines or manufacturing markets,

or the complexity of the international aviation agreements. There is another option, which is not a positive economic measure nor a market-based approach but a regulatory approach. The ICAO is now investigating a CO2 standard similar to noise and NOx. In aviation operation, strict noise standard, such as ICAO “chapter”, or on the U.S. “stage”, plays a significant role to reduce noisy aircrafts. If an aircraft doesn’t satisfy the noise standard, the aircraft can not operate. The standard has proven its big effect on airline fleet strategies.

FUTURE RESEARCH DIRECTIONS In previous sections, we have seen that there are various projects of aviation sustainability and we have analyzed the perspectives of these projects. While we found growing networks, we recognized that the driving forces from markets are within the limits of expectation on cost-efficiency. Besides of these facts, we must note the IATA’s report, which warns that even we implement all of the technology and operational innovations (a) lighter weight, (b) low air resistance aircraft design, (c) lean combustion and a high bypass engine, (d) an optimized electric system and (e) optimized flight routes), it is not achievable to bring aviaFigure 1. Schematic roadmap of aviation CO2 emissions under the effect of reduction measures (Adapted from IATA, 2009)

67

Innovation for Sustainability in Aviation

tion to CO2 carbon neutral emissions (Figure 1). “Regime” changing innovations are expected for “Carbon Neutral Growth from 2020”. We need to discuss how to manage a radical technology or system change. And we think it is important to understand the driving force in the aviation socio-technical system in multi-level perspectives. Multi-Level Perspectives (MLP) is a useful approach to understanding transition pathways of an innovative idea to integrate in the main stream of a system or a society. It comes from SNM researches and has a complementary relationship with SNM (Schot & Geel, 2008). The MLP distinguishes three levels (niche, regime and landscape) in a system. Niches are a level of emerging innovations and are situated at the margin of the regime. Regimes are a level of the main or existing streams and create stability of the system. Landscapes are the macro-level of society as a whole. The interplay between dynamics at multiple levels leads transitions. See Geels (2006) for further explication. In brief, Geels concluded that co-evolution at the regime level was clearly visible in his case studies of past technology or system replacements. There was a strong interaction between technology and markets. Transitions are not caused by a change in a single aspect, but by the interplay of many aspects and actors. A MLP approach may help Green’s (2002, 2006) radical idea of flight with short-range aircraft with several refuelings before arriving at their destination. A lot of technical papers and significant benefit have been proposed, but this idea doesn’t appear in a roadmap of this sector. Green’s idea is against the development of longrange aircraft, or of aircraft technology itself. The development of longer-range flights is often described in the first slides of manufacturers and airline presentations. For example, development of aircraft technology reduced the number of stops of the London-Sydney flight from 32 stops and 10 days in 1939 by Flying Boat, 2 stops and 26 hours in 1990 by 747-400 to 0 stops and 19.5 hours in 2006 by 777-200LR, according to Qan-

68

tas. But according to Green, using an aircraft of 5000km range capacity with stops of lubrications at airports can be about 40% more fuel efficient than carrying the same number of passengers along a 15000km distance using an aircraft of 15000km range capacity. This difference is due to the weight of fuel, which covers all of the flight. In other words, for carrying fuels, a long distance flight consumes nearly half of the fuel. Green’s short-range aircraft idea is an effective solution for the reduction of CO2 emissions, but it is considered unrealistic. Customers will not accept the trouble of stopping in several airports once they have taken a non-stop flight. Although there is the idea of air-to-air refuelling, this type of refuelling is risky in terms of safety. For such a socially challenging issues, MLP approach will be useful to list the problems to solve and organize the learning process. Some of MLP researchers study the interaction of different niches or regimes. There are several options for the future aviation system. Many stakeholders wish aviation for sustainability. On the other hand, there are some options that may go opposite direction of “sustainability”. Supersonic transportation attracts some of airlines and business travellers. Cohen (2010) detected the small but strong human desires for personal aeromobility pushing back the force for sustainability. Each innovative aviation scenario including “sustainability” has opposite and favourable driving forces and may not able to be realized by itself. If we could combine the favourable driving forces, we might be able to obtain sustainability and even further ideals for the sector. For example, we may be able to load low-carbon technologies on personal aircraft in the same way as Toyota obtained technology and cost supremacy in the hybrid engine mark by mounting the hybrid engine in the compact size car and pursuing low profit but high volume. Even though the requirements for safety and security will not change between small and large aircraft, small aircraft might have advantages in terms of the difficulty of develop-

Innovation for Sustainability in Aviation

ment because of the strength and complexities of the system as well as the scale of the market. Manufacturers may be able to innovate their technology development from small aircraft, which has fewer constraints, and transform these technological developments in big aircraft much earlier than in direct development to big aircraft. Therefore, we propose management of the sector’s future options in multi-level perspectives as a future research directions for sustainable aviation.

need a specific remedy before a trade scheme is finally put into effect after many more necessary long discussions. Finally, we have presented future research directions using a multi-level perspective approach, which is useful in discussing how to bring innovations to practice. The aviation sector has had a number of innovative successes. Sustainability issues, however, may need a paradigm shift due to the higher overall complexity of issues.

CONCLUSION

REFERENCES

Only 1% of the world population has flown yet, but rapid growth of airline traffic, especially in Asia is expected in the near future (Upham, 2003). Air transportation interacts with current business and the economical practices and policies and well as through social activities, such as allowing people to meet their families on different continents. How to achieve aviation for sustainability without jeopardizing mobility is a huge issue for the sector. We collected and analyzed the latest experts talks from four international meetings for Aviation and the Environment held by ICAS, AIAA, and CAIR between Sep. 2009 and May. 2010. These meetings invited experts and researchers from Japan, Europe, and North America to mitigate the aviation impact to climate change. We saw that various levels of vision are well shared between agencies and many technology and system innovations are upcoming. We also found that the networks between agencies are expanding through initiatives. In spite of ambitious innovation plans, strong traffic growth makes it difficult to suppress the aviation impact to climate change. We discussed the need for positive economic measures to put a higher value on the need for low- carbon technology in the sustainability context. The cap-and-trade scheme is considered to be one of the best solutions, but at the same time, we may

Boeing (2010). Current Market Outolook 20102019. Retrieved August 28, 2010, from http:// www.boeing.com/ commercial/cmo/ Collier, F. (2010, May). NASA’s Environmentally Responsible Aviation (ERA) program.Presented at the University of Tokyo Boeing Aviation Environment Workshop, Tokyo. Conference of the Parties (1997, December). Kyoto Protocol to the United Nations Framework Convention on Climate Change, 3rd Session, Kyoto. Bauldreay, J. M. (2010). Aviation – Current energy challenges. A fuel producer’s perspective. Presented at the AIAA Inside Aerospace Conference, Arlington, VA. Blackner, A. (2010, May). Environmental technologies update. Presented at the University of Tokyo Boeing Aviation Environment Workshop, Tokyo. Daley, B., & Preston, H. (2009). Aviation and climate change: Assessment of policy options. In Gossling, S., & Upham, P. (Eds.), Climate change and aviation (pp. 347–372). Earthscan Climate. Dries, D. L. T., van Villet, J., & van Villet, B. J. M. (2007). Niche management and its contribution to regime change: The case of innovation in sanitation. Technology Analysis and Strategic Management, 9, 729–746.

69

Innovation for Sustainability in Aviation

Duval, D. T. (2009). Aeropolitics and economics aviation emissions mitigation. In Gossling, S., & Upham, P. (Eds.), Climate change and aviation (pp. 179–192). Earthscan Climate. Funai, Y. (2010, February). Overview of ASPIRE flight: The ultimate CO2 reduction flight. Presented at the International Semiar on Aviation and Climate Change, Tokyo. Geels, F. W. (2006). Co-evolutionary and multilevel dynamics in transitions: The transformation of aviation systems and the shift from propeller to turbojet (1930-1970). Technovation, 26, 999– 1016. doi:10.1016/j.technovation.2005.08.010 Green, J. (2002). Greener by design - The technology challenge. Aeronautical Journal, 106, 57–113.

Homepage, A. I. A. A. (n. d.). Retrieved from http://www.aiaa.org/ Homepage, C. A. I. R. (n. d.). Retrieved from http://aviation.u-tokyo.ac.jp/ Homepage, F. A. A. (n. d.). Retrieved from http:// www.faa.gov/ HomepageI. C. A. S. (n. d.). http://www.icas.org/ Hoogma, R., Kemp, R., Schot, J., & Truffer, B. (2002). Experimenting for sustainable transport: The approach of strategic niche management. London, New York: Spon Press. IATA. (2009). The IATA Technology Roadmap Report (3rd ed.). Swizerland.

Green, J. (2006). Kuchemanns weight model as applied in the 1st Greener by Design Technology Sub Group Report: A correction, adaptation and commentary. Aeronautical Journal, 110, 551–516.

ICAO. (2009). ICAO-Uniting international aviation on climate change. ICAO news release, PIO 14/09. Retrieved on July 17, 2010, from http:// www.bangkok.icao.int/ news/2010/ pio-14-09final.pdf

Haag, K. (2009, September). Environmental policy of a global airline. Presented at ICAS Workshop 2009, Amsterdam, The Netherlands.

Ito, T. (2010, February). Shell energy scenario 2050. Presented at the International Semiar on Aviation and Climate Change, Tokyo, Japan.

Haan, A., & de Mulder, K. (2002). Sustainable air transport: Identifying possibilities for technological regime shifts in aircraft construction. International Journal of Innovation Management, 6, 301–318. doi:10.1142/S1363919602000628

Kivitsa, R., Charlesa, M. B., & Ryanb, N. (2010). A post-carbon aviation future: Airports and the transition to a cleaner aviation sector. Future, 42, 199–211. doi:10.1016/j.futures.2009.11.005

Hanlon, D. (2010, May). FAA environmental initiatives. Presented at the University of Tokyo Boeing Aviation Environment Workshop, Tokyo, Japan. Hansen, E. G., Große-Dunker, F., & Reichwald, R. (2009). Sustainability innovation cube — A framework to evaluate sustainability-Oriented innovations. International Journal of Innovation Management, 13, 683–713. doi:10.1142/ S1363919609002479 Homepage, A. C. A. R. E. (n. d.). Retrieved from http://www.acare4europe.com/

70

Lee, D. S., Pitari, G., Grewe, V., Gierens, K., Penner, J. E., Petzold, A.,...Sausen, R. (2009). Transport impacts on atmosphere and climate: Aviation, Journal of Atmospheric Environment. doi:10.1016/j.atmosenv.2009.06.005 Maurice, L. (2010, May). Greening U. S. Aviation. Presented at the AIAA Inside Aerospace Conference, Arlington, VA. McCann, M. G. (2010, May). Greenhouse gas regulations and associated energy issues. Presented at the AIAA Inside Aerospace Conference, Arlington, VA.

Innovation for Sustainability in Aviation

NASA. (2010). Subsonic fixed wing – Research overview. Retrieved August 28, 2010, from http:// www. aeronautics.nasa.gov/ fap/ sfw_research_ overview_feature.html Okai, K. (2010, February). R&D on de-carbonized engines at JAXA. Paper presented at the University of Tokyo Boeing Aviation Environment Workshop, Tokyo. Randles, R., & Bows, A. (2009). Editorial, aviation, emissions and the climate change debate. Technology Analysis and Strategic Management, 21, 1–16. doi:10.1080/09537320802557194 Raven, R. O. J. M., & Geels, F. W. (2010). Socio-cognitive evolution in niche development: Comparative analysis of biogas development in Denmark and the Netherlands (1973-2004). Technovation, 30, 87–99. doi:10.1016/j.technovation.2009.08.006 Rumizen, M. (2009). Aviation turbine fuels, ASTM standardization news. Retreived August 16, 2010, from http://www.astm.org/ SNEWS/ ND_2009/ d02J006_nd09.html Schaltegger, S., & Burritt, R. (2005). Corporate sustainability. In Folmer, H., & Tietenberg, T. (Eds.), The International Yearbook of Environmental And Resource Economics 2005/2006: A Survey of Current Issues (pp. 185–222). Cheltenham, UK: Edward Elgar. Schot, J., & Geels, F. W. (2008). Strategic niche management and sustainable innovation journeys: Theory, findings, research agenda, and policy. Technology Analysis and Strategic Management, 20, 537–554. doi:10.1080/09537320802292651 Smith, A. (2006). Niche-based approaches to sustainable development: Radical activists versus strategic managers. In Bauknecht, D., Kemp, R., & Voss, J. (Eds.), Sustainability and reflexive governance. Camberley, UK: Edward Elgar.

Sunetra, M. (2010, March). Assistant director of Department for Business Innovation & Skills. Private Discussion. Sustainable Aviation. (2010). Sustainable alternative fuels progress paper, Summer 2010. Retreived November 18 2010 from http://www. sustainableaviation.co.uk Szodruch, J. (2009, September). DLR climate research and aircraft technologies. Presented at ICAS Workshop 2009, Amsterdam, The Netherlands. The Group of Personalities. (2001). European aeronautics: A vision for 2020. European Communities. Luxemburg. Upham, P. (2003). Introduction: Perspectives on sustainability and aviation. In Upham, P., Maughan, J., Raper, D., & Thoams, C. (Eds.), Towards sustainable aviation (pp. 3–18). Earthscan Climate. Van der Laak, W., Raven, R., & Verbong, G. (2007). Strategic niche management for biofuels. Analysing past experiments for developing new biofuel policies. Energy Policy, 35, 3213–3225. doi:10.1016/j.enpol.2006.11.009 Weber, M., Hoogma, R., Lane, B., & Schot, J. (1999). Experimenting with sustainable transport innovations. Workbook for Strategic Niche Management. CEC Joint Research Centre in Seville. Wetzel, F. (2010, February). Air pollution abatement and energy saving in the transport sector. Presented at the International Semiar on Aviation and Climate Change, Tokyo, Japan. Young, N. N. (2010, May). Aviation – Current energy challenges: A view from the airline industry on energy & environment. Presented at the AIAA Inside Aerospace Conference, Arlington, VA.

71

Innovation for Sustainability in Aviation

KEY TERMS AND DEFINITIONS Carbon Neutral Growth: Airlines are the first global industry, which committed their growth without increase the carbon emission from 2020. IATA 4 Pillars Strategies: The International Air Transport Association (IATA), created and have been promoting a four-pillar strategy, ‘Improved technology’, ‘Effective operations’, ‘Efficient infrastructure’ and ‘Positive economic measures’, since 2007 to achieve a vision of “carbon-neutral growth in the mid-term and to build a zero emission commercial aircraft within the next 50 years” (IATA homepage).

72

Multi-Level Perspectives (MLP): MLP is a useful approach to understanding transition pathways of an innovative idea to integrate in the main stream of a system or a society (Schot and Geel, 2008). Strong Air Traffic Growth: The growth of air traffic is statistically faster than economic, GDP growth and eventually has canceled the recent effort of fuel-efficient improvement (Szodruch, 2009). Sustainable System Innovation: Researchers of systems innovation have been recently developing many theories and tools to promote the transitions required to make it possible to move innovations from laboratories to market.

73

Chapter 5

Diffusion and Adoption of Innovations for Sustainability Helen E. Muga University of Mount Union, USA Ken D. Thomas Auburn University, USA

ABTRACT The primary focus of this chapter is on the theory and concepts of sustainability and why they are important to innovation and vice-versa. Key reductionist approaches to assessing sustainability such life cycle assessment (LCA), life cycle cost analysis (LCCA), and sustainability indicators are discussed in detail and applied to an engineering infrastructure scenario. The integrated sustainability methods of life cycle assessment and life cycle cost analysis enable a business to assess alternative products or processes at the planning and design stages. They may also be used during the production stages to assess whether a business needs to use a different raw material to make their products. The role of management, social network analysis, and mental models of individuals in the diffusion and adoption of innovations are also explored.

INTRODUCTION Over the centuries, energy consumption has increased from 10 quadrillion BTU (10.055 x 1018 joules) in year 1800 to 500 quadrillion BTU (5000 x 1018 joules) in year 2000 (UN Environment Programme, 2007). Population, carbon dioxide emissions, water use, amounted of domesticated DOI: 10.4018/978-1-61350-165-8.ch005

land, loss of tropical rain forest and woodland, and nitrogen flux to coastal zones have also increased over time. Population increased from 600 million in year 1750 to 6 billion in year 2000. Carbon dioxide emissions increased from 250 ppmv in year 1800 to 360 ppmv in year 2000. Water use increased from 200 km3/year in 1900 to 5000 km3/yr in 2000 and nitrogen fluxes increased from 0.25x1012 moles/year in year 1850 to 9x1012 moles/year in 2000 (Crutzen, 2005). Unsustainable

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Diffusion and Adoption of Innovations for Sustainability

practices such as excess consumption, unsustainable management practices exacerbate current global problems. These global challenges/issues are intricately linked to one another. Figure 1 shows the interaction between population, natural resources and services, energy, emissions, and climate change. The introduction, and the diffusion and adoption of sustainability concepts and theory to a large extent attempts to address current global challenges that society and future generations face by reducing excess consumption, promoting efficient management and use of natural resources, and reducing consumption of energy sources that contribute to climate change The term “sustainability” has different meanings to different people. One of the definitions of sustainability is that it is “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (Brundtland, 1987). At the business level, sustainability is defined as, “meeting the needs of a firm’s direct and indirect stakeholders (such as shareholders, employees, clients, pressure groups, communities etc), without compromising its ability to meet the needs of future stakeholders as well” (Dyllick & Hockerts, 2002). In this chapter, we focus on the theory and concepts of sustainability (life cycle assessment, life cycle cost analysis, and indicators) and their application to the built environment. In this chapter, we focus on the theory and concepts of sustainability (life cycle assessment, life cycle cost analysis, and indicators) and their application to the built environment. The built environment includes “all of the physical structures engineered and built by people—the places where we live, work, and play. These edifices include homes, workplaces, schools, parks, and transit arrangements” (Dearry, 2004). They also include roads, power generation facilities, harbors, treatment plants, bike paths, and storm-water management systems. These engineered structures sustain and support human activity and continuity. The built environment is one of the largest consumers of raw materials and 74

energy. Over three billion tons per year of global raw materials (40%) are consumed in the United States (U.S. Green Building Council, 2005). Commercial and residential buildings consume around 36% of energy and over 65% of electricity in the U.S. (U.S Green Building Council, 2005). Further, construction, renovation, and demolition of buildings contribute a significant amount to total solid waste in the U.S. and around the world. In 1997 alone, construction and demolition waste amounted to 65% of all solid waste in the U.S (U.S.EPA, 2000). We also focus on the role of management in the diffusion and adoption of innovative strategies that contribute to sustainability and drive it over the ‘tipping point- defined as the point at which an object is displaced from its current state (of trajectory) into a new state (of trajectory). Of great importance are the types of strategies that businesses and various entities adopt and their impact on sustainability. For example, do the innovative strategies that are adopted drive the business toward sustainability or away from it? A great deal of emphasis is given to the role of learning and its impact on the change in mental models of individuals as these play a critical role in the adoption and diffusion of innovation.

OVERVIEW OF SUSTAINABILITY AND SUSTAINABLE DEVELOPMENT While there are varying definitions of sustainability from different sectors of industry, what is important is that it strives for protection of the environment, prudent use of natural resources, equitable social progress, and maintenance of economic well-being without compromising the environment and society. Figure 1 shows the three dimensions of sustainability. Long-term strategies towards achieving sustainability should consider all three aspects (i.e. the whole or complex system), either at the decision stage or during the operational stage.

Diffusion and Adoption of Innovations for Sustainability

Figure 1. Linkages between population, resources, consumption, emissions, and climate change. Population growth requires significant amount of natural resources and energy to sustain and support, with positive and negative impacts. An increase in population, leads to an increase in energy and natural resources (+). This subsequently contributes to increase in emissions (+) which in turn contribute to climate change (+). A decrease in population leads to a decrease in energy and resource consumption (-). The adoption of sustainable practices by the public and in the energy sector also contributes to a decrease in energy consumption (-).

The three core pillars of sustainability (Figure 2) or the ‘triple bottom-line’ (i.e. People. Planet and Prosperity) are inter-connected and hence may influence each other in multiple ways. Understanding the inter-connectedness and employing strategies that consider all three dimensions is critical to achieving sustainability. Strategies that concentrate on short-term gains often focus on one aspect of the triple bottom line. Ongoing research and development in the field of sustainability science has expanded those 3 core pillars to 5 pillars of sustainability: environment, culture, politics, society and economy (McConville & Mihelcic, 2007). Inclusion of environmental and societal aspects in addition to economic aspect into long-term strategies enables a company/firm or other entities to meet the needs of the present without compromising the needs of the future. It also gives the entity a competitive advantage over its competitors as the public and society become socially and environmentally conscious. Further inclusion of

the triple bottom line in decision-making, brought about by a change in mental model of the decisionmaker towards sustainability, has the potential to significantly reduce/mitigate the upward trend in carbon dioxide emissions, energy consumption, water use and nitrogen fluxes in waterways. Adoption and diffusion of sustainable strategies (sustainable management practices, education, technology) is key to controlling, reducing, mitigating the upward trend unsustainable practices. According to Mihelcic et al. (2003), sustainable development is the design and use of human and industrial systems to ensure that humankind’s use of natural resources and cycles do not lead to diminished quality of life due either to losses in future economic opportunities or to adverse impacts on social conditions, human health and the environment. According to the United Nations Educational, Scientific and Cultural Organization (UNESCO), sustainable development ‘is a vision of development that encompasses populations, animal and plant species, ecosystems, natural

75

Diffusion and Adoption of Innovations for Sustainability

Figure 2. The three interconnected pillars of sustainability consist primarily of the environmental (planet), economic (prosperity), and social (people) dimensions with emerging dimensions of culture and politics

• • •

• • •

Recognition of emerging risks and or conflictive issues, thus allowing prevention; Detection of impacts to allow for timely remedial action when needed; Performance measurement of the implementation of development plans and management actions; Reduced risk of planning mistakes; Reduced public liability; and Regular monitoring which can lead to rolling improvement.

According to the Organization for Economic Cooperation and Development, there are different kinds of indicators, each with different purposes for decision makers: •

resources and that integrates concerns such as the fight against poverty, gender equality, human rights, education for all, health, human security, intercultural dialogue, etc.’ In the context of sustainable development, indicators are information sets which are formally selected to measure changes in assets and issues that are key for the product development and management. Indicators are measures expressed in single numbers, percentage or ratios, qualitative descriptions or existence/non-existence of certain elements concerning environmental, social and economic issues (OECD, 1993). They are signals of current issues, emerging situations or problems, need for action and results of actions. Sustainability indicators should be easy to comprehend, as well as be economically and technically feasible to measure for them to be classified as good (OECD, 2003). Benefits from good indicators include (adapted from OECD, 2003): •

76

Better decision making in order to lower risks or costs;

• • •

• •

Early warning indicators (e.g., decline in product sales and number of customers who intend to return); Indicators of stresses on the system (e.g., raw material shortages); Measures of the current state of the industry that the product primarily serves; Measures of the impact of product development and production on the biophysical and socio-economic environments (e.g. indices of the level of deforestation, changes of consumption patterns and income levels in local communities); Measures of management efforts; and Measures of management effect, results or performance.

SUSTAINBILITY THEORY AND CONCEPTS Sustainability, as defined by The Brundtland Commission, strives to achieve the following: (1) maintenance of economic well-being, (2) social progress, and (3) environmental protection for the present and future generation through the use of various assessment methods such as life

Diffusion and Adoption of Innovations for Sustainability

cycle assessment, life cycle cost analysis, and sustainability indicators. These various integrated methods of assessment attempt to evaluate the impacts of various processes, products, and activities over a set lifetime. They are also used to compare alternatives from a systematic, holistic perspective. Results from such a study that utilizes integrated assessment methods to gauge the environmental, economic and societal impacts of competing alternatives may be used as a guide to aid in decision-making in selecting and implementing the most appropriate strategy. Such integrated assessment methods can also be used in determining where improvements/innovative strategies can be made. The following paragraphs cover the basic concepts and theories of sustainability including the methods of various methods of assessment and how such methods lead to innovation. The concepts of sustainability as covered in the Introduction section are applied to the built environment as a system.

SUSTAINABILITY ASSESSMENT METHODS APPLIED TO THE BUILT ENVIRONMENT The built environment and urban systems are a complex interaction between human activity (economy), human well-being (social), and the natural systems (air, land, water) with each other and with the civil infrastructures and the interface at which they converge. The built environment is a system that consists of all types of buildings such as houses, shops, together with engineering works such as roads, treatment plants, storm-water management systems, bridges, power generation facilities, and other civil infrastructures that support and enable human activity and urbanization. Water and wastewater treatment facilities and storm-water management systems are design to protect human lives, other civil infrastructures, and the environment by removing and or reducing contaminants.

Power generating facilities enable human activity, industrial processes, and transportation to be possible and also sustain society. Transportation systems including roads, bridges are the “veins” or “conduits” that provide accessibility to goods and services from the natural and built environment and maintain and/or improve human well-being. They also enable dynamic interaction of human activity (e.g., economic activity), human wellbeing, and the natural environment with each other and other infrastructure that makes up the built environment. These civil infrastructures are part of the considered human system. Engineering projects that build these infrastructures are always hinged on a single reductionist assessment method, e.g. economic approach to evaluating the project across all life cycle stages (planning, design, to construction, to operation and maintenance and demolition/retrofitting). The piece of the puzzle that is often not connected in practice is that the built environment also encompasses socio-cultural activities and human interaction with the physical infrastructure and with the natural environment. Hence social and environmental assessment methods are also critical. Human activity influences behavior of the built environment components in unexpected ways. When these interactions are not considered the analysis remains incomplete. In order to assess the impacts of various projects, a holistic, systematic approach that considers the triple bottom line is essential for long-term and possible short-term planning. We can evaluate the impacts of process, products, and activities in the built environment using a single-method approach, Table 1. Or alternatively, we can reduce the problem into smaller problems and evaluate them separately, then appropriately reconnect them within a systems context – a ‘sum of all the parts’ approach. Once we’ve reduced the problem to smaller problems we can then apply a systematic analysis to each of the specific problems or component. For example in the built environment, we can study buildings and we can

77

Diffusion and Adoption of Innovations for Sustainability

Table 1. Reductionist and systematic approaches to addressing sustainability (adapted from Muga, 2009) Reductionist Approach to Identifying Problem Reductionist Approach to Assessing Sustainability

Economic assessment, such as cost-benefit analysis and life cycle cost analysis. Traditional methods of assessment, where cost was the only factor taken into consideration.

Systematic Approach to Assessing Sustainability

Economic (life cycle cost analysis), Environmental (life cycle assessment), and Societal (societal indicators). Integrated methods of assessment that attempt to address the three pillars of sustainability: economic, environment, and society.

study pavements/roads separately then reconnect them to a systems context. According to General Systems Theory, reductionist approaches are best applied in the study of sub-systems whereas the systems approach looks at whole systems (Checkland, 1993). Therefore the reductionist approach is used to attempt to solve problems within a system while the complex systems approach is used to thereafter to frame and define the issues (Checkland, 1993; Greenwood, 2006; Muga, 2009). The various reductionist approaches to addressing sustainability can be seen in Table 1. As an example, a company may focus on the economic aspect by reducing costs in order to achieve short-term gain often times at the detriment of environmental and social dimensions (i.e. a reductionist or subsystem approach). Strategies that are top-down and/or bottom-up approach have the potential to move a company or entity towards sustainability or away from it. Applying reductionist approach to the built environment, the system can be divided into smaller parts that inherently are connected and support its overall function. Some of the critical components or parts of the built environment include buildings/structural support, transportation systems, services, gas and water lines, water reservoirs, information systems, etc. Once each ‘part’ is identified, a systematic approach to as-

78

Systematic Approach to Identifying Problem

Economic (life cycle cost analysis), Environmental (life cycle assessment), Societal (risk assessment), triple bottom line. This is where we would like to be. However uncertainty of data and lack of data make getting to this stage challenging.

sessment, one that incorporates the triple bottom line (societal, economic, and environmental assessment) can then be applied to each part. Each of these ‘parts’ may be put together to gauge the overall sustainability of the system. With such a complex system as the built environment, a reductionist approach to identifying a problem along with the application of a systematic approach to assessment is often the best option. Such an option is also best suited when long-term strategies are concerned. A systematic methods approach such as an integrated framework of life cycle assessment (LCA), life cycle cost analysis (LCCA), and indicators are necessary to evaluate these component-specific impacts from a sustainability perspective. Life cycle assessment (LCA), Economic-Input Output Model (EIO-LCA), and Simapro are tools that can be used to evaluate the environmental impacts of a given product, process, activity/service at various life stages (raw material extraction, manufacturing, distribution, use, and disposal, Figure 3). With LCA/EIO-LCA/Simapro we can determine the environmental outputs for, for example raw materials that are used to build a commercial property. We can also use these tools to evaluate the outputs from various energy sources used during the operation of the facility. LCA/EIO-LCA/ Simapro enables us to identify what stage of a product’s or process’ life significant environment

Diffusion and Adoption of Innovations for Sustainability

Figure 3. Life cycle stages involved in the manufacture of a product. Integrated assessment methods such as LCA and LCCA may be used at the planning and design stage to evaluate the impacts of alternative materials, processes, and end of life uses of a product before a project begins. These methods may also be used to evaluate the operation and maintenance stages when it is in progress.

emissions occur and where improvements can be made. They are useful tools in aiding decisionmaking. While the integrated assessment methods for sustainability enable us to compare alternatives processes, and technologies with the least negative impacts, they also enable us to identify, processes, technologies, and pathways where innovation can take place further reducing undesirable outcomes or increasing desirable outcomes. The life cycle stages, Figure 3, of various competing alternatives can be compared using LCA, LCCA or other assessment methods, to determine the alternative with the least environmental, economic and societal impacts. Innovation can also take place when performing an LCA or LCCA over the different life cycle stages. For example in Figure 3, in the extraction stage, an innovation might be what kind of equipments do we use and how do we carry out the extraction so that have minimal impacts. In the processing and manufacturing stages, an innovation might be re-designing a process so that less energy is consumed, or capturing heat for in-house energy use, or utiliz-

ing waste material that might otherwise be landfilled. In the use stage it might be, an innovation might be re-designing and manufacturing the products so that they have long-lives. In the endof-life stage, an innovation might be to re-use of the product in another process, or recycle the product in order to make a completely different product, hence avoiding land-fill. When it comes innovating and designing sustainably, it pays to think light. Products made with less material have less negative impact all the way from production to disposal, often making them cheaper to produce. It is clear how a light-weight truck can save energy as it takes less fuel to operate. But for any product that is made lighter it affects the entire LCA since it reduces costs from materials required to shipping of raw materials and final products. Thus this whole system thinking or systems approach to innovating sustainably has been captured by the Rock Mountain Institute in the following principles to be considered for sustainable integrative design, innovation and engineering:

79

Diffusion and Adoption of Innovations for Sustainability

• • • • • • • •

• • • • • • • •

Define the shared and aggressive goals Collaborate across disciplines Design nonlinearly Reward desired outcomes Define the end-use Optimize over time and space Establish baseline parametric values Establish the minimum energy or resource theoretically required, then identify and minimize constraints to achieving that minimum in practice Start with a clean sheet Use measures data and explicit analysis, not assumptions and rules Start downstream Seek radical simplicity Tunnel through the cost barrier Wring multiple benefits from single expenditures Meet minimized peak demand; optimize over integrated demand Include feedback in the design

INNOVATION AND SUSTAINABILITY Innovation and sustainability go hand in hand. Innovations and the development of new technology provide a way for humans to improve their lives (social progress) through better, smarter ways of conducting their activities. According to Nidumolu, Prahalad and Rangaswami (2009), sustainability is now the key driver of innovation. These authors say that contemporary innovation, with sustainability at the core, takes on a cyclical process with evaluation of sustainability challenges, competencies and opportunities for any given business. Their key findings are highlighted in Figure 4. Energy systems (photovoltaic cells, biomass, geothermal) are one of the innovative technologies that provide clean, renewable energy to humans, thereby reducing carbon dioxide emissions from fossil fuel use and contributing to a sustainable

80

planet. Innovative energy systems are a tremendous business opportunity for companies. Understanding these emerging energy systems, what materials works best, how to increase their life span spurs further innovation. Competing businesses emerging with similar, product possibly of a higher quality and increased life span yet spurs further innovation. Where innovations are concerned, there is a need for calculated and strategic management of resources; particularly human resources. This is one key area where the application of Social Network Analysis (SNA) can assist; in the development of the best innovation network to ensure a business has the best competitive advantage possible. SNA is used widely in the social and behavioral sciences, as well as in economics, marketing, and somewhat for project management in industrial engineering (Taagepera, 2008). The social network perspective focuses on relationships among social entities and is an important addition to standard social and behavioral research, which is primarily concerned with attributes of the social units (Wasserman & Faust, 1994). Management, of any kind, refers to the use of people (i.e. social units), in some level of seniority to others, to control some commodity. According to some measuring indices of SNA, characteristics of each actor’s interaction or management activities will affect the holistic management of assets in terms of sustainability and structure (Li & Chen, 2006). Thus an understanding of the actual and perceived managerial structure for arriving at innovations will allow for altering the social network to reduce ‘processing time’ for innovative product development. This reshuffling of human resources for optimum yield of innovative throughput necessitates continuous monitoring of internal social networks through the calculation of key SNA indices such as centrality, adjacency, relationship, reachability, network density, boundary spanners, betweeness and closeness. Table 2 describes these in some depth. Innovation needs to be influenced by a population’s current mental model with regards to any

Diffusion and Adoption of Innovations for Sustainability

Figure 4. Sustainability challenges, competencies and opportunities in relation to innovation (adapted from Nidumolu, Prahalad & Rangaswami, 2009)

product expected to be developed for use within this population. Thus there is a need for developers to be connected with the population for which the innovation is intended. So as a major preinnovation step, a needs assessment of the population should be done and used as the driving force of the innovation research and development.

Within this assessment key understanding of the population’s knowledge, beliefs and notion of complexity should be revealed for consideration of what the innovated product needs to appease. This is key to the sustainability of the innovation. During the innovation development process this is where the proponent of the innovation has the

81

Diffusion and Adoption of Innovations for Sustainability

Table 2. Quantitative measures and relational characteristics of strength of management in SNA (adapted from Freeman, White & Romney, 1989; Hassan, 2009; Outhwaite & Turner, 2007) Numerical measure

Definition

SNA matrices

Adjacency - Adjacency tells us whether there is a direct connection from one actor to another (or between 2 actors for un-directed data). Relationship – This matrix shows the relations between actors using integers that represent the strength of the relation between 2 actors. The resulting matrix represents the sum of frequencies or the ‘frequency of contact’ required between 2 actors. Reachability – Reachability is a measure of path distance, the “length” or number of unique walks between actors. The reachability matrix is the product of the adjacency matrix with itself and it uncovers the number of paths that an actor can be reached. To determine path distances of more than one, the adjacency matrix is multiplied by itself as many times as the path requires. Reachability tells us whether two actors are connected or not by way of either a direct or an indirect pathways of any length.

Centrality ratio (Ci)

This ratio is the ratio of the aggregate relations involving the actor over all relations in the management structure. The centrality can be found from: N

C

i

=

∑ (z j =1

+ z ji)

ij

N

N

i =1

j =1

∑∑Z

where Ci is the centrality of the ith actor; Zij is the value of a relation from the ith actor

ij

directed to the jth actor in the kth network. Note that i ≠ j and N is the number of actors in the network. Network density

This is a measure of the percentage of all the possible ties present and varies from 0 to 1. This gives a ready index of the degree of dyadic connection in a population. For binary data this is simply the ratio of the number of adjacencies that are present divided by the number of pairs i.e. the proportion of possible dyadic connections actually present. Simply put it is the proportion of ties present to the maximum number of ties possible. It can be calculated by: Network density =

T N ( N −1) / 2

where T is the number of ties present; N is the number of actors in the network. Betweenness

This refers to the extent to which an actor acts as a ‘broker’ or ‘gatekeeper’ in the network.

Closeness

An actor is considered to be close when it has the shortest paths to all others. This means that actor can avoid the potential control of others.

Boundary spanners

A boundary spanner refers to an actor that has access to other networks.

Centrality

Centrality identifies the most important actors in a social network, which are usually nodes located in strategic locations within the network. The centrality value of the actors in asset management will therefore depend on the frequency of contact of an actor relative to that of other actors.

overarching power to infuse sustainability into the design of the product/technology/strategy. For example, the innovation developer should consider the life cycle analysis (LCA) of the material chosen with regards to where the raw materials come from through to how the materials can impact the environment at the end of life (i.e. a cradle to grave analysis). Here all the pillars of

82

sustainability should be considered, in tandem with the pre-innovation mental models of the population, in achieving an innovative product that attains the company’s triple bottom line. The post-innovation sustainability hinges upon acceptance of the product by the target population through a change in their mental models. This necessitates aggressive strategic marketing (i.e.

Diffusion and Adoption of Innovations for Sustainability

diffusion) to lead the population to adoption of the product. In addition, once a strategy or an innovative technology that addresses sustainability has been developed/identified, decision-making be it from the top-down or bottom-up is critical to its diffusion and adoption within an organization and into mainstream. The mental models of individuals play a critical function on how they weigh the alternatives, what they weigh their alternative on, and their eventual decision. The high cost of photovoltaic cells and lack of governmental incentives mean that companies and individuals will not adopt it even though it is sustainable, because it is not economically viable compared to other alternatives such as fossil fuel. In the preceding paragraphs we discussed key parameters that link innovation to diffusion and adoption to achieve sustainability. These include mental models of individuals that lead to diffusion and adoption, social networks, and the role management. Social Network theory and methods of SNA are being increasingly used to study real-world networks in order to support knowledge management and decision making in organizations (Hu, 2009). SNA has been used since the early 1970’s as the theoretical basis for the examination of general social and behavioral science communities (Wasserman & Faust, 1994). The importance of SNA is highlighted by the demonstration that an individual’s behavior can often times be categorized by their relations with others. According to Rogers (2003), social network research can range from small-scale studies (i.e. micro level) of a person’s intimate social network to system studies (i.e. macro level) focusing on larger societal and community organizational structure. SNA is inherently based on the underlying premise that “the structure of relations among actors and the location of individual actors in the network have important behavioral, perceptual, and attitudinal consequences both for the individual units and for the system as a whole” (Knoke & Kuklinski, 1982).

MENTAL MODELS AND DIFFUSION AND ADOPTION OF INNOVATIONS The mental model of an individual is critical to adoption of an innovative strategy that contributes to sustainability. Adoption describes the acceptance of a new product, idea or technology according to the demographic and psychological characteristics of defined adopter groups (Rogers, 2003). Adoption of an innovation or green thinking by an individual is due to a shift in their mental models, caused by interactions in their professional networks. Craik (1943) suggested that the mind constructs “small-scale models” of reality that it uses to anticipate events (Johnson-Laird & Byrne, 2000). Such models are conceptualizations of the world that the mind builds by incorporating the individuals’ views of the world, of themselves, of their own capabilities and of the tasks that they are required to perform (Norman, 1983) and are referred to as mental models. Individuals construct mental models of themselves and the environment that they are required to interact with from perception, imagination, the comprehension of discourse, and use them in their decision-making. An individual’s mental model of innovation/ green technology and sustainability reflects their awareness and perception of how it improves for example the organization that they work for and its operations, their clear comprehension of the discourse on sustainability, and intention to involve innovation that contribute to green thinking/ sustainability in their decision-making process. Individuals interacting with their immediate environment are exposed to new ideas, and learning which results in a shift in their mental models. The ability for an individual in an organization to adopt an innovative idea is largely dependent on their interactions in social networks and its influence on the diffusion of the innovative idea. A change in mental model of an individual can impact or ‘infect’ others in their network to adopt

83

Diffusion and Adoption of Innovations for Sustainability

an idea. This gives rise to social network analysis (SNA), defined as the mapping and measuring of relationships and flows between people, groups, organizations, computers, web sites, and other information/knowledge processing entities (Wasserman & Faust, 1994). Figure 4 shows how diffusion spreads through a social network of an individual over time. The social network in Figure 4 is comprised of two individuals. A faster diffusion and change in mental model (Adoption Curve 1, Figure 5) of an individual leads to a quicker adoption rate (steep inflection point) and a rapid spread of the ‘infection’ within the individual’s immediate social network with the innovative idea. A rapid change in mental model, diffusion/ adoption rate, and spread of the ‘infection’ or innovative idea is crucial to achieving sustainability (reducing carbon dioxide emissions, excess consumption, etc). The adoption of an innovative idea becomes self-sustaining when the ‘tipping point’ is reached. Critical mass or the ‘tipping point’ (Figure 5), is the point at which enough individuals in a system have adopted an innovation so that the information’s further rate of adoption becomes self-sustaining (Rogers, 2003)

Management plays an important role in the diffusion and adoption of an innovative strategy that addresses sustainability. Transposing the idea of social network to a management structure, diffusion and adoption is a function of the strength of a management structure of a firm or company, the ties between the individuals within the structure, and the key individual connectors who enable transmission of the innovative idea and/or policies between the different hierarchies. From organizational theory of management, two way ties between individuals (a←→b) are more important than one-way time (a→ b). Two way ties represent transfer of crucial information among lateral and/or lower rank individuals to a lateral/ higher rank managerial individual.

FUTURE RESEARCH DIRECTION AND CONCLUSIONS The primary focus of this chapter was on the theory and concepts of sustainability, how they can be applied to a business, and why they important to innovation and vice-versa. Sustainability as-

Figure 5. The dynamics of diffusion and adoption of innovation over time due to change in mental models of individuals (adapted from Mukherjee & Muga, 2010)

84

Diffusion and Adoption of Innovations for Sustainability

sessment methods such as LCA and LCCA were discussed to a great length. These methods are useful when a business is evaluating alternative products or processes at the planning and design stages. They may also be used during the operation stage if a business is considering switching to an alternative raw material. In addition the role of management, social network analysis, and the influences of an individual’s mental model on diffusion and adoption of innovation were also explored. While this chapter provides some insights into the relationship between sustainability and innovation, there is still a need for more research into the area. One area of interest is the mental models of individuals in the diffusion and adoption of sustainable innovations. When does an individual decide to adopt a product that was produced in a sustainable manner? Individuals/ consumers to a large extent drive the market. If all individuals are educated in the concepts and theories sustainability as is the case in higher educational institutions where there are courses such as “Green Engineering”, “Green Design”, “Sustainable World”, etc, how would these impact businesses? Will there competition? Will business innovate till they can’t innovate anymore? When will this plateau be reached? Social networks are critical to the diffusion and adoption of new knowledge/innovations. Given the above scenario, what would be the role of social networks, specifically in the diffusion and adoption of sustainable innovations to different social, political, and cultural demographics? These scenarios need to be further explored to gauge the true relationship between sustainability and innovation in the short- and long-term and across different socio-cultural and political boundaries.

REFERENCES Brundtland, G. H. (1987). Our common future. Brussels, Belgium: World Commission on Environment and Development. Checkland, P. (1993). Systems thinking, systems practice. New York, NY: John Wiley and Sons Ltd. Craik, K. (1943). The nature of explanation. Cambridge, UK: Cambridge University Press. Crutzen, P. J. (2005). The Anthropocene: The current human-dominated geological era – Human impacts on climate and the environment. Climate Change and Its Effect on Sustainable Development, In Proceedings of the Global Environmental Action International Conference, Tokyo, Japan. Dearry, A. (2004). Impacts of our built environment on public health. Environmental Health Perspectives, 12(11), A600. doi:10.1289/ehp.112a600 Dyllick, T., & Hockerts, K. (2002). Beyond the business case for corporate sustainability. Business Strategy and the Environment, 11(2), 130–141. doi:10.1002/bse.323 Freeman, L. C., White, D. R., & Romney, A. K. (Eds.). (1989). Research methods in social network analysis. Fairfax, VA: Greg Manson University Press. Greenwood, J. B. (2006). Sustainable development in a tourism destination context: A Plimsoll model of sustainability in Tyrell county, North Carolina. Doctoral dissertation, North Carolina State University, Raleigh. Hassan, N. R. (2009). Using social network analysis to measure IT-enabled business process performance. Information Systems Management, 26(1), 61–76. doi:10.1080/10580530802557762

85

Diffusion and Adoption of Innovations for Sustainability

Hu, D. (2009). Analysis and applications of social network formation. Doctoral dissertation, University of Arizona, Tucson. Johnson‐Laird, P., & Byrne, R. (2000). Mental models website: A gentle introduction. Retrieved February 19, 2008, from http://www.tcd.ie/Psychology/ Ruth_Byrne/mental_models/ Knoke, D., & Kuklinski, J. H. (1982). Network analysis. Beverly Hills, CA: Sage Publications. Li, J., & Chen, Y. (2006). Social network analysis: A new approach for business process reengineering. Paper presented at the 10th World Scientific and Engineering Academy and Society (WSEAS) International Conference on Applied Mathematics, Dallas, TX. McConville, J. R., & Mihelcic, J. R. (2007). Adapting life cycle thinking tools to evaluate project sustainability in international water and sanitation development work. Environmental Engineering Science, 24(7), 937–948. doi:10.1089/ ees.2006.0225 Mihelcic, J. R., Crittenden, J. C., Small, M. J., Shonnard, D. R., Hokanson, D. R., & Zhang, Q. (2003). Sustainability science and engineering: Emergence of a new metadiscipline. Environmental Science & Technology, 37(23), 5314–5324. doi:10.1021/es034605h Muga, H. E. (2009). An integrated framework for assessing the sustainability of components that make up the built environment. Doctoral dissertation, Michigan Technological University, Houghton. Mukherjee, A. M., & Muga, H. E. (2010). An integrative framework for studying sustainable practices and its adoption in the AEC industry: A case study. Journal of Engineering and Technology Management, 27(3-4), 197–214. doi:10.1016/j. jengtecman.2010.06.006

86

Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation. Retrieved December 10, 2010, from http://www.acteonline.org/ uploadedFiles/ Why%20Sustainability%20Is%20 Now%20the%20Key%20 Driver%20of%20Innovation%20 Harvard%20Review.pdf Norman, D. A. (1983). Some observations on mental models. In Gentner, D., & Stevens, A. L. (Eds.), Mental models. Hillsdale, NJ: Lawrence Earlbaum Associates, Publishers. Organization for Economic Co-operation and Development (OECD). (1993). Environment monographs no. 83: OECD Core Set of Indicators for Environmental Performance Reviews. Paris, France: Organization for Economic Co-operation and Development. Outhwaite, W., & Turner, S. P. (Eds.). (2007). The SAGE handbook of social science methodology. London, UK: SAGE Publications Ltd. Rogers, E. M. (2003). Diffusion of innovations (4th ed.). New York, NY: The Free Press. Taagepera, R. (2008). Making social sciences more scientific: The need for predictive models. New York, NY: Oxford University Press. doi:10.1093/ acprof:oso/9780199534661.001.0001 UN Environment Programme. (2007). Global environmental outlook: Environment for development; Report GEO – 4. Valletta, Malta: Progress Press. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (structural analysis in the social sciences). Cambridge, UK: Cambridge University Press.

Diffusion and Adoption of Innovations for Sustainability

ADDITIONAL READING Bazerman, M. H., Messick, D. M., Tenbrunsel, A. E., & Wade-Benzoni, K. A. (Eds.). (1997). Environment, ethics, and behavior. San Francisco, CA: The New Lexington Press. Brown, D. (2002). Insatiable is not sustainable. Westport, CT: Praeger Publishers. Brown, L. A. (1981). Innovation diffusion: A new perspective. New York, NY: Methuen & Co. Ltd. Burgelman, R. A., Maidique, M. A., & Wheelwright, S. C. (2001). Strategic management of technology and innovation (3rd ed.). New York, NY: McGraw-Hill/Irwin. Burns, R. O. (1975). Innovation: The management connection. Lexington, MA: D.C. Heath and Company. Chacko, G. K. (1988). Technology management. New York, NY: Praeger Publishers. Coombs, R., Saviotti, P., & Walsh, V. (Eds.). (1992). Technological change and company strategies. London, UK: Academic Press Limited. Doppelt, B. (2003). Overcoming the seven sustainability blunders. The Systems Thinker, 14(5), 2–7. Fagerberg, J., Verspagen, B., & von Tunzelmann, N. (Eds.). (1994). Dynamics of technology, trade and growth. Brookfield, VT: Edward Elgar Publishing Limited. Fauconnier, G., & Turner, M. (2002). The way we think: Conceptual blending and the mind’s hidden complexities. New York, NY: Basic Books. Garud, R., Nayyar, P. R., & Shapira, Z. B. (1997). Technological innovation: Oversights and foresights. Cambridge, UK: Cambridge University Press.

Goodstein, L. P., Andersen, H. B., & Olsen, S. E. (Eds.). (1988). Tasks, errors and mental models. Philadelphia, PA: Taylor & Francis Ltd. Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riversdale, CA: University of California. Loveridge, R., & Pitt, M. (Eds.). (1990). The strategic management of technological innovation. West Sussex, England: John Wiley & Sons Ltd. Marcum,J.W.(2009).Mentalmodelsforsustainability. The Bottom Line: Managing Library Finances, 22(2), 45–49. doi:10.1108/08880450910982620 Meadows, D. (2005). Dancing with systems. San Francisco, CA: Sierra Club. Rosner, W. J. (1995). Mental models for sustainability. Journal of Cleaner Production, 3(1-2), 107–121. doi:10.1016/0959-6526(95)00057-L Sundbo, J. (1998). The theory of innovation: Entrepreneurs, technology and strategy. Cheltenham, UK: Edward Elgar Publishing Limited. Szakonyi, R. (1988). Managing new product technology. New York, NY: American Management Association. Terwiesch, C., & Ulrich, K. T. (2009). Innovation tournaments: Creating and selecting exceptional opportunities. Boston, MA: Harvard Business Press. U.S. Environmental Protection Agency. (2000). Solid waste and emergency response, building savings: Strategies for waste reduction of construction and demolition debris from buildings. Washington, DC, USA: Environmental Protection Agency. U.S. Green Building Council. (2005). An introduction to the U.S. Green Building Council (USGBC) and the LEED Green Building Rating System. Washington, DC, USA: USGBC.

87

Diffusion and Adoption of Innovations for Sustainability

KEY TERMS AND DEFINITIONS Adoption: The acceptance of a new product, idea or technology according to the demographic and psychological characteristics of defined adopter groups (Rogers, 2003). Built Environment: All of the physical structures engineered and built by people—the places where we live, work, and play (examples: homes, workplaces, schools, parks, and transit arrangements) (Dearry, 2004). Diffusion: The spread of new product, idea or technology (Rogers, 2003). Mental Model: Conceptualizations of the world that the mind builds by incorporating the individuals’ views of the world, of themselves, of their own capabilities and of the tasks that they are required to perform (Norman, 1983). Reductionist and Systems Approach: Reductionist approaches are best applied in the study of sub-systems whereas the systems approach looks at whole systems (Checkland, 1993).

88

Social Network Analysis (SNA): Mapping and measuring of relationships and flows between people, groups, organizations, computers, web sites, and other information/knowledge processing entities (Wasserman & Faust, 1994). Sustainability Indicators: Information sets which are formally selected to measure changes in assets and issues that are key for the product development and management. Indicators are measures expressed in single numbers, percentage or ratios, qualitative descriptions or existence/non-existence of certain elements concerning environmental, social and economic issues (OECD, 1993). Sustainability: Development that meets the needs of the present without compromising the ability of future generations to meet their own needs (Brundtland, 1987). Tipping Point: Point at which enough individuals in a system have adopted an innovation so that the information’s further rate of adoption becomes self-sustaining (Rogers, 2003).

89

Chapter 6

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage and Firm Performance Javier Amores Salvadó Universidad Complutense de Madrid, Spain José Emilio Navas López Universidad Complutense de Madrid, Spain Gregorio Martín de Castro Universidad Complutense de Madrid, Spain

ABSTRACT The proposal below provides a special emphasis on the relationship between businesses and natural environment. It is argued that the inclusion of environmental criteria to business activities promotes the creation of new core competencies, offering a creative and innovative perspective to the organization that can lead to the achievement of sustainable competitive advantages. More specifically, we analyze both the existence of a direct relationship between Environmental Innovation and Firm Performance and the existence of an indirect relationship between the two, which highlights the mediating role of the kind of competitive advantage generated. It also provides an innovative approach, as it explains the Environmental Innovation from the literature on Social Innovation, considering Environmental Innovation as an expression of Social Innovation through the incorporation of ethical arguments to products, processes and organizational modes of the company. The main contributions of this work can be summarized as follows: (1) It explains the nature of Environmental Innovation through the Social Innovation literature, which allows consideration of some key aspects of administrative and technological innovations that have not been taken into account the academic literature. (2) The different types DOI: 10.4018/978-1-61350-165-8.ch006

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

of environmental innovations are analyzed as a necessary step to understand the strategic options in the environmental field. (3) Environmental Innovation is related to business performance. The practical implications of the relationship between environmental innovation and performance are of great importance, since it directly influence the type of environmental strategy chosen, allowing the company to choose from innovative strategies (based on pollution prevention) or more conservative strategies (emissions control).

INTRODUCTION The concept of Social Innovation is directly linked to the idea of change. The systemic changes offer many opportunities for Social Innovation and the societies at large are immersed in learning new habits and rules. New forms of efficiency and new ways of seeing and doing things are discovered. The connection between Social Innovation and changing environments is confirmed by the words of the Nobel Prize Simon Kuznets (Pol & Ville, 2009). According to Kuznets, without the existence of firms and banks (both defined as social innovations), the industrial revolution had not taken place, and also would have been much more difficult the development of railways if they had not also developed securities markets. Nowadays, our society is experiencing a time of change, the paradigm shift towards Sustainable Development, defined by the Brundtland Commission (World Commission on Economic Development, 1987) in its report to the United Nations as the kind of development that meets the needs of present without compromising the needs of future generations (Sharma & Vredenburg, 1998). Although industrial development of the last two hundred years has brought prosperity and wealth, it has unintentionally caused environmental degradation as well (Shrivastava, 1995). Industrial activity has grown to such an extent that has already produced irreversible effects on our global environment, including impacts on climate, biodiversity and ecosystems. For these reasons, companies must be able to reduce their emissions and their levels of consumption of materials, developing new clean

90

technologies that are more efficient than current and inclusive business models that facilitate the creation and distribution of wealth more evenly. According to these arguments, in this chapter we will analyze the role of the Environmental Innovation (understood as an expression of Social Innovation) in achieving business results. Taking Social Innovation as starting point, throughout the chapter the nature, determinants and types of environmental innovations will be shown in order to show a complete picture of the topic. More specifically, both the existence of a direct relationship between Environmental Innovation and Firm Performance and the existence of an indirect relationship between the two will be analyzed, highlighting the mediating role of the kind of competitive advantage generated. A broad concept of Social Innovation is used, which allows consideration of some key aspects of administrative and technological innovations that have not been taken into account the academic literature. Furthermore, the practical implications of the relationship between Environmental Innovation and performance are of great importance, since it directly influences the type of environmental strategy chosen, allowing the company to choose from innovative strategies (based on the creation of new core competencies via pollution prevention) or more conservative strategies (emissions control). The remainder of the chapter will be structured as follows: The first section discusses the concept of Social Innovation. A review of the major contributions made by the literature regarding the term is carried out. Additionally, a definition in line with the concept of Environmental Innova-

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Figure 1. Social innovation as mission and change

tion is proposed. The second section examines the concept of Environmental Innovation emphasizing its nature, determinants and typology, and the third section highlights the relationship between Environmental Innovation with the economic performance of the company. Finally, the main conclusions will be provided.

SOCIAL INNOVATION Social Innovation is an emerging field that remains under-researched (Social Innovation Exchange and Young Foundation, 2010). Very few are the efforts to classify and organize the various contributions. In this sense, is very interesting the contribution carried out by Pol and Ville (2009), which discusses some of the definitions given to the concept of Social Innovation elaborating a four group classification (understanding the concept as linked to institutional change, to social purposes, to the public good or to the satisfaction of needs not covered by the market). On this first contribution, and taking as reference the characterization of the different types of businesses proposed by Professor Yunus (Yunus et

al., 2010), two basic directions can be identified in the existing definitions in Social Innovation literature as shown by the four quadrants of Figure 1. On the one hand, companies can be seen as profit-maximizing businesses, and on the other, non-profit organizations exist to fulfill social objectives. In between, we can find social businesses that at the same time have to cover operations cost but also are more cause-driven than profit-driven. Both, companies and social businesses have the potential to act as change agents for the world and also be economically viable. On the contrary, not for profit organizations, usually, are not economically viable, and their objectives are more aimed to meet the social needs of those more disadvantaged than to create a global change. The distinction outlined above fits perfectly with the two main streams on the literature on Social Innovation. Thus, as Pol and Ville (2009) pointed out, some authors associate the term Social Innovation with the idea of institutional and social change (Lewin, 1947; Scherhorn et al., 1997; Duchin, 1999; Mumford, 2002; Martin, 2006; Hamalainen & Heiscala, 2007; Centre for Social Innovation, 2008). This approach provides

91

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Table 1. Social innovation as change AUTHOR

DEFINITION

Lewin (1947)

Researcher as a strategist for Social Innovation.

Scherhorn et al. (1997)

Social Innovations as the changes in lifestyles or behavior of consumers.

Duchin (1999)

Social Innovation as new technologies and new lifestyle dynamics.

Mumford (2002)

Social Innovation as the generation and implementation of new ideas about how people should organize their interpersonal activities or social interactions to get one or more common goals.

Martin (2006)

Social Innovation associated with social experimentation.

Hamalainen and Heiscala (2007)

Social Innovation as the changes in social structures that enhance the social and economic performance and the collective power of resources.

Centre for Social Innovation (2008)

Those new ideas that address current economic, social, cultural and environmental challenges to benefit the planet and the people who inhabit it.

Yunus, Moingeon and Lehmann-Ortega (2010)

Building social innovation models require two additional specificities: (i) favoring social profit-oriented shareholders; and (ii)clearly specifying the social profit objective.

Dawson, Daniel and Farmer (2010)

Social Innovations are triggered by an interest in improving the well-being of people in society. Its aim to improve the welfare of groups and communities, as such they may: seek to further the social conditions of work; hope to provide socially useful solutions to ongoing community problems; or provide improvements in well-being for remote or socially isolated communities.

a wide-ranging concept, since it does not focus only on meeting specific social needs but also understands the term as a necessary instrument that accompanies the change in values, ways of acting and thinking and institutions. Understanding the company as an agent of social change (Bies et al., 2007), one can see that this conception of Social Innovation is perfectly compatible with the entrepreneurial phenomenon. Following Yunus et al., (2010), within this category can be included some businesses whose objective is to maximize the economic benefits such as those based on the use of green technologies or social businesses in general (understanding these as those that maximize social benefit and are also financially sustainable). (Figure 1, top and bottom right). In contrast, other authors, in defining Social Innovation emphasize its social mission (Taylor, 1970; Gabor, 1970; Forum on Social Innovation (OECD); Mulgan, 2006; Phills et al., 2008, Pol and Ville, 2009). So, they argue that Social Innovation’s mission is to satisfy unmet social needs. This conception does not explicitly links Social Innovation with the idea of change, meaning that the Social Innovation fulfill its mission if social

92

needs are met, even if this does not mean a broader social change. This emphasis on the social aspect of the term, place it near from philanthropic activities and away from the idea of economic benefit. Within this category can be included those activities carried out by nongovernmental organizations (NGO’s), most of which are not created to recover the full cost of their operations (Yunus et al., 2010). (Figure 1, bottom left). Once exposed the different approaches given to the term, this chapter will focus on the development of the former. That is, starting from the idea of Social Innovation and change we will try to reconcile the achievement of economic returns with the Sustainable Development paradigm through Environmental Innovation. The authors that associate the term Social Innovation with the idea of institutional and social change, provide different definitions of the concept (Table 1). Lewin (1947) conceives the researcher as a strategist for Social Innovation and demands the production of theories for the transformation of society. From another point of view, changes in lifestyles or behavior of consumers are often defined

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

as Social Innovations (Scherhorn et al., 1997). Duchin (1999) argues that the idea of Social Innovation is new and requires not only new technologies but also new lifestyle dynamics. In the same vein, Mumford (2002) considers the Social Innovation as the generation and implementation of new ideas about how people should organize their interpersonal activities or social interactions to get one or more common goals. It adds that the Social Innovation can lead to the development of new business practices, processes and procedures. This view is consistent with Martin (2006) who stresses that social experimentation is beneficial for Social Innovation and claims that the biggest obstacle for Social Innovation is the drag created by entrenched interests. Also emphasizing the idea of change, (Hamalainen & Heiscala, 2007) understand Social Innovation as the changes in social structures that enhance the social and economic performance and the collective power of resources. Also, on the same line, mention must be made to the definition given by the Centre for Social Innovation, that trying to define the concept, understands as Social Innovations those new ideas that address current economic, social, cultural and environmental challenges to benefit the planet and the people who inhabit it. Thus, authentic Social Innovations are the ones that change the system by altering the perceptions, behaviors and structures (Centre for Social Innovation, 2008). As mentioned above, this orientation is typical of companies that understand the changes as business opportunities. It is therefore considered that the fact of adding a social dimension to the value proposition of the company offers a new frontier in competitive positioning (Porter & Kramer, 2006). Therefore, after consideration of the literature on Social Innovation and the various proposals that are encompassed within it, we understand Social Innovation as the combination of innovative activities carried out by the company with the

potential to promote social change. This social change is expressed through the incorporation of ethical arguments to the products, processes and organizational modes of the company and results in changes in consumer behavior, changes within the enterprise and changes in the company’s relationship with the social and natural environment.

ENVIRONMENTAL INNOVATION: NATURE, DETERMINANTS AND TYPES As a Social Innovation, Environmental Innovation incorporates ethical arguments to products, processes and organizational modes of the company. This statement, however, lacks specificity. Therefore, it’s necessary to specify in more detail its nature, its determinants and the different types of environmental innovations in order to understand the strategic options in the environmental field. Some academics suggest that Environmental Innovation have different natures (Rennings, 2000). Thus, its nature can be technological, organizational, institutional or social. Technological nature can be seen in environmental technologies for the prevention of environmental pollution or for the control of the same, commonly called “end of pipe”. In relation to its organizational nature it includes environmental management tools such as ISO 14001 or EMAS. Institutional and social nature can be seen in the environmental institutions such as the intergovernmental panel on climate change and in changes in styles and dynamics of life and consumption respectively. However, arguing that Environmental Innovation has different natures implies, from our point of view, to assume a very limited concept of Social Innovation. Accordingly, the social nature of Environmental Innovation would be restricted exclusively to changes in lifestyles and consumption habits, leaving out those changes in behavior and relationships of individuals as a result of the emergence of administrative and technological

93

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

environmental innovations such as environmental management systems or recycling of materials for re-entry into the production process. In other words, under that limited scope of the social nature of the Environmental Innovation, we are not considering the changes (in behavior and relationships) that occur inside the business when administrative or technological environmental innovations are implemented. We believe, therefore, from Business Strategy, that is more appropriate to use a broad definition of Social Innovation. A broader definition of the concept is needed in order to be able to classify as environmental innovations the changes (in behavior and relationships) that occur inside the business when administrative or technological environmental innovations are implemented. Environmental Innovations have been defined from different points of view. Thus, according to Chen et al., (2006), Green Innovations are hardware or software innovations related to green products or processes, including the innovation in technologies that are involved in energy-saving, pollution prevention, waste recycling, green product design or corporate environmental management. Kemp et al., (2001, in Horbach, 2008) argues that Environmental Innovations consist of new or modified processes, techniques, systems and products to avoid or reduce environmental damage, and according to Rennings (2000), Environmental Innovations can be defined as the measures of relevant actors consisting in the development, application or introduction of new ideas, behaviors, products and processes that contributes to a reduction of environmental burdens or to ecologically specified sustainability targets. In line with the extensive concept of Social Innovation that we are using in this chapter, Rennings’s definition is the one that fits better to our purposes since it refers not only to environmental product and process innovation but also to ideas and behaviors, which, from our point of view, are particularly important to understand environmental organizational innovations like

94

environmental management systems or “green teams”. Note that this definition encompasses technological environmental innovations as well (regarding the changes in behavior and relationships that occur inside the business technological environmental innovations are implemented) as we have highlighted before. Regarding the determinants of Environmental Innovation, the literature suggests that these are supply factors, demand factors and institutional and political influences (Horbach, 2008). From the supply side, the Environmental Innovations (as many innovations) are conditioned by the available technological possibilities of the firm and by the return appropriation of the innovation activities. At this regard, the double externality problem must be highlighted. Environmental Innovations, besides the positive externalities from spillovers which are common to all innovations, are characterized by the fact that while the whole society benefits from a technical environmental innovation, the cost have to be borne by a single firm (Rennings, 2000). From the demand side, both the potential market demand and the social awareness can determine the posture of the firm regarding the Environmental Innovations. Thus, through the Environmental Innovation, firms may have access to those segments of the market willing to pay a premium for green products (Miles et al., 1997) and also create a green reputation (Chen, 2008). Furthermore, companies can leverage their reputation for environmental innovation to gain preferential access to new and lucrative businesses like waste management, recycling services and environmental impact analysis among others (Nidumolu et al., 2009). In relation to the institutional and political influences, the role of the environmental regulation should be noted. First, environmental regulation may force firms to realize economically benign Environmental Innovation, and second, firms may find early movers advantages from adapting to

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Figure 2. Types of environmental innovations

regulation before than their rivals (Porter & Van der Linde, 1995; Horbach, 2008). Finally, in addition to the nature and determinants of environmental innovations, we must refer to the environmental innovation types in order to show a complete picture of the topic. Thus, following the OECD (1997) Guidelines, we can distinguish between technical and organizational innovations. Thus, technical environmental innovations are specific kinds of innovations that consist of new or modified products and processes to avoid or reduce the environmental burden, and environmental organizational innovations include the re-organization of processes and responsibilities within the firm with the objective to reduce environmental impacts (Rennings et al., 2006). (Figure 2) Among technical environmental innovations we can find environmental process innovations and environmental product innovations. As process innovations we can include those aimed at reducing energy consumption during the production process or those that convert waste into new ways of creating value, both through its reuse within the enterprise or outside, selling the waste

in those businesses where they could be useful (Porter & Van der Linde, 1995). Among environmental process innovations we can include the reductions in air or water emissions, improvements in resource and energy efficiency, reductions in water consumption and switching fossils fuels to bioenergy (Kivimaa & Kautto, 2010). Environmental process innovations can be subdivided into innovations in end-of-pipe technologies and innovations in integrated technologies (also called cleaner production technologies). While end-of pipe technologies are oriented to comply with the environmental regulation (waste disposal, water protection, noise abatement or air quality control technologies), cleaner production technologies emphasize continuous improvement and cost minimization. Examples of cleaner production technologies are the recirculation of materials, the use of environmental friendly materials and the modification of the combustion chamber design. Some authors, adding more detail to the technological environmental innovations typology, distinguish between end-of-pipe integrated (preventive) and end-of-pipe non integrated (control) depending whether these technologies

95

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

are integrated in the production process or not Hartie (1990, in Hemmelskamp, 1997). On the other hand, among the environmental product innovations we have to mention product design innovations like those responding to the concept of “design for disassembly”, which is based on creating products that are designed for easy recovery, dismantling and recycling, thus extending the life of each of the components (Shrivastava, 1995b), improvements in the durability of the products, raw materials reductions, selection of environmentally less harmful raw materials and removal of hazardous substances (Kivimaa & Kautto, 2010). Environmental organizational innovations, in turn, can be supporting factors for technical environmental innovations. Among them, we can mention as one of the most prominent initiatives the utilization of environmental management systems (EMS) like EMAS (Environmental Management and Auditing Scheme) or ISO 14001 and the “green teams” which are composed of members of the organization from various departments and levels of responsibility whose job is to advise the company on the impact of their activities on the environment. This advisory work covers all areas of business activities and includes the development of programs for waste management, energy and resources conservation or renewable energy sources exploration (Shrivastava & Hart, 1995).

Environmental Innovation and Firm Performance: An Approach to Direct and Indirect Effects The environmental factor provides opportunities to foster innovation and develop technologies to improve efficiency. According to Hart and Milstein (2003), problems associated to industrialization like material consumption, waste and emissions represent an opportunity for companies to develop skills and capabilities in the fields of pollution prevention and ecological efficiency (Nidumolu et al., 2009).

96

Russo and Fouts (1995), referring to different environmental strategies as mentioned by Hart (1995), emphasize that companies that carry out pollution prevention strategies (beyond compliance with the law) focusing on process environmental innovation, have a resource base that enhances their ability to generate profits and also makes them able to protect themselves against future risk arising from resource depletion or fluctuating cost of energy (Shrivastava, 1995). Dechant and Altman (1994, in Karagozoglu & Lindell, 2000), in the same vein, argue that environmental innovations enables companies to position themselves ahead of their competitors in meeting environmental regulations, which in turn helps them to protect their markets Therefore, the importance of incorporating environmental considerations in strategic decision making is increasing (Sharma and Vredenburg, 1998). Thus, through environmental innovations the firm can improve its efficiency, achieve significant cost reductions and meet the demands of those consumers especially sensitive to the environmental factor. Firms can save costs through a better use of raw materials and energy, selling the surpluses of the production process or reducing the control and waste treatment cost (Murillo et al., 2008), idea that is shared by Berrone and Gómez-Mejía (2009, in López Gamero et al., 2009) for whom proactive environmental management, characterized by innovation, can minimize waste disposal costs, reduce unnecessary steps and optimize the use of inputs in the production process. Klassen and Whybark (1999) relate pollution prevention technologies to the existence of greater opportunities for innovation and improvement in production efficiency. In the same line, Wagner (2005) shows that environmental strategies based on pollution prevention (as opposed to the additive and control strategies or “end of pipe”) result in improved economic performance of the company. Rennings et al., (2006) show evidence of the relationship between Environmental Innovation and increased

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Figure 3. Environmental innovation: Direct and indirect effects

turnover of the plant, while according to Radonjic and Tominc (2007), the new, cleaner technologies lead to the optimization processes and result in increased productivity. Therefore, with appropriate skill sets and capabilities, companies that carry out prevention strategies and reduce waste emissions are able to reduce costs and increase profits (Sharma & Vredenburg, 1998; Christmann, 2000). In addition, besides the cost factor, the respect for the environment can also be a key element to meet the demands of those conscious customers who specially value the environmental performance of products, packaging and sustainable forms of business management. These customers will be willing to pay and additional price for such environmental features (Sharma et al., 1999). Although by 2001, Hamschmidt and Dyllick argued that the market for environmentally innovative products was reduced, the development of new products more “green” or sustainable has been also studied by the researchers. Among the beneficial effects of designing new and more sustainable products we can mention increases in sales and corporate image enhancement (Tien et al., 2005; Chen, 2007), increased market share (Cleff & Rennings,1999) and company growth (Chen et al., 2006). Likewise, environmental marketing activities positively affect the business performance of companies (Fraj-Andrés et al., 2009). These are what we call the “direct

effects” between Environmental Innovation and firm performance. However, if technical and organizational possibilities for sustainable businesses are available for all the firms in the market, the achievement of some degree of cost reduction, improved efficiency or product differentiation may not be enough to obtain a significant improvement in the economic performance of the firm. Therefore, it may be necessary the existence of competitive advantage in terms of cost or differentiation. In this sense, competitive advantage can play a mediating role in the achievement of business results and better firm performance. In short, attention must be paid to what we call the “indirect effects” (Figure 3). According to Christmann (2000), Environmental Innovation practices can result in different types of competitive advantage. In the same line, Chen et al., (2006) argues that environmental innovation in both product and process is positively related to the achievement of competitive advantage. Thus, starting from the distinction of Porter (1980) between differentiation and cost leadership and in line with the relationship between strategy and competitive environmental strategy (Shrivastava, 1995), cost advantage can result from incorporating best environmental practices on the production process (Hart, 1995). These process oriented environmental innovations include the redesign of production processes or the use of

97

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

productive inputs that are less polluting and recycling of byproducts of processes, among other measures (Hart, 1995; Porter & Van der Linde, 1995). Other broader approaches to environmental management also contribute to the cost advantage. Such is the case of the Sustainable Management of Product Life Cycle (Hart, 1995, 1997), Ecocentric Management (Shrivastava, 1995), Design for Disassembly (Shrivastava, 1995) or Design for the Environment (Hart, 1997). In regard to environmental differentiation, innovations related to the packaging design or environmentally friendly product development must be mentioned. Raw materials utilization and business process modifications can be used as differentiation factors when selling products and services on the market (Murillo et al., 2008). As pointed out by Reinhardt (1998) through environmental innovations seeking product differentiation is that consumers pay a higher price because of the ecological attributes of the products sold. Also playing an important role in terms of differentiation we can find the environmental management systems like ISO 14001 or EMAS. According to Johnstone and Labonne (2009), environmental management systems are very important to send signals to regulators and play a role in differentiation against other competitors from the market. This argument is consistent with what has been described by Fombrun and Shanley (1990), for which the fact of producing according to criteria of social responsibility (in our case by providing an environmental argument to products and processes) may contribute to product differentiation and enhanced reputation, though, according to Barin and Dirk (2008), also should be noted that this kind of product differentiation will be effective if is adopted by the value chain as a whole. However, there are also more critical perspectives in relation to Environmental Innovation in terms of differentiation and cost. Some studies find no relationship between the certification of environmental management systems and economic performance of companies (Link & Naveh,

98

2006). Some authors doubt about the potential of environmental management systems to produce differentiation because not all markets are familiar with and value these certifications and it is also controversial the fact that eco efficient activities are a way to gain cost advantages because firms aren’t punished in proportion to the damage caused (Aragón-Correa & Rubio-López, 2007). In a similar vein, according to Frondel et al., (2008) there is a negative relationship between cost reductions and the adoption of environmental management systems.

FUTURE RESEARCH DIRECTIONS As can be seen, the debate on the economic effects of environmental innovation is still open. Direct links between Environmental Innovation and firm performance may be valid in some cases but not in others. Therefore, future studies should analyze more in detail the moderating factors in the relationship between Environmental Innovation and business performance. In particular, the role of the environmental management systems is not clear yet. According to Nawrocka and Parker (2009), the study of the influence of environmental management systems on environmental performance of companies yields inconclusive results. Thus, the casual link between environmental management systems and Environmental Innovation is not resolved by the literature and there is no consensus on whether the environmental management systems are key determinants of Environmental Innovation (Ziegler & Rennings, 2004; Rennings et al., 2006), are factors that help the emergence of environmental innovations (Wagner, 2007; Rehfeld et al., 2007) (playing a moderating role), or on the contrary, do not affect at all to the emergence of environmental innovations (Frondell et al., 2008). Likewise, other factors such as environmental capacity building (Aragón-Correa & RubioLópez, 2007), the complementary deployment of

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

environmental capabilities, firm size (Ziegler & Nogareda, 2009; Iraldo et al, 2009; Wagner, 2007; Chen, 2008; Cleff and Rennings, 1999) or industry (Horbach, 2008; Darnall et al., 2008; Frondel et al., 2008) among others are also relevant and must be taken into account in future research.

CONCLUSION This chapter takes a new perspective in the study of Environmental Innovation. Thus, it is considered that Environmental Innovation can be explained from the theory of Social Innovation. This approach is justified on the grounds that Environmental Innovation is a way of introducing ethical arguments to the activities of the company within a general context of change towards sustainable development. Therefore, according to our view, Environmental Innovation is considered as a kind of Social Innovation. Contrary to other authors, that suggest the existence of different natures for Environmental Innovation, (Rennings, 2000), we argue that, Environmental Innovation is a Social Innovation in nature, which is very important to classify as environmental innovations the changes (in behavior and relationships) that occur inside the business when administrative or technological environmental innovations are implemented. Additionally, it provides an analysis of Environmental Innovation, taking into account its nature, determinants, types and the relationship between environmental innovations and the economic performance of the firms. Escuchar Leer fonéticamente Diccionario - Ver diccionario detallado 1. adverbio a. even 2. preposición a. with b. by c. cum d. in spite of

3. conjunción a. else Demand factors like environmentally conscious consumers or general environmental concern, supply factors arising from the technological capabilities of enterprises in relation to environmental innovations, and institutional factors such as regulatory pressure are taken into account. Escuchar Leer fonéticamente Diccionario - Ver diccionario detallado 1. preposición a. in spite of 2. conjunción a. however b. nevertheless c. notwithstanding d. nonetheless Also, a typology of environmental innovations in line with OECD guidelines (1997) is presented. Providing examples of the most cited environmental innovations (organizational, product and process) and differentiating environmental process innovations between Innovations in End-of -pipe Technologies and Innovations in Cleaner Production Technologies, a complete picture of environmental innovations is offered. Finally, the relationship between Environmental Innovation and business performance is examined. We argue that Environmental Innovation represents an opportunity for companies, promoting the creation of new core competencies and offering a creative and innovative perspective to the organization that can lead to the achievement of sustainable competitive advantages. However, in order to exploit the full potential of Environmental Innovation, further investigation is needed. In this regard, the importance of other factors such as size, environmental capacity or industry, this, among many others, may be useful to advance the study of the field. Empirical research regarding these aspects is of great importance for the 99

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

determination of environmental strategies. Thus, if environmental innovation results in business benefits, companies will devote more resources to pollution prevention strategies (based on innovation), while otherwise will focus in emission control strategies. Escuchar Leer fonéticamente Diccionario - Ver diccionario detallado 1. nombre a. si b. B 2. conjunción a. if b. whether c. once d. supposing

REFERENCES Aragón-Correa, J. A., & Rubio-López, E. A. (2007). Proactive corporate environmental strategies: myths and misunderstandings. Long Range Planning, 40, 357–381. doi:10.1016/j. lrp.2007.02.008 Barin, L., & Dirk, M. (2008). CSR in the global marketplace; Towards sustainable global value chains. Management Decision, 46, 1187–1209. doi:10.1108/00251740810901381 Bies, R., Bartunek, J., Fort, T., & Zald, M. (2007). Corporations as social change agents: Individual, interpersonal, institutional, and environmental dynamics. Academy of Management Review, 32, 788–793. doi:10.5465/AMR.2007.25275515 Centre for Social Innovation. (2008). Retrieved from http://www.socialinnovation.ca/about/ Chen, Y. (2008). The driver of green innovation and green image-green core competence. Journal of Business Ethics, 81, 531–543. doi:10.1007/ s10551-007-9522-1

100

Chen, Y., Lai, S., & Wen, C. (2006). The influence of green innovation performance on corporate advantage in Taiwan. Journal of Business Ethics, 67, 331–339. doi:10.1007/s10551-006-9025-5 Christmann, P. (2000). Effects of “best practices” of environmental management on cost advantage: The role of complementary assets. Academy of Management Journal, 43, 663–680. doi:10.2307/1556360 Cleff, T., & Rennings, K. (1999). Determinants of environmental product and process innovation. European Environment, 9, 191–201. doi:10.1002/ (SICI)1099-0976(199909/10)9:5<191::AIDEET201>3.0.CO;2-M Darnall, N., Henriques, H., & Sadorsky, P. (2008). Do environmental management systems improve business performance in an international setting? Journal of International Management, 14, 364–376. doi:10.1016/j.intman.2007.09.006 Dawson, P., Farmer, J., & Daniel, L. (2010). Introduction paper to a special issue on social innovation. International Journal of Technology Management, 51, 1–8. Fombrun, C., & Shanley, M. (1990). What’s in a name? Reputation building and corporate strategy. Academy of Management Journal, 33, 233–258. doi:10.2307/256324 Fraj-Andrés, E., Martinez-Salinas, E., & Matute Vallejo, J. (2009). A multidimensional approach to the influence of environmental marketing and orientation on the firm’s organizational performance. Journal of Business Ethics, 88, 263–286. doi:10.1007/s10551-008-9962-2 Frondel, M., Horbach, J., & Rennings, K. (2008). What triggers environmental management and innovation? Empirical evidence from Germany. Ecological Economics, 66, 153–160. doi:10.1016/j. ecolecon.2007.08.016

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Gabor, D. (1970). Innovations: Scientific, technological, and social. New York, NY: Oxford University Press. Hamschmidt, J., & Dyllick, T. (2001). ISO14001: Profitable? Yes! But is it Ecoeffective? Greener Management International, 34, 43–54. Hart, S. (1995). A natural resource-based view of the firm. Academy of Management Review, 20, 986–1014. Hart, S. (1997). Beyond greening: Strategies for a sustainable world. Harvard Business Review, 75, 66–77. Hart, S., & Milstein, M. B. (2003). Creating sustainable value. The Academy of Management Executive, 17, 56–67. doi:10.5465/ AME.2003.10025194 Hemmelskamp, J. (1997). Environmental policy instruments and their effects on innovation. European Planning Studies, 5, 177–194. Horbach, J. (2008). Determinants of environmental innovation-new evidence from German panel data sources. Research Policy, 37, 163–173. doi:10.1016/j.respol.2007.08.006 Iraldo, F., Testa, F., & Frey, M. (2009). Is an environmental management system able to influence environmental and competitive performance? The case of the Eco-Management and Audit Scheme (EMAS) in the European Union. Journal of Cleaner Production, 17, 1444–1452. doi:10.1016/j.jclepro.2009.05.013 Johnstone, N., & Labonne, J. (2009). Why do manufacturing facilities introduce environmental management systems? Improving and/or signaling performance. Ecological Economics, 68, 719–730. doi:10.1016/j.ecolecon.2008.06.003 Karagozoglu, N., & Lindell, M. (2000). Environmental management: Testing the win-win model. Journal of Environmental Planning and Management, 43, 817–829. doi:10.1080/09640560020001700

Kivimaa, P., & Kautto, P. (2010). Making or breaking environmental innovation? Technological change and innovation markets in the pulp and paper industry. Management Research Review, 10, 289–305. doi:10.1108/01409171011030426 Link, S., & Naveh, E. (2006). Standardization and discretion: Does the environmental standard ISO 14001 lead to performance benefits? IEEE Transactions on Engineering Management, 53, 508–519. doi:10.1109/TEM.2006.883704 López Gamero, M. D., Molina-Azorín, J. F., & Claver-Cortés, E. (2009). The whole relationship between environmental variables and firm performance: Competitive advantage and firm resources as mediator variables. Journal of Environmental Management, (90): 3110–3121. doi:10.1016/j. jenvman.2009.05.007 Melnyk, S., Sroufe, S., & Calantone, R. (2003). Assessing the impact of environmental management systems on corporate and environmental performance. Journal of Operations Management, 21, 329–351. doi:10.1016/S0272-6963(02)00109-2 Miles, M., Munilla, L., & Russell, G. (1997). Marketing and environmental registration/ certification: What industrial marketers should know about ISO14000. Industrial Marketing Management, 26, 363–370. doi:10.1016/S0019-8501(96)00144-7 Mulgan, G. (2006). Social Innovation: What it is, why it matters, how it can be accelerated. London, UK: NESTA. Mumford, M. D. (2002). Social innovation: 10 cases from Benjamin Franklin. Creativity Research Journal, 14, 253–266. doi:10.1207/ S15326934CRJ1402_11 Murillo, J., Garcés, C., & Rivera, P. (2008). Estrategia medioambiental y expectativas de ventajas competitivas. Cuadernos de Estudios Empresariales, 18, 9–31.

101

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Nawrocka, D., & Parker, T. (2009). Finding the connection: Environmental management systems and environmental performance. Journal of Cleaner Production, 17, 601–607. doi:10.1016/j. jclepro.2008.10.003

Rehfeld, K. M., Rennings, K., & Ziegler, A. (2006). Integrated product policy and environmental product innovations: An empirical analysis. Ecological Economics, 61, 91–100. doi:10.1016/j. ecolecon.2006.02.003

Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation? Harvard Business Review, 87, 56–64.

Reinhardt, F. (1998). Environmental product differentiation: Implications for corporate strategy. California Management Review, 40, 43–73.

OECD LEED. (n. d.). Forum on Social Innovations. Retrieved from http://www.oecd.org OECD/EUROSTAT. (1997). Oslo manual. Proposed guidelines for collecting and interpreting technological innovation data. Paris, France: OECD. Phills, J. A., Deiglmeier, K., & Miller, D. T. (2008). Rediscovering social innovation. Stanford Social Innovation Review, 6, 34–43. Pol, E., & Ville, S. (2009). Social innovation: Buzz word or enduring term? Journal of Socio-Economics, 38, 878–885. doi:10.1016/j.socec.2009.02.011 Porter, M. (1980). Competitive strategy: Techniques for analyzing industries and competitors. New York, NY: Free Press. Porter, M., & Kramer, M. (2006). Strategy & society: The link between competitive advantage and corporate social responsibility. Harvard Business Review, 84, 78–94. Porter, M., & Van der Linde, C. (1995). Toward a new conception of the environment-competitiveness relationship. The Journal of Economic Perspectives, 9, 97–118. Radonjic, A., & Tominc, P. (2007). The role of environmental management system on introduction of new technologies in the metal and chemical/paper/plastics industries. Journal of Cleaner Production, 15, 1482–1493. doi:10.1016/j. jclepro.2006.03.010

102

Rennings, K. (2000). Redefining innovation–Environmental innovation research and the contribution from ecological economics. Ecological Economics, 32, 319–332. doi:10.1016/S09218009(99)00112-3 Rennings, K., Ziegler, A., Ankele, K., & Hoffmann, E. (2006). The influence of different characteristics of the EU environmental management and auditing scheme on technical environmental innovations and economic performance. Ecological Economics, 57, 45–59. doi:10.1016/j. ecolecon.2005.03.013 Russo, M. & Fouts, P. (1997). A resource-based perspective on corporate environmental performance and profitability. Academy of Management Journal. Sharma, S., Pablo, A., & Vredenburg, H. (1999). Corporate environmental responsiveness strategies. The Journal of Applied Behavioral Science, 35, 87–109. doi:10.1177/0021886399351008 Sharma, S., & Vredenburg, H. (1998). Proactive corporate environmental strategy and the development of competitively valuable organizational capabilities. Strategic Management Journal, 19, 729–753. doi:10.1002/ (SICI)1097-0266(199808)19:8<729::AIDSMJ967>3.0.CO;2-4 Shrivastava, P. (1995). The Role of Corporations in Achieving Ecological Sustainability. Academy of Management Review, 20, 936–961.

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

Shrivastava, P. (1995b). Environmental technologies and competitive advantage. Strategic Management Journal, 16, 183–200. doi:10.1002/ smj.4250160923 Shrivastava, P., & Hart, S. (1995). Creating sustainable corporations. Business Strategy and the Environment, 4, 154–165. doi:10.1002/ bse.3280040307 Social Innovation Exchange and Young Foundation. (2010). Study on social innovation (Working Paper). Taylor, J. B. (1970). Introducing social innovation. The Journal of Applied Behavioral Science, 6, 69–77. doi:10.1177/002188637000600104 Tien, S. W., Chung, Y. C., & Tsai, C. H. (2005). An empirical study on the correlation between environmental design implementation and business competitive advantages in taiwan’s industries. Technovation, 25, 783–794. doi:10.1016/j. technovation.2004.01.004 Wagner, M. (2007). On the relationship between environmental management, environmental innovation and patenting: Evidence from German manufacturing firms. Research Policy, 36, 1587–1602. doi:10.1016/j.respol.2007.08.004 World Commission on Economic Development. (1987). Our common future. Oxford, UK: Oxford University Press. Yunus, M., Moingeon, B., & Lehmann-Ortega, L. (2010). Building social business models: Lessons from the Grameen experience. Long Range Planning, 43, 308–325. doi:10.1016/j.lrp.2009.12.005 Ziegler, A., & Nogareda, J. (2009). Environmental management systems and technological environmental innovations: Exploring the causal relationship. Research Policy, 38, 885–893. doi:10.1016/j. respol.2009.01.020

Ziegler, A., & Rennings, K. (2004). Determinants of environmental innovations in Germany: Do organizational measures matter? A discrete choice analysis at the firm level. ZEW Discussion Paper, Nº, 04-30.

KEY TERMS AND DEFINITIONS Cleaner Production Technologies: Environmental technologies that emphasize continuous improvement and cost minimization. (Rennings et al., 2006). End of Pipe Technologies: Environmental technologies designed to diminish harmful substances that occur as by-products of production (Frondel et al., 2006). Environmental Innovation Double Externality: Environmental Innovations, besides the positive externalities from spillovers which are common to all innovations, are characterized by the fact that while the whole society benefits from a technical environmental innovation, the cost have to be borne by a single firm (Rennings, 2000). Environmental Innovation: The measures of relevant actors consisting in the development, application or introduction of new ideas, behaviors, products and processes that contributes to a reduction of environmental burdens or to ecologically specified sustainability targets (Rennings, 2000). Environmental Organizational Innovations: The re-organization of processes and responsibilities within the firm with the objective to reduce environmental impacts (Frondel et al., 2006). Social Innovation: Social Innovation as the combination of innovative activities carried out by the company with the potential to promote social change. This social change is expressed through the incorporation of ethical arguments to the products, processes and organizational

103

Social Innovation, Environmental Innovation, and Their Effect on Competitive Advantage

modes of the company and results in changes in consumer behavior, changes within the enterprise and changes in the company’s relationship with the social and natural environment.

104

Technical Environmental Innovations: Specific kinds of innovations that consist of new or modified products and processes to avoid or reduce the environmental burden. (Rennings et al., 2006).

105

Chapter 7

Observe, Conceive, Design, Implement and Operate: Innovation for Sustainability Javier Alejandro Carvajal Díaz Universidad de los Andes, Colombia María Catalina Ramírez Cajiao Universidad de los Andes, Colombia José Tiberio Hernández Peñaloza Universidad de los Andes, Colombia

ABSTRACT Innovation within organisations permits the transformation of knowledge into applications for the development of new knowledge and new organisations that are able to respond to the needs and changes of the society. However, how can we establish a framework for acquisition of the skills needed to manage successful initiatives for innovation in organisations and how can we guarantee the sustainability of these innovations? In order to provide an answer to these questions, this chapter presents a proposal for the promotion of sustainable innovation based on the engineering cycle of Observe, Conceive, Design, Implement and Operate (OCDIO). For this purpose, we reviewed examples of innovation in some world class universities, analized cases of education for innovation and developed a case study. We conclude that the OCDIO cycle was set up in a framework that enables the development of sustainable innovations through a permanent cycle of observation and adjustment of the systems designed to resolve problematic situations. The phase of observation allows the professionals facing the challenges of innovation inside organisations to obtain the relevant information for the conception, design, implementation and operation of sustainable engineering systems that take into account the relevant economic, social, technical, environmental and cultural aspects.

DOI: 10.4018/978-1-61350-165-8.ch007

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Observe, Conceive, Design, Implement and Operate

INTRODUCTION “…The world is becoming increasingly more complex and connected, the advance of science is accelerating, and socio-technical problems are abundant” (Steiner, Ramírez, Hernández, & Plazas, 2008, p 141). This rapid process of change implies that organisations and society in general should be ready to constantly adapt to their changing conditions and evolve in order to survive in their environment. In order to accomplish this goal, innovation has become a key element that enables organisations to respond to the increasingly demanding and complex conditions of the market (Evans, Parks, & Nichols, 2007). Innovation within organisations permits the transformation of knowledge into applications for the development of new knowledge and new organisations that are able to respond to the needs of the society (Edmondson & Nembhard, 2009). “In the future, only companies that make sustainability a goal will achieve competitive advantage. That means rethinking business models as well as products, technologies, and processes” (Nidumolu, Prhalad, & Rangaswami, 2009. p. 1). In this sense, new companies with an innovative spirit are able to take the place of established companies which have become old and tired, creating an innovative attitude that generates a higher level of development (Thurik, 2009). However, how can we establish a framework for the acquisition of the skills needed to manage successful initiatives for innovation in organisations? In addition, how can we guarantee the sustainability of these innovations? In order to provide an initial answer to these questions, we need to develop a way to introduce innovation into the education of the professionals that are going to be part of organisations, promoting the development of innovative ideas from different fields of action or simply favouring a continuous process of innovation in the daily running of organisations. We have to keep in mind that innovation generates value in many different ways, and not only in terms

106

of the final sale price; it also adds social value, intellectual value, improves the competences of the organisation (not only commercially but in terms of the quality of production) and helps to clearly define the objectives of the organisation (Organisation for Economic Co-operation and Development [OECD], 2004). Traditionally, engineering as a profession has been one of the disciplines in charge of leading the processes of innovation generated in the Academy or in the production sector. For this reason, many schools of engineering have highlighted the importance of the development of skills in order to tackle the challenges of innovation in the market, so that these skills may be used in the future to create successful projects (Siller, Rosales, Haines, & Benally, 2009). One initiative that had been gaining ground in recent years is the CDIO cycle, which aims to structure education in engineering based on the cycle of observe, conceive, design, implement and operate. This proposal is intended to assist the transformation of innovative ideas into real projects using the CDIO cycle (CDIO, 2010; Crawley & Brodeur, 2008). The aim is that the engineering professionals of the future will have effective communication and teamwork skills and an innovative attitude, which will allow them to successfully carry out sustainable innovation proposals based on the proposed cycle (Hernández, Ramírez & Carvajal, 2010). Sustainability is achieved through a permanent cycle of observation of the designed systems within a process of constant adjustment (Carvajal, Ramírez, & Hernández, 2010; Carvajal, Ramírez, Torres, & Arias, 2010). After several years of research, and obtaining pragmatic innovation results from student teams, a group of researchers proposed the introduction of an additional initial phase of observation into the CDIO framework (Steiner, Ramírez, Hernández, & Plazas, 2008). These researchers believe that a person (or a group of people) trying to develop an initiative for the purpose of innovation in any context must observe his/her context in order to attempt to

Observe, Conceive, Design, Implement and Operate

understand it (market needs, restrictions in the systems, economic, technical, environmental and human conditions, the current situation, etc.). In order to innovate you have to know your customer, his community, his ideas (OECD, 2004). Based on such an understanding, a solution with which to tackle the observed situation is conceived; the solution is designed, taking into account the restrictions and projections for the future, and then the design is implemented and materialised in order to operate it. The cycle restarts, and the project is observed as it runs with the purpose of improving it in each iteration, thus making the solution (project) sustainable. This chapter starts by presenting cases of innovation training initiatives developed by prestigious institutions which operate in this area. It continues by presenting the OCDIO cycle as a framework for the development of sustainable innovation. Later, it presents the progress of innovations in Colombia such as the framework of the proposed OCDIO cycle. Afterwards, this research presents innovations and innovation training initiatives, and discusses the particular case of the School of Engineering at the Universidad de los Andes. Finally, this chapter presents the results of the application of the OCDIO proposal in specific engineering contexts. We conclude this research suggesting future work in this initiative and presenting some reflections on it.

INNOVATION IN ENGINEERING Innovation as a Concept The concept of innovation has several interpretations and meanings. Schumpeter (1936) propounded that innovation is the commercial or industrial application of something new: product, process or production process, market source of offer, organisational form. Cozzens and Kaplinsky

(2009, p. 58) added to that definition by stating that “innovation provides the private producer with competitive advantage or allows the social producer to better meet the needs of consumers with a given resource cost”. For Chesbrough (2003), innovation is an invention implemented and taken to the market. However, Zoltan, Audretsch and Strom (2009) have stated that an innovative spirit allows new companies to take the place of those companies that are unable to develop innovative activity and promote a higher level of development. The National Academy of Engineering (NAE) (2000, p. 44) of the United States of America (USA) defines innovation as “the transformation of an idea into a marketable product or service, a new or improved manufacturing or distribution process, or even a new method of providing a social service”. Although reaching a consensus regarding the definition of innovation is outside of the scope of this chapter, the proposed definitions allow us to create a framework with which to introduce a concept that is more relevant for us: the innovation process. Davenport reinforced the idea of innovation processes by stating that it is clear that innovation is the introduction of something new, but that “we presume that the purpose of introducing something new into a process is to bring about major, radical change” (Davenport, 1993, p. 10). Innovation processes are combinations of structures for the development of work oriented towards achieving visible and measurable results with a clear business objective (Davenport, 1993). Taking into account that it is more important to focus on the processes of innovation than the concept of innovation, we will then present the OCDIO cycle with the aim of answering our two questions relating to the necessary skills for innovation processes and the sustainability of innovation.

107

Observe, Conceive, Design, Implement and Operate

Education for Innovation: Several Cases Several schools of engineering across the world are working to structure innovative engineering curricula, which will include the challenges of engineering in the 21st century as identified by organisations such as the Accreditation Board of Engineering and Technology (ABET). The objective of these curricula is to respond to the needs and requirements of existing organisations regarding the professional education of engineers in particular. At the same time, an awareness of the development of the necessary competences for innovation has been developed as one of the pillars of economic development and the growth of society. Institutions such as the Franklin W. Olin College of Engineering (Olin College), the Massachusetts Institute of Technology (MIT), the Chalmers University of Technology (Chalmers), the KTH Royal Institute of Technology (KTH) and Linköping University (Linköping) have developed successful initiatives for the purposes of education in innovation; the first three in the USA and the remaining three in Sweden (Bankel et al., 2005). MIT, Chalmers, KTH and Linköping, as well as being known for their success in the field of innovation, lead the CDIO initiative that had been spreading to several universities around the world (Crawley & Brodeur, 2008). Olin College, which does not belong to the CDIO initiative, has developed a curricular structure which is consistent with elements of the CDIO framework. The cases of these universities allow us to understand the role of education (in this case in engineering) as a key element in the development of the competences required for sustainable innovation in organisations. Let us begin with the case of the engineering curricula at MIT that have been structured around three large domains: “science and technology, culture and society, and the prior preparation and aspiration of students” (MIT, 2006, p. 1).

108

Based on these domains, MIT has created a flexible curriculum in which the students receive a solid education in basic sciences (mathematics, chemistry, biology and physics). The students can choose from different education cycles in humanities, arts and social sciences. Alongside these components of the curriculum, the students receive specific education in an area of engineering of their choosing. During their education, the students apply the concepts and skills they acquire in the different areas of their curriculum in their undergraduate curriculum by developing real engineering projects. These projects are developed based on the CDIO framework guidelines, combined with the “…research teams that confront the great scientific challenges that we face today” (MIT, 2006, p. 7). The education model at MIT aims to aims to develop skills which can be integrated with the knowledge the students possess. Therefore, they expect that innovative ideas will emerge as a result of the intersection between science and technology, humanities, arts, social sciences and the academic interests of each student (MIT, 2010). Meanwhile, Chalmers bases its curricula on the “knowledge triangle”, the base of which is composed of education and research. On the top of the triangle is innovation, which forms a primary objective of education at Chalmers (see Figure 1). This innovation is developed within the framework of the five areas of advancement: energy, the science of materials, nanoscience and nanotechnology, production, and transport. In order to achieve this goal, Chalmers structures its curricula around a sound education in the basic sciences that provides the students with enough knowledge to build an excellence profile in an active field. “Excellence profiles are areas where we take a national responsibility with the potential to meet the challenges of today and tomorrow. They are positioned in the international forefront of research, education and innovation with a mission to meet the long-term needs from society and industry” (Chalmers, 2010a).

Observe, Conceive, Design, Implement and Operate

“Active fields on the next level describe research areas within or between excellence profiles. They include excellence centers, research programs [sic], clusters of research groups and international networks, coupled with education and innovation activities in collaboration with research institutes, industry and society. The research is very often carried out at several departments in joint effort where both applied and basic sciences are vital parts” (Chalmers, 2010b, p. 2). This model indicates that Chalmers is the leading university in Europe for providing support for the creation of businesses’. Chalmers is well known for the development of systems of innovation based on the creation of companies that exploit research applications in the commercial arena (Chalmers University of Technology, 2010c). These activities are closely connected with government efforts, the business sector and initiatives by the University itself (Chalmers University of Technology, 2010c). “Chalmers is an open arena in which the forces of innovation are gathered together. And Chalmers’ researchers are also successful as regards creating a stimulating collaboration between the business world and the university” (Chalmers University of Technology, 2010a).

Figure 1. Chalmers’ knowledge triangle

KTH and Linköping, as Swedish universities, have structured their curricula in the same fashion as Chalmers, which, in part, accounts for their position as the three universities (along with MIT) leading the development of the CDIO framework. Regarding innovation, “KTH is to be positioned as an entrepreneurial university that values innovation and entrepreneurship in education and stimulates the creativity and innovative attitude of students and researchers” (KTH Royal Institute of Technology, 2009, p. 31). Meanwhile, Linköping aims to continue developing its skills as a university which combines basic and applied research in innovative contexts. Olin College (USA) was established in the autumn of 2002 as a result of an initiative to prepare “...students to become exemplary engineering innovators who recognize [sic] needs, design solutions, and engage in creative enterprises for the good of the world” (Kerns, 2001). Olin College does not see itself as a teaching institution where the faculty teaches something new to a group of students who are only going to be in the University for a couple of years (Kerns, 2001). In this sense, the faculty and the students “…will nurture a culture of innovation, inquiry, problem-solving, entrepreneurship, research, [among others], to ensure the faculty stay current with the latest developments in their field, that they are encouraged to explore interdisciplinary areas, and that faculty transmit the results of this intellectual vitality to students both in and outside of the classroom” (Kerns, 2001). In addition, Olin College developed the conceptual framework known as the “Olin triangle” (see Figure 2a). “At the peak of the Triangle was Superb Engineering, supported by the Arts, Humanities and Social Sciences (“AHS”) (encompassing Design, Creativity and Innovation) and by Entrepreneurship (including Philanthropy and Ethics)” (Greis, 2009, p. 25; Kerns, Miller, & Kerns, 2000).

109

Observe, Conceive, Design, Implement and Operate

Figure 2. Olin College’s triangles

Based on the “Olin triangle” framework, Olin college has designed an engineering curriculum structured around four years of education, as follows: “…two-year foundation course and project work, a third year of specialization in which the student focuses on a particular area of interest and a fourth year (realization) during which the expertise is applied to a project of professional caliber” (Greis, 2009, p. 25; Kerns, Miller, & Kerns, 2000). In the first two years, the students work in projects based around “…integrated course blocks (ICBs), large course blocks that combine two areas of study (say, engineering and biology) and an interdisciplinary project” (Greis, 2009, p. 26). “The ICB…provides teamwork opportunities for faculty and students…the fourth-year senior capstone project, pairs student teams with businesses to develop a solution that incorporates the students’ specialized [sic] skills and meets the business clients’ requirements and schedules” (Greis, 2009, p. 26). In their final year, the “…students not only learn the fundamentals of engineering science, but also can apply these techniques to the solution of real-world problems” (Greis, 2009, p. 26). Through this curriculum structure, Olin College aims to “…prepare leaders who can predict, create, and manage the technologies of the future”

110

(Kerns, Miller, & Kerns, 2000, p. 105). Olin College has presented a second triangle in which the courses are related (in terms of curricular content) with competences (skills such as team work, effective communication and an innovative attitude, among others) and the incorporation of spaces in the development of projects. Olin College considers that the development of competences through the application of content in real projects permits the creation of innovative ideas, while spaces based only in courses with disciplinary content (traditional spaces) do not necessarily guarantee such innovation. Another common element in the listed universities is their participation in their innovation systems. These tight links with companies, business people, local and national governments, research groups and international networks of innovation have allowed these institutions to generate meaningful contributions to the economic and social development of Sweden and the USA. This relationship among the actors in their innovation systems has resulted in the success of innovative projects that have become productive organisations with a direct impact on the economic indicators in these countries. In later sections, we will present the experience of Colombia regarding the running of its own innovation system.

Observe, Conceive, Design, Implement and Operate

We have presented the innovation process as raised by Davenport (1993); this concept is tightly linked with the idea of educating professionals and developing their competences in order to develop innovation processes. The leading team of universities in terms of the CDIO have structured their educational programmes around the integration of areas of knowledge such as the arts, humanities, social sciences and exact sciences. At the intersection of these areas is where these universities have managed to capitalise on opportunities for the development of innovative projects that include engineering as a basis for their development. At the same time, the development of innovative ideas is based on the framework of CDIO that began in courses included in the engineering curricula. Lately, these universities have begun to hope that their alumni develop similar processes in the organisations that they go on to work for. The core of the CDIO framework is the development of skills to be used at each of the stages of the proposed cycle. These skills are acquired by the students through their study programme and used by them throughout their entire professional career. In this way, we can start to form an answer to the question regarding the creation of a framework for the acquisition of skills for the successful development of initiatives for innovation in organisations. This is because CDIO is the framework for the development of competences that will allow workers to conceive, design, implement and operate systems (projects) for innovation in their organisations. Regarding our second question, we will propose an initial stage in the CDIO framework: observation. This stage has been proposed by the research team of Universidad de los Andes in order to guarantee the sustainability over time of the innovations achieved through the OCDIO framework.

OCDIO AS A PILLAR OF SUSTAINABLE INNOVATION: A MODEL OF EDUCATION IN THE FIELD OF INNOVATION IN ENGINEERING Engineering as a profession has been experimenting with changes in its education-learning models, with the purpose of educating the engineers who will face the challenges of this particular discipline in the 21st century (Siller, Rosales, Haines, & Benalli, 2009; ABET, 2004). One of the most relevant changes has been moving from the knowledge transfer paradigm to the development of professional skills paradigm (Hernández, Caicedo, Duque, & Gómez, 2004; Siller et al., 2009; Witt, Alabart, Giralt, Herrero, Vernis, & Medir, 2006). Examples of these changes have been reviewed by various global institutions such as the NAE (Siller et al., 2009) and the ABET in the USA. Nonetheless, the teaching-learning of these skills is difficult, especially for faculties that are looking to find a balance between the need to include or increase the technical content in the curriculum (Siller et al., 2009) and the formation of engineers who are able to apply such content and acquire new skills through what is known as lifelong learning (McCowan, 2002). In response to the new challenges involved in education in the field of engineering, a group of globally renowned institutions (MIT, Chalmers, KTH and Linköping) developed a proposal based on the CDIO cycle for engineering projects (Crawley & Brodeur, 2008). The proposal has three main principles: (i) scientific breakthroughs and technological developments; (2) internationalisation; and (3) the skills and attitudes of first-year students of engineering. Scientific breakthroughs and technological developments: With regard to technological developments, the question is whether schools of engineering have enough resources to be able to develop applied research, or if there is a way to

111

Observe, Conceive, Design, Implement and Operate

integrate engineering programmes into industry developments. The closeness between engineering programmes and the industry is fundamental to a country’s technological development. The CDIO initiative allows students to experience learning in pragmatic terms in the midst of a social context in which engineering can add value (Cutkosky & Fukuda, 2004; Froyd & Ohland, 2005; Lloyd et al., 2004). Internationalisation: Globalisation demands that engineers have the capacity to adapt very quickly to contexts that are different from their own. Such is the case in European student exchange programmes such as the Erasmus European programme and the Socrates programme, where professionals with the ability to adapt to different environments are sought after. In the USA and Canada, the same thing happens with Chinese and Indian students (CDIO, 2010). According to the Asociación Colombiana de Facultades de Ingeniería (Colombian Association of Engineering Faculties, ACOFI), engineers are being drawn to developing countries other than their own. In this sense, additional efforts should be made in order to include analyses of different contexts as an integral component of their training. The skills and attitudes of first-year students of engineering: One of the main concerns of schools of engineering is the level of knowledge in basic sciences which is applied in projects developed by engineering students (Cutkosky & Fukuda, 2004). It is necessary to generate curricular processes in which knowledge of engineering and basic sciences is integrated into the development of real projects. This requires a widespread effort at every educational level (school, undergraduate and postgraduate). With this in mind, the CDIO initiative promotes the development of hands-on activities that allow the integration and implementation of a scientific basis into real projects. Taking into account the challenges highlighted by the NAE and the ABET, which have been discussed in multiple schools of engineering throughout the world, and the principles of the CDIO cycle,

112

the School of Engineering at the Universidad de los Andes has proposed a curricular space which is designed to develop some of the skills proposed by the ABET together with students, professors and businessmen. As a contribution to the CDIO framework, we have proposed an additional initial phase of observation. This phase allows a careful investigation process based on a literature review and creativity workshops that allow us to explore the technological conditions that surround us and to approach potentially problematic situations that could be addressed from the point of view of different fields of engineering. This first phase of what we have decided to call the OCDIO cycle provides the necessary information to start the conception of ideas as proposed in the CDIO cycle. The CDIO framework starts with the conception of an idea that will later be designed, implemented and operated through a project. “The Conceive stage includes defining customer needs; considering technology, enterprise strategy, and regulations; and developing conceptual, technical, and business plans” (Crawley & Brodeur, 2008, p. 138). These activities are important immediately prior to the design of a solution and are the basis for the structure of a project that executes the design. However, a research group of Universidad de los Andes proposed that before an idea can be conceived, a rigorous observation stage is required (Ramírez, Carvajal & Hernández, 2010). In this stage, opportunities for innovation are identified, as, by observing the world around us, its variables, its agents and the iteration among them, we can understand the different complexities that surround us and we can propose mechanisms (solutions) that could absorb part of that complexity (innovations) (Vest, 2000). For this reason, we believe that the first stage in the OCDIO cycle should be the observation stage. Connecting these ideas with the proposals of the CDIO leadership team, it is possible to argue that in the crossover between the social sciences, arts and humanities lies opportunities for the

Observe, Conceive, Design, Implement and Operate

development of innovative ideas. However, for the identification of such ideas to be possible, the development of the observation processes we have previously discussed is absolutely necessary. If we move to the final stage of the cycle (operate), we find that it is necessary to develop a new process of observation of that solution (or system) which has been designed, implemented and is now operating. Based on these new observations, we could conceive, design, implement and operate new solutions or improvements to the same solutions in the OCDIO cycle. This stage of the initial-final observation process allows us to ensure the sustainability of the solutions developed in the CDIO framework. However, the question remains of why this is so. The reason is that in a constant and systematic process of observing the results and the behaviour of implemented and operating solutions, there is the possibility and opportunity to improve with each iteration, by finding the shortcomings and obstacles that can then be overcome in new versions of the OCDIO cycle. In this way, we can guarantee that over time, innovative engineering solutions will adapt to these new conditions, challenges and requirements identified in the observation process. Therefore, we have established that the CDIO cycle is an adequate framework for the acquisition of the skills required for successful innovative ideas. We have included an initial stage of observation that guarantees the sustainability of those innovations over time. In this way, we will carry on building an answer to the two questions that guide this chapter. In the next section, we will present the details of the educational contexts in which we used the OCDIO framework for the development of sustainable innovative ideas. For this, we believe it to be important to present the context in which these education spaces are developed. Therefore, we will present elements of the Colombian innovation system as the environment of the School of Engineering of the Universidad de los Andes.

THE INNOVATION SYSTEM IN COLOMBIA There are plenty of opportunities to develop sustainable ideas for innovation in countries with the current characteristics of Colombia. We will present the main reasons for this fact in the following section. One indicator of a country’s competitiveness in terms of research and development is the publication of scholarly articles as a measure of scientific activity and knowledge production (Jaramillo, Lugones, & Salazar, 2001). Between 1997 and 2002, the Colombian participation in bibliographical production in Latin America relating to publications in indexed journals was 2.42%, which is higher than that of Bolivia (0.33%), Costa Rica (0.96%), Ecuador (0.45%), Paraguay (0.11%), Peru (0.85%) and Uruguay (1.35%) (Jaramillo, 2003). However, Colombia ranked below the production of countries such as Argentina (18.10%), Brazil (43.77%), Chile (7.99%), México (18.54%) and Venezuela (4.08%) (Jaramillo, 2003). Figure 3 shows the increase in the Thomson Scientific (ISI) publications in Colombia between 1975 and 2005. Figure 3 shows that between 1980 and 1995, the number of publications in Colombia, as is usual in a developing country, increased slowly. Since 1995, with the appearance of science and technology policies and investment in international cooperation (see Figure 4), a rapid and sustained increase in the number of publications emerged. From then on, the increase inclines, once again, towards moderation. The question that arises is why the behaviour of Colombian publications changed after 2005. It seems that the country reached its peak in terms of production capacity, and does not have the institutional infrastructure to support any further increase in new knowledge production. When comparing the results for Colombia with those of more developed countries, such as Brazil, similar patterns are found but with significant

113

Observe, Conceive, Design, Implement and Operate

differences in the number of publications, which in the case of Colombia is in the hundreds whereas in Brazil it is in the thousands (see Figure 5). Furthermore, both countries have a growing number of publications, but in Brazil the growth in faster than in Colombia. The relevance of Brazil is based on two reasons: (i) Brazil is the most developed country in the region (South America); and (ii) economically speaking, Brazil is one of the strongest countries in the world (it is a member of the G20). The academic development of Brazil is closely related with its innovation system that, as a result of the relations between the different actors that participate in it, generates a high level of knowledge and sustained economic growth. Colombia has been advancing in terms of the structure and consolidation of its innovation system since the nineties; however, this initiative has not yet been as successful as the Brazilian equivalent. Colombia has made new efforts via legislative initiatives to foster scientific and technological innovation. Examples of these efforts include several bills that are being discussed in the Colombian Congress and which aim to improve the institutional infrastructure regarding science, technology and innovation. There is an initiative for the creation of a Ministry of Science, Technology and Innovation, a National Trust for the Funding of Science, Technology and Innovation and a National System of Science, Technology and Innovation. These initiatives ratify the clear need for Colombia to be introduced into the knowledge society and to improve its position in the regional context and worldwide. These initiatives are aligned with Colombian history regarding the creation of an innovation system which will be consolidated in the coming years. Figure 2 shows the milestones that allowed Colombia to advance towards its incorporation into the knowledge society, which demonstrate their efforts to develop social, institutional, human and financial capital. In this manner, the National

114

System of Science and Technology (SNCyT) and the National Innovation System (SIN) have been consolidated, with the aim of supporting and improving knowledge production and its subsequent application in order to foster economic growth. Two characteristics of the incipient Colombian innovation system in terms of human capital are presented by Gómez (1999) as the common aspect for Colombians: on one hand, their capacity to solve individual problems and, on the other hand, their incapacity to solve collective problems. The latter issue is aggravated because of a lack of resources and investment. For the resolution of collective problems, there is a clear need for engineering and other disciplines to immerse themselves in topics such as security, environment, infrastructure, public health, and knowledge, among others. Public goods related to knowledge are those that “are most urgently needed in Colombia. This lack makes extremely expensive the production of private goods” (Gómez, 1999). These assessments by Gomez pose two challenges: increasing the investment in knowledge development so as to enhance competitiveness, and increasing the ability of Colombians to work in teams, aiming towards the same collective goal. With regard to the first challenge, private investment in technology in Colombia, according to the National Planning Department, oscillates between 15% and 20% of the national budget, whereas in countries such as Mexico and Brazil that percentage in 2003 was 29.8% and 39.8% respectively. In the period 2002-2004 in Colombia, an average of 0.03 patents per 100.000 inhabitants were issued, while in Chile the same indicator was 0.13 and in Argentina it was 0.53. The total expenditure on investigation and research as a percentage of the Gross Domestic Product GDP in 2004 in Colombia was 0.37%. The number of researchers per 100,000 inhabitants in Colombia was 109 in 2003. These indicators show that Colombia is on the right track but lacks the driving force required to boost its economic growth.

Observe, Conceive, Design, Implement and Operate

Figure 3. Increase in Colombian ISI publications (Source: General Research Office of the Universidad de los Andes)

Figure 4. Milestones in the creation of the Colombian innovation system

115

Observe, Conceive, Design, Implement and Operate

Figure 5. Brazilian ISI publications

In countries such as Colombia, companies should coordinate with national research groups and universities in order to find sources of proposals for new products, processes and services (National Research Council, 2007) which would reduce the gap between these organisations and multinational companies with specialised departments and a budget for research and development. This joint work may be modelled on the processes developed by the universities presented above. Regarding the second challenge, proposals like the one set out by the School of Engineering at the Universidad de los Andes seek to strengthen the competences of teamwork, observation and conception in constantly changing scenarios (negotiation processes and technology, among others). This has a huge impact on the competitiveness of companies, fostering a culture of innovation in new generations of professionals as an essential practice for the economic development of their country. This will allow the national industry to participate to a greater extent in the international market. Taking this into account, we will present the generalities of the OCDIO proposal and contextualise it with an example of its application in the School of Engineering at the Universidad de los Andes. 116

THE CASE OF THE SCHOOL OF ENGINEERING AT THE UNIVERSIDAD DE LOS ANDES In the aforementioned scenario, the University of Los Andes has been a key actor. The School of Engineering has made explicit its aim of contributing to the country’s competitiveness through innovation. The strategic postulates (mission and vision) of the School Development Plan 2002–2005 refer to innovation capacity based on technology as one of the core characteristics that its undergraduate alumni must have, and to adding value to companies as one of the focal points of the School of Engineering. It also express it intention to have a positive impact on the competitiveness of the country through research. For the period 2006–2010, the School kept on track in terms of the previous plan concerning innovation, but introduced an additional element: the level of participation that it must have in the technological renovation processes in national industry. These principles are based on the University’s interest in participating in the Colombian innovation system and becoming a relevant actor in the transferral of knowledge from the academy to the production sector.

Observe, Conceive, Design, Implement and Operate

There are several diverse initiatives created by the School with the objective of developing its capacity to promote and support innovation in national industry. In the 1990s, it participated in the establishment and direction of INNOVAR, an institution dedicated to the incubation of businesses with the potential to succeed. In the same decade, at the end of 1993, it created the Innovation and Technological Development Centre (CITEC) with the expectation of helping to increase the welfare of citizens through its participation in the industrial development of the country. The CITEC established its objective as the execution of projects with a high component of innovation, oriented towards the solution of problems in the field of engineering. In 2000, the newly available infrastructure of facilities and laboratories and the realisation of the importance of working closely with the production sector motivated the School to reflect on how to formally incorporate the innovation process into the institutional dynamic. Under the name of InnovAndes, a proposal was prepared for the creation of an innovation centre building upon the experiences gained through the CITEC, with the aim of boosting the development of the graduate School through applied investigation. The idea was to open spaces up for effective interaction among research groups and companies, with the aim of solving the relevant problems in the field of Colombian engineering. Other initiatives such as the Centro Guía (Guidance Centre) or the Red de Empresas Asociadas a la Universidad de los Andes (Network of Companies Associated with the Universidad de los Andes), both in an alliance with the Business Management School, also tried to offer the participating companies a way to resolve their management and competitiveness problems through the transfer of the appropriate technology. The Universidad de los Andes (and particularly the School of Engineering) had been working to reinforce the activities of teaching and investigation related to innovation. The University cited

conducting high level research as one of its institutional aims, which means producing its own knowledge about relevant problems. With this objective in mind, the School focussed on activities such as strengthening its master’s and doctorate programmes, using its own resources for research, subscribing to international scientific databases, upgrading its infrastructure, equipping its laboratories with the latest technology and educating and assigning its professors staff for research purposes. In 2007, the university created the Vice Rector’s Office of Investigations, which was focussed on managing the accomplishment of these objectives. As a result of these initiatives, the Universidad de los Andes has experienced a sustainable growth in indicators such as the number of ISI publications (see Figure 6), placing itself in 5th place in the ranking of Ibero-American research institutions. The results presented in Figure 6 accompanied a significant growth in the rate of production of ISI articles per professor: 0.36, 0.45 and 0.59 for 2007, 2008 and 2009 respectively. In the same way, 20 of the 130 research groups at the University are in the highest category of the National Administrative Department for Science and Technology (Colciencias) in terms of the quality and frequency of their publications and researches results.

Model of Education in Innovation in the Field of Engineering: The OCDIO Cycle in the Context of Undergraduate Students of Engineering at the Universidad de los Andes Taking into account the national context and the context of the Universidad de los Andes, the School of Engineering has been consolidating a space for the development of engineering projects from the first semester until the end of the undergraduate programme (see Figure 7).

117

Observe, Conceive, Design, Implement and Operate

Figure 6. Growth of the number of ISI publications of the Universidad de los Andes

Figure 7 presents the undergraduate engineering programme and the points in the course at which certain projects are developed. These projects are developed across the curriculum and aim to be a way of integrating the students into the curriculum. In the following sections, we will develop two of these points in the course as part of the OCDIO model of education for innovation.

First Semester In the first semester, the students of all of the engineering programmes undertake a project which is based around a specific topic that is defined according to the context of the different introductory courses to the engineering programme. This active learning scheme is called ExpoAndes. At the end of the semester, around 150 groups of students present projects that aim to provide an initial approach to innovation in engineering with regard to a specific problem (Ramírez & Hernández, 2008). This phase of the undergraduate programme is intended to start the development of an innovative attitude through activities with an emphasis on the observation and conception of engineering projects. Activities intended to foster the design of these projects are also supported,

118

although with less emphasis. Without a doubt, the main strength of ExpoAndes is its capacity to generate in the students the ability to come up with teamwork solutions. There are some very interesting issues concerning this matter. In the evaluation of the ExpoAndes process, the most positive opinions regarding teamwork belonged to the students in the final semesters of their undergraduate programmes. The a priori hypothesis of the research team is that these were the students that first had the opportunity to work in interdisciplinary teams. This was the first phase of change for ExpoAndes, in which engineering projects were undertaken by teams composed of students of industrial engineering, chemical engineering, computing and systems engineering, and general engineering. This process required a complete integration of the students with the group and with the professors in charge. The identification and resolution of the problems being addressed showed that knowledge from each discipline was necessary. Another interesting result concerns the development of the students’ communication skills, due to the interdisciplinary nature of the teams. It is noticeable that the teams (both the ones composed of students from the programme as well as those

Observe, Conceive, Design, Implement and Operate

Figure 7. Projects in the education of engineers at the Universidad de los Andes

composed of students of different engineering programmes) were unable to develop their oral expression skills. The researchers relate this to the fact that the students presented their projects only once, in a very demanding and pressure-filled open exhibition with more than 2000 guests (including parents, business people, engineers and professors). Even though the students have shown some resourcefulness in presenting their projects in the proper way, it would be sensible to create opportunities for smaller oral presentations during the semester. In this way, permanent systematic training of this skill would be guaranteed. Regardless of its limitations, ExpoAndes presents itself as an opportunity for professors to guide the students in the process of observation, identification and design using an engineering approach. Although it is clear that the students will be unable to solve a problem like engineers in the first semester, we want to them to experience what they will be doing in their professional lives. The results show that there are good perceptions of different relevant actors regarding this matter. A learning process such as ExpoAndes aims to develop an innovative attitude in the engineering students from the first semester, so that the students will be able to identify opportunities to add real value to their society. The senior students perceived that the greatest strength of ExpoAndes is the development of the capacity for innovation applied to the resolution of a problematic situation. The students who had just gone through ExpoAndes had contrasting opinions.

One hypothesis (which may be too strong) is that these contradictory results may be associated with the different approaches that ExpoAndes has employed in recent years. The new students had to design their solutions using only their knowledge of their own engineering discipline. The question that arises is whether or not interdisciplinary teamwork promotes innovation in the design of an engineering solution. These preliminary results may indicate that this is in fact the case. In that sense, it is important to explore in depth such a strong asseveration in the middle of a learning process. In this way, ExpoAndes is an initial opportunity for students to develop their capacities as entrepreneurs. There is a significant and potentially big research opportunity in exploring whether or not this competence develops in the same way for the students of each different engineering programme. The preliminary results show, for example, that the perceptions of students regarding their innovative attitudes were more positive for chemical engineering students than industrial engineering students. This result is interesting if we take into account that in the industrial engineering department, the students have more courses in which to develop an entrepreneurial attitude. This may lead us to assume that, at least initially, the industrial engineering students were more critical of what they did in the first semester, because they had more opportunities to develop opportunities for entrepreneurship. This discussion is important, but should be explored in future research.

119

Observe, Conceive, Design, Implement and Operate

The Middle of the Study Programme The next point at which the students engaged in the elaboration of an engineering project with a special emphasis is called the intermediate project. In this project (like in ExpoAndes) the students work in teams to develop more compelling projects than those they made in the first semester. In this process, the activities for the elaboration of their projects are defined with a strong emphasis on observation, conception and design. In addition, the aim of this project is for students to develop the first activities relating to the implementation of the prototype they have developed (see Figure 8). Both in the first semester and in the middle of the study programme, the project is intended to foster attitudes which are conducive to teamwork, the design of engineering solutions and effective communication, among other aspects. This is the reason why the CDIO framework with the proposed additional observation phase forms a good context for the design of these projects (Hernández, Ramírez & Carvajal, 2010).

In particular, in recent years the OCDIO framework has been used in the course known as the “middle study programme project”. This course is taken by students in the fifth and sixth semester of the study programme. In the following section, we will present the details of the process developed by the students in each of the stages of the OCDIO cycle in the “middle study programme project”. In this course, the students work on problems related to information and communication technologies (ICT). Observation: Conception Over a period of six weeks, the teams engage in four activities that require the participants to develop observation skills. The students make a presentation referring to the technological changes in the world and the central role of information technologies. For this purpose, a panel of engineer-entrepreneurs is assembled, and the research teams make presentations on tendencies and opportunities. Parallel to these national interventions, there are videoconferences with project development experts in

Figure 8. Application of the OCDIO proposal in the middle of study programme course with ICT

120

Observe, Conceive, Design, Implement and Operate

other parts of the world. With these presentations, the students not only begin to visualise potential areas for their engineering proposals both nationally and internationally, but also start to make connections with entrepreneurs who could eventually become their mentors. In the next step, the students begin, on an individual basis, a bibliographical research process, in which they produce written technical reports about engineering proposals that may or may not have been particularly innovative. This second activity seeks to strengthen their research skills through a systematic review of the relevant texts, as well as strengthening their written communication skills. For that purpose, the students receive feedback on their reports from their professors. This process is repeated several times during the semester. During the third and fourth weeks of the semester, the students participate actively in an observation for innovation workshop. During the first three hours of the workshop, the students observe and make comments on images of projects that have been acknowledged for their creative content and innovation. After this, teams of five students are drawn up, who have to identify during the following week a situation that has attracted their attention, essentially because it refers to the behaviour of a representative sample of people in the communities that surround them. The situations may be as commonplace as the behaviour of people riding on public transport, in an lift, inside the classroom, writing a text on a mobile phone, etc. Once the situation is identified, they must make an audiovisual record of the different behaviours at different times during the week. With the audiovisual material obtained by each team, all of the students get together and the chosen situations are presented. For three hours, each group produces a visual 3D presentation and an intervention proposal for the selected situation. The team should construct their presentation using materials such as paper, cardboard, photographs from magazines, etc. At the end of the session, each team shares their proposal with the rest of

the students. The following week, each team must integrate the result of their proposal with the information gathered in the bibliographical research, stressing the added value supplied by information technologies. The entire process of observation for the innovation workshop is repeated, with each team choosing a different situation. The intention of the workshop is that the student will sharpen his/her observation skills and start to work successfully with other students in a team. At the end of this observation stage, the students attend a presentation of the advanced projects of teams that are one semester ahead. The goal of this final activity of the observation stage is that the students who are beginning their projects observe and analyse the work of other teams that are ahead in their innovation proposals with information technologies. This phase ends with the presentation of ideas for the conception stage of the project. Conception: Design In this stage (during four weeks), the groups must capture their observations and produce a project proposal that must be presented and refined based on the critique and contributions made by entrepreneurs, professors and students. This stage, like all of the following ones, is characterised by cycles of teamwork, feedback and coaching sessions with an engineer-entrepreneur and the professors. After one week of work, a proposal with the initial project requirements must be generated. It must be presented in a written report that identifies the problematic situation in which the students intend to intervene using engineering tools, establishes the objectives of the project, defines the field of technological relevance and determines the niche in the market in which the proposal would have a potential impact. Teamwork plays a fundamental role in this process of helping students to reach their learning goals. Based on a communication-feedback process, a full session (poster-session) is held with the

121

Observe, Conceive, Design, Implement and Operate

participation of the engineer-entrepreneurs, the professors and the students. In this session, each group presents its proposal orally and exhibits a poster with the main features of the proposal displayed on it. Each group has seven minutes for its oral presentation, which must be focussed on the results of their observations and the initial conception phase of their proposal. This is followed by immediate feedback (three minutes of questions and commentaries), and an evaluation given by the engineer-entrepreneurs and the professors based on effectiveness of the teamwork and the development of their innovation abilities. The efficiency of the teamwork is evaluated according to criteria which are related to the oral and written presentations, as follows: support material; oral expression; time management, structure of the document; written expression, and proper use of the bibliography. The development of innovation abilities is evaluated according to criteria which are related to: project content; project objective; state of the existing prototype; projects referred to; deliverable definition of the innovation with an information technologies showcase; knowledge and technologies involved, and work schedule. At the end of the presentations, the engineerentrepreneurs offer another round of questions, this time more specialised, to each group. At the end of the poster-session, each entrepreneur chooses the two projects that captured their attention the most. From then on, each entrepreneur follows their two chosen projects. The engineer-entrepreneur assists the team in the strengthening of their communication, teamwork and innovation with information technologies skills. These skills are assessed based on numerical criteria, in which 1 means that the student has not developed the skill and that he/she may still improve. Entrepreneurs may choose the groups that are of the most interest to them. At this point, the coaching process begins. Successful cases such as the ones presented by the University of Texas at Austin, UPC and Stanford University, provide evidence that if a couching process is

122

conducted by entrepreneurs, the potential for innovation, effective communication, knowledge development and the capacity to work in teams increases considerably (Evans, Parks, & Nichols, 2007; NAE, 2000; Skogstad, Currano, & Leifer, 2008; de la Hoz, & de Blas, 2009). From the sixth week onwards, the design phase becomes more relevant in the development project. Two-week cycles are defined by meetings with the engineer-entrepreneur who is assessing the project. The purpose at this stage is to make progress in terms of the relationship between the requirements of the selected situation and potential alternative solutions derived from the application of information technology. The entrepreneur helps to analyse the project, encourages teamwork, provides oral and written expression tools to the students, and assists them so that the prototype has a concrete application that generates value in a determined area. This teamwork between businessmen, teachers and students generates value within the learning process in the sense that each member brings the expertise and perspective of his or her own field to the collaborative task (Edmondson & Nembhard, 2009). After the first two weeks of the cycle, there is a presentation and feedback session with the group of professors. Design: Implementation Over a period of four weeks, the design must be consolidated, based on teamwork and assistance from the professors and entrepreneurs. Ideally, by the end of this phase, the project will have its first prototype to illustrate the proposal and a defined implementation programme. This phase is the last one of the first semester in the teamwork and innovation learning period, and, at the end, there is a Public Showcase of Innovation with Informatics Technology in which the first results of the implementation of the proposal are displayed. The public display lasts for one day, with students and professors from the university attending,

Observe, Conceive, Design, Implement and Operate

along with entrepreneurs invited by the School of Engineering and the engineer-entrepreneurs who have assisted with the projects. The process described above takes place during the first semester of the third year of study in the engineering course. The teams can either pass or fail the semester. If they pass, they enter the second semester of the third year, in which there are four phases, each of which culminates in a communication-feedback activity. Operation The best projects participate in the Innovation Contest that takes place at the end of the semester. The jury for this contest is made up of entrepreneurs who evaluate the students’ development in terms of teamwork and innovation skills using criteria such as the establishment of an objective, target market determination, precision in the presentation of the solution design, sustainability analysis (economic and technological), innovation (design, price, technology), endeavour (planning, understanding the problem, understanding the solution). The winners of the contest receive incentives to put their proposed prototype into operation. During the next year, they have access to a space in one of the faculty laboratories, economic resources (1500 US dollars) and the coaching of a board of directors made up of two entrepreneurs and a professor. During the fourth year of the course, the teams can strengthen their proposals and plans using the academic resources that are at their disposal (courses, course projects, laboratories, coaching from entrepreneurs and their graduation project), thus attaining a very high level for competing in international contests of innovation using information technology and endeavour. During public presentations, the groups have to explain criteria such as “sustainability” which are very important in an education in engineering.

RESULTS OF THE IMPLEMENTATION OF THE OCDIO PROPOSAL AT THE SCHOOL OF ENGINERING (UNIVERSIDAD DE LOS ANDES) Through the aforementioned methodology for learning and developing engineering projects, it is intended that students will develop the necessary skills for eventually becoming innovators in their own organisations, as well as making those innovations sustainable over time. One of the groups which formed during this learning process was among the top four in a national entrepreneurship award (“Santander Award: Entrepreneurship, Science and Innovation 2010”), which had more than 400 contestants. Similarly, another group, whose members are now graduates from the engineering programme, formed a company and recently became one of the five winners of the Ventures 2010 national contest, which had more than 1200 participants. DataTraffic received the award for the project with the greatest potential for growth, and received $10 million COP in shares granted by the Colombian Stock Exchange. The projects summarised below were developed with the aim of providing innovative ICT solutions in the context of transportation in big cities.

Information System of Routs and Transportation (Sistema de Información de Rutas y Transporte, SIRT): The intensification of urban development in cities during the twentieth century, caused by rapid population growth and the concentration of people in urban areas in search of opportunities, made engineers, architects, politicians and economists think about what the formula could be for building viable cities and making them sustainable over time. Such sustainability would largely depend on mobility. Nowadays, this issue is a priority in Bogota (Colombia), because we are at a critical

123

Observe, Conceive, Design, Implement and Operate

point at which the decisions made today will have a major impact on the future. Bogota’s Master Plan for Mobility proposes that it is necessary to integrate different forms of public transportation, and therefore the passengers should have access to all available information regarding routes, stations and times of arrival. Currently, such information is not available for the public bus system (excluding Transmilenio), and therefore its users cannot easily find answers for questions such as which bus to take, where to take the bus and where to get off, or where to walk in order to reach their final destination. From the perspective of a city in the not too distant future, using public transportation should be an enjoyable experience. From this perspective, SIRT was born with the intention of intention of making a contribution to the city, by enabling people to better organise their time. In order to achieve this, this group is proposing a solution that informs users of the estimated time of arrival of the next bus in two ways: 1. The user tells SIRT where he/she is located and where he/she wants to go; 2. The user tells SIRT where he/she is located and which route he/she wants to take; The project is being carried out in phases. The first one was developed in the second semester of 2008. In this phase, a prototype was designed which informed the user of the estimated time of bus arrival using a Java based simulator. The information travelled across the cellular network (GSM) and text messages (SMS). The preliminary model of the prototype is presented in Figure 9.

DataTraffic This project develops innovative solutions using digital maps which generate value within the processes of its clients, through the development of solutions which are focussed on the areas of logistics, maintenance and marketing, among others, in order to increase control over the em124

ployees, supervise their functions and increase their efficiency. In its short trajectory, DataTraffic has participated actively in the development of solutions for the Urban Development Institute, the Transportation Secretary Office, and the Bogota Emergency Telephone Number. These projects are examples of the results of the sustainability of the OCDIO learning proposal for developing the innovation, company-building talents and skills of our students, and of the mentoring and advisory work carried out by teachers and businessmen who are interested in technology and encourage the building of knowledge. Both groups have been acknowledged by academic and business entities as projects with a high potential for sustainability. This sustainability has been conceived in the learning model comprised of the OCDIO cycle. There are several results which appear to show that the students’ and professors’ attitudes to innovation were strengthened through the elaboration of projects in the first semester and in the middle of the study programme. The current synergy between professors and students shows a high level of connection between the courses, which exists in order to promote an innovative attitude in engineering students. Every year, around 300 Figure 9. SIRT’s project

Observe, Conceive, Design, Implement and Operate

projects are developed, with the participation of 1,500 students and 20 professors from all of the engineering programmes. Some of these projects are reinforced later on thanks to the knowledge of basic sciences acquired later on by the students. Some of them are resumed in the middle of the study programme, where we have been able to strengthen the synergy between the professors involved. Regarding with Innovation Projects with ICT course, we have managed to develop 40 projects annually with the participation of 10 business leaders, professors and students from several study programmes, particularly students of Computing and Systems Engineering and Industrial Engineering. Without a doubt, one big achievement has been the consolidation of an educational space where students from several study programmes are in constant communication with one another in order to identify problems that can be addressed using engineering and to share multidisciplinary knowledge to facilitate the design of solutions. In the last years, 5% of these projects have transformed into final study programme projects. In addition, some groups have achieved important positions in competitions such as “Imagine

Cup 2009 - Colombia”, “TIC Americas 2010 - ECO CHALLENGE 2010”, “2010 Computer Society Student Competition” and “Calling All Innovators”. The professors have written nearly 10 articles about this subject and presented them in congresses and national and international magazines. With these results, we are starting to generate a mass of criticism that is having an impact on the Universidad de los Andes, its environment and other universities in the country. In order to evaluate the development of competences in the engineering students who participate in the Middle Study Programme Project with ICT, the people who attended the Innovation Showcase (businessmen, professors, researchers, MSc students and PhD students) evaluated different aspects of the activity. Figure 10 shows the average perception of the different evaluators of the work done by the students who had been part of the education space during the last three semesters. These results show favourable and sustained evaluations in areas such as the capacity of the students to identify problems, their innovative attitudes, and the quality of the proposed solutions among others. The results are motivating and confirm those mentioned before.

Figure 10. Results of the OCDIO cycle in the Middle Study Programme Project with ICT

125

Observe, Conceive, Design, Implement and Operate

CONCLUSION AND FUTURE WORK A diverse range of engineering education institutions across the world has developed initiatives for the education of professionals in the field of innovation, particularly for engineers. These institutions have successfully incorporated themselves into the innovation systems of developed countries and of others that are searching for economic development. In this way, they contribute to the development of favourable conditions for the development of innovative ideas that have a positive impact on society. Colombia, being a country that is seeking to move from a feudal-capitalist economy to a knowledge-based economy, is working to consolidate an innovation system with the participation of the government, companies, business people, research centres and society in general. This intended alliance requires certain characteristics and competences for the fundamental players of an innovation system: the engineers. In this way, the School of Engineering at the Universidad de los Andes seeks to educate engineers so that they may be able to face the challenges of innovation and transfer their knowledge later on to the market in the shape of products, services and business models. The purpose of the School of Engineering, as part of the innovation system in Colombia, is that its alumni may develop innovative attitudes and the capacity to work in teams through effective processes of communication, not only with engineers from several disciplines but with professionals from other areas. This school intends to achieve this objective through the undertaking of curricular activities framed in the CDIO cycle with an initial phase of observation that guarantees the conception of ideas as proposed by the CDIO framework and warrants the sustainability in the time of the innovations which are developed. In this way, the OCDIO cycle has established itself as a framework with which to educate the engineers of the future to face not only the challenges of the engineering as a profession, but of society

126

in general, where projects have an increasingly short lifecycle and where it is necessary to have a significant capacity for observation, adaptation, learning and change in order to respond to these challenges. The OCDIO proposal was set up in a framework that enables the development of sustainable innovations. This is achieved through a permanent cycle of observation and adjustment of the systems (solutions) designed to resolve problematic situations in a particular society. The additional phase of observation that has been proposed as a complementary initial stage of the CDIO framework allows the professionals facing the challenges of innovation inside organisations to obtain the relevant information for the conception, design, implementation and operation of sustainable engineering systems that take into account the relevant economic, social, technical, environmental and cultural aspects. We may be able to argue that we obtained incipient results from this education proposal, which would allow us to continue the development of this initiative in other universities, with the aim of it becoming a successful and replicable model that results in a positive impact on the performance indicators relating to the development of the economy, science, technology and innovation in Colombia. The OCDIO framework has been examined during this chapter which has focused on the education of engineers, but the researcher team believes that the proposal can be replicated in other areas such as basic sciences, social sciences, and in general in the interdisciplinary work which has become a motif in society. In this sense, the OCDIO proposal can become a point of reference for other professions. For future investigations, we intend to refine our instruments of evaluation and the ways in which the innovation projects that arise in the proposed context of engineers’ education are monitored. In order to consolidate this investigation, it is very important to observe in detail the

Observe, Conceive, Design, Implement and Operate

development of the sustainable innovative engineering projects which arise from the education of the engineers until the consolidation of their projects in organisations. Similarly, it is important to monitor the development of their innovation skills and their contribution to entrepreneurship in Colombia the contribution made to entrepreneurship in Columbia by the groups formed during this process, such as the ones presented in this chapter.

REFERENCES Accreditation Board for Engineering and Technology (ABET). (2004). Criteria for accrediting engineering programs. Retrieved from http:// www.abet.org Bankel, J., Berggren, K. F., Engström, M., Wiklund, I., Crawley, E. F., Soderholm, D., & Ostlund, S. (2005). Benchmarking engineering curricula with the CDIO syllabus. International Journal of Engineering Education, 21(1), 121–133. Carvajal, J. A., Ramírez, M. C., & Hernández, J. T. (2010). Innovation training in undergraduate computing engineering education: An evaluation model proposal. In Proceedings of the International Conference of Engineering Education in Sustainable Development (EESD’10), Gothenburg, Sweden. Carvajal, J. A., Ramírez, M. C., Torres, C. A., & Arias, L. J. (2010). Innovation, effective communication and teamwork training for build engineering solutions in sustainable development of vulnerable communities. In Proceedings of International Conference of Engineering Education in Sustainable Development (EESD’10), Gothenburg, Sweden. CDIOTM (2010). CDIO. Retrieved from http:// cdio.org

Chalmers University of Technology. (2010a). Retrieved from http://www.chalmers.se /en/sections/ collaboration Chalmers University of Technology. (2010b). Areas of advance. Retrieved from http://www. chalmers.se/ en/areas-of-advance/ Documents/ Areas%20of%20advance%20print.pdf Chalmers University of Technology. (2010c). Retrieved from http://www.chalmers.se/ en/sections/ about_chalmers Chesbrough, H. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston, MA, USA: Harvard Business School Press. Cozzens, S. E., & Kaplinsky, R. (2009). Innovation, poverty and inequality: Cause, coincidence, or co-evolution? In Lundvall, B. A., Joseph, K. J., Chaminade, C., & Vang, J. (Eds.), Handbook of innovation systems and developing countries: Building domestic capabilities in a global setting (pp. 57–82). Cheltenham, UK: Edward Elgar Publishing Limited. Crawley, E. F., & Brodeur, D. R. (2008). The education of future aeronautical engineers: Conceiving, designing, implementing and operating. Journal of Science Education and Technology, 17, 138–151. doi:10.1007/s10956-008-9088-4 Cutkosky, M., & Fukuda, S. (2004). Global PBL design course: A way to design our life and future. 2004 ASME Curriculum Innovation Award Honorable Mention. Retrieved from http://files. asme.org/ asmeorg/ Governance/Honors/4850.pdf Davenport, T. H. (1993). Process innovation: Reengineering work through Information Technology. Boston, MA, USA: Harvard Business School Press.

127

Observe, Conceive, Design, Implement and Operate

De la Hoz, J., & de Blas, A. (2009). ‘Learning by doing’ methodology applied to the practical teaching of electrical machines. International Journal of Electrical Engineering Education, 46(2), 133–149. Edmondson, A. C., & Nembhard, I. M. (2009). Product development and learning in project teams: The challenges are the benefits. Journal of Product Innovation Management, 26(2), 123–138. doi:10.1111/j.1540-5885.2009.00341.x Evans, R. S., Parks, J., & Nichols, S. (2007). The idea to Product® program: An educational model uniting emerging technologies, student leadership and societal applications. International Journal of Engineering Education, 23(1), 95–104. Froyd, J. E., & Ohland, M. W. (2005). Integrated engineering curricula. Journal of Engineering Education, 94(1), 147–164. G ómez, H. (1999). H acia dónd e v a Colombia?Bogotá, Colombia: Tercer Mundo Editores. Greis, G. P. (2009). From the ground up: The founding and early history of the Franklin W. Olin College of Engineering, a bold experiment in engineering education. Needham, USA: Olin College. Hernández, J. T., Caicedo, B., Duque, M., & Gómez, R. (2004). Engineering school renovation project. Proceedings of 4th International Workshop on Active Learning in Engineering Education, Nantes, France. Hernández, J. T., Ramírez, C., & Carvajal, A. (2010). Formación para la innovación con tics: Un proyecto conjunto Facultad de Ingeniería Empresarios. Revista Educación en Ingeniería, 9, 12–20.

128

Jaramillo, H. (2003). Políticas científicas y tecnológicas en Colombia: Evaluación de impacto durante la década de los noventa. Bogotá, Colombia: CEPAL. Jaramillo, H., Lugones, G., & Salazar, M. (2001). Normalización de indicadores de innovación tecnológica en América Latina y el Caribe: Manual de Bogotá. Bogotá, Colombia: Colciencias. Kerns, D. V. (2001). The Olin College curriculum vision: Fall 2001. Retrieved from http://www.olin. edu/ academics/ olin_history/vision.aspx Kerns, S. E., Miller, R. K., & Kerns, D. V. (2000). Designing from a blank slate: The development of the initial Olin College curriculum. In National Academy of Engineering (NAE) (Ed.), Educating the engineering of 2020: Adapting engineering education to the new century. Washington, DC, USA: The National Academies Press. KTH Royal Institute of Technology. (2009). The strategic plan 2009-2012: KTH in the service of humanity, for the society of tomorrow. Retrieved from http://www.kth.se/polopoly_fs/ 1.9709!devpl09.pdf Leta, J., & Chaimovich, H. (2002). Recognition and international collaboration: The Brazilian case. Scientometrics, 53(3), 325–335. doi:10.1023/A:1014868928349 Lloyd, J. R., Hinds, T. J., David, K., Chung, M. J., Gonzalez, M., & Timmer, D. (2004). INTEnD: A dispersed design team approach for the globalization of engineering education. 2004 ASME Curriculum Innovation Award Honorable Mention. Retrieved from http://files.asme.org/asmeorg/ Governance/Honors/4852.pdf Massachusetts Institute of Technology. (2006). Report of the task force on the undergraduate educational commons: To the president of the Massachusetts Institute of Technology. Retrieved from http://web.mit.edu/committees/ edcommons/ documents/ tf_full_report.pdf

Observe, Conceive, Design, Implement and Operate

McCowan, J. D. (2002). An integrated and comprehensive approach to engineering curricula, part two: Techniques. International Journal of Engineering Education, 18(6), 638–643. National Academy of Engineering (NAE). (2000). Educating the engineering of 2020: Adapting engineering education to the new century. Washington, DC, USA: The National Academies Press. National Research Council (NRC). (2007). Innovation policies for the 21st century: Report of a symposium. Washington, USA: The National Academy Press. Nidumolu, R., Prahalad, C. K., & Rangaswami, M. R. (2009). Why sustainability is now the key driver of innovation. Harvard Business Review, (September): 2009. Organization for Economic Co-operation and Development. (2004). Science and innovation policy: Key challenges and opportunities. Retrieved from http://www.oecd.org/ dataoecd/18/17/ 23706075. pdf Ramírez, M. C., Carvajal, J. A., & Hernández, J. T. (2010). Innovation and teamwork training in undergraduate engineering education: A case of a computing engineering course. International Journal of Engineering Education, 26(6), 1536–1549. Ramírez, M. C., & Hernández, J. T. (2008). Teamwork and innovation competences: A 1st -semester engineering students’ hands-on course. SEFI Annual Conference 2008, Aalborg, Denmark. Schumpeter, J. A. (1936). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle. Cambridge, USA: Harvard University Press.

Siller, T. J., Rosales, A., Haines, J., & Benally, A. (2009). Development of undergraduate students’ professional skills. Journal of Professional Issues in Engineering Education and Practice, 135(3), 102–108. doi:10.1061/(ASCE)10523928(2009)135:3(102) Skogstad, P. L., Currano, R. M., & Leifer, L. J. (2008). An experiment in design pedagogy transfer across cultures and disciplines. International Journal of Engineering Education, 24(2), 367–376. Steiner, M., Ramírez, C., Hernández, J. T., & Plazas, J. (2008). Aprendizaje en ingeniería basado en proyectos, algunos casos. In Duque, M. (Ed.), Ciencia e ingeniería en la formación de ingenieros para el siglo XXI: Fundamentos, estrategias y casos (pp. 129–147). Bogotá, Colombia: Asociación Colombiana de Facultades de Ingeniería-ACOFI. Thurik, A. R. (2009). Entreprenomics: Entrepreneurship, economic growth and policy. In Acs, Z. J., Audretsch, D. B., & Strom, R. (Eds.), Entrepreneurship, growth and public policy (pp. 219–249). Cambridge, UK: Cambridge University Press. Vest, C. M. (2000). Educating engineers for 2020 and beyond. In NAE (Ed.), Educating the engineering of 2020: Adapting engineering education to the new century. Washington, DC., USA: The National Academies Press. Witt, H. J., Alabart, J. R., Giralt, F., Herrero, J., Vernis, L., & Medir, M. (2006). A competencybased educational model in a chemical engineering school. International Journal of Engineering Education, 22(2), 218–235. Zoltan, A., Audretsch, D., & Strom, R. (2009). Entrepreneurship, growth and public policy. Cambridge, UK: Cambridge University Press.

129

Section 2

Organizational Networks and Innovation

131

Chapter 8

The Integration of Independent Inventors in Open Innovation Gavin Smeilus University of Wolverhampton, UK & Caparo Innovation Centre, UK Robert Harris University of Wolverhampton, UK Andrew Pollard University of Wolverhampton, UK & Caparo Innovation Centre, UK

ABSTRACT Whilst current academic literature points to the growing importance of Open Innovation as a means of companies capturing new products from sources other than internal R & D facilities; the integration of independent inventors, a source of innovative new products, within Open Innovation has proven challenging. This chapter presents a series of preliminary Critical Success Factors, driven by current academic literature, which are intended to positively contribute towards independent inventors becoming more successful suppliers of new product ideas to businesses operating an open innovation model; with the intention that adherence to such factors may have a positive influence on the effectiveness and future sustainability of Open Innovation.

INTRODUCTION The Open Innovation model, at a theoretical level, allows for independent inventors to become suppliers of new product ideas to companies. There is little evidence however, to suggest that the practical integration of independent inventors as suppliers, to businesses operating an Open Innovation mechanism, has been fruitful. Indeed, data DOI: 10.4018/978-1-61350-165-8.ch008

from an existing open innovation centre suggests that just 0.7% of new product ideas supplied by independent inventors resulted in the business launching a new product on to the market. This statistic raises concerns as to whether open innovation models operated by companies, which rely on inputs from independent inventors, are sustainable. The chapter will present a series of preliminary Critical Success Factors, driven by academic literature, intended to positively contribute towards

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Integration of Independent Inventors in Open Innovation

Figure 1. The closed innovation model (Chesbrough, 2003)

independent inventors becoming more successful suppliers of new product ideas to businesses operating an open innovation model; with the intention that adherence to such factors may have a positive influence on the future sustainability of such operations. The chapter is structured as follows; firstly a summary of the key principles behind Open Innovation is outlined. Secondly, a discussion suggests what is currently understood about independent inventors and then finally, a series of preliminary critical success factors are proposed, underpinned by current academic literature. The identification of Critical Success Factors will guide independent inventors to operate as successful suppliers of new product ideas to businesses following an Open Innovation model.

Open Innovation Principles A formal definition of Open Innovation is suggested by Chesbrough, Vanhaverbeke & West (2006, p.1) “Open Innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively.” Essentially a mechanism for organising innovation related activity within large R&D led busi-

132

nesses (Chesbrough, 2003); the Open Innovation model provides a relatively new and contrasting approach to the Closed Innovation model, which is historically prevalent amongst large innovative companies. The traditional Closed Innovation model relies heavily upon the internal capabilities of businesses to develop and commercialise a new product or service with little or no input, regarding the innovation process, coming from external sources. Within the Closed Innovation model, businesses typically generate the innovative concepts, perform R&D related activities that facilitate the metamorphosis from concept to innovative product, then complete commercialisation related activity in the form of marketing through to distribution (Chesbrough, 2003). The diagram in Figure 1 proposed by Chesbrough (2003) summarises this process very effectively: In interpreting Figure 1, the critical aspect is research investigations and development projects reside within non-permeable firm boundaries. As such, there is a heavy reliance upon the company’s internal science and technology base to originate, research and develop innovations. The figure illustrates the funnelling effect experienced as research investigations are filtered down in number as go/no-go decisions are reached, regarding in-

The Integration of Independent Inventors in Open Innovation

Figure 2. The open innovation model (Chesbrough, 2003)

dividual projects, potentially through a stage-gate process. In terms of outputs, the company is constrained to direct commercialisation of its development projects.

Open Innovation The Open Innovation model, as proposed by Chesbrough (2003) has two distinct elements: “Inbound Open Innovation” and “Outbound Open Innovation”. Inbound Open Innovation is directly related to the aspect of the model that allows the company to search for and integrate innovative concepts and products from sources outside of the company (Chesbrough, 2003). Outbound Open Innovation is concerned with using external routes to commercialisation (Chesbrough, 2003). It can be argued that a useful source of innovations for a business is through researching best practice in industries and markets outside of its own. The Open Innovation model allows inter-industry exploration and collaboration to take place. The diagram in Figure 2 proposed by Chesbrough (2003) provides an effective illustration of this opportunity.

In interpreting Figure 2, the important point is research investigations and development may originate within the company or be in-sourced through permeable firm boundaries. As such, reliance upon the company’s internal science and technology base to originate, research and develop innovations is reduced as input can be taken from external sources. In terms of outputs, the company can launch new products directly into current markets, form spin-out companies to carry the technology into a new market or license the intellectual property rights to a third party company who subsequently launches it into the market. The contention is made that innovation has, and potentially still is, undergoing a “…paradigm shift from a closed to an open model” (Chesbrough & Crowther, 2006, p.229); although some acknowledgement should be made that there is the potential for huge variation across industry sectors, since innovation is never homogenous. A number of environmental factors have contributed to this alleged paradigm shift, including: an increase in the number of and quality of external suppliers, the growth and apparent success of the venture capital sector, which has facilitated the development of new, usually relatively small businesses that

133

The Integration of Independent Inventors in Open Innovation

hold the intellectual property rights to innovative technology and the increased freedom enjoyed by knowledge workers (Christensen et al., 2005). It is also possible to suggest that factors such as: a general trend towards outsourcing, strengthening of international patent law and globalisation may be contributory. This chapter focuses on the inbound element of the Open Innovation model that facilitates the use of external parties, specifically independent inventors, as suppliers of new product ideas.

A Profile of Independent Inventors Independent inventors are characterised by two factors; firstly their inventive activity is conducted outside the confines of an established business and secondly, the independent inventor has no formal obligation to invent (Lettl et al., 2009; Whalley, 1991) From a demographic perspective independent inventors have historically tended to be male rather than female (Parker et al., 1996). This appears to reinforce Albaum’s (1975) research which, based on a sample of 103 independent inventors who had approached the Experimental Center for the Advancement of Invention and Innovation at the University of Oregon between 1974-1975, suggested that female inventors were responsible for just 10-11% of invention. A number of studies (Albaum, 1975; Parker et al., 1996; Sirilli, 1987; Hisrich, 1985; Weick and Eakin, 2005) make an attempt to identify the typical age of an independent inventor. Whilst the age categories used in some studies, Parker et al. (1996) for example, makes the result too broad to be helpful, the results of three studies suggest that independent inventors are likely to be in their late forties to early fifties. Sirilli (1987) suggests an average age of 46.5 years; Weick and Eakin (2005) conclude an average age of 50-years and Albaum (1975) 54 years of age. In terms of future demographic trends within the independent

134

inventor community, there is an expectation that the average age of independent inventors will increase as more retired people take up inventing (Richards, 2002) With regard to educational attainment, independent inventors appear to be more educated, in a formal sense at least, than the general public (Parker et al., 1996). 68% of those independent inventors studied by Parker et al., (1996) had been in receipt of college training. This view is supported by Albaum (1975) who suggests that of respondents to his study 30.1% had some Higher Education experience, 11.7% had an undergraduate degree, 18.4% undertook post-graduate training and 16.5% held a post-graduate degree. In terms of profession, independent inventors are not heavily concentrated in any particular occupational classification, however those in technical, skilled and farmer occupations were represented to a greater degree in the sample of 141 independent inventors used for the study conducted by Parker et al., (1996) than they were in the general population; as determined by the Statistical Abstract of the United States, 1990. In addition to demographic characteristics, the current body of literature on independent inventors suggest a number of other interesting characteristics. Firstly, independent inventors place a significant importance on both “…autonomy and individuality.” (Weick & Martin, 2006, p.10). Whilst the definition of independent inventors does not prescribe an autonomous approach to working, the ability to work alone when required appears to be important to this group. Secondly, independent inventors have a particular skill in the identification of problems (Weick and Martin, 2006). This suggests that independent inventors may be well equipped to operate a market pull, as opposed to technology push strategy for invention; firstly identifying problems and then developing an inventive solution. Thirdly, surprisingly few independent inventors aspire to be an entrepreneur (Parker et al.,1996).

The Integration of Independent Inventors in Open Innovation

Types of Independent Inventors

Inventive Activity

Meyer (2005) illustrates the diversity of inventors by suggesting that there may be as many as four different types. The first category identified is: “Inventor-Entrepreneurs”, which denotes an inventor that attempts to use their invention in an entrepreneurial sense by setting up a startup company as a vehicle to commercialisation. The second category: “Proprietor-inventors” are inventors that already operate a company and are seeking to exploit the invention through this company. The third category: “Licensing/transfer inventors” relates to inventors that opt to either license the intellectual property behind their invention to a third party or sell the intellectual property to a third party, in its entirety. The final category: “Academic Inventors” denotes inventions developed by academics within the HE sector (Mayer, 2005, p. 115). In reflecting upon the definition of the independent inventor provided by Whalley (1991) and its emphasis on the inventor being external to a corporate institution, it is easy to see how independent inventors could stem from both the “Inventor-entrepreneur” and “Licensing/transfer inventors” group. It is slightly more difficult, although not impossible, to imagine that inventors categorised as “Academic Inventors” or “Proprietor-Inventors” have the corporate independence necessary to be classed as independent inventors. Clearly, in the case of the “Inventor-entrepreneur” it could be that inventing is not part of the job role, but the inventor chooses to commercialise the invention via his or her existing company. Likewise in some parts of the world academics have no obligation to invent but do assume the full rights to intellectual property they develop and as such could be classified as an independent inventor.

Weick and Eakin (2005) present an insight into the activity undertaken by independent inventors. Their study, based on a sample of 351 questionnaires from full-time and part-time independent inventors, produced a number of interesting findings, firstly they noted that an average independent inventor had progressed six inventions to the stage of having a working prototype, however they acknowledged that the median and modal average was considerably lower; 2 and 1 respectively. In terms of the nature of the inventions developed, Weick and Eakin (2005) identified that the most common areas for inventions were: • • • •

Hardware/Tools (23%) Household Products (23%) Novelty Items (15%) Toys/Games and Hobbies (15%)

The nature of these innovations is consistent with the view of Astebro (1998) who made the assertion that independent inventors were most likely to develop inventions that are technically uncomplicated and demanded relatively lower financial investment. The findings of Weick and Eakin (2005); Dahlin et al. (2000) and Astebro (1998) seem to suggest that independent inventors are most likely to concentrate their efforts in industries that follow the Schumpeterian type I pattern of innovation, often referred to as “Creative Destruction” or “Widening” (Breschi et al., 2000). Conversely, the industries where fewer inventions were developed by independent inventors, include: Mineral recovery/processing, 2%; Biological/ microbiological, 2%; Marine/ocean technology, 3%; Telecommunications, 3%; (Weick & Eakin, 2005 p.10) appear to fit the characteristics of the Schumpeterian type II pattern of innovation (Breschi et al., 2000): patent applications often originate from a small number of companies that

135

The Integration of Independent Inventors in Open Innovation

already hold a significant number of patents and hold established market leading positions; the knowledge upon which innovations are developed is likely to be strongly rooted in scientific principles; investment of significant sums of money is no guarantee of developing an innovative new product, however for new ideas that are developed they are likely to be patentable and founded on knowledge developed through prior innovations (Breschi et al., 2000).

Typical Commercialisation Paths Used by Independent Inventors Weick and Eakin (2005) found that in their survey of independent inventors, 16% made no attempt to take their innovation to market, whilst Mayer (2005) found that commercial success was not the objective of all independent inventors with some inventors believing that their efforts are validated by non-commercial success such as: placing the invention in the public domain to enhance accessibility, improving public wealth or pursuing an innovation because it was interesting from a technical perspective. None the less, commercialisation remains the intention of the majority of independent inventors (Weick & Eakin, 2005). Weick and Eakin (2005) suggest that there are potentially four commercialisation paths that can be utilised by independent inventors: 1. A start-up business maybe formed specifically to act as a vehicle to carry a new innovation to market. 2. The inventor is already the proprietor of a business that will be used to carry the innovation to market. 3. The inventor chooses to license the intellectual property rights behind their innovation to a third party company, typically in return for a royalty on sales.

136

4. The inventor decides to sell the intellectual property rights behind the innovation outright to a third party organisation. In analysing the degree to which these potential routes to market are utilised by independent inventors, Weick and Eakin (2005, p.11) identified that licensing the intellectual property rights behind an innovation to a third party company was the most frequently used route to market with 44% of the 351 respondents to their study having employed this strategy. The second most popular commercialisation path was via a company inventor that distributes the innovation, but outsources the manufacturing element to a third party. This strategy was utilised by 29% of the independent inventors surveyed by Weick and Eakin (2005). Almost as frequently used was commercialisation through a company inventor that undertakes both the manufacturing and distribution of the innovation. 26% of respondents to the survey conducted by Weick and Eakin (2005) indicated that they had employed this commercialisation strategy. Of those independent inventors that responded to the survey, selling the innovation to another company in its entirety was the least utilised strategy with just 16% of respondents indicating that they had pursued this option. Whilst the licensing of the intellectual property behind an invention is the most commonly used commercialisation path by independent inventors, consideration also needs to be given as to the extent to which the various commercialisation paths yield sales. Weick and Eakin (2005) make the assertion that those independent inventors that employed a licensing strategy were more inclined to achieve a higher level of sales than inventors that engaged with one of the other commercialisation paths: commercialisation via their own company or selling the rights to the innovation to another company outright.

The Integration of Independent Inventors in Open Innovation

PROPOSED CRITICAL SUCCESS FACTORS Central to this chapter is the notion that independent inventors can enhance the prospect of achieving commercial success and become more effective suppliers of innovations to businesses, via an Open Innovation model, by paying heed to critical success factors. The 12 critical success factors proposed are driven by current academic literature and represent our view of the key factors that emerge across multiple published texts (see Table 1). We acknowledge the omission of factors relating directly to the product/innovation under development as these reside outside of the scope of this particular study.

1. Time Commitment There is a small portion of academic literature that discusses the extent to which the time commitment made by independent inventors to inventive activity impacts upon the level of commercial success achieved. Weick and Martin (2006) suggest a positive correlation between the time an independent inventor commits to inventing and the potential for commercial success. In the first instance, full-time inventors are more productive when it comes to developing prototypes when compared to their part-time equivalent. In terms of commercialisation, full-time inventors are more likely to take a product to market, achieve sales and make a profit than part-time inventors (Weick & Martin, 2006). This led Weick and Martin (2006, p.10) to conclude that the “…level of sales was a function of making a full-time commitment to inventing…” In a similar vein, Whalley (1991) notes that family commitments can impact upon the effectiveness of independent inventors. For those independent inventors that do have a family and invent in their spare time, which is often the case

Table 1. Proposed critical success factors 1

Time commitment

2

Use of intellectual property protection

3

Advice, support and guidance received

4

Timing of approach

5

Access to resources

6

Access to formal and informal social support networks

7

Ability to adopt a credible business persona

8

Willingness to share information

9

Ability to identify and gain access to potential commercial partners

10

Ability to select an appropriate commercialisation path

11

Alignment of inventor and corporate objectives

12

Experience of the inventor

(Mayer, 2005), family issues may create an obstacle to committing time to an innovation. Moving away from literature relating directly to independent inventors, Poolton and Barclay (1998) identify the need for long-term commitment to innovation projects as a critical factor in achieving new product introduction success at company level. In addition, Cooper and Kleinschmidt (2007) reinforce the importance of time commitment by suggest that many new product introduction attempts, at a business level, are hampered by a lack of time available to perform key tasks properly. Thus, the availability of time is viewed as potentially critical to successful new product introduction.

2. Use of Intellectual Property Protection In addition to the time committed to invention, Weick and Martin (2006) note the importance of independent inventors being willing to invest in patents. Indeed Dahlin, Taylor & Finchman (2000); Khan and Sokoloff (1992) and Dagenais et al. (1991) are in agreement that the commercial success achieved by independent inventors

137

The Integration of Independent Inventors in Open Innovation

is closely coupled with their use of the patenting system. Whalley (1991, p.223) claims that patent protection “…turns the use value of the idea into something that has commercial possibility.” Reflecting on this statement there certainly appears some logic. For example, if an independent inventor sought to commercialise their innovation via a start-up company then a patent adds to the commercial legitimacy of the business case by providing a legally founded mechanism for restricting competing products that infringe upon the technology outlined in the patent. This is an important issue when seeking investment in the new business. Perhaps more importantly, in particular for this research inquiry is the pivotal role patent protection plays in new product introduction via a licensing deal. As Whalley (1991) suggests, the innovation developed by the inventor may have intrinsic value in so much that it resolves an acknowledged problem, but the innovation only has commercial value, in this instance, if it is patented. This is true in so much that a licensing deal works on the basis that the inventor agrees to allow a third party manufacturer to utilise their intellectual property (patent), for a given period of time, within a specified territory; in return for a predetermined royalty on sales. Without a patent, the inventor has little to exchange in return for a royalty, so the basis of the exchange breaks down and a commercial deal is unlikely to be brokered. Bakos and Nowotarski (2003) add to the debate by suggesting that the existence of a patent for an innovation is not, in itself, enough to ensure a licensing deal because the patent still needs to be viewed as being credible in the eyes of the potential licensee. In discussing credibility, Bakos and Nowotarski (2003) suggest that a credible patent application is one which under review of a professional Patent Agent would be expected to be granted with the majority of its original claims still in place. Whilst we believe that this is a reasonable statement to an extent, in that it attempts to mitigate against patents that become

138

very narrow as claims get removed and amalgamated, it does suppose that the originally drafted claims were of a reasonable scope to begin with.

3. Advice, Support and Guidance Received Meyer (2005) suggests that the social and business skills possessed by an independent inventor have a considerable bearing on whether that individual is able to successfully commercialise their innovation. Unfortunately, Mayer (2005) also suggests that commercialisation of innovations is hampered by the skills set that many independent inventors actually possess. As a result of this apparent deficiency in skills; the advice, support and guidance received by independent inventors from third party sources becomes critically important to the prospect of commercialisation. For example, Parker et al. (1996) make an assertion that the progress made by independent inventors towards commercialisation of their innovation is positively influenced by the business, including marketing, advice and mentoring that they receive. Mayer (2005) suggests that independent inventors in receipt of intellectual property guidance and advice, early in the development process, are more able to select the most commercially relevant invention from their invention portfolio and as a result pursue the development and commercialisation of fewer ideas that are flawed, from an intellectual property perspective, from the outset. Weick and Martin (2006) suggest that independent inventors should engage with the growing support structure and resource pool accessible via the Internet, as a means of ensuring they pay closer attention to financial and market factors during the development and commercialisation phase. In identifying the types of advice, support and guidance required to negotiate the new product introduction process, Cooper and Kleinschmidt (2007) suggest that, at company level at least, market and technical assessments and clear

The Integration of Independent Inventors in Open Innovation

product definition are essential to success. This is reinforced by Lynn et al., (1999) who emphasise the need for a clear appreciation of the market and it dynamic characteristics, if successful negotiation of the new product introduction process is to be achieved.

4. Timing of Approach In addition to the time commitment allocated to the invention process, Mayer (2005) suggests that the innovations developed by independent inventors are susceptible to the issue of timing. Innovations that are ahead of their time are likely to suffer at the hands of conservative or unconvinced investors or potential licensees, whilst those innovations that are too late are unlikely to appeal to potential investors or licensees. Indeed, Sun and Wing (2005) in their review of critical success factors for new product development in the Hong Kong toy industry identified the need to make innovations accessible to customers at the right time. With regard to timing, independent inventors would appear to have a more difficult job satisfying the criteria than commercial inventors. Whilst independent inventors may have difficulty in knowing what the current state of technological development is in an industry and the types of new innovations that are being sought, particularly given that they are by definition inventing outside of a corporate structure; commercial inventors may have cues as to what type of innovations are required and will almost certainly be aware of the current state of technological development in their industry much of which development is hidden.

5. Access to Resources The capacity for an independent inventor to commercialise their innovation appears to be influenced by the resources they have available to them. From a financial perspective, Whalley (1991) claims that the majority of independent

inventors are reliant upon their own personal funds or the financial support of their family to finance the development and commercialisation of their innovations. Access to inventive space, raw materials and appropriate tools is also identified by Whalley (1991) as an important resource requirement. This would appear to be particularly appropriate when considering physical, mechanical innovations, where the absence of these resources and manufacturing equipment may prevent the invention being developed (Whalley, 1991). Indeed, evidence at company level suggests that a lack of resources is the scourge of new product introduction projects and often results in inadequately executed commercialisation attempts (Cooper and Kleinschmidt, 2007)

6. Access to Formal and Informal Social Support Networks If innovation networks theory is applied at independent inventor level then those individuals with enhanced network linkages would appear to benefit, both prior to invention conceptualisation and during the new product introduction process. In the first instance, the act of innovation arguably occurs as the result of knowledge being transferred or shared through networks, independent of spatial definitions, whereby said knowledge is either utilised in its original form or reapplied in a new innovative way (Coe & Bunnell, 2003). As such, independent inventors that interact with corporations: businesses, universities, government and research institutes; those that can strike up social relationships with knowledgeable individuals; and those that access and utilise knowledge from published sources, such as patent databases, newspapers, conference papers and academic journals should be better placed to generate innovative ideas in the first place (Coe & Bunnell, 2003 p.452). Post innovation origination, Whalley (1991) proposes that the effectiveness of independent

139

The Integration of Independent Inventors in Open Innovation

inventors is influenced by the degree of social support they receive; partially because of their need for feedback on their inventions and social confirmation that what they are doing is useful. In this respect, the role of family and friends in providing a social support network can be viewed as essential (Whalley, 1991). Interestingly, Whalley (1991) suggests that, family and friends aside, individual inventors lack the mutual support groups that can be found in other creative disciplines. Whilst this was perhaps a valid assertion to make in 1991, a simple Google Search of the term “UK Inventor Clubs” yields a list of organisations in East London, Wessex, Birmingham, London, Malvern, Sheffield, the Black Country, Kingston and Liverpool, which certainly points to this issue being addressed, although not resolved. Indeed, Von Hippel (2005) argues that the trend towards making innovation more democratic, through mechanisms such as open innovation, has resulted in a rapid increase in the number of support communities, which should positively influence the ability of independent inventors to develop commercially successful innovations. Interestingly, the work of Lettl et al.,(2009) points to the fact that independent inventors who actively engage with social support networks and communities are more able to access resources that are usually reserved for corporate inventors. Indeed, the Black Country Inventors Club in the UK is a good example of this, as it allows a group of independent inventors to operate as a collective with enough critical mass to enlist the assistance of an Intellectual Property Rights specialist at favourable rates.

7. Ability to Adopt a Credible Business Persona A potentially significant obstacle for independent inventors to overcome, when attempting to commercialise their innovation, is the negative perception held by industry and potential investors. Parker et al. (1996 p.7) makes the following

140

statement: “The independent inventor has often been portrayed as something of a mad scientisttype individual or an uneducated dreamer in search of the holy-grail. The result of this perception is that the independent inventor no longer is viewed as a serious source of product innovation.” Whalley (1991 p.225) suggests that manufacturers, potential licensees in many cases, are all too willing to believe the negative image of inventors as “…odd, even crazy…” A view which is corroborated when inventors not only lack business expertise, but perhaps more importantly, do not adopt accepted business conventions and “…do not want to play by the rules that manufacturers think are appropriate.” (Whalley, 1991, p.225). Whalley (1991) suggests that this may not be intentionally contrary behaviour on the part of independent inventors, simply the result of many years of segregation from the commercial world of inventing and the socially accepted norms that are associated with it. Although speculative at this point, it would appear that the more capable an independent inventor is at adopting appropriate business etiquette, speaking the language of business, using the correct terminology and following modern business practice, the greater the potential for commercial success. If we are to make the assertion that independent inventors should behave in a more business like fashion when presenting their innovation to potential licensees then extant best practice literature surrounding successful new product introduction becomes pertinent. At a basic level there is a need for good communication skills, indeed Lester (1998) highlights the ability to effectively communicate information, regarding the product and associated opportunity, to management is a critical element of successful new product introduction. In addition, Cooper and Kleinschmidt (2007), in their paper on critical success factors for businesses introducing new products, identify a number of constructs under their “A high-quality new product process” Critical Success Factor that are potentially valuable

The Integration of Independent Inventors in Open Innovation

to this research inquiry. Firstly they suggest that assessments are made of the technical and market potential for the proposed innovation, prior to its development. These assessments may move from preliminary overviews of potential into increasingly detailed insights. Key components in these assessments, include: market research with potential end-users focussing on the identification of customer needs, desires and requirement; assessment of technical requirements: possible manufacturing methods, technical viability of proposition, costs associated with production, timescale and resource requirements; analysis of the financial case at different levels of sensitivity (Cooper & Kleinschmidt, 2007) In addition to providing documented evidence of market and technical assessments of the innovation, Cooper and Kleinschmidt (2007 p. 7) also identify the importance of being able to precisely define key aspects of the business case, namely: “…the product – its target market; the concept, benefits and positioning; and its requirements, features and specs…” Although purely conjecture at this point, it would appear that independent inventors who have a working knowledge of the early stages of the new product introduction processes that businesses are accustomed to will be able to talk about their project and the introduction process, with potential licensees, in terms they are familiar with. As such they may be viewed as more credible.

8. Willingness to Share Information The ability to share information concerning an innovation may aid the early stages of the development. At a more advanced stage, the sharing of information is critical to obtaining investment in the innovation, whether to enable a new business to be formed or at the point of negotiating a licensing agreement or outright sale of the intellectual property rights. The problem is that independent inventors often feel unable to share information concerning

their innovation. Whalley (1991) suggests that the legislation governing intellectual property protection acts as a constraint, hampering the independent inventor’s ability to disclose details of their innovation. This is presumably a reference to the notion that in order to obtain patent protection the intellectual property behind an idea cannot be in the public domain. In addition to the restricting force of intellectual property legislation (Whalley, 1991), the degree of trust between the independent inventor and the third party is seemingly central to the prospect of invention commercialisation. Mayer (2005 p.115) notes that: “Inventors have developed a mistrust towards manufacturers and innovation professionals partly because of bad experiences with the world of business professionals and also fraudulent support services.”

9. Ability to Identify and Gain Access to Potential Commercial Partners Appropriate selection of commercial partners is by no means an easy task. Firstly, businesses often do not welcome new ideas, regardless of their origin (Whalley, 1991) and those that are open to external ideas will not deal with independent inventors because of the associated costs of administering the enquiries when compared to the probability of successfully launching and generating profit from an innovation brought into the company via this source (Whalley, 1991). Those independent inventors that are able to identify a commercial partner that has access to manufacturing methods appropriate to the requirements of the innovation; is able to provide a route to market that allows penetration of domestic and international markets (Mayer, 2005) and then is able to identify and gain access to key decision makers in that organisation are likely to fare well commercially. Interestingly, Kotabe et al., (2007) note companies are increasingly moving away from centralised research and development decisions

141

The Integration of Independent Inventors in Open Innovation

towards a decentralised approach. From a UK independent inventor perspective this may be critical, since it would theoretically provide access to a larger base of potential licensees.

10. Ability to Select an Appropriate Commercialisation Path Mayer (2005, p.114) points to the fact that: “Those inventors, who choose to commercialise their inventions on their own, in the form of a start-up company, face the full complexity of the business world. Starting up a business is a challenging endeavour requiring different skills at different times.” This appears to imply that the independent inventor needs to carefully align his or her skills set and willingness to commit time against the requirements for each of the potential commercialisation paths open to them. Those that do this most successfully would appear to stand a better chance of realising commercial success.

11. Alignment of Inventor and Corporate Objectives The degree to which the independent inventor and commercial partner have aligned commercial objectives is a potentially important success factor. Whalley (1991) notes that independent inventors and businesses often have divergent opinions concerning commercialisation and that, for example, whilst a business may be heavily biased towards income generation, income generation may not be central to the wishes of the independent inventor. With regard to expectations over the financial rewards for the innovative endeavour, independent inventors need to have some appreciation that the spectre of failure looms large over potential licensees and as such independent inventors should be modest in their expectations over the licence fee, especially since a modest fee reduces the probability that the potential licensee will seek to challenge or infringe upon the patent (Bakos and Nowotarski, 2003).

142

12. Experience of the Inventor The extant literature points to the fact that independent inventors with greater experience of the development and commercialisation of innovations are more likely to have commercial success than inexperienced inventors. Whilst Eakin and Martin (2006) suggest that experienced inventors are more likely to have access to the informal networks that enable commercialisation and experience of attempting to take a previous product to market is beneficial in later attempts, Von Hippel (1988) and Henderson and Clark (1990) make the assertion that inventors with direct experience of the industry in which they are inventing in are more likely to achieve commercialisation. The effect of previous experience is also evident when consideration is given to new product introduction at company level. Lynn et al., (1999), for example, identify the need for relevant experience and the ability to learn lessons from previous projects as fundamental to new product introduction success. In the US Insurance industry, 75% of new patents emanate from independent inventors with the vast proportion specialists in that field: Actuaries, underwriters, and programmers (Bakos and Nowotarski, 2003). Indeed, Lettl et al. (2009) in their study of 1681, medical equipment, patent families from the Derwent World Patent Index filed between 1980 and 2005; found evidence that focussing inventive efforts in an industry where the independent inventor has some specialist knowledge, rather than inventing for disparate industries, is very beneficial to the prospect of an impactful technology being developed. Whilst not all impactful technologies go on to become a commercial success there is certainly grounds to argue that commercial success appears more probable in this instance.

The Integration of Independent Inventors in Open Innovation

CONCLUSION This chapter proposes 12 preliminary critical success factors that we anticipate will enhance the prospect of independent inventors achieving commercial success and becoming more effective suppliers of new products to businesses, via an Open Innovation model. We have amalgamated the current body of academic literature surrounding independent inventors and new product introduction in order to identify these factors. At this stage, no critical success factors are eliminated. The following chapter will take the preliminary critical success factors proposed in this chapter and utilise them as priori constructs (Eisenhardt, 1989) as evidence is sought through case study for their presence or non-presence in a practical context.

REFERENCES Albaum, G. (1975). The independent inventor. Eugene, Oregon, USA. Astebro (1998). Basic statistics on the success rate and profits for independent inventors. Entrepreneurship Theory and Practice, 23(1), 41-48. Bakos, T., & Nowotarski, M. (2003). Independent inventors get lion’s share of insurance industry patents. National Underwriter, 107(42), 1–3. Breschi, S., Malerba, F., & Orsenigo, L. (2000). Technological regimes and Schumpeterian patterns of innovation. The Economic Journal, 110(463), 388–410. doi:10.1111/1468-0297.00530 Chesbrough, H. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Publishing. Chesbrough, H. (2006). Open business models: How to thrive in the new innovation landscape. Boston, MA: Harvard Business School Press.

Chesbrough, H., & Crowther, A. K. (2006). Beyond high tech: Early adopters of open innovation in other industries. R & D Management, 36(3), 229–236. doi:10.1111/j.1467-9310.2006.00428.x Chesbrough, H., Vanhaverbeke, W., & West, J. (2006). Open innovation: Researching a new paradigm. Oxford, UK: Oxford University Press. Christensen, C. M. (1997). The inventors dilemma. Boston, MA: Harvard Business School Press. Christensen, J. F., Olesen, M. H., & Kjaer, J. S. (2005). The industrial dynamics of open innovation - Evidence from the transformation of consumer electronics. Research Policy, 34(1), 1533–1549. doi:10.1016/j.respol.2005.07.002 Coe, N. M., & Bunnell, T. G. (2003). “Spatializing” knowledge communities: Towards a conceptualisation of transnational innovation networks. Global Networks, 3(4), 437–456. doi:10.1111/1471-0374.00071 Cooper, R. G., & Kleinschmidt, E. J. (2007). Winning businesses in new product development: The critical success factors. Research. Technology management (pp.1-19). Dagenais, D. L., Seguin-Delude, L., & Desranleau, C. (1991). Analysis of individual Canadian inventor behaviour. Technovation, 11(6), 357–372. Dahlin, K., Taylor, M., & Fichman, M. (2000). Differences in inventive content between independent inventors and corporate inventors. Rotman School of Management. University of Toronto. Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. Henderson, R., & Clark, K. (1990). Architectural innovation: The re-configuration of existing product technologies and the failure of existing firms. Administrative Science Quarterly, 35(1), 9–30. doi:10.2307/2393549

143

The Integration of Independent Inventors in Open Innovation

Hisrich (1985). The inventor: A potential source for new products. The Mid Atlantic Journal of Business, 24(1), 67-80.

Parker, R. S., Udell, G. G., & Blades, L. (1996). The new independent inventor: Implications for corporate policy. Review of Business, 17(3), 7–11.

Khan, B. Z., & Sokoloff, K. L. (1992). Schemes of practical utility: Entrepreneurship and innovation among the great inventors in the United States, 1790 - 1895. The Journal of Economic History, 53(1), 289–307.

Pellet, J. (2002). Inventors for hire (p. 9). Chief Executive.

Kotabe, M., Martin, X., & Domoto, H. (2003). Gaining from vertical partnerships: Knowledge transfer, relationship duration, and supplier performance improvement in the U. S. and Japanese automotive industries. Strategic Management Journal, 24(4), 293–315. doi:10.1002/smj.297 Lester, D. H. (1998). Critical success factors for new product development. Research Technology Management, 41(1), 36–43. Lettl, C., Rost, K., & Von Wartberg, I. (2009). Why are some independent inventors ‘heroes’ and others ‘hobbyists’? The moderating role of technological diversity and specialization. Research Policy, 38(2), 243–254. doi:10.1016/j. respol.2008.12.004 Lynn, G. S., Abel, K. D., Valentine, W. S., & Wright, R. C. (1999). Key factors in increasing speed to market and improving new product success rates. Industrial Marketing Management, 28(1), 320–329. Mayer, M. (2005). Independent inventors and public support measures: Insights from 33 case studies in Finland. World Patent Information, 27(1), 113–123. Munsch, K. (2004). Outsourcing design and innovation. Research Technology Management, 53(1), 27–30. Neff, J. (2004)... Advertising Age, (n.d.) 3–4.

144

Poolton, J., & Barclay, I. (1998). New product development from past research to future application. Industrial Marketing Management, 27(1), 197–212. doi:10.1016/S0019-8501(97)00047-3 Quinn, J. B. (2000). Outsourcing innovation: The new engine of growth. Sloan Management Review, 41(4), 13–28. Richards, B. (2002). Light bulb moments: More inventors are finding their creative juices begin flowing later in life. Wall Street Journal, 30th September. Sirilli, G. (1987). Patents and Inventors: An empirical study. Research Policy, 16(1), 157–169. doi:10.1016/0048-7333(87)90029-1 Sun, H., & Wing, W. C. (2005). Critical success factors for new product development in the Hong Kong toy industry. Technovation, 25(1), 293–303. Von Hippel, E. (1988). The sources of invention. Oxford, UK: Oxford University Press. Weick, C. W., & Eakin, C. F. (2005). Independent inventors and innovation:An empirical study. International Journal of Entrepreneurship and Innovation, 6(1), 5–15. doi:10.5367/0000000053026400 Weick, C. W., & Martin, J. D. (2006). Full-time and part-time independent inventors: Rising with the creative class. Entrepreneurship and Innovation, 7(1), 5–12. doi:10.5367/000000006775870460 Whalley, P. (1991). The social practice of independent inventing. Science, Technology & Human Values, 16(2), 232–256. doi:10.1177/016224399101600205

The Integration of Independent Inventors in Open Innovation

KEY TERMS AND DEFINITIONS Independent Inventors: Independent inventors are characterised by two factors; firstly their inventive activity is conducted outside the confines of an established business and secondly, the independent inventor has no formal obligation to invent (Lettl et al., 2009).

Open Innovation: “Open Innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively” (Chesbrough, Vanhaverbeke & West, 2006: p.1)

145

146

Chapter 9

An Examination of Independent Inventor Integration in Open Innovation Gavin Smeilus University of Wolverhampton & Caparo Innovation Centre, UK Robert Harris University of Wolverhampton, UK Andrew Pollard University of Wolverhampton & Caparo Innovation Centre, UK

ABSTRACT Open Innovation allows independent inventors to become suppliers of new product ideas to businesses. Unfortunately, only a small percentage of independent inventor approaches, to companies operating Open Innovation mechanisms, result in a commercialised product. Preliminary Critical Success Factors proposed in the previous chapter seek to improve the ability of independent inventors to operate as effective suppliers of new product ideas to businesses through Open Innovation. This chapter will take the preliminary critical success factors proposed in the previous chapter and utilise them as priori constructs (Eisenhardt, 1989) as evidence is sought through case study for their presence or non-presence in a practical context. A case study on the Caparo RightFuel, an automotive device originating from an independent inventor and commercialised through an Open Innovation model, forms the basis of this chapter.

INTRODUCTION Open Innovation provides a mechanism for independent inventors to become suppliers of new product ideas to businesses. Unfortunately, only a small percentage of independent inventor approaches to Open Innovation schemes result in a DOI: 10.4018/978-1-61350-165-8.ch009

commercialised product. The figure for the Caparo Innovation Centre open innovation programme, at the time of writing, stands at 0.7%. Preliminary Critical Success Factors proposed in the previous chapter seek to improve the ability of independent inventors to operate as effective suppliers of new product ideas to businesses through Open Innovation.

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

An Examination of Independent Inventor Integration in Open Innovation

This chapter reinforces the previous chapter by focusing on a case study - The Caparo RightFuel, an automotive device originating from an independent inventor and commercialised through Open Innovation. The case study examines the presence or non-presence of the proposed critical success factors in an actual open innovation context.

BACKGROUND Caparo is a multinational manufacturer of steel, automotive and general engineering products. With its headquarters in London, England Caparo was founded in 1968 by the industrialist the Lord Paul of Marylebone. In 2002, in response to increased competitive pressure from low-cost Far-East manufacturers, Caparo took a strategic decision to supplement its steel processing and manufacturing activity with product ownership. In particular, the organisation were keen to introduce a portfolio of technically innovative new products that benefited from patent protection, as a means of generating alternative higher-margin income streams. Of particular interest to Caparo were mechanically engineered products that have a good synergy with manufacturing processes conducted within the organisation or the markets they currently address: • • • • • • • • • • • • •

Aerospace Agriculture Automotive Commercial Vehicles Construction Defence Furniture Industry Leisure Marine Oil and Gas Power Generation Railways

The physical manifestation of the strategic move towards product ownership was the formation of the Caparo Innovation Centre (CIC), a collaboration between Caparo and the University of Wolverhampton, which was launched in 2003. The CIC’s remit was, and continues to be, the identification and sourcing of innovative new products, typically of a mechanical or engineered nature, that display commercial potential, either through exploitation by Caparo directly or as a revenue stream from a license with an alternative commercial enterprise. The CIC source innovative ideas exclusively from independent inventors and have, at the time of writing, received 805 approaches since inception. By supplementing traditional sources of innovative new products, through internal R&D teams, with an external source of innovation, Caparo have implemented an Open Innovation strategy skewed towards inbound open innovation (Chesbrough & Crowther, 2006, p. 229).

METHODOLOGY One of the innovations successfully commercialised via the Open Innovation model employed by the Caparo Innovation Centre is the Caparo RightFuel, which will form the basis of this case study. This chapter utilises the preliminary critical success factors proposed in the previous chapter, as priori constructs (Eisenhardt, 1989); as evidence is sought through case study for their presence or non-presence in a practical context (see Table 1). The Caparo RightFuel, an automotive device originating from an independent inventor, Martin White, and commercialised through an Open Innovation model, is used as a case study to contextualise twelve critical success factors (identified through current academic literature), in a “reallife” Open Innovation setting. A case study approach was selected for this exploratory research because it is an effective method of developing

147

An Examination of Independent Inventor Integration in Open Innovation

Table 1. Critical Success Factors enabling independent inventors to becoming more successful suppliers of new product ideas to businesses operating an open innovation model 1

Time commitment

2

Use of intellectual property protection

3

Advice, support and guidance received

4

Timing of approach

5

Access to resources

6

Access to formal and informal social support networks

7

Ability to adopt a credible business persona

8

Willingness to share information

9

Ability to identify and gain access to potential commercial partners

10

Ability to select an appropriate commercialisation path

11

Alignment of inventor and corporate objectives

12

Experience of the inventor

new theoretical notions that ultimately provide direction to future research inquiries (Dyer & Wilkins, 1991) The Caparo RightFuel case is one of four planned cases, selected through a theoretical sampling method (Glaser & Strauss, 1967) that emphasises the examination of ‘polar types’ (Eisenhardt, 1989 p.537). This particular case was hand-picked because it provides a good example of how an independent inventor can achieve commercial success through the licensing of their intellectual property rights to a company, via an open innovation model. Given the reliance on a single case study, the question of whether it is appropriate to make generalisations is pertinent. Reference is, therefore, made to the work of Flyvbjerg (2006) who lends support to the notion that generalisations are permissible from even a single case study. Indeed, Yin (1994) argues that the number of case studies completed is not in itself important, since the qualitative paradigm does not subscribe to the link between sample sizes and generalisability.

148

Case Studies allow for a variety of data collection methods, including secondary data from archival sources and data emanating from primary data collection methods, such as: questionnaires, observations and interviews (Eisenhardt, 1989). For this particular research inquiry a series of three in-depth interviews with four key participants in the new product introduction process were undertaken. The interviewees1 were selected to provide a multi-perspective view of the integration of independent inventors in open innovation. This primary data was supplemented with secondary data in the form of the written documentation provided by Martin White to the Caparo Innovation Centre at their initial meeting. This data included: the initial PowerPoint presentation of the opportunity associated with the innovation and a formal Business Plan detailing the technical and commercial case for the innovation. Secondary data on diesel car registrations in the UK obtained from The Society of Motor Manufacturers and Traders Ltd and details of the inventor’s intellectual property position at the point of approaching the Caparo Innovation Centre, accessed via the UK Intellectual Property Office website and original patent documentation, were also considered. The Proquest database, which enables quantification of the number of times a particular search term is mentioned in Newspapers, was also used as a guide to the amount of coverage the act of “Misfuelling” received in UK Newspapers.

Semi-Structured, In-Depth Interviews The interviews conducted as part of the case study approach to this research inquiry were semi-structured and based on a series of interview prompts. Each interview lasted on average 61 minutes. Each respondent was given the opportunity to review and comment upon the transcribed interviews prior to their utilisation.

An Examination of Independent Inventor Integration in Open Innovation

CASE STUDY BACKGROUND: THE CAPARO RIGHTFUEL The Problem In relation to this chapter, the term misfuelling relates specifically to incidents of drivers incorrectly putting petrol into diesel powered cars. The effects of such action can be both far reaching and expensive. In most modern diesel engines the oil content within the diesel is essential to lubricate the engine; in the event of petrol being added and the engine being started, or primed, the potential for serious engine damage is considerable due to the lack of lubrication. In addition, the seals within a diesel engine are adversely affected by petrol, which causes them to soften, contributing further engine damage. The cost of rectifying this mistake can vary from less than one hundred pounds to have the fuel tank drained, up to tens of thousands of pounds for replacement parts for a sophisticated engine. Misfuelling a petrol car with diesel is very difficult because a diesel nozzle on a garage forecourt is too large to fit into the filling aperture on a petrol car; however the smaller petrol nozzle can easily be inserted into the filling aperture on a diesel car. Since the process of fuelling a vehicle usually involves little conscious thought and combined petrol//diesel pumps are commonplace the high incidence of misfuelling is understandable.

The Market According to the AA Motoring Trust, misfuelling diesel vehicles occurs in the UK approximately 120,000 times a year2 with the average repair costs standing at £70003. Fleet and Lease Vehicle operators are the most heavily affected by misfuelling incidents with data from Lloyds TSB Autolease indicating costs of £250,000 as a result of 750 misfuelling incidents in first 8-months of 20064

With sales of new diesel cars increasing yearon-year, both within the UK and parts of Western Europe, there is acknowledgment that misfuelling is becoming an increasingly common problem5 At the time the Caparo RightFuel device was initially presented to the Caparo Innovation Centre, Misfuelling Prevention Devices were being introduced as Original Equipment on the Ford Mondeo; however there was no evidence of competing retro-fit devices. This situation changed during the development programme when the inventor and licensee became aware of two competing development projects: SoloDiesel and the Fuel Angel.

The Product The Caparo RightFuel is a retro-fit device, which prevents motorists putting petrol in diesel powered cars. The device replaces the filler cap on the vehicles and is designed so that when a diesel fuel filler nozzle is inserted, a physical barrier incorporated within the device swings out of the way allowing fuel to be added to the vehicle. The device can distinguish between petrol and diesel fuelling nozzles and will not open when someone attempts to insert the smaller diameter petrol nozzle, therefore preventing the wrong fuel being added to the vehicle (see Figures 1 and 2).

The Inventor The Caparo RightFuel device was invented by Martin White. Martin is a retired Royal Navy Commander with a career that spanned 37-years. He lives in Somerset, England with his wife Teresa. Upon joining the Royal Navy in 1967, Martin was employed as an Airframes and Engines Artificer where his duties included the maintenance of Phantom, Vixen and Hunter Jets and Wasp and Sea King Helicopters. It was in this role that Martin developed his mechanical engineering

149

An Examination of Independent Inventor Integration in Open Innovation

Figure 1. The Caparo RightFuel Device (1)

Figure 2. The Caparo RightFuel Device (2)

Command Structure. His duties included creating the vision, concepts and detailed requirements for the future of intelligence within NATO, providing military advice to NATO HQ (Brussels) and the nations and the production of directives and plans for current military operations. In terms of formal education Martin has an ONC in Aeronautical Engineering from Dundrum Technical College, Dublin, Republic of Ireland. Martin makes use of the additional spare time he has in retirement by undertaking building design and construction tasks and developing innovations and fabrications in metal, wood and Glass Reinforced Plastic. Martin is a member of the South West Inventors Club, UK.

skills that he later applied to the Caparo RightFuel innovation. By 1975, Martin had been appointed into his first Air Traffic Control position and by 1998 he had risen up the ranks to Senior Royal Navy staff officer for Aviation Operations Support and Head of the Royal Navy Air Traffic Control Branch. In 2001, Martin served within Strategic HQ Allied Powers Europe (SHAPE) in Mons, Belgium where he was responsible for transformation of intelligence organisation within the new NATO

Findings

150

Time Commitment The Caparo RightFuel case provides support for the notion that time commitment plays an important part in the capacity of independent inventors to act as effective suppliers of innovations to businesses through Open Innovation. The concept of an independent inventor operating as a supplier is reliant upon the inventor having something to

An Examination of Independent Inventor Integration in Open Innovation

supply. Without the time and importantly dedication to inventing this particular inventor would not have had a product with which to approach Caparo. “I had plenty of time having recently retired and I had always had an interest in innovation, I had several ideas in the past that I never had time to work on, but here was an ideal problem that needed a solution and because I thought the solution lay within my sphere of experience, I decided to dedicate quite a bit of time to it.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. “When I decided to run with this project, I did become quite single minded about dedicating a lot of time to it and there was one particular winter where I was quite happy to spend 10 hours at a stretch in a cold workshop cutting metal when I got to that phase, so, the time is very important and to be focussed on a project I think is quite important.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. In addition to both having free-time and the dedication to spend that time on innovation, the inventor reveals that devoting time to selecting a single innovation to pursue and then focussing fully on that innovation is more advantageous, in his eyes, than pursuing multiple innovations with less focus. “…an individual can’t have lots of great ideas that they’ve really worked through and can offer them as being of significant potential; you need a huge amount of research and time dedicated to this sort of endeavour to decide that the one project is worth proceeding with, so available time and dedication are quite important.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January.

Use of Intellectual Property Protection The inventor of the Caparo RightFuel demonstrated a willingness to invest in intellectual property protection, in the form of a Patent, prior to engaging with the Open Innovation programme operated by Caparo. A UK patent application, GB0524168.2, was filed by the inventor on the 26th November 2005 carrying the title of: “Diesel Vehicle Misfuelling Preventer”, whilst the initial approach to the Caparo Innovation Centre was made on the 29th August 2006, just over 9-months later. The inventor’s views on patent utilisation are particularly interesting. Whilst conventional wisdom may suggest that independent inventors are best served by having their patent application drafted by a professional Patent Agent, this course of action was not pursued by the inventor. Instead he chose to draft the patent application to the UK Intellectual Property Office himself, without professional assistance. “First of all I could easily decipher that this sort of product needed to be protected by patenting rather than any other form of protection and having spent a lot of time researching alternative prior art out there it seemed to me that it wasn’t that hugely difficult to put together some sort of a patent.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. Under questioning as to why he chose to file for patent without Patent Agent involvement the inventor revealed that five factors were influential. Firstly, he was confident in his ability to draft an application that covered the critical technical aspects of the innovation. Secondly, the financial cost of filing a patent application, via a patent agent, is notably more expensive than the inventor drafting a submission himself, so this approach minimised cost. Thirdly, the inventor expressed a view that having filed for a patent he felt more able to disclose details of the product to third parties enabling progress towards commercialisation.

151

An Examination of Independent Inventor Integration in Open Innovation

“There was no point in having a prototype and exposing it to other people unless I could also say that I had some form of protection in place…” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. Fourthly, the existence of a patent application was seen as adding credibility to the business case around the innovation, making it more appealing to potential investors. Finally, filing of a UK Patent acted as a holding mechanism, enabling the inventor to place a stake in the ground and secure a priority date at an early stage in the development process; before another party lay claim to a similar innovation. This was particularly important given that diesel misfuelling was becoming a nationally recognised issue, illustrated by the Telegraph newspaper article entitled “A Costly Mistake” published on the 27th August 2005, just 2-months before the inventor filed his UK patent application.

Advice, Support and Guidance Received The inventor had benefitted from particularly wide-ranging experience and was equipped to develop a credible technical and commercial case for the innovation in his own right. This fact is pertinent in so much as the inventor rarely sought advice, support or guidance from third party organisations. “I would rather spend a lot of time acquiring the machinery so that I could do it with my own hands rather than entrusting anything to a third party.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. Indeed the inventor only sought a professional opinion of his patent application after submission, when he received a free 30 minute consultation, and although he was interacting with an Innovation Councillor from a public-sector advice provider

152

during the R&D process, he appeared to find this experience less rewarding than it might have been. “The one negative aspect in all this was that I was appointed an Innovation Counsellor who supported our Inventors Club and that linkage was quite useful, but my counsellor was of the opinion that private inventors very rarely break into the motor trade because the motor industry has huge amounts of R & D capacity and it’s quite difficult for an individual outside of that business to bring anything new to the party. But nevertheless I was undeterred because I still felt that the weight of evidence said there was a market there.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. A fascinating feature of this particular case is the extent to which the inventor appears to value the practical, first-hand experience of other inventors more than that offered by professional innovation experts. The tone and enthusiasm evident when discussing the advice he received from members of the South-West Inventors Club was in stark contrast to the air of disappointment articulated when discussing the views expressed by his appointed professional Innovation Councillor. “Fortunately I had identified an inventors club and joined that about the same time as I made the prototypes and found that there was a mine of information there, people who had succeeded and people who were struggling, but there were people here with lots of advice about non disclosure agreements, about the requirement to patent, about the limitations on the protection provided by patenting.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. A feature of the interview conducted with the independent inventor of RightFuel was the degree to which he was aware of the various organisations responsible for innovation within the UK.

An Examination of Independent Inventor Integration in Open Innovation

“Nesta produced quite a good paper about 8 years ago which talked about a strategy for invention, it floundered for lack of finance I guess and then later our own regional development agency in the South West instituted a study, lots of public money expended on revisiting work and brain storming with people in business and Universities and, they put together a new document which was called ‘The Strategy for Supporting Invention’but again it came to a full stop when it got beyond the concept…” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. To this end there is very little evidence to suggest that the inventor’s limited use of third party advice was attributable to a general lack of awareness over available support.

Timing of the Approach The Caparo RightFuel case does little to dispel the proposal that timing plays an important role in the effectiveness of independent inventors to act as suppliers of new products to businesses through Open Innovation. Whilst it is not possible to form an accurate judgement as to whether the inventor would have been more or less successful had his approach been made at a different point in time, the case study provides evidence that the timing of the approach from the inventor to Caparo was advantageous. Consideration is given to the following; the initial approach made by the inventor, to the Caparo Innovation Centre, was made on the 29th August 2006. As an automotive accessory, for use exclusively on diesel powered cars, the market potential for this innovation is intrinsically linked to the number of diesel cars on the road. Secondary data in the form of New Car Registration figures for the UK provided by The Society of Motor Manufacturers and Traders Ltd suggests that whilst diesel powered cars held a market share of just 14.1% of all new car registrations in the year 2000, the market share held by newly registered diesel powered cars, in the

UK in the year 2006, when the commercialisation attempt was made, was significantly greater at 38.3%. In volume terms this equates to an increase in the registration of new diesel powered cars of 65.1% over the 7-year period, between the year 2000 and 2006 (see Table 2). Whilst there appears scope to argue that the new car registration figures for the year 2000 may still have provided enough of an incentive for a prospective licensee to show interest in the product, the fact that an automotive device, designed to fit exclusively on diesel cars, was introduced to Caparo at a point in time when the number of newly registered diesel cars were at an all time high, was critical to the positive view taken of this innovation. This assertion is reinforced by the comments of the eventual licensee, Caparo AP Braking, who revealed that the decision to take on a new product was primarily data-driven. “Its data driven, it’s strategically driven where the business is looking at entering a market or entering a product range and financial yes.” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January. The data contained in Table 3 illustrates the extent to which the act of misfuelling gained prominence in UK newspapers between the year 2000 and 2007. At the point when the inventor filed his UK Patent application in 2005, there were double the number of newspaper articles containing the term misfuelling than the previous year, suggesting recognition of the misfuelling problem was growing. By the 17th October 2007, when the Collaboration Agreement was signed between the inventor Martin White, the Caparo Innovation Centre and the eventual licensee, the number of newspaper articles containing the term “misfuelling” had again doubled from 10 articles in 2005 to 20 articles in 2007. This suggests that either by luck or judgement the inventors timing in seeking to commercialise this innovation was impeccable.

153

An Examination of Independent Inventor Integration in Open Innovation

Table 2. New Diesel Car Registrations UK: Year 2000 - 2006 Year

Volume (cars)

Market Share (%)

2000

313,192

14.1

2001

436,591

17.8

2002

602,623

23.5

2003

704,637

27.3

2004

835,334

32.5

2005

897,887

36.8

2006

898,521

38.3

Source: The Society of Motor Manufacturers and Traders Ltd (2008) SMMT New Car Registrations 2003-2008 [online]. Available at: http://www.smmt.co.uk/search/searchresults2. cfm?fid=2&stid=1 [accessed 11th January 2010].

The following comment by the Managing Director of the Caparo AP Braking, who took the license for this technology, summarises the degree to which the inventor introduced the product at an appropriate point in time and the impact it had: “…at the time there was a screaming demand for something, you had companies saying how much they were spending on misfuelling and putting equipment right. It was a key thing in a lot of the newspapers ‘what can we do to overcome this problem.’You remember Top Gear playing around with different scenarios and then slating the simple solution or what was classed as rubbish solutions. There was a very clear demand and as I said diesel market, how big is it?” Geldard-Williams, N. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January.

Access to Resources The inventor of the Caparo RightFuel benefitted from access to potentially critical resources. Having recently retired from a military career spanning 37-years, at least part of which was spent in senior positions, financial constraints were

154

not a significant barrier to the inventor’s ability to negotiate the early stages of the new product introduction process. Indeed, the inventor had purchased machining equipment, in the form of a lathe, to support his progress towards developing a working prototype, financed his own patent application and purchased the raw material and components required for several iterations of the prototype using his own money. In terms of non-financial resources, the inventor divulged during interview that he had access to a concrete resource, in the form of a workshop at his home, which provided him with space in which to develop his innovation in private. “…I just created a small workshop, I have got a reasonable size garage and I just found a home for the lathe, it’s quite a large machine, but I had various other little machine tools.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. In addition to traditional non-financial resources, the inventor’s mechanical engineering knowledge garnered as a Royal Navy Aircraft Artificer between 1967-73, was a most significant resource, giving him the ability to design, draw and craft in metal.

Access to Formal and Informal Social Support Networks Whilst extant literature points to the family being the primary source of social support for independent inventors (Whalley, 1991) it is notable that no direct mention was made of the inventor relying on his family for support during the development of this innovation. Seemingly more integral to his success was his involvement with the South-West Inventors Club. This organisation provided a formal social support network where the inventor could discuss his innovation with other inventors under the protection of a Non-Disclosure

An Examination of Independent Inventor Integration in Open Innovation

Table 3. Number of ProQuest Newspaper articles containing the term “Misfuelling” 2000-2007 (UK) Year

Number of articles containing the word “misfuelling”

2000

1

2001

0

2002

1

2003

1

2004

5

2005

10

2006

4

2007

20

Agreement. The shared practical experience of individuals in this network, combined with the absence of commercial business representation, was highly valued by the inventor. “Right from the outset they appeared to be a good group to expose ideas to because each meeting is proceeded by a non disclosure agreement where everyone around the table agrees not to discuss what has been exposed and usually new members will come to the club and they won’t say anything for the first time round, but very quickly they realise that it’s a friendly environment, there are no poachers, so I talked about my idea quite openly at the second meeting and people made various suggestions and I learnt a little bit more about patent protection and the forms of non disclosure agreements, so yes I found it was a an extremely beneficial environment to be involved in.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. Interestingly, whilst it might be assumed that the primary function of a social support network is to provide encouragement and morale support for the inventor in what has the potential to be an isolating activity; the inventor of the Caparo

RightFuel appeared to place greater importance on the frankness of the discussions that took place at the inventor club meetings. This is an intriguing consideration, whilst family members and friends may contribute positive and reassuring comments out of a close personal bond with the inventor, the formal structure of the inventor club environment coupled with looser personal ties appears to allow a frank exchange of views, regarding an innovation, that is potentially important to future commercial success.

Ability to Adopt a Credible Business Persona This case provides evidence of the importance of adopting a credible business persona. Consideration is given to the following two excerpts from the interview with a Caparo Innovation Centre representative: “…I think inventors are quite poor at presenting ideas and it is difficult to directly transfer the knowledge the inventor has derived straight into a company. There needs to be some manipulation of that first.” Lester, J. (2010) Personal Interview (views on the Caparo RightFuel programme), 13th January. “Martin came to us face-to-face and he had come especially well prepared really for an inventor. He had produced a well thought out business case and a written description and he had also produced a PowerPoint pitch presentation and really good prototypes. Just by coming so prepared is refreshing really because so many inventors come to us with little supporting evidence that to actually have this presented to us was a positive thing in terms of where Martin is concerned and we obviously sat and listened a little bit more.” Lester, J. (2010) Personal Interview (views on the Caparo RightFuel programme), 13th January.

155

An Examination of Independent Inventor Integration in Open Innovation

In considering the statements above, it is possible to draw a contrast between the almost formal business approach adopted by the inventor of the Caparo RightFuel, which contained a Business Plan, formal presentation and demonstration of prototypes, with the relatively ill considered and amateurish approach apparently taken by some independent inventors. The excerpts also provide a clue as to how much simpler it is for a receiving company to have information presented to them that requires little manipulation before use. Certainly, formal training, broad experience and exposure to both technical and business functions appeared to have been pivotal to the inventor’s ability to come across as credible to the licensee and product assessment team at the Caparo Innovation Centre. The following excerpts illustrate the technical, commercial and legal competence of the inventor: “These rely upon the lubricating properties of diesel oil to maintain the pumps and metering devices in the vehicle fuel system. If these are contaminated with petrol, metal-to-metal contact will quickly occur, producing fine swarf that can destroy components.” White, M. (2006) Personal Communication (Business Plan), 22nd September. “The main impediment to marketing is the belief by many owners that it will never happen to them. However, the following logic indicates otherwise. The device is a form of insurance and its retail pricing maybe influenced by the insurance analogy; for a one off payment the owner of an expensive product (diesel car) is insured for the lifetime of the vehicle from misfuelling repairs well over £1000 (Daily Telegraph average = £7000). Now consider the UK Statistical likelihood of misfuelling taking the 3.6 million cars (diesels under 6-years old) divided by 120,000 (incidents per year) = 3.33% over a period of 6-years of ownership = 20%. In other words, there is a 1 in 5 chance the average UK diesel user will misfuel…” White, M. (2006)

156

Personal Communication (Business Plan), 22nd September. “The issue has been raised at EU Commission level, by MEP Liz Lynne …” White, M. (2006) Personal Communication (Business Plan), 22nd September. In addition to competence across engineering and business functions and adherence to formal business practices; the ability to speak the language of business was also evident in the case. This appears to have benefitted the inventor in so much as it made him easier to work with and ensured the licensee and assessment team fully understood the nature of his pitch and the advantages brought about by his innovation. “It was a brief business plan with the expected headings that you would generally see in a standard type of layout and it addressed a lot of the marketing type of qualification and justification issues, it also demonstrated Martins technical competence because he was a recognised engineer in the navy and it added to his case really and it left us some real good evidence to take away and to just check up on certain elements. It was a good written document.” Lester, J. (2010) Personal Interview (views on the Caparo RightFuel programme), 13th January. In forming a view as to how the inventor was able to achieve such a formalised business approach, consideration is given to the time the inventor spent as an aviation engineer in the military, which would have fostered a reasonable understanding of engineering principles and subsequent administrative duties undertaken as his naval career developed, which would have assisted with developing business acumen and the ability to adhere to common business etiquette.

An Examination of Independent Inventor Integration in Open Innovation

“I think given his background as a Naval Commander he has always been used to having structure, having not worked in an abstract environment that probably some of the other inventors have had…” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January. “…having been in the Royal Navy for 37 years but within that 37 years I had done so many different things from engineering in terms of actually cutting metal and making things, right the way through to dealing with an Industry and procurement. Understanding a little bit about contracts, about the difficulties of delivering services, but also in my years as a Staff Officer framing arguments and putting together arguments in a fairly concise fashion, the importance of presentation, so I felt that I had the administrative skills as well as the engineering background and then in the middle the aviation industry appreciation of safety factors, engineering out problems, understanding that for every modification you make to something there will be negative aspects as well as positive aspects…” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January.

Willingness to Share Information This case provides evidence of an inventor that was willing to share information concerning his innovation with others in a formal setting, but always under the protection of a Non-Disclosure Agreement or filed UK Patent Application. The provision of a written Business Plan and a formal pitch presentation provides evidence that the inventor was willing to share considerable amounts of information in order to convince potential licensees of the innovations value. Again referring to Caparo’s reliance upon data to inform the decision to take on a new product, it seems inconceivable that the inventor would have been successful had he not been willing to share information.

Whilst it may be assumed that trust is a critical ingredient in the willingness to share information concerning an innovation, the inventor took the view that he became more trusting of the licensee as time passed and their contact levels grew. This suggests that in the early stages of the new product introduction process, the lower levels of trust were mitigated by the presence of formal legal agreements that helped ensure confidentiality and facilitated a willingness to share information.

Ability to Identify and Gain Access to Potential Commercial Partners “The ideal prime licensee will be experienced in the automotive industry, be seeking a new marketleading product and will possess: The expertise to deal with the legal and business aspects Manufacturing capability or the experience and connections to source more effective production abroad.” White, M. (2006) Personal Communication (Business Plan), 22nd September. This statement made by the inventor in his initial business plan demonstrates that he had little problem in identifying the characteristics he desired in a potential commercial partner. However, the inventor also expressed a view that identifying the right people in an organisation and gaining an invitation to present to organisations is challenging. “Whilst I was waiting for a response from them I had prepared documents, PowerPoint presentation, a brief on the basic invention without disclosing too much and started short listing Industries, Companies that might be partners, written to a number of people and had lengthy conversations, managed to have interviews with about four Companies under non disclosure agreements and I started to realise that this was the real difficulty,

157

An Examination of Independent Inventor Integration in Open Innovation

this was the most difficult area for my invention, probably for most inventors, to convince people that the idea had a commercial future and that it was worth investing in at some risk.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January.

Ability to Select an Appropriate Commercialisation Path “The aim of this plan is to seek a licensing agreement with a capable firm …” White, M. (2006) Personal Communication (Business Plan), 22nd September. The inventor of the Caparo RightFuel identified his preference for commercialisation, via a licensing arrangement, at a relatively early stage in the development process; prior to prototype production. A key driver behind the decision to pursue commercialisation via a licensing agreement was the inventors desire to concentrate on aspects of the new product introduction process that he enjoyed. “…it goes back to the desire to use my engineering skills rather than spending a lot of time running a business… for me the passion of being involved in design, taking something from a concept through to a prototype was much more important than the administration of running the business.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. “…I really wanted to concentrate on engineering and for me the licensing route was always the natural choice.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. In commenting upon the selection of a commercialisation path, the inventor felt that early decision making, concerning a suitable commercial route, was critical to avoiding costly and unnecessary

158

expenditure, especially in the area of intellectual property protection, where he argued that such protection was not always essential for success, depending on the planned commercialisation path, and occasionally a poor investment.

Alignment of Inventor and Corporate Objectives Whilst developing a solution to a problem he had personally experienced was a satisfying process for the inventor, the focus of the RightFuel project, from the inventor’s perspective, was always one of income generation; as such there was a good synergy between the inventor and corporate objectives. “I think his expectations of the product in terms of volume movement are certainly higher than where it is at the moment and so was ours.” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January. “…I never wanted to invest a lot of time without reward” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. In considering the expectations of the inventor towards the product commercialisation process, three important issues are illustrated by this particular case. Firstly, the inventor’s expectations and aspirations for the project were not onerous. “The inventor desires to be involved in the further development of this project only in so far as the licensee considers his services to be beneficial.” White, M. (2006) Personal Communication (Business Plan), 22nd September. Secondly, the inventor displayed a willingness to compromise and be flexible with his expectations as the development process progressed

An Examination of Independent Inventor Integration in Open Innovation

“I would appreciate the opportunity to discuss your quarterly reports in accordance with Clause 3.d. to our assignment agreement, but would be content to meet every 6-months.” White, M. (2008) Personal Communication (Meeting review schedule), 4th October. Finally, the inventor was professional in his conduct in instances when his expectations were not met. “…I think sometimes he is a little frustrated with the speed of progress but he is professional through and through and he doesn’t rant and rave at the Company which would be detrimental and he always provides his services if they need assistance with certain technical points.” Lester, J. (2010) Personal Interview (views on the Caparo RightFuel programme), 13th January. “He hasn’t gone up in the air and said you’re doing it wrong…” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January.

Experience of the Inventor Whilst the inventor revealed that he had no personal experience of new product introduction, prior to his attempts with the Caparo RightFuel, he had significant experience of operating within a technical field closely aligned with his innovation, which aided him in developing a relevant innovation and in supporting the development and commercialisation of the product. “…going back to my early days as an artificer, we had spent an awful lot of time in the classroom dealing with fluid dynamics, mainly to do with air and aviation but also to do with liquid fluid systems, air being a fluid as well, but to do with hydraulic systems and fuel systems but I had spent a lot of time setting engines and gearboxes to helicopters and jet aircrafts so I knew quite a lot

about fluid systems involved in those platforms, so in a way this particular project was a bit of a gift because again it was down to fluid dynamics, to control valves and a lot of the bits of metal that I was making I had some familiarity with, how they would be employed in an aircraft system so it was a joy to go back to my engineering days and to become familiar again with things I had known so many years earlier, certainly a gift.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. The case provides evidence that the inventor’s previous employment experience was important to the process of commercialisation and his ability to convince the eventual licensee as to the merits of the innovation. “I think that subconsciously that some of the guys when they talk to him out there and whatever, that knowing his background was as a Naval Commander they listened to him more …” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January. “He is not just a guy who has come in with an idea off the street, he’s a guy who has lived in the real world and he has obviously been to meetings where he has had to behave in that forum.” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January.

Emergent Critical Success Factors In addition to the proposed critical success factors presented in the previous chapter, “withincase analysis” (Eisenhardt, 1989) suggests three emergent critical success factors.

Ability to Operate within a Partnership Both the Caparo Innovation Centre and Caparo AP Braking identified the need for independent inventors to act as a partner to the commercialis-

159

An Examination of Independent Inventor Integration in Open Innovation

ing company. The ability to understand that the potential licensee is not a contract manufacturer producing a product to specification, but rather an entity that is invested in and committed to progressing and evolving an innovation is critical. “I think where Martin worked and I think as a general for inventors is that they have to understand that when they are bringing this to somebody, they are going to be working as a partnership and that partnership, like any partnership, whether it be person or business will go through rough stages and you will have to be able to bare your soul and be able to take on criticism when it’s intended to be from a positive point of view.” Sarel-Cooke, H. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January. “Martin came to the table wanting to work with us rather than us to do some work for him. The ownership was different, rather than us do work on a project that belonged to an inventor, it’s more like I have got this to share and we can take it together to get it commercialised. His whole approach was different from the outset.” Lester, J. (2010) Personal Interview (views on the Caparo RightFuel programme), 13th January.

Ability to Relinquish Control This case provides evidence that a critical factor in the inventor’s success was his ability to relinquish total control of the innovation and not hold on too tightly. As such accepting that the receiving company will have certain areas of expertise and putting faith in that expertise appears important. “…I didn’t have too much difficulty with the idea of them owning the project, taking it forward and taking a back seat because I suppose from the outset I had always had the view that concept to prototype and a bit of admin to convince other people to come on board was what I really wanted to do. I can see that other inventors who haven’t

160

got a definite view on the licensing route might find that process difficult. If they had a mind perhaps to manufacture themselves or to set up a business or to be a partner within a business then they might find that detachment a little bit difficult.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. “…it is very important for them (the licensee) to start to view the project as their project and this business of relinquishing your control or ownership is very important for the overall success of the project. Other people have to buy into it and you have got to be prepared to be sidelined and to relinquish a lot of control. That’s a fairly necessary part of the licensing route and I suppose a lot of inventors find that very difficult to live with.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January. “…he has been pretty smart and took the back seat at times and been very supportive.” GeldardWilliams, N. (2010) Personal Interview (experiences from the Caparo RightFuel programme), 7th January.

Ability to Filter Out Unviable Innovations An apparently important factor for independent inventors seeking to become recognised as a viable supplier of new products is their ability to filter-out weak and unviable innovations to allow them to dedicate their resources effectively. This case provides a number of pieces of evidence to support this, in particular, instances where the inventor trialled ideas before discarding those that were deemed unviable. “I started drawing and over a very long period of time dismissed lots of ideas …” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January.

An Examination of Independent Inventor Integration in Open Innovation

The dangers of not filtering out innovations effectively lies in the misplaced allocation of resources, often in support of new product ideas that are flawed from the outset. “One of the most difficult things I guess is to tell people that actually their idea is rubbish and they need to go back to the drawing board, but I guess a lot of people have got to realise that. We have met individuals in our own Inventors Club who have invested a huge amount of money on ideas that are never going to return any of that money, because they missed a few steps at the outset, became obsessed with a view that they were right when patently they were wrong and no one ever really had the guts to stand up to them and say you need to look at this there is plenty prior art, this is on the market, think long and hard before you proceed any further.” White, M. (2010) Personal Interview (Caparo RightFuel), 14th January.

DISCOURSE This work acknowledges twelve critical success factors, proposed in the previous chapter. We find support for the twelve critical success factors, which are present within the Caparo RightFuel case study. In terms of Time Commitment both having time available and making a decision to commit that available time to innovation is important. It is our view that without the necessary time commitment made to inventing and developing the business case, independent inventors will find it difficult to firstly develop the innovations they wish to supply businesses with and secondly provide the level of data required to mitigate the increased risk associated with taking on externally generated innovations. In considering the Use of Intellectual Property a willingness to invest in Intellectual Property Protection is important. In addition, a patent application, which covers a multitude of technical

solutions to the problem in question, certainly appears to enhance the commercial value of the inventor’s business proposition, by making it more difficult to circumvent. In our opinion independent inventors must make every effort to familiarise themselves with the Intellectual Property Protection mechanisms open to them, how they are utilised in a commercial sense and whether investment in intellectual property is appropriate for their particular innovation, given the proposed mode of commercialisation, the industry sector they are hoping to enter and their available financial resource to both take out IP Protection and pursue those that infringe their rights. The importance of advice, guidance and support appears to be influenced by the extent of the inventor’s technical and commercial competence or previous experience of negotiating the new product introduction process. As such, in some instances support maybe vital whilst in other cases the inventor maybe able to fair well without additional assistance. In considering the type of advice, guidance and support provided for independent inventors it is important to note that reliance on professional innovation practitioners is not always desirable and that much can be gained from engaging the assistance of peers with practical experience of innovation and new product introduction, potentially via Inventor Clubs. There is reasonable evidence from the case study to suggest that the timing of the innovation approach is important. This perhaps reinforces the need for inventors to look for solutions to current problems and avoid the situation where they continue to invest in and promote an innovation that no longer meets need. Conversely, it may be difficult for independent inventors who propose products that speculate heavily on what the market may need in the future, as the associated risks in this situation are considerable and are likely to deter businesses.

161

An Examination of Independent Inventor Integration in Open Innovation

Access to resources whether financial, concrete, raw materials or suitable tools are critical to the inventors ability to prove the concept and produce a functioning prototype. At present independent inventors are overly reliant on their own ability to acquire these resources. The provision of community based inventor groups that provide the physical resources for inventors may therefore be worth considering. Consideration should also be given as to why there is so little financial support available to independent inventors, when there is so much available to SME’s. Access to formal and informal social support networks appears important, but not in the way extant literature seemed to indicate. Whilst the inventor’s family maybe critical in providing support, motivation and reassurance to independent inventors, formal support networks, in the guise of inventors clubs, provide a platform for a frank exchange of views regarding innovation. To a degree, the objective, constructive criticism offered by a formal support network provides a good counterbalance to the subjective support of family members and helps prevent inventors pursuing inventions that are commercially or technically unviable. The ability to convey a credible business persona is central to the success of independent inventors. The credibility of independent inventors is an important consideration in the review process undertaken for new products originating from outside a company. The ability to talk the language of business, operate in a formal business environment and present data in a fashion that facilitates understanding and minimises the need for excessive manipulation adds credibility to both the inventor and the business case. It would appear that previous experience of operating in a formal business context is advantageous or alternatively it would be helpful for independent inventors to undergo training in business practice and conventions. A willingness to share information is critical because of the effect good quality information has

162

on the perceived risk associated with an externally generated innovation. Disclosure of information should be restricted to those instances where either a Non-Disclosure Agreement or Patent application is in place. The ability to identify and gain access to potential commercial partners is both important and challenging for independent inventors. Whilst inventors maybe able to take a view as to whether a business is operating in a suitable industrial sector it is much more difficult to identify the manufacturing capability, desire for new products and appropriate internal point of contact within a company. Whilst those companies that operate a formal Open Innovation Strategy may make this process less demanding, we believe that there continues to be a large number of businesses that are receptive to external ideas from inventors that do not make this known to the independent inventor community. The ability to select a commercialisation path early in the new product development process is beneficial in terms of providing focus to the new product introduction process and minimising the number of blind alleys the inventor travels down. In addition, selection of a commercialisation path early in the process can inform the degree to which IP protection is required and as such prevent unnecessary costs from being accumulated. In deciding upon a preferred commercialisation path, we would advocate the that the inventor appraise their skills-set and as such their ability to run a business, the extent to which they want to risk personal wealth, their desire to control and be involved in commercialisation and their expectations over financial reward, if any. Close alignment of inventor and corporate objectives seems beneficial to the chances of inventors operating effectively as suppliers of new products to business. The corporate objective of introducing a new product is biased towards generating a financial return. Inventors need to be aware of this from the outset and understand that many of the decisions regarding the product

An Examination of Independent Inventor Integration in Open Innovation

development and introduction will be governed by this objective. From how the product is manufactured, where it’s manufactured, what material it’s made from, through to the market it’s targeted at. The experience of the inventor is critical to the extent that specialist knowledge in a certain industry may be viewed as positive by potential commercial partners and in addition improves the potential that an innovation is market driven and relevant. Experience in a formal business context would appear be more useful in adding credibility to a business proposal. The findings from this research inquiry suggest a further three emergent critical success factors (see Table 4). Independent inventors should view commercialisation of new products via Open Innovation as a partnership arrangement. Despite originating the innovation, independent inventors need to acknowledge that the success of the project is often contingent upon the receiving company and inventor working together to fully understand the legacy of the product, garner specialist industry insight and minimise divertive actions. An ability to operate within a partnership is therefore critical. The ability to relinquish total control of an innovation is essential if independent inventors are to become effective suppliers of new products to businesses through Open Innovation. It is fundamentally important that the receiving company buys-in to the innovation. As such it is necessary for independent inventors to take a back-seat on occasion and allow the collective expertise of the business to add to the project.

Table 4. Emergent critical success factors Additional proposed critical success factors 13

Ability to operate within a partnership

14

Ability to relinquish total control

15

Ability to filter out unviable innovations

For independent inventors to supply the most commercially and technically viable product solutions to businesses they must make frequent assessments of their innovation and take on-board external input. If after research and consultation innovations appear flawed they should be filtered out and attention should switch to an alternative solution or project.

CONCLUSION Independent inventors have the potential to be effective suppliers of new product ideas to businesses operating Open Innovation. If the commercialisation opportunities presented by Open Innovation, for independent inventors, are to be maintained then inventors must become more successful suppliers. Within this chapter we find support for the twelve critical success factors proposed in the previous chapter. A further three emergent critical success factors are acknowledged and we will continue to investigate the significance of these as this research inquiry progresses. We believe that the biggest contribution made by these two chapters is the amalgamation and communication of critical success factors, from disparate academic literature, in a format that independent inventors and those businesses operating open innovation will find usable in a practical sense; by paying heed to these factors independent inventors should become more effective suppliers to companies operating Open Innovation and enhance the sustainability of such operations. Whilst this chapter is geared towards the steps that independent inventors should take to become more effective suppliers, there are some important implications for those individuals responsible for the management of Open Innovation. Firstly, management may wish to consider how they can improve their visibility as an organisation operating Open Innovation. Independent inventors find it difficult to identify companies to approach with their innovations and within those companies

163

An Examination of Independent Inventor Integration in Open Innovation

identify who the key contact is. Importantly, managers may wish to consider identifying themselves as being open to approaches from independent inventors. Open Innovation Managers may also wish to consider the proposed Critical Success Factors and determine how they can encourage independent inventors that want to engage with their business to operate accordingly. A prescriptive process that requires independent inventors to submit specific written details as part of the initial approach would help to ensure that inventors have given due consideration to key factors in advance of the first meeting. Whilst much can be learnt about a proposed innovation from reading documentation prepared by an independent inventor, the degree to which an independent inventor and business can work together is critical to success. As such we would advocate that managers operating Open Innovation request a face-to-face meeting with independent inventors early in their process. A potential concern of management operating Open Innovation models that allow independent inventors to act as suppliers is the cost of handling the high quantity of inquiries. Consideration should be given as to how administrative hurdles can be utilised to deter approaches from those that do not have the capacity or desire to see-out a potentially long development programme. A final consideration for those managers wishing to encourage independent inventors to act as suppliers is the stance they propose to take over confidential information. As a general rule independent inventors are unlikely to disclose information concerning a proposed new product without either having filed a patent application or completed a Non-Disclosure Agreement (NDA). Whilst smaller companies may feel able to sign up to NDA and adhere to the principles of this arrangement, many larger businesses feel this is practically impossible. As such independent inventors will need to file for patent.

164

LIMITATIONS AND FUTURE RESEARCH This work identifies the preliminary findings of an exploratory larger scale research inquiry and as such should be viewed in the context of work-in progress. Although it represents a narrow view of a complex subject we believe that the case study approach to this inquiry has added valuable evidence in support of twelve critical success factors, and has identified three emergent critical success factors. It is envisaged that through the examination of further cases, the knowledge relating to this field of research will be extended. As mentioned earlier in the chapter, the value of the case study approach is in the formation of new insights that drive future research inquiries (Dyer and Wilkins, 1991). In terms of future research, studies that test the boundaries of the identified critical success factors by focussing on potential regional variations or variations across industry sectors would be valuable. It is important to acknowledge that the critical success factors identified in this chapter are intentionally focussed on improving the ability of independent inventors to become successful suppliers of innovative product ideas to businesses operating open innovation. This is of course one-side of the coin. As such, there is potential for shifting the research focus away from the independent inventor and on to the receiving company, licensee, to discover if critical success factors relating to their involvement in the integration of independent inventors in open innovation can be established.

ACKNOWLEDGMENT The authors wish to thank Caparo for allowing us access to their facilities during this research inquiry. In addition we wish to extend our thanks

An Examination of Independent Inventor Integration in Open Innovation

to Martin White the independent inventor behind the Caparo RightFuel.

REFERENCES Chesbrough, H., & Crowther, A. K. (2006). Beyond high tech: Early adopters of open innovation in other industries. R & D Management, 36(3), 229–236. doi:10.1111/j.1467-9310.2006.00428.x

Whalley, P. (1991). The social practice of independent inventing. Science, Technology & Human Values, 16(2), 232–256. doi:10.1177/016224399101600205 White, M. (2010). Interviewed by: Smeilus, G., Caparo RightFuel. Wolverhampton, U. K.: University of Wolverhampton. Yin, R. K. (1984). Case study research. London, New Dehli: Sage.

Chesbrough, H., Vanhaverbeke, W., & West, J. (2006). Open Innovation: Researching a new paradigm. Oxford, UK: Oxford University Press.

Yin, R. K. (1994). Case study research: Design and methods. London, UK: Sage Publications.

Dyer, W. G. Jr, & Wilkins, A. (1991). Better stories, not better constructs, to generate better theory: A rejoinder to Eisenhardt. Academy of Management Review, 16(1), 613–620.

KEY TERMS AND DEFINITIONS

Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. Flyvbjerg, B. (2006). Five misunderstandings about case-study research. Qualitative Inquiry, 12(2), 219–245. doi:10.1177/1077800405284363 Geldard-Williams, N., & Sarel-Cooke, H. (2010). Experiences from the Caparo RightFuel Programme. Interviewed by: Smeilus, G. Leamington Spa, U. K.: Caparo AP Braking. Glaser, B., & Strauss, A. (1967). The discovery of grounded theory: Strategies of qualitative research. London, UK: Wledenfeld & Nicholson. Lester, J. (2010). Views on the Caparo RightFuel programme. Interviewed by: Smeilus, G. Wolverhampton, U. K.: University of Wolverhampton. Lettl, C., Rost, K., & Von Wartberg, I. (2009). Why are some independent inventors ‘heroes’ and others ‘hobbyists’? The moderating role of technological diversity and specialization. Research Policy, 38(2), 243–254. doi:10.1016/j. respol.2008.12.004

Independent Inventors: Independent inventors are characterised by two factors; firstly their inventive activity is conducted outside the confines of an established business and secondly, the independent inventor has no formal obligation to invent (Lettl et al., 2009). Open Innovation: “Open Innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively” (Chesbrough, Vanhaverbeke & West, 2006: p.1).

ENDNOTES 1



The interviewees were selected as they provided insight from three critical vantagepoints: the independent inventor; the open innovation contact team and the eventual company licensee. The interviewees were: Martin White (Independent Inventor); Jonathan Lester (Caparo Innovation Centre – open innovation contact team); Neil Geldard-Williams (Managing Director Caparo AP Braking – company licensee) and

165

An Examination of Independent Inventor Integration in Open Innovation

2



3



166

Henry Sarel-Cooke (Sales Director Caparo AP Braking) AA Motoring Trust Report (Feb 2004) – Misfuelling: Don’t get caught out! Telegraph Motoring Section (27th Aug’05) – A costly mistake

4



5



Fleet News Magazine (5th Sep’06) – Misfuelling hits new record level AA Motoring Trust Report (Feb 2004) – Misfuelling: Don’t get caught out!

167

Chapter 10

Firm-Specific Factors and the Degree of Innovation Openness Valentina Lazzarotti Carlo Cattaneo University, Italy Raffaella Manzini Carlo Cattaneo University, Italy Luisa Pellegrini University of Pisa, Italy

ABSTRACT This chapter investigates the topic of how open innovation is actually implemented by companies, according to a conceptual approach in which open and closed models of innovation represent the two extremes of a continuum of different openness degrees; though, these are not the only two possible models. By means of a survey conducted among Italian manufacturing companies, this chapter sheds light on the many different ways in which companies open their innovation processes. Four main models emerge from the empirical study, which are investigated in depth in order to understand the relationship between a set of firm-specific factors (such as size, R&D intensity, sector of activity, company organization) and the specific open innovation model adopted by a company.

INTRODUCTION The concept of “Open Innovation” (OI) is often studied supposing an artificial dichotomy between closed and open approaches, whilst the idea of exploring different degrees and types of openness in a sort of continuum seems to provide a more interesting avenue (Chesbrough, 2003b). Prior research has highlighted that open innovation may DOI: 10.4018/978-1-61350-165-8.ch010

be pursued in different ways, which are identifiable in terms of organisational form of acquisition or commercialization, number and typologies of partners, phases of the innovation process that are actually open, the direction of opennes (inbound and/or outbound) and governance (hierarchical or flat). Moreover, previous research has also attempted to study the relationships among different OI models and several contextual factors, driven by the idea that these factors could explain or,

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Firm-Specific Factors and the Degree of Innovation Openness

at least, characterize the companies’ choices in terms of degree of openness. Lastly, different OI models, defined according to this concept (i.e. degree of openness and models within their specific context), have been analysed in some preliminary work in terms of their performance (Lichtenthaler, 2008; 2009). The objective of this chapter is thus threefold: first, to provide evidence in support of Chesbrough’s (2003b) theoretical proposition that businesses may be located along an Open Innovation Continuum, second, through the use of extensive study, to identify any potential intermediate states between the extreme points of the Continuum - Open and Closed Innovators - and, third, to identify the contextual factors that affect the choices firms make along the Open Innovation Continuum. In particular, for the identification of the potential intermediate states in the OI Continuum, we focalized on two variables representing the openness degree, which are not still deeply investigated: (1) the number and type of partners (partners variety) and (2) the number and type of phases of the innovation process open to external contributions in and/or out (innovation phase variety). It should be noted that we assume that the innovation process is composed of different phases: idea generation (identification of a technology opportunity through scouting, monitoring, market analysis, trends analysis); experimentation (from the idea to the prototype); engineering (transforming the prototype into an industrial project); manufacturing (defining and organising the “plant”); commercialisation (planning of commercialisation and promotional activities). The choices in terms of OI will be investigated in terms of those contextual factors whose role is still controversial (Lichtenthaler, 2008), or otherwise it can be better understood in light of the concept of openness suggested here. Our investigation was carried out in Italy, where empirical evidence about OI is still poor. However, there are many pressures, arising from institutions, too,

168

towards the establishment of collaborative models (Global Business Summit, 2010). Thus, investigating if, how and with what results companies work together becomes a relevant issue for both Italian scholars and practitioners. We would also like to emphasize that our endeavour to identify any in-between states along the Open Innovation Continuum is the first attempt to research this topic and that the subject indeed requires further research in order to better characterise such intermediate states. The following sections are divided into subtopics: a description of the pertinent literature (so as to better understand the research questions we posed), a description of the empirical study we carried out and the methodology used, the main research results, a discussion of the results, conclusions and future research.

THEORETICAL BACKGROUND The Theoretical Framework and the Research Questions Traditionally, large firms relied on internal research and development (R&D) to innovate and, in many industries, large internal R&D labs were a strategic asset and firms could internally discover, develop and commercialize technologies. This approach has been labelled the “closed innovation model” (Chesbrough, 2003a). Although it worked well for quite some time, the current innovation landscape has changed. Due to labour mobility, increasing R&D costs, abundant venture capital and widely dispersed knowledge across multiple public and private organizations and the need for specialisation in knowledge production, enterprises can no longer afford to innovate on their own, but rather need to engage in alternative innovation practices. In this regard, Open Innovation (OI) represents an important innovation practice that can help firms to innovate without having to rely only on their inhouse strengths. Since Chesbrough published his

Firm-Specific Factors and the Degree of Innovation Openness

book in 2003, the concept of “Open Innovation” has received a considerable amount of attention from practitioners and researchers. A large number of studies are adopting this term to describe the phenomenon where firms rely increasingly on external sources of innovation, which means that ideas, resources and individuals flow in and out of organizations (Chesbrough, 2003a). While contributions are still growing (Gassmann, 2006; Enkel et al., 2009; Enkel et al., 2010), the debate on innovation management is enriched by studies that critically examine the Open Innovation concept by exposing its weakness and limitations (Dahlander & Gann, 2007; Trott and Hartmann, 2009). In particular, the concept of Open Innovation is criticized because of the widespread view that the concept highlights an artificial dichotomy between closed and open approaches. On the other hand, the idea of exploring different degrees and types of openness in a sort of continuum (i.e. the openness degree concept) seems to provide a more interesting and richer avenue to investigate, (Chesbrough, 2003b; Dahlander & Gann, 2007). Indeed, this view allows for a deeper and more real investigation into company behaviour and into the particular nature and context of innovation sources (Chesbrough, 2003b; Gassmann, 2006; Dahlander & Gann, 2007). In any case, the era of open innovation has begun and many firms are opening their innovation process to the outside world (Enkel et al., 2009). The way the innovation process can be opened has been studied in management literature from a variety of perspectives. Although the perspective that has received most of the attention in the literature is undoubtedly the direction of openness, other approaches have also been investigated. More specifically, these look at the number and types of partners, the kind of governance in the innovation networks, and the organisational forms chosen to define the links among partners (high vs. low integration level). As regards the perspective connected with the “direction of openness”, three models of

open innovation can be observed: the inbound, exploration or outside-in process, the outbound, exploitation or inside-out process, and the coupled process (Keupp & Gassman, 2009; Lichtentaler, 2008; Enkel, et al., 2009). Thanks to the outsidein process, firms aim at enriching the company’s own knowledge base through the integration of external knowledge sourcing, and hence increase their innovativeness (Enkel et al., 2009). Through the inside-out process, firms aim at earning profits by bringing ideas to market, selling IP, and multiplying technology by transferring ideas to the outside environment, in order to bring ideas to market faster than they could through internal development (Enkel et al., 2009). The coupled process combines the two abovementioned processes to simultaneously gain external knowledge and bring ideas to market. As regards the perspective connected with the “types of partners” (Enkel et al., 2009), literature has highlighted the interactive character of the innovation process, suggesting that innovators use ideas and knowledge of external actors in their innovation processes: firms rely heavily on their interaction with lead users, suppliers, and a range of institutions inside the innovation system (von Hippel, 1988; Lundvall, 1992; Brown & Eisenhardt, 1995; Szulanski, 1996). With each innovation source, an organization can achieve different intensity levels of collaboration (Laursen & Salter 2006; Keupp & Gassman 2009). Hence, it is possible to define different open innovation models depending on both breadth (i.e., the number of sources used for innovation activities) and depth (i.e., the intensity of collaboration with each source). As regards the perspective connected with the “kind of governance” in the innovation networks, there are two dimensions which need to be considered (Pisano & Verganti, 2008): openness, i.e. a large number of involved partners and hierarchy, i.e. the level of ‘democracy’ in decision making. On the basis of two such aspects, four open innovation models emerge: (1) the open/

169

Firm-Specific Factors and the Degree of Innovation Openness

hierarchical model, in which anyone can offer ideas but only one company defines the problem and chooses the solution; (2) the open/flat model, in which anyone can generate ideas, and no one has the authority to decide what is or is not a valid innovation; (3) the closed/hierarchical model, in which a company selects certain participants and decides which ideas are to be developed; (4) the closed/flat model, in which a selected group offers ideas, while making critical decisions together. As regards the “organisational forms” chosen to define the links among partners (high vs. low integration level), there are four technology sourcing modes that firms can adopt: corporate Venture Capital investments, non-equity alliances, equity alliances and acquisitions. Each form carries with it different implications in terms of the investing company’s reversibility and commitment (Chiesa & Manzini, 1998; van de Vrande et al., 2006). More precisely, corporate Venture Capital investments and non-equity alliances are reversible to some extent and involve a relatively low level of commitment from the investing company, while equity alliances and acquisitions require a high level of commitment and are hardly reversible. In our opinion, all these contributions share two aspects: on one hand, they have a common interpretation of open innovation, while, on the other, they have a weakness. Regarding common interpretation, all these contributions share the understanding that the open innovation models which the firms follow are not exclusively open or closed, but rather show varying degrees of openness: i.e. between the two pure models – open or closed, which represent the two extremes of a continuum – there are many shades of grey (Chesbrough, 2003b). Indeed, according to Dahlaner and Gann (2007), the dichotomy between open vs. closed is artificial and it is necessary to explore different degrees and types of openness: this can yield more insight in understanding openness. With regards to weakness, the perspectives used in the previous contributions are not exhaus-

170

tive in explaining the open innovation models followed by firms. In other words, the latest literature still does not fully explain in what ways the degree of openness can happen. Indeed, to the best of our knowledge, the literature does not address the question whether some firms conduct open innovation in many phases of their innovation funnel and if others focus only on a very few of them; if this is the case, we must consider which phases of the innovation funnel are open or closed. Hence, literature does not help companies to find the right balance between closed and open phases of the innovation funnel. Neither is it clear if the phases of the innovation funnel that are permeable are open to many or just a few partners. With few exceptions, it is not even clear if the involved partners are different in terms of typologies or not. For instance, De Backer et al. (2008) analyzed such a problem and found that universities and government research institutes are generally considered to be an important source of knowledge transfer for the innovation activities of companies, especially regarding more upstream/ research activities. On the basis of these premises, our objective is to contribute to the literature which sustains that business reality is not based on pure open innovation, but on companies that invest simultaneously in closed as well as in open innovation activities (Enkel et al., 2009) throughout the innovation funnel with different partners. Hence, we will introduce a new perspective that considers both the number/typology of partners and the number/ typology of phases, in order to understand if such a perspective can confirm the existence of different models of open innovation. Within this context we will try to answer the following specific research questions: • •

Do different firm-specific factors characterize the models of open innovation? Do such different models show a different level of innovative performance?

Firm-Specific Factors and the Degree of Innovation Openness

Figure 1 depicts the constructs of our theoretical framework. The operationalisation of each construct is reported in detail in the Appendix (all questions were measured on a four-point Likert scale to indicate the frequency of use, with 1 = disagreement and 4 = agreement). As explained in the introduction, the main objective of the chapter is to provide empirical evidence to the notion of OI as a continuum, that is to say that different OI models may exist. Before characterizing them by means of our empirical analysis, in the following we will analyze what the literature says about the relationships between some contextual factors (i.e. R&D intensity, size, type of industry, approach to innovation, company’s objectives for collaboration, managerialorganizational actions supporting open innovation) and OI models and their performance, by highlighting areas that are lacking which justify our subsequent empirical analysis. First, an analysis of the relationships between the firmspecific factors and the open innovation models will be made. Then, an analysis of the impact of the open innovation models on innovative performance will follow. Specifically, what is lacking in the literature has been highlighted for each of the relationships studied.

The Firm-Specific Factors and Open innovation Relationship between R&D Intensity and Open Innovation Models As regards the role played by R&D intensity, Lichtenthaler (2008), Lichtenthater and Ernst (2009), Calantone and Stanko (2007) and Sofka and Grimpe (2008) investigated this role from different viewpoints. Lichtenthaler (2008) and Lichtenthater and Ernst (2009) analysed the effect of R&D intensity and found that the greater the level of R&D intensity the greater the technological exploration. This provides support for the assumption that firms pursue external technology acquisition as a complement to internal R&D and not as a substitute (Cohen & Levinthal, 1990, Zahra & George, 2002). Calantone and Stanko (2007) underpin that firms’ exploration activities cannot occur frequently: therefore, given the high costs for developing specialized structures, firms are more likely to resort to outside expertise. Moreover, they state that firms performing a great deal of in-house exploratory research are likely to be led by this exploration away from their competencies, and will therefore be more likely to seek out outside expertise.

Figure 1. Theoretical framework

171

Firm-Specific Factors and the Degree of Innovation Openness

Sofka and Grimpe (2008) studied the effect of internal R&D investments on “breadth” (i.e. extent of partner typology) and “depth” (i.e. intensity of collaboration for each partner) of research strategies. They hypothesize that internal R&D investments lead to deep research strategies rather than broad ones. With their survey, which involved firms from twelve European countries, they argue that firms building absorptive capacities through internal R&D have both broader and deeper research strategies. However, the effect on depth is stronger than the effect on breadth. In other words, committing internal resources to in-house labs and specialized scientists and engineers is therefore the primary path for innovation managers to achieve more depth in their search strategies. Hence, on the basis of these contributions, the role played by R&D intensity is studied in relation to two of the abovementioned perspectives, through which it is possible to investigate how the innovation process can be opened: the perspective connected with the “direction of openness” and the perspective connected with the “types of partners”. Thus, literature lacks the investigation of the role that R&D intensity plays with regards to the perspective offered in this chapter, which will consider both the variety of partners involved and the variety of stages in which companies collaborate.

Relationship between Size and Open Innovation Models Size is one of the most investigated of the contextual factors and it is still a controversial subject. On the one hand, empirical literature suggests that open innovation is mainly driven by larger companies. Empirical investigations show that size impacts on two variables representing the openness degree: the extent of both technology exploitation and exploration (Lichtenthaler, 2008; Lichtenthaler & Ernst, 2009). Indeed, as regards technology exploitation, larger companies seem to have a bigger technology portfolio than smaller

172

companies and hence have wider technological knowledge that is potentially suitable for commercialization. As regards technology exploration, larger firms do not seem to be able to completely rely on internal activities due to the diversity of the technological knowledge that they use. In general, the fact that larger firms seem to drive the opening of the innovation process can be justified by the more systematic approach they have in their innovation processes (Lichtentaler, 2008) and the larger resources they possess with respect to small and medium enterprises (Lichtentaler, 2008; De Backer et al., 2008; van de Vrande et al., 2008). In addition, according to Lichtentaler (2008), it should be noted that the effect of size seems to be stronger in the case of technology commercialization than in technology exploration, in that commercialization is rather a newer phenomena than acquisition. As the external mode of technology exploitation has become a broader trend only in recent years, it is still driven by large pioneering firms, while the acquisition of external technology is distributed more evenly across firms of different sizes. Keupp and Gassman (2009) analyse the effect of size on two different variables representing the openness degree: the number of knowledge sources used for OI activities (i.e. the breath of OI) and the intensity of collaboration with each source (i.e. the depth of OI) and show that there is a positive and significant effect of firm size on both the breadth and the depth of OI. On the other hand, some literature emphasises that especially small companies, often lacking resources and competence to innovate by themselves, would have great benefits from exploiting the OI model. In fact, SME are increasingly adopting OI practices (van deVrande et al., 2008). Hence, on the basis of these contributions, it is possible to draw considerations similar to those regarding the role played by R&D intensity. Indeed, the role of size is studied in relation to the same two abovementioned perspectives: the perspective connected with the direction of openness and the perspective connected with the types

Firm-Specific Factors and the Degree of Innovation Openness

of partners. In addition, its role is still controversial. As a consequence, it is possible to assert that literature lacks the investigation of the role that size plays with regard to the perspective offered in this chapter (number/typology of partners and number/typology of phases).

Relationship between Type of Industry and Open Innovation Models Some authors investigate the impact that industry exerts on OI, interpreting industry as the typology of sector in which firms operate. Also in this case, literature is not unidirectional in that empirical findings show contrasting results. What’s more, the same Lichtenthaler in different publications (Lichtenthaler, 2008 and Lichtenthaler & Ernst, 2009), while referring to the same sample, finds different results. In fact, on the one hand, Lichtenthaler and Ernst (2009) show that a firm belonging to a particular industry does not produce any impact either on the external technology acquisition or on external technology exploitation. Similarly, Lichtenthaler (2008) states that his findings demonstrate the insignificant effect which industry differences have across the clusters. Thus, the openness of the innovation process does not seem to be determined principally by industry characteristics. On the other hand, the studies by Gassman and Enkel (2004) and De Backer et al. (2008) demonstrate the opposite. More in particular, Gassman and Enkel (2004) state that the relative importance of internal and external sources varies across different industries. De Backer et al. (2008), although focusing on particular aspects, such as patent licensing, find important differences among industries, with chemical/drugs, electronic/ electrical/semiconductors and machinery/equipment/computers as the industries where licensing deals take place more frequently than in others.

Relationship between Approach to Innovation and OI Models A relevant concept investigated in the literature is that of “technology aggressiveness” (measured by three items, among them “the emphasis on radical innovation rather than incremental innovation”)1. Lichtenthaler and Ernst (2009) find that technology aggressiveness is negatively related to the extent of external technology acquisition and is positively related to external technology exploitation, in that commercialization nurtures benefits in terms of setting industry standards, entering into new markets, and realizing learning effects. In another publication, Lichtenthaler (2008) studies the implications connected with firms’ emphasis on radical innovation and finds that the degree of openness seems to rise with the degree of emphasis on radical innovation, especially concerning the degree of external technology commercialization. There are two reasons for this: first, the opportunity to commercialize knowledge which, when not applied in the organization, turns out to be residual; second, the possibility to facilitate acceptance on the market and the creation of a standard. Lichtenthaler (2008) also finds that firms which emphasize radical innovation are obviously not able to develop all knowledge internally, but they have to strongly rely on complementary external sources and thus they use technology acquisition (Perrons et al., 2005). Hence we can draw even more restrictive considerations than those regarding R&D intensity: technological aggressiveness is studied in the literature in relation only with the perspective connected with the direction of openness. If we add that this factor’s role is still controversial, it emerges that new empirical investigation is needed to analyze the impact exerted by technological aggressiveness on OI models.

173

Firm-Specific Factors and the Degree of Innovation Openness

Company Collaboration Objectives and OI Models The main reasons that push firms towards choices of open innovation are, on the one hand, the need to reduce innovation costs and business risks, and on the other, the need to extend skills, competences and creativity (Huang et al., 2009). As regards the objective of diminishing costs and risks, Calantone and Stanko (2007) analyze outsourcing as a tool for increasing staffing efficiency measured in terms of employee sales efficiency. They infer that the decision to reduce the number of employees is related to the outsourcing of innovation in the short run but not over the long term. Gassmann and Enkel (2004) state that research-driven companies usually aim at reducing the R&D’s fixed costs and sharing risk. Chiaroni, Chiesa and Frattini (2009) state that the reason for accessing external sources is the willingness to minimize risk by investing in technologies that are already proven in other applications. Another main reason for firms to undertake R&D outsourcing includes accessing specialized skill sets and creativity, which exposes the internal development staff to new knowledge, technology, and organizational development processes (Catalone & Stanko, 2007; Chesbrough and Teece, 1996; Linder, 2004; Lynch, 2004), even if this strategy has drawbacks in terms of opening the market to new entrants (Porter, 1980) and exposing core competencies to imitation and substitution (Piachaud, 2005). In comparison with the other firm-specific variables, the objectives of collaboration are studied in the literature even more restrictively; not only are they studied in relation to the perspective connected with the direction of openness, but also mainly in relation to one of the two directions, i.e. with the inbound process. Hence, for this firmspecific variable, too, there is a gap in the research literature which needs to be filled, that being an analysis of the impact exerted by collaboration objectives on the open innovation models.

174

Managerial-Organizational Actions Supporting Open Innovation and OI Models Managerial-organisational actions allow open innovation to be pursued easily and more deeply, Some of these actions include the commitment of top management to promote the transition towards an open innovation approach (Vanhaverbeke, 2006; vandeMeer, 2007; Chiaroni et al., 2009, Pisano & Verganti, 2008); the need for a champion supporting the integration of external technology into an existing product development phase–gate process (Chesbrough, 2006; Chesbrough & Crowther, 2006); the exploitation of the personal relationship of the R&D managers for starting technological collaborations; the formal evaluation of collaboration objectives and risks, as well as the analysis and selection of the potential partners with a formal and explicit process (Sakkab, 2002; Huston & Sakkab, 2006). Although the works cited have shed light on how organizational and managerial factors facilitate the implementation of open models, we believe that enriching this line of inquiry with new empirical evidence is in any case quite important.

The Impact on Performance The debate is still open on whether and how openness degree and contextual factors impact on innovative and economic performance. The results are still quite limited and contradictory, although very recent contributions (Chiang & Hung, 2010; Sofka & Grimpe, 2010) shed more light on the topic. A widely accepted assumption is that the relations between openness degree and performance must be analyzed considering the moderator role of external environmental moderators (e.g. patent protection status: Lichtentaler, 2009; Slowinsky & Zerby, 2008; MacCormack & Iansiti, 2009). Indeed, regarding performance, it should be noted that the analysis of the company’s financial

Firm-Specific Factors and the Degree of Innovation Openness

performance is a complex topic due to the fact it can be explained only by considering a wide set of factors that can have contrasting effects. Probably, the concept of innovative performance (Chiang & Hung, 2010; Sofka & Grimpe, 2010) is more understandable. The impact of open innovation models on innovative performance has been analysed in terms of a company’s competence base, development costs, time to market and the level of innovation of new products/processes. Literature is unidirectional in showing the impact of the outside-in process on the access and integration of internal company capabilities with new and complementary knowledge of external firms (Gassmann and Enkel, 2004). Instead, literature results are not unidirectional as far as the reduction of development time is considered: for instance, on one hand, Gassmann and Enkel (2004) state that the benefits of co-operation are seen in an improvement in the competitive position and in risk minimisation, but not in a reduction of development time; on the other hand, according to Kolk and Püümann (2008) firms not concentrating on Open Innovation strategies fail, as rising development costs and shorter product life cycles make it increasingly difficult to justify investments in innovation. Other studies (e.g. Dahlaner & Gann, 2007) show that relationships with other actors help firms to increase the level of innovativeness. In summary, as suggested by the literature listed above, certain relationships between the selected firm-specific variables and the openness degree are still controversial or lacking in depth. Below, we suggest improving the empirical evidence available by adopting a perspective based on number/typology of partners and the number/ typology of phases, with particular reference to Italy, where partnerships are desired by many subjects, including institutional ones, though the issue is still poorly studied.

RESEARCH DESIGN AND METHODOLOGY Survey Design The empirical study has focused on companies located in Lombardy, a Northern Italian region; in 2008 the companies had applied for funding from the Chamber of Commerce to conduct innovative activities within different manufacturing sectors, including the mechanical and machinery sectors, as well as in sectors dealing with automotive, metallurgy, textiles, food, electronics, chemicals, pharmaceuticals, plastic, rubber, paper and paperboard, publishing and printing, wood and wood products (NACE rev.2 codes). This engagement in innovation by such companies, combined with the fact that Lombardy is marked by a particular propensity for innovation (if measured by the number of patents, Lombardy ranks first among the Italian regions according to the European Patent Office data for Italy elaborated by the Unioncamere Observatory of Patents and Brands, 2008) make them very interesting topics of innovation study. The data was collected by means of questionnaires distributed by email to participants. The advantages of such a method include low cost, completion at the respondent’s convenience, absence of time constraints, guarantee of anonymity and reduction of interviewer bias (Forza, 2002). Its shortcomings, on the other hand, are represented by lower response rate as compared to other methods, longer completion times and greater effects due to the lack of both interviewer involvement and open-ended questions. The survey tool was conducted as a questionnaire whose items regarded company characteristics (sector, size), innovation strategy; organization for innovation; collaborations and innovative performance, as will be clarified in more detail below.

175

Firm-Specific Factors and the Degree of Innovation Openness

Before sending the questionnaire to the companies, a pilot test was conducted to assess the quality of the measure items. The items were tested by a group of senior managers and academics with working experience in innovation. They were asked to analyze the questionnaire in order to eliminate items not having strong content validity. After this stage, the resulting questionnaire was sent to the key informants of the companies that we identified as the R&D manager (if present in the company) or the company owner, if deeply involved in the definition of the company’s innovation strategy (as is very common in Italian companies).

Statistical Analysis Among the companies that have applied for funding (about 500) 99 firms have responded during a four-months period in 2009 (i.e. with a response rate equal to 20%). A general premise should be made as concerns company size (in terms of number of employees and revenues): except for few big subjects, the size of the studied companies can be classified as middle/small2. This imbalance can hardly be avoided because it is due to the intrinsic major sectoral composition in Lombardia, where the small size plays an important role. If, from the one hand, it is also found in non-respondents and thus it protects against the potential non-response bias, on the other hand it may prevent capture size differences when we will analyze firms characterized by different openness degrees. We must therefore bear in mind that this cannot make next comparisons between companies significant because of the intrinsic nature of the sample. However, this is the typical situation in Lombardia as well as in Italy. As clarified above in the theoretical background, we adopt the partner variety and the phase variety as relevant variables to represent and to investigate the degree of openness. Regarding their operation-

176

alization, we used subjective measures based on four-point Likert-type scales (1=strongly disagree; 4 = strongly agree) as given in the Appendix. In order to better specify the partner variety and the phase variety we introduced the variables: intensity of collaboration with partner and intensity of collaboration on phases that make up the innovation funnel (measures also based on the Likert-type scale). The study of correlations between these two variables allowed us to understand which are the most typical combination partner/phase and thus to characterize the innovation process in practice. To study firms’ approaches to open innovation, we firstly carried out a cluster analysis (“complete linkage method”, recommended when researcher wants to identify groups which are distinct from each other as much as possible; Barbaranelli, 2006) based on the partner variety and the phase variety. Secondly, concerning the firm-specific variables, with which we intended to describe the companies belonging to different clusters, we carried out the following procedure. Items of the questionnaire were defined on the basis of scales already used in previous works or coming from partial reworking of such scales (still Likert-type). Anyway, we applied to the gathered data an exploratory factor analysis (principal axis factoring as extraction method and promax rotation in the case of initially unclear solution) in order to delete weakly related items and to understand the factor structure and the measurement quality. An evaluation of the Eigenvalues and the Scree plot were used to identify the number of factors to retain. In addition, all factor loadings were above the acceptance level of 0.50 (Hair et al., 2006; Barbaranelli, 2006; Cheng and Shiu, 2008), thus indicating the unidimensionality of the various factors. These were saved as variables and employed in the subsequent analysis. The factors/ firm-specific variables were the following (see the Appendix for detail):

Firm-Specific Factors and the Degree of Innovation Openness

Objectives of collaborations classified in two factors: 1. aims to extend skills, competences and creativity (three items, inspired by the work of Huang et al., 2009; Cronbach’s α: 0,71); 2. aims to share risks and costs (two items, based on Calantone and Stanko, 2007; Cronbach’s α: 0,84). Approach to innovation: technological aggressiveness with emphasis on radical innovation (five items, inspired by Lichtenthaler and Ernst, 2009, that use suggestion by Brockoff and Pearson, 1992. We re-adapted the scale also on SURVEY TOOL 2.1 basis, a questionnaire sponsored by Industrial Research Institute, Cronbach’s α: 0,71) Organizational and managerial actions for open innovation (five items, scale based on SURVEY TOOL 2.1, Cronbach’s α: 0,85) Some other variables, not presented in Appendix, were measured directly (and eventually transformed in logarithmic scale to improve normality), such as: • • • •

R&D intensity (i.e. percentage of R&D expenses/sales) Revenues (i.e. to operazionalize size) Number of employees (i.e. to operazionalize size) Indicators of company’s performance (ROA – Return On Assets - and ROS – Return On Sales).

As concerns company’s results, also a factor representing innovative performance was defined (five items reported in the Appendix, our scale based on Calantone et al. (2002); Cronbach’s α: 0,82). After all, dummy variables were included for: the type of industry; the existence of organizational unit specifically devoted to support collaboration; the type of organizational structure used by companies for innovation activities (inputoriented, output-oriented, matrix; Chiesa, 2001).

Finally, as concerns data analysis, we applied the one-way variance analysis (i.e. ANOVA), in order to appreciate differences among clusters in terms of scale variables, and Chi-square test to compare the frequency on nominal variables.

RESULTS Figure 2 illustrates the results of cluster analysis based on the partner variety and the phase variety. This has resulted in a solution with four groups of firms. The decision on the number of clusters has been determined by the criterion that suggests of stopping the aggregation process at the stage that precedes the one with the highest increase in the coefficient of agglomeration (Barbaranelli, 2006). In the four-cluster solution, the variance inside clusters is about 21% whereas the variance among clusters is about 72% (F-tests sig. <.001). Despite the quite high correlation between partner variety and phase variety variables, which suggests that most firms adopt open or closed innovation approach on both dimensions, small intermediate clusters - 2 and 3 - exist (i.e. they open their innovation process more strongly in one direction rather than in the other) and thus they are worth to be analyzed although they only provide clues for further analysis. Cluster 1 refers to the open innovators, companies that make up the largest group. From data about partner and phase variety variables (reported in Table 1), we found that these companies are really able to manage a wide set of technological relationships, that impact on the whole innovation funnel and involve a wide set of different partners. Although the open innovators strongly collaborate especially with the supplier in the engineering and experimentation phases3, many other types of partners (particularly, firms operating in different sectors of activity, customers, universities, technical and scientific service companies, governmental institutions) are involved at different stages (especially in the idea generation,

177

Firm-Specific Factors and the Degree of Innovation Openness

Figure 2. Results of cluster analysis

experimentation and engineering). An example is a medium-sized company from the machinery industry that conceptualizes and produces boilers for industrial use. Cluster 4 refers to the closed innovators, companies that form the second largest group. From data in Table 1, we realized that these companies access to external sources of knowledge only for a specific, single phase of the innovation funnel and typically in dyadic collaborations. The prevalent partners are in fact suppliers and customers, especially on the idea generation phase. Particularly little-used in the closed companies are the collaborations with universities and firms operating in different sectors of activity. A good example here is a small-sized textile company that has declared in some follow-up interviews, carried out after data-analysis stage, to follow a traditional innovation approach (i.e. internal research and development procedures “jealously preserved”) by using the low-intensity contribution of its customers and suppliers on the idea generation phase. The companies in the smallest cluster 2 can be named integrated collaborators. Already found in the evidence emerged by a multiple case-study in a previous work (Lazzarotti & Manzini, 2009), these companies are the most

178

similar to the closed ones: collaborations are with few types of partners (typically suppliers and customers), but instead of being tightly focused on one stage, they can be extended to the whole funnel. This means that the integrated collaborators “share” with their few trusted partners the whole process of innovation. An example is a small company in the electronics industry that produces and commercializes panels and electrical equipment: suppliers and customers, with whom the company has a longstanding relationship, support it through the whole process of innovation. Finally, companies in the other small cluster 4 can be classified as specialized collaborators. Already also emerged in our previous work, they form a group similar to open innovators regarding the variety of partners (suppliers, customers, universities, governmental institutions) but they concentrate their collaborations in a single/few points of the innovation funnel (typically the idea generation and the experimentation). From the follow-up interviews, these companies still seem a “bit behind the open”, but it is a matter of time: with increasing confidence in partners, the cooperation will also increase by covering all the innovation process. An example here is a mediumsized company in the electronics industry that open to many partners (universities and governmental institutions as well as the traditional customers and suppliers) the idea generation phase. To analyze differences across clusters, in particular the open and closed ones, one-way variance analysis (i.e. ANOVA) has been used for comparing means of scale variables (i.e. company’s size expressed by revenues and number of employees, R&D intensity, approach to innovation, types of objectives, organizational and managerial actions for open innovation, performance expressed by innovative performance) and Chi-square test has been employed to compare the frequency on nominal variables (i.e. type of industry, existence of organizational units supporting collaborations). It must be said that the scarcity of observations on clusters integrated and specialized makes not

Firm-Specific Factors and the Degree of Innovation Openness

applicable Chi-square tests as well as the results regarding scale variables are often not significant. Anyway, although the following evidence is useful above all to compare open and closed companies, some clues on other two clusters also emerge and thus, if interesting, they will be briefly presented in order to deepen them with next research. Regarding R&D intensity, we found significant difference among open and closed clusters (see Table 1): the open companies invest more on average than the closed companies. This finding provides support for the assumption that firms consider open innovation as complementary with internal R&D and not a substitute (Lichtenthaler, 2008). This is consistent with the theory of absorptive capacity (Cohen & Levinthal, 1990, Zahra & George, 2002) in the sense that to be able to absorb from the outside, a company must have the appropriate skills and competences. This does not mean that the closed invests little, just it seems they invest less than open. As clues relatively to integrated and specialized clusters, interestingly the integrated shows the lowest average of R&D intensity whereas the specialist is more similar to the open one. Perhaps the integrated innovator invests internally less because it relies on a few trusted collaborators along the whole innovation process. In addition, in similar vein with previous absorptive capacity interpretation, Chi-square tests on internal organizational structure for innovation activities show that the input-oriented one (i.e. where people are organized according to their specific area of expertise, whose growth is continuously fed - Chiesa 2001) is typical for open innovators rather than for closed (for which an informal type of organization is prevalent). Indeed, the competence-building receives also a formally structured attention and thus it could suggest competence is considered a pre-requisite to openness. As concerns size (see Table 1), we did not find significant differences among clusters. However, we reiterate that this may be due to the inherent imbalance of the investigated sample (i.e. high

weight of medium-small sizes for companies) that reflects the Lombardia’s and Italy’s condition. But what perhaps we can say is that Italian companies, despite being small, are nevertheless brought to open up to outside sources, in keeping the stream of literature that argues that small firms behave like this (van de Vrande et al., 2008). Groups do not seem different even for type of industry (see Table 2). As suggested by the follow-up interviews, the degree of open innovation seems to be mainly determined by the individual strategic choice of a company rather than by industry characteristics (for similar evidence, see Lichtenthaler, 2008). As concerns approach to innovation, with emphasis on radical innovation rather than incremental innovation, we found that the open cluster has a higher mean (in the factor score resulting by factor analysis) than the closed and this difference is statistically significant. This is consistent with the literature and empirical evidence that suggest that companies, when focalized on radical innovations, must collaborate because they are not able to internally develop all relevant knowledge (Lichtenthaler, 2008; Perrons et al., 2005). “Relevant knowledge” that our data seem to suggest is coming from a higher degree of openness in term of wide partner variety and wide phase variety. Interestingly, the specialized, although very little, shows a mean higher than integrated, which might suggest that perhaps the partner variety is more relevant. Regarding the type of objectives pushing companies to collaborate, open cluster shows higher mean (and statistical different) in the first-type goal “aim to extend skills, competences, creativity” with respect to closed companies. Very similar to each other (and in intermediate position between open and closed), the integrated and the specialized cluster. This finding suggests that companies look for competences and creativity by opening up in some way: to a wide variety of partners (even if on few phases), to a wide variety of phases (even if with few partners) or, at the highest level, in

179

Firm-Specific Factors and the Degree of Innovation Openness

Table 1. Information on the clusters and main differences (scale variables) Variables

Sample (n=99)

Cluster 1 (n=43) Open

Cluster 2 (n=9) Integrated collaborator

Cluster 3 (n=11) Specialized collaborator

Cluster 4 (n=36) Closed

Significance (Anova test)

Partner and phase variables Partner variety

2.63

3.44

1.89

3.18

1.67

.000

Phase variety

2.61

3.49

3.11

1.82

1.67

.000

Intensity of collaboration with University and Research centres

1.38

1.59

1.16

1.36

1.18

.005

Intensity of collaboration with Technical and Scientific Service Companies

1.37

1.56

1.29

1.05

1.25

.02

Intensity of collaboration with Governmental institutions

1.11

1.20

1.00

1.18

1.01

.03

Intensity of collaboration with customers

1.70

1.77

1.56

1.80

1.61

.63

Intensity of collaboration with suppliers

1.93

2.12

1.80

1.87

1.74

.17

Intensity of collaboration with competitors

1.09

1.08

1.18

1.29

1.03

.01

Intensity of collaboration with firms operating in different sectors of activity

1.40

1.61

1.29

1.33

1.19

.04

Intensity of collaboration on Idea generation

1.51

1.62

1.38

1.52

1.39

.11

Intensity of collaboration on Experimentation

1.56

1.72

1.35

1.69

1.36

.000

Intensity of collaboration on Engineering

1.44

1.61

1.40

.1.32

1.29

.002

Intensity of collaboration on Manufacturing set up

1.34

1.49

1.13

1.26

1.22

.002

Intensity of collaboration on Commercialization

1.28

1.35

1.35

1.25

1.18

.23

Revenues (Log)

7.35

7.5

7.5

7.35

6.9

0.53

Employees (Log)

1.52

1.63

1.58

1.66

1.32

0.41

R&D intensity (Log)

0.59

0.86

0.20

0.59

0.35

.01

Innovation approach

-0.04

0.33

-0.07

0.30

-0.47

.000

Objective of extending skill and competence

-0.20

0.45

-0.13

-0.11

-0.47

.000

Objective of sharing risks and costs

0.02

0.28

-0.29

-0.13

-0.22

.05

Organizational and managerial actions for OI

0.01

0.37

0.26

0.34

-0.61

.000

Firm-specific contextual variables/factors

continued on following page

180

Firm-Specific Factors and the Degree of Innovation Openness

Table 1. Continued Variables

Sample (n=99)

Cluster 1 (n=43) Open

Cluster 2 (n=9) Integrated collaborator

Cluster 3 (n=11) Specialized collaborator

Cluster 4 (n=36) Closed

Significance (Anova test)

Performance Innovative performance

-0.04

0.30

0.08

0.29

-0.48

.001

ROS (Log)

0.73

0.76

0.80

0.65

0.70

0.89

ROA (Log)

0.78

0.78

0.69

0.75

0.81

0.94

both directions. Similarly, the second-type goal of sharing risks and costs is related to the degree of openness in our conception. It is also interesting to note the prevalent objective in each cluster. Whereas in open cluster the main goal is the first, closed companies are pushed to open by the objective of sharing costs and risks. As concerns the organizational and managerial actions, open cluster shows an average intensity on these tools statistically higher than closed (integrated and specialised still similar each other and in intermediate position between open and closed). As suggested by literature (Pisano & Verganti, 2008) these type of actions are necessary to ensure successful collaborations and this is confirmed by our evidence. Integrated and specialised have got a lower degree of openness (the integrated

lower than the specialized) and probably a lower complexity in the collaborations. Thus, it is not necessary to introduce high-intensive managerial and organizational actions. Also a significant Chisquare test on the existence of an organizational unit supporting collaboration (see Table 2) gives evidence of the organizational and managerial differences between open and closed approaches. Regarding performance (see Table 1) we obtained only some preliminary indications and mainly focus on innovative performance. Indeed, we believe that the analysis of overall company’s performance is a complex topic due to the fact it can be “explained” only by considering a wide set of factors that can have opposite impacts. With this premise, we studied the differences between clusters only with an explorative purpose to define

Table 2. Information on open and closed and main differences (dummy variables) Variables

Sample (n=99)

Cluster 1 (n=43) Open

Cluster 4 (n=36) Closed

Significance (Chi-square test)

Industry Mechanic/machinery

41%

46%

34%

0.29

Metallurgy

14%

12%

18%

0.38

Textile

8%

7%

9%

0.7

Food

4%

5%

3%

0.7

Electronics

7%

7%

6%

0.9

Chemical/pharmaceuticals

10%

14%

6%

0.42

Organization input-oriented

44%

53%

33%

.05

Existence of organizational unit supporting collaboration

35%

47%

22%

.02

Organizational context

181

Firm-Specific Factors and the Degree of Innovation Openness

next steps of research and in terms of innovative performance (i.e. factor that is a combination of five items). We found that open cluster seems more performing than closed (and better than the sample average). Moreover, by studying correlations between innovative performance and partner variety, we found a high and significant relation. Particularly strong were the relations between the single item “The company’s competence base was enlarged” and partner variety and “the level of innovativeness of new products/processes was improved” and still the partner variety, suggesting that the open is more innovative and that the innovativeness seems to be linked to the partner variety. Another clue for this type of interpretation is given by the specialist innovative performance: higher than integrated just in these two items. Anyway, it is important to keep in mind that they are only clues, not confirmed by the analysis of company’s overall performance (measured by means of ROS and ROA), that is even greater in the closed than in the open cluster. Thus, further investigation on performance is surely required.

here, that is difficult to generalise because of the limited number of companies included in these clusters. Open and closed innovators actually emerge from this analysis as two significantly different open innovation models, especially in terms of: •

•

DISCUSSION In this chapter, different models for open innovation are studied, by means of a survey conducted among 99 Italian manufacturing companies, with respect to two variables: the partner variety and the innovation phase variety. Although these two variables are highly correlated (.71; p<.001), intermediate cases (i.e. companies for which the two variables are different in their value, low or high) were found among companies. As a result, four different models for open innovation were found in the practice of companies: open innovators, specialised collaborators, integrated collaborators, closed innovators. The two extreme models – open and closed - are far more diffused (in coherence with the correlation found between the two variables), so the intermediate ones need a more dedicated analysis to confirm what is emerging

182

•

Approach to innovation: open innovators are those who choose an aggressive technology and innovation strategy, in which they work to be technological leaders, to come first to the market with new products, to lead the technology evolution with superior know-how, to pursue even radical innovations. In other words, it can be argued that opening the innovation process to a wide variety of partners and all along the innovation funnel is conceived as part of an aggressive strategy; R&D intensity: open innovators invest more in R&D than closed, and this in some way confirms the difference in the strategy for the two clusters; aggressive innovators spend significantly more in R&D and, as part of their effort, they spend for opening up their innovation process. Another interesting explanation of this result refers to the need to invest in internal competences in order to be open, as the absorptive capacity of the company is critical to identify and exploit potential collaborations and exchanges with external partners. In perfect coherence with this result, there is evidence that an input-oriented organisational structure for the R&D activities, which maximises the absorptive capacity, is typical for open innovators rather than for closed; Type of objectives: in coherence with the two results above, open innovators, with respect to closed ones, mainly open their innovation process to achieve benefits related to internal competences, i.e. to deepen and integrate the knowledge base, to in-

Firm-Specific Factors and the Degree of Innovation Openness

•

•

crease creativity and flexibility, to achieve excellence in knowledge production. On the other side, closed innovators are rather focused on reducing the costs and risks of innovation, by sharing them with external partners; Organisational and managerial actions implemented to support openness: open innovators have actually modified their organisational structure and management techniques, by introducing roles, routines and tools especially dedicated to the design, development and implementation of collaborations with external partners; The results concerning the two “intermediate” models of open innovation, i.e. specialised collaborators and integrated collaborators, are less robust, because of the limited number of companies found for these two clusters. As a consequence, only some tentative interpretation of the achieved results can be put forward. However, it is relevant to reflect on such results since they can represent the starting point for a future research aimed at verifying whether these two open innovation models can actually represent a valid alternative to open and closed models and, if so, in which specific context conditions. By making a synthesis of all results achieved for specialised and integrated collaborators, it seems that there is a sort of “continuum” in the openness of companies, in terms of the most relevant context conditions emerged in this study, as shown in Figure 3.

Figure 3 clearly shows that specialised and integrated collaborators can be really considered as “intermediate” models: the most significant variables that characterise the open and closed models, in fact, have values that are between the two extremes4. Integrated and specialised collaborators are thus viable options for companies

that don’t have a highly aggressive approach to innovation and that don’t want to invest too much for opening up the innovation process. As a consequence, these companies have limited expectations in terms of benefits deriving from open innovation, but do not want to completely abandon the opportunity to access to external sources of knowledge and competencies. As an example, let’s take a specialised collaborator, the electronic company cited above: the general manager wanted to spend a limited amount of resources on studying opportunities for opening the innovation process, but, at the same time, R&D managers clearly felt the need to integrate their knowledge with external contributions coming from other industries, universities, excellent research centres. As a consequence, they decided to open only the idea generation phase to a wide variety of partners. Even in terms of performance the four models are different and a first tentative conclusion in this sense is that the degree of openness is positively correlated to the innovative performance: from closed innovators to open ones the level of innovative performance increases (in terms of new products and services, time to market, level of novelty, learning, costs for new products). But this does not seem to have an effect on the company’s economic performance in the short term, as already discussed above. This result is in contrast with other studies (Lichtenthaler 2009), which found a positive correlation between the degree of openness (measured in terms of intensity of outbound licensing) and the economic performance (measured through ROS and ROI). In our opinion, the relation between performance and open innovation is very complex to be studied: performance is intrinsically a multi-dimensional concept (think, just to quote a well known framework, to the balanced scorecard concept), as well as the degree of openness. This can probably lead to many different measures for evaluating the relationship between openness and performance that certainly requires further in depth studies.

183

Firm-Specific Factors and the Degree of Innovation Openness

Figure 3. Specialised and integrated collaborators between the two extreme models (C=closed innovators; I=integrated collaborators; S= specialised collaborators; O=open innovators)

CONCLUSION AND FUTURE RESEARCH DIRECTIONS Our area of research is related and contributes to innovation because collaborations and networks (in particular, technological collaboration), and the proper ways to manage them, are today largely recognized as means to improve, or at least to support, firms’ innovation capabilities (Chesbrough, 2006). The study is conducted by means of a survey involving 99 Italian companies operating in manufacturing industries. Different models for open innovation are found in the practice of companies: open innovators, specialized collaborators, integrated collaborators, closed innovators. The two extreme models – open and closed - are far more diffused and actually emerge as two significantly different open innovation models, in terms of approach to innovation, R&D intensity, type of objectives, organizational and managerial actions implemented to support openness. The two intermediate models - specialized and the integrated collaborators - although in need of further empirical investigation, provide evidence in support of Chesbrough’s (2003b) theoretical proposition that businesses may be located along an Open Innovation Continuum.

184

In conclusion, the chapter introduces a new perspective that integrates both the number/typology of partners and the number/typology of phases, in order to understand if such perspective can confirm the existence of different open innovation models. Moreover, it provides useful managerial implications because it suggests that OI is not an “on/off” choice, but it can be interpreted and adopted with different degrees (Chesbrough, 2003b), consistently with the company’s specific context. Thus, intermediate open innovation models (i.e. integrated and specialized collaborators) are viable options for companies that do not have a highly aggressive approach to innovation and that do not want to invest too much for opening up the innovation process. As a consequence, these companies have limited expectations in terms of benefits deriving form open innovation, but do not want to completely abandon the opportunity to access to external sources of knowledge and competencies. We suggest that intermediate models for opening the innovation process can be a first relevant topic for future research; performance of open innovation can be a second one and, finally, a third one may concern the study of open innovation models in a dynamic perspective, i.e. analyzing the path followed by companies to open their innovation process (Chiaroni et al., 2009).

Firm-Specific Factors and the Degree of Innovation Openness

Adopting a dynamic perspective, the different models found in this study may be interpreted as different steps in a long term path towards open innovation: starting from a closed innovation process, companies may gradually open to a very limited set of well known partners (suppliers and customers) in a integrated collaboration model, or may decide to open only a single phase of the innovation process to a wide variety of partners with a specialized collaborator approach. Some of the cases studied in a previous work (Lazzarotti & Manzini, 2009) seem to confirm this hypothesis. A future research with longitudinal case studies can probably improve the understanding of this dynamic path to open innovation. Finally, it should be noted that the number of respondents is still very limited. Moreover, it is studied only the relationship between some firm-specific factors and the degree of openness (defined specifically in terms of partner variety and phase variety): a wider investigation is recommendable to include more contextual factors, i.e. external/environmental ones, or more variables that can help to define the openness degree.

Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation capability and firm performance. Industrial Marketing Management, 31, 515–524. doi:10.1016/ S0019-8501(01)00203-6

REFERENCES

Chesbrough, H. W., & Crowther, A. K. (2006). Beyond high tech: Early adopters of open innovation in other industries. R & D Management, 36, 229–236. doi:10.1111/j.1467-9310.2006.00428.x

Barbaranelli, C. (2006). Analisi dei Dati: Tecniche Multivariate per la Ricerca Sociale. LED Edizioni. Brockhoff, K., & Pearson, A. (1992). Technical and marketing aggressiveness and the effectiveness of research and development. IEEE Transactions on Engineering Management, 39, 318–324. doi:10.1109/17.165413 Brown, S. L., & Eisenhardt, K. M. (1995). Product development: Past research, present findings and future directions. Academy of Management Review, 20(2), 343–378.

Calantone, R. J., & Stanko, M. A. (2007). Drivers of outsourced innovation: An exploratory study. Journal of Product Innovation Management, 24, 230–241. doi:10.1111/j.1540-5885.2007.00247.x Cheng, C. J., & Shiu, E. C. C. (2008). Re-innovation: The construct, measurement and validation. Technovation, 28, 658–666. doi:10.1016/j. technovation.2007.08.002 Chesbrough, H. W. (2003a). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press. Chesbrough, H. W. (2003b). The era of open innovation. MIT Sloan Management Review, SPRING, 2003, 35–41. Chesbrough, H. W. (2006). Open business models: How to thrive in the new innovation landscape. Boston, MA: Harvard Business School Press.

Chesbrough, H. W., & Teece, D. J. (1996). When is virtual virtuous? Organizing for innovation. Harvard Business Review, 74(1), 65–71. Chiang, Y. H., & Hung, K. P. (2010). Exploring open search strategies and perceived innovation performance from the perspective of inter-organizational knowledge flows. R&D Management. Special Issue Open Innovation, 40(3), 292–299. Chiaroni, D., Chiesa, V., & Frattini, F. (2009). The open innovation journey: How firms dynamically implement the emerging innovation management paradigm. Technovation, 29(9), 588–595.

185

Firm-Specific Factors and the Degree of Innovation Openness

Chiesa, V. (2001). R&D strategy and organization, managing technical change in dynamic contexts. London, UK: Imperial College Press.

Gassmann, O. (2006). Opening up the innovation process: Towards an agenda. R&D Management. Special Issue Open Innovation, 36, 223–228.

Chiesa, V., & Manzini, R. (1998). Organising for technological collaborations: A managerial perspective. R & D Management, 28(3), 199–212. doi:10.1111/1467-9310.00096

Gassmann, O., & Enkel, E. (2004). Towards a theory of open innovation: Three core process archetypes. Paper presented at R&D Management Conference, Lisbon, Portugal.

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152. doi:10.2307/2393553

Global Business Summit. (2010). Crescita e sfide globali, Il Sole 24 ore. Harvard Business Review, Milano, May, 17-18.

Dahlander, L., & Gann, D. (2007). How open is innovation? Paper presented at DRUID Summer Conference. Appropriability, Proximity, Routines and Innovation, Copenhagen, CBS, Denmark, June 18 – 20. De Backer, L.-B. K. V., & Martinez, C. (2008). Open innovation in a global perspective: What do existing data tell us? (OECD Science, Technology and Industry Working Papers). OECD publishing. doi:10.1787/230073468188. Enkel, E., Gassmann, O., & Chesbrough, H. (2009). Open R&D and open innovation: Exploring the phenomenon. R & D Management, 39(4), 311–316. doi:10.1111/j.1467-9310.2009.00570.x Enkel, E., Gassmann, O. & Chesbrough, H. (2010). The future of open innovation. R&D Management, special issue open innovation, 40(3), 213-221. European Commission. (2005). The new SME definition. User Guide and Model Declaration. Bruxelles, Belgium: Enterprise and Industry Publications. Forza, C. (2002). Survey research in operations management: A process-based perspective. International Journal of Operations & Production Management, 22(2), 152–194. doi:10.1108/01443570210414310

186

Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2006). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall. Huang, Y., Chung, H., & Lin, C. (2009). R&D sourcing strategies: Determinants and consequences. Technovation, 29, 155–169. doi:10.1016/j.technovation.2008.08.002 Huston, L., & Sakkab, N. (2006). Connect and develop: Inside Procter and Gamble’s new model for innovation. Harvard Business Review, 85, 58–66. Keupp, M. M., & Gassmann, O. (2009). Determinants and Archetype users of open innovation. R & D Management, 39(4), 331–341. doi:10.1111/ j.1467-9310.2009.00563.x Kolk, A., & Püümann, K. (2008). Co-development of open innovation strategy and dynamic capabilities as a source of corporate growth. Journal of Economic Literaturem, (n.d), 73–83. Laursen, K., & Salter, A. (2006). Open for innovation: The role of openness in explaining innovation performance among U. K. manufacturing firms. Strategic Management Journal, 27(2), 131–150. doi:10.1002/smj.507 Lazzarotti, V., & Manzini, R. (2009). Different modes of open innovation: A theoretical framework and an empirical study. Journal of Innovation Management, 13(4), 1–22.

Firm-Specific Factors and the Degree of Innovation Openness

Lichtenthaler, U. (2008). Open innovation in practice: An analysis of strategic approaches to technology transactions. IEEE Transactions on Engineering Management, 55(1), 148–157. doi:10.1109/TEM.2007.912932

Perrons, R. K., Richards, M. G., & Platts, K. (2005). What the hare can teach the tortoise about make-buy strategies for radical innovations. Management Decision, 43, 670–690. doi:10.1108/00251740510597707

Lichtenthaler, U. (2009). Outbound open innovation and its effect on firm performance: Examining environmental influences. R & D Management, 39(4), 317–330. doi:10.1111/j.14679310.2009.00561.x

Piachaud, B. (2005). Outsourcing technology. Research Technology Management, 48(3), 40–46.

Lichtenthaler, U., & Ernst, H. (2009). Opening up the innovation process: The role of technology aggressiveness. R & D Management, 39(1), 317–329. doi:10.1111/j.1467-9310.2009.00561.x Linder, J. C. (2004). Transformational outsourcing. MIT Sloan Management Review, 45(2), 52–58. Lundvall, B. A. (1992). National systems of innovation: Towards a theory of innovation and interactive learning. London, UK: Pinter. Lynch, C. F. (2004). Why outsource? Supply Chain Management Review, 8(7), 44–51. MacCormack, A., & Iansiti, M. (2009). Intellectual property, architecture, and the management of technological transition: Evidence from Microsoft Corporation. Journal of Product Innovation Management, 26, 248–263. doi:10.1111/j.15405885.2009.00656.x MINE SURVEY TOOLS 2.1 (n. d.). École Politechnique Montreal (Survey), Social Sciences and Humanities Research Council of Canada, Industrial Research Institute. Available on www. minesurvey.polymtl.ca Osservatorio Unioncamere Brevetti e Marchi Report. (2008). Osservatorio Unioncamere Brevetti e Marchi Report. ISBN: 886077067X ISBN-13: 9788860770677.

Pisano, G. P., & Verganti, R. (2008). Which kind of collaboration is right for you? Harvard Business Review, (December): 1–9. Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. New York, NY: Free Press. Sakkab, N. (2002). Connect & develop complements research & develop at P&G. ResearchTechnology Management, 45(2), 38–45. Slowinski, G., & Zerby, K. W. (2008). Protecting IP in collaborative research. Research and Technology Management, November-December, 58-65. Sofka, W., & Grimpe, C. (2008). Managing search strategies for open innovation – The role of environmental munificence as well as internal and external R&D. Discussion Paper No. 08-075, Centre for European economic research. Sofka, W., & Grimpe, C. (2010). Specialized search and innovation performance – Evidence across Europe. R&D Management, Special Issue Open Innovation, 40(3). Szulanski, G. (1996). Exploiting internal stickiness: Impediments to the transfer of best practice. Strategic Management Journal, Winter Special Issue, 17, 27–43. Trott, P., & Hartmann, D. (2009). Why “open innovation” is old wine in new bottles. International Journal of Innovation Management, 13(3), 715–736. doi:10.1142/S1363919609002509

187

Firm-Specific Factors and the Degree of Innovation Openness

van de Vrande, V., deJong, J., Vanhaverbekec, W., & deRochemont, M. (2008). Open innovation in SMEs: Trends, motives and management challenges. Technovation, 29, 423–437. doi:10.1016/j. technovation.2008.10.001 van de Vrande, V., Lemmens, C., & Vanhaverbeke, W. (2006). Choosing governance modes for external technology sourcing. R & D Management, 36(3), 347–363. doi:10.1111/j.14679310.2006.00434.x vandeMeer, H. (2007). Open innovation — The Dutch treat: Challenges in thinking in business models. Creativity and Innovation Management, 6(2), 192–202. Vanhaverbeke, W. (2006). The interorganisational context of open innovation. In H. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), Open Innovation: Researching a new paradigm (pp. 205–219). Oxford, UK: Oxford University Press. von Hippel, E. (1988). The sources of innovation. New York, NY: Oxford University Press. Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, re-conceptualization and extension. Academy of Management Review, 27, 185–203.

base through the integration of suppliers, customers and external knowledge sourcing (Gassmann & Enkel, 2004). Open Innovation: Firms rely increasingly on external sources of innovation, which means that ideas, resources and individuals flow in and out of organizations (Chesbrough, 2003a). Open Innovation Continuum: Innovation models which the firms follow are not exclusively open or closed, but rather show varying degrees of openness. Between the two pure models - open or closed - there are many shades of grey and the dichotomy between open vs. closed is artificial (Chesbrough, 2003b; Dahlaner & Gann, 2007). Outbound Open Innovation (Inside-Out Process): Earning profits by bringing ideas to market, selling IP and multiplying technology by transferring ideas to the outside environment (Gassmann & Enkel, 2004). Technology Aggressiveness: Firms with aggressive technology strategies constantly developing new technologies that are superior to the technologies of their competitors. R&D activities of firms with aggressive technology strategies are usually highly specialized. Based on this specialization, the firms tend to focus on radical rather than incremental innovations (Brockhoff, & Pearson, 1992; Lichtenthaler & Ernst, 2009).

KEY TERMS AND DEFINITIONS

ENDNOTES

Absorptive Capacity: The ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends (Cohen & Levinthal, 1990). Closed Innovation Model: In closed innovation model a company generates, develops and commercializes its own ideas. This philosophy of self-reliance dominated the R&D operations of many leading industrial corporations for most of the 20th century (Chesbrough, 2003b). Inbound Open Innovation (Outside-In Process): Enriching the company’s own knowledge

1



2



188

The other two items are: the specialization of the company’s R&D activities and the high importance of development activities (the D part of R&D) relative to the firm’s overall R&D activities (Lichtenthaler and Ernst, 2009). We applied the criteria suggested by the EU (European Commission, 2005) for classifying firms on the basis of their size. Specifically, an autonomous company is classified as: (i) small, if the number of workers is < 50 and turnover is <= 10 million € or the

Firm-Specific Factors and the Degree of Innovation Openness

3



annual balance sheet total is <= 10 million € (ii) medium, if the number of workers is between 50 and 250 and turnover is between 10 and 50 million € or the annual balance sheet total is between 10 and 43 million €; (iii) large, if the number of workers is > 250 and revenues > 50 million € or the annual balance sheet total is > 43 million €. Data about correlations between intensity of collaboration with each typology of partner

4



and each typology of phase are not reported in this chapter but they are available upon request. Only R&D intensity is lowest in the case of integrated collaborators, but this is coherent with the fact that closed innovators need to invest a lot in R&D, since they have to develop internally all tangible and intangible resources needed for innovation.

189

Firm-Specific Factors and the Degree of Innovation Openness

APPENDIX 1. Partner variety: in the last five years you have collaborated with a wide variety of external actors 2. Phase variety: in the last five years you have collaborated on a wide variety of phases. 3. Intensity of collaboration with (each) partner: in the last five years you have collaborated very strongly with the following partner (University and Research centres, Technical and Scientific Service Companies, Governmental institutions, Customers, Suppliers, Competitors, Firms operating in different sectors of activity). 4. Intensity of collaboration on phase: in the last five years you have collaborated very strongly on the following phases (Idea generation, Experimentation, Engineering, Manufacturing set up, Commercialization). 5. Objectives of collaboration a. aims to extend skills, competences and creativity: i. Enlarge the company’s competence base ii. Increase the flexibility of the internal organization iii. Stimulate creativity and idea generation capability b. aims to share risks and costs: i. Reduce or share the risks of innovation ii. Reduce or share the costs of innovation 6. Approach to innovation (technology aggressiveness) a. Investing for technological leadership b. Aggressive acquiring new business areas by means of innovation c. Influencing the industry structure and rules by means of products characteristics d. Trying to recruit the best researchers and experts available on the market e. Giving emphasis on radical rather than incremental innovation 7. Organizational and managerial actions for open innovation a. Top management is committed towards the maximization of the collaborations results b. Personal relationship of the R&D manager are exploited to start technological collaborations c. For each collaboration, there is a “champion” acting as a facilitator for the collaboration success d. The company formally evaluates the objectives and risks of the collaboration e. The company analyses and selects the potential partners with a formal and explicit process 8. Innovative performance a. The company’s competence base was enlarged b. The average development costs of new products/processes was reduced c. The time to market of new products / processes was reduced d. The level of innovativeness of new products / processes was improved e. Sales volume and market acceptance of new products was improved

190

191

Chapter 11

Effects of Product Development Phases on Innovation Network Relationships Christina Öberg Lund University, Sweden

ABSTRACT In research literature, product development has frequently been associated with four distinct phases: introduction, growth, maturity, and decline. While these phases have been related to and used for the study of product life cycle, market strategies and competition, less or no attention has been given to the subject of Innovation Network Relationships (INRs), and more specifically, to whether and how INRs are affected by these Product Development Phases (PDPs). Based on a literature review of Resource Dependence Theory (RDT) and four case studies, this chapter contributes by discussing how various INRs are affected by PDPs of an innovative firm. Findings include: (1) the specific needs and resource dependence by the innovative firm during different PDPs affect the status of the firm’s INRs, whereas new relationships are built and old ones are finished; (2) during product development, the INRs become increasingly complex where network parties become negative resources of the innovative firm through increased uncertainty being introduced into previous relationships; and (3) the development of INRs cannot be captured on a dyadic level, but various parties’ relationships with one another need to be considered.

DOI: 10.4018/978-1-61350-165-8.ch011

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Effects of Product Development Phases on Innovation Network Relationships

INTRODUCTION Studies on products and markets often describe their development as consisting of four phases: introduction, growth, maturity, and decline (Christiansen, Varnes, Gasparin, Storm-Nielsen & Vinther, 2010; Levitt, 1965). These PDPs would expectedly follow one another, and companies would act differently in the various phases (Moon, 2005). The phases have been described in terms of how a company should act in marketing, and what the competition looks like during the different phases (Lehmann & Winer, 2008). The PDPs could, however, also be considered in terms of INRs. INRs here describe the ties to external parties that an innovative firm is connected to by means of contracts, collaboration, ownership, or business deals. Thus, they include relationships with both equity and non-equity partners, as well as pure business partners. An innovative firm describes a new venture that was created to market a new product or service idea. External parties have proven to be important for the development and prosperity of a company (Baldwin, Hienerth & von Hippel, 2006; Heide & John, 1990; Johnsen, Phillips, Caldwell & Lewis, 2006; Magnusson, 2003; Thomke & von Hippel, 2002; Öberg & Grundström, 2009), yet less seems to be known about how the relationships with these parties are affected by the development of an innovative firm. The purpose of the chapter is to discuss various INRs and how they are affected by the PDPs of an innovative firm. Various network parties are discussed based on their roles as suppliers, customers, finance bodies, and so on, and how they are affected by the phases of development (introduction, growth, maturity, and decline). The chapter shows that: (1) the specific needs and resource dependence by the innovative firm during different PDPs affect the status of the firm’s INRs, whereas new relationships are built and old

192

ones are finished; (2) during product development, the INRs become increasingly complex where network parties become negative resources of the innovative firm through increased uncertainty being introduced into previous relationships; and (3) the development of INRs cannot be captured on a dyadic (between two parties) level, but various network parties’ relationships with one another need to be considered. The concept of negative resources is developed in the chapter to express how relationships of a company may be negative in that company’s relationship with other firms. Negative resources thus describe assets or relationships of a company, and mean that other companies become less inclined to establish or maintain a relationship with the firm. This chapter contributes to the field of RDT through discussions on negative resources in terms of connected relationships and how such relationships need to be incorporated to fully understand the development of dependence, resource provision and balance/ imbalance between them. This chapter further contributes to research into business networks by showing that business relationships may develop and expire as a consequence of an innovative firm’s PDPs. In addition, this research contributes to the field of innovation by demonstrating how these PDPs involve different needs and dependencies on network parties. The chapter is structured as follows. The next section describes the theoretical point of departure, RDT, and also refers to the PDPs and INRs. Thereafter, the method is described. The empirical part of the chapter is based on four case studies of innovative firms. These are summarized after the method section and then analyzed in terms of the development phases, the network parties, and whether and how RDT explains the effects on network relationships in the various phases. The chapter ends with conclusions and ideas for further research.

Effects of Product Development Phases on Innovation Network Relationships

THEORETICAL FRAMING This section outlines the theoretical point of departure, RDT, and briefly introduces research on PDP and network relationships in innovations.

A Resource Dependence View on Network Relationships RDT was developed from power-dependence (Emerson, 1962; Högberg, 1999) to explain why companies commit into business relationships with one another and the consequences of such relationships. The power-dependence idea suggests that relationships would only continue as long as there is a balance between power from one firm’s perspective and dependence from its business partner’s point of view. The idea thus focuses on the dyadic level of relationships to explain their continuity. When not in balance, four basic strategic alternatives would expectedly apply: (1) the party with less power withdraws from the relationship; (2) extension of the power network, leading to bounding with and creating new relationships; (3) emergence of status, where the party with less power is given status recognition; or (4) coalition formation, meaning that alliances are created with other actors. This consequently means that when a relationship becomes imbalanced, this would potentially lead to other parties being considered or that changes are induced on the dyadic level. RDT developed from this (Pfeffer & Salancik, 1978), while focusing more on how companies should make themselves as little dependent on other parties as possible. Consequently, RDT replaced the discussion on power with a similar one on resources. Dependence and uncertainty became those variables to minimize, while simultaneously optimizing company autonomy. Pfeffer (1972) used this argument early to explain mergers (cf. Katila, Rosenberger & Eisenhardt, 2008; Thompson, 1967), while the alliance literature has explained joint ventures and similar as

a means to decrease uncertainty (Doz & Hamel, 1998; Gomes-Casseres, 1996). The wider network aspect of resource dependence suggests that other relationships are kept to ensure that alternatives are available, to decrease dependence on a single party and to maintain options should the first relationship become imbalanced to the detriment of the company. While much of the focus in power and resource dependency theory remains on the dyadic relationship level, a wider network is consequently considered, however mostly as rescue plans or to decrease imminent dependence on a single actor. Network parties may act as alternatives to decrease dependence on existing business partners, or may become allies to retain a balance towards business partners.

Phases of Development The product life cycle is frequently used in marketing and product management research to depict how products, or even companies or industries progress (Agarwal, Sarkar & Echambadi, 2002; Rink & Swan, 1979; Tellis & Crawford, 1981; Van De Ven & Scott Pole, 1995). Levitt (1965) outlined the product life cycle as consisting of market development/introduction, growth, maturity, and decline. The introduction phase describes how a product is first brought to market without there necessarily being a demand for it, and without it necessarily having reached complete functionality. The growth phase is marked by increased demand and competition. Maturity describes how the product reaches a peak in terms of number of users, while also decreasing the number of new users. The decline phase refers to how customers abandon the product. Each phase means new challenges, and these could be expected to focus on various types of resource needs, and consequently also affect resource providers, dependence between firms and thereby network relationships in different ways.

193

Effects of Product Development Phases on Innovation Network Relationships

Network Parties in Product Development Several researchers have highlighted external parties in innovations. Von Hippel (1978), for instance, describes customers in idea generation. Lee, Lee and Pennings (2001) focus on venture capitalists. Chandra and MacPherson (1994) describe consultants, suppliers and customers in product development. Öberg and Grundström (2009) summarize external parties to innovative firms in the following categories: innovators, financial backers, non-equity partners, owners, suppliers, customers, and public bodies. It is thus evident that various network parties provide the innovative firm with different resources, and the resource provision could, as argued in this chapter, be expected to vary with the PDPs of the innovation. But how are the network relationships then affected by the various PDPs?

METHOD This chapter is based on case study research. The case study method enables the exploration of data and allows additional analyses on previously collected data (Dul & Hak, 2008; Yin, 1994). Case study research is often criticized for not allowing generalization of findings. However, many case study results would be expected to be transferable to other situations and cases (Hirschman, 1986). Such arguments are further strengthened if similar findings are repeated between various cases studied while not being the reason for their selection. Those particular companies studied here are innovative firms in mature industries. They have all gone through the phases of introduction and growth and reached a phase of maturity or even decline, which made them suitable for this chapter. They were chosen based on how they represent various innovations, and their different reasons for founding the companies (technology-

194

driven or customer initiative). The case companies however share resemblances in terms of how they now are part of mature industry structures, and that they have relied on external parties for support in their early developments. The data collection for the four case studies consisted of interviews with owners, venture capital companies, managers, innovators, customers, suppliers, and other external parties. A total of forty-one interviews were conducted between 2003 and 2008. The interviews were complemented with a secondary data analysis to gather background data on the firms and check the accuracy of interviews (Welch, 2000). Results from the interviews have previously been presented in Öberg and Grundström (2009). The article by Öberg and Grundström (2009) focused on challenges and opportunities related to the development of innovative firms’ networks, and was explorative in that sense. Compared to this study, the present chapter deals with effects on INRs and use the RDT lens to understand such relationship effects. It further relates network parties to various PDPs. In the analysis procedure, notes from interviews, interview transcripts and secondary data were coded. The coding was first performed to capture the content of the individual interviews, and as a second step to compare data on a crossinterview, cross-case basis. The second step also entailed the analysis of the data using the framework of RDT and the division of development into PDPs. Findings from the four cases presented in this chapter confirm each other through indicating similar findings (Guba & Lincoln, 1989; Hirschman, 1986). An additional four case studies have recently been performed to further ensure the transferability of the findings from this chapter. Thus, and as a consequence, the findings suggested in this chapter could be expected to be general (with certain case-specific differences) for INR effects in various phases of innovative firms’ development. Further, the conclusion on

Effects of Product Development Phases on Innovation Network Relationships

how various INRs need to considered beyond their dyadic relation with the innovative firm finds support beyond those specific circumstances of innovative firms, and contributes to RDT through describing network relationships as positive and negative resources of a firm.

EMPIRICAL FINDINGS This section summarizes the four cases through describing them in the various phases of development. All four companies are small or middle-sized companies with a turnover running from six to two-hundred million SEK, and with five to fifty employees. Companies B and D are the largest of the firms, while Companies A and C still have less than ten employees each. They were founded in the 1980s to the early years of the 21st century, Company B being the oldest of the firms. When they were first established, they all operated on the Swedish market, but have since expanded into new geographical markets. Three of the companies (Companies A, B and D) are today part of multinational industry groups, while Company C remains domestically owned.

Introduction Phase The four cases studied all describe companies developing software solutions, either to be implemented in other products or to be sold as standalone solutions. Three of the companies (Companies A-C) developed their innovations based on technological ideas, while the fourth (Company D) based its innovation on a customer initiative. This was also the company that developed the standalone solution. Those three companies (Companies A-C), that were not initially backed by a customer providing ideas and financial resources, became dependent on such actors as venture capital companies or incubators in their early development. The three companies

also had strong foundations in university environments. For one of the companies, its financial backers were industrial actors in the industry the company aimed for (Company A), while the other two companies (B and C) were supported by venture firms with good knowledge on how to develop companies but less knowledge on the specific innovations developed. “They were financial bodies, first and foremost with no actual knowledge on our product.” (Company C.) An industry-related venture firm allowed for contacts with other firms through its network, while those supported by pure financial bodies developed skills in how to get to market, without these skills being specifically encompassed by the company and without it leading to any inherited relationships. The innovative firm built on a customer initiative (Company D) relied heavily on the customer to understand specific needs related to the product, and the customer also helped in spreading the innovation to other customers. “Often when we are about to invest in a new system, we check if any colleagues have it.” (Customer to Company D.)

Growth Phase All four companies managed to establish relationships with other industry actors: suppliers, additional customers or money providers. In the early phases of development, there was no conflict of interest between these parties, although several of them actually were competitors. Additional relationships were mainly established during the growth phase, and network parties then helped the innovative firm to grow through providing initial income (Company D) and financial resources to the innovative firm (Companies A-C).

195

Effects of Product Development Phases on Innovation Network Relationships

The network parties’ reasons for doing so much related to expectations on future returns: in terms of return on investments (venture firms), in terms of own revenues (customers and suppliers), or in terms of those products provided (customers). Venture firms had an explicit exit plan, and hence connected such returns to that point, while other network parties often saw returns as long-term and as benefitting the parties in also other than financial terms. “It was clear from start that their (the venture firms’) interest was only temporal.” (Company B.) Relationships were often strong and close, and thus marked by a difference in time between experienced dependence and resource provision between the innovative firm and its network parties.

Maturity Phase To secure financial resources long-term, the innovative firms were acquired. The acquired parties (that is, the innovative firms) were active to various extents in those processes, but clear for all cases is that the firms looked for long-term financial solutions for further growth at that point in time. “A new owner was needed if we should be able to develop further.” (Company C.) The acquisitions meant that the companies indeed reached those financial resources provided, but also meant a lessened focus on developing innovations further. This was either a consequence of the acquirer having other intentions with the firm (Company C) or resulted from a more restricted innovation process than previously (Companies A, B and D). In addition, the acquisitions meant that previous business partners distanced themselves from the innovative firm (Companies A-D). The acquisitions largely meant that the innovative

196

firms reached a maturity phase. Network parties experienced competition with the acquirers, either because they were competing industry parties (Companies A and B), or as a result of how the acquisitions changed their abilities to realize those long-term intentions that the network parties had had with the innovative firm (Companies A-C). Thus, for network parties, the acquisitions introduced an imbalance in their relationships with the innovative firms. Those future resources accounted for previously would not be realized, and the connection between the innovative firm and its new owner constructed a negative resource in that way, as well as a result of competition. For network parties, the maturity phase hence caused them to lose resources accounted for previously.

Decline Phase Unless the acquisition was performed successfully, the innovative firm reached a decline phase. This resulted from network parties no longer providing ideas, in combination with the performance and actions of the acquirer. Such declines were foremost seen in two of the four cases (Companies C and D). In the first of these (Company C), the acquirer only had interest in part of the innovative firm, and hence, the rest of the company was not given sufficient resources to continue, at the same time as those network parties that had previously supported its development decided to dissolve their relationships with the innovative firm. The other case (Company D) describes how the acquirer continued to make additional acquisitions. These subsequently drained the acquirer’s financial resources, in turn affecting the innovative firm and finally ending up in liquidation of the acquirer and the innovative firm. Network parties experienced this decline as fewer resources being provided, and also that expectations on future resources increasingly disappeared. Dissolutions or further distancing in network relationships followed.

Effects of Product Development Phases on Innovation Network Relationships

ANALYSIS Based on the cases, it seems apparent that several different network parties contributed resources to various extents, and at various times, to the development of products and the company established for the sake of the product. The innovative firm equally became dependent on these resources for its development. As new parties entered, such dependence decreased while also leading to increased uncertainty among network parties, resulting in the possibility of new relationships being considered as negative resources by the network parties. The introduction phase was marked by innovators providing knowledge skills related to the innovation, and customers or financial bodies providing financial resources to enable possible growth. These network parties were affected by the introduction phase in terms of how it provided them with the potential for future business opportunities; hence, the resource balance between the innovative firm and its network parties was based on how resources provided were expected to equal future returns. Such returns were expressed in terms of finances for venture firms, and in longer-term perspectives for innovators. To customers, it was instead dependence on future resource provisions (in terms of the innovation as a complete functional product) that drove the customers to that phase, where they were dependent on the innovative firm for its knowledge in those specific areas that the customers did not comprehend themselves. Relationships during the introduction phase were close, yet often marked by how companies only included a limited amount of resources and actors in them. There was a balance between the expectations for future returns and the dependence on these external parties by the innovative firm. The growth phase mostly entailed similar network parties as in the introduction phase. However, more customers or venture firms were included in the network. Similar balances, as in the previ-

ous phase, made them continue their relationship with the innovative firm, where the potential for returns in terms of actual products increased, and hence also for financial returns, while the per-party dependence of the innovative firm decreased. Incubators or universities in this phase realized that their resources were no longer needed, and such relationships were often dissolved. The innovative firm was not as dependent on their resources, and in their constructs as incubators, the innovative firm no longer provided the right fit. What is more, based on additional parties being included in the network (e.g., more customers), each party’s importance for the innovative firm decreased, potentially causing an imbalance in individual relationships. Resources provided by the innovative firm were less customized, for instance, and less attention was paid to individual needs as a consequence, thus creating an increased distance in relationships with customers. For network parties, however, those other established relationships of the innovative firm often were considered as positive resources of the innovative company that vouched for its continuity. Additional customers increased the likelihood of successful developments, for instance. Therefore, while individual relationships became increasingly distanced, they still remained. Little conflict was seen between various relationships in this phase, and they were thus considered rather as positive resources of the innovative firm, decreasing uncertainty in the relationship. Similar to the introduction phase, the growth phase meant that relationships were close, while also being marked by less-specific resources and actors of those network parties. The maturity phase was in the cases reached through acquisitions. These acquisitions further increased the distance in existing network relationships, or caused them to dissolve. Previous research has related acquisitions to how a balance can be recreated in relationships, or how they may be a means to decrease dependence and uncertainty (Pfeffer, 1972). This chapter, however, shows that the maturity phase meant that an imbalance

197

Effects of Product Development Phases on Innovation Network Relationships

was created as a consequence of the acquisitions. This imbalance can be explained twofold. First, the network parties faced how their future positions with the innovative firm were challenged, and therefore reevaluated their relationships as future resources from the innovative firm would not meet their needs. Second, the relationship established between the innovative firm and the acquirer could be seen as a negative resource, resulting in less present positive resources from the innovative firm. The negative resource in terms of the ownership ties with the new owner resulted from competition between those other network partners and the owner, or was a consequence of other network parties intending to acquire the innovative firm. Such an acquisition would not take place, since the innovative firm had found another owner. The network parties did not automatically choose another party to compensate the loss, which underlines how, while they were the parties taking the initiative to dissolve the relationships, they did not dissolve the relationship as a result of other options. Two of the companies reached the decline phase. Such a phase is marked by less competition and also decreasing customer interest (Levitt, 1965). This affected network relationships in terms of how customers dissolved their relationships with the company, a consequence of them not thinking that the innovative firm provided resources that were sufficiently attractive. At this point, network relationships had been increasingly distanced during the maturity phase, and were also marked more by business-related buyer-seller conditions than by financial resource provisions. The decline phase can be described as how business partners dissolved their relationships as a consequence of their dependence on the firm actually decreasing. Other alternatives were indeed available, but such dissolutions resulted rather from disappointments in the present relationship than from the attractiveness of other options. While decreasing dependence would normally make a company more inclined to continue its relation-

198

ship with a firm, the decreasing dependence was less than the perceived decline in the need for the resource. Table 1 summarizes the various phases. The figures (i) to (iv) refer to the various ways a company would be expected to react based on RDT, when the relationship with another party becomes imbalanced: (i) withdrawal of the party with less power from the relationship; (ii) extension of the power network, leading to bonding with and creating new relationships; (iii) emergence of status, where the party with less power is given status recognition;, or (iv) coalition formation, meaning that alliances are created with other actors. Based on Table 1, certain issues would need to be addressed compared to RDT. For one thing, it is not certain that it is the party that negatively experiences an imbalance is the one to act. Rather, as seen in the decline phase, the stronger party was the one withdrawing from the relationship. Secondly, relationships of the network partners may need to be considered, thus extending the focus beyond the dyadic level of analysis. Here, they are introduced as positive and negative resources, depending on whether they bring credibility to the innovative firm or lead to competition between such parties and the acting network party.

CONCLUSION This chapter discussed how INRs are affected by PDPs of innovative firms. Findings of a literature review on RDT and case studies were: 1. the specific resource needs of the innovative firm during various phases of development leads to new INRs being established while previous ones are dissolved, 2. during the development, the network becomes increasingly complex, also leading to competition between network parties, and

Effects of Product Development Phases on Innovation Network Relationships

Table 1. Innovative Firms and Network Parties in the Various Phases Innovative firm

Network parties

Balance/Imbalance

Introduction

Dependent on resources (financial and idea generation)

Expectations on future returns as resource

Balance

Growth

(ii) extension of the power network, leading to bounding with and creating new relationships Decreased dependence on individual parties as network grew

(i) the party with less power withdraws from the relationship Incubators, universities withdrew

Imbalance: network parties’ power decreased.

Maturity

(iv) coalition formation, meaning that alliances are created with other actors

(i) the party with less power withdraws from the relationship Parties dissolved their relationships as the innovative firm’s connection with its acquirer was considered negative, also increasing uncertainty

Imbalance through acquisition: network parties perceived acquirer as negative resource of the innovative firm, leading to a decrease in resources.

Here the party that became less dependent withdrew (in contrast to (i)).

Imbalance through network parties’ decreased dependence.

Decline

3. the development of INRs cannot be captured on a dyadic level, but various parties’ relationships with one another needs to be considered, where relationships as positive and negative resources become a means to capture network parties’ impact on a relationship. RDT suggests that the reason that the dyadic relationships are there in the first place is the company’s needs for resources provided by others, since it cannot make everything itself. If relating this to INRs during various PDPs of an innovative firm, this would suggest that the innovative firm’s resource needs vary with the PDPs. As a consequence, the innovative firm would choose to establish yet also dissolve relationships with different network parties (Alajoutsijärvi, Möller & Tähtinen, 2000; Dwyer, Schurr & Oh, 1987) as it develops. Such changes in resource needs would consequently affect the INRs. Secondly, the innovative firm would establish new relationships to outweigh possible imbalance in existing ones, and the firm would aim to decrease its dependence on individual parties through either alliances with other firms or by dissolving relationships in imbalance. From the network parties’ perspectives,

similar considerations would be anticipated: the network parties would keep their relationships with the innovative firm as long as they provide them with relevant resources (presumably in terms of innovations or returns on investments), and they would spread their risks to other parties if their dependence on the innovative firm becomes too strong. While resource dependence theory may be used to explain changes on a dyadic level, as well as why additional network relationships are established (and indeed dissolved), indirect effects in networks are not as easily explained. Such effects include how changes in one dyadic relationship affect others, and may be seen as domino effects along a supply chain or how indirect business relationships affect one another on a network level (Havila & Salmi, 2000; Hertz, 1998). To exemplify the latter, this includes how a dissolved customer relationship may lead to other customers dissolving their relationships with the same supplier. Such other relationships could be accounted for as positive or negative resources of a firm, but this has not previously been addressed in RDT. It could also be described as how increased uncertainty is introduced into a relationship, but this is somewhat different from 199

Effects of Product Development Phases on Innovation Network Relationships

how uncertainty is usually dealt with based on a resource dependence view. It is the business partner that becomes embedded in increased uncertainty, rather than describing uncertainty on behalf of the acting firm. This chapter hence introduces the discussion on negative resources, where these describe how relationships of one party through competition between actors may be negative for other firms. When judging the balance or imbalance in a relationship, these relationships become negative resources of the party and hence lead to an imbalance between dependence and resources in the relationship. The purpose of this chapter was to discuss various INRs and how they are affected by the PDPs of an innovative firm. The findings show that INRs are indeed affected by the different PDPs of an innovative firm. Different decisions are taken by the innovative firm and its network parties as a result of changes in resource needs, dependencies on individual parties, and how relationships with other firms affect relationship decisions. Each new PDP creates a new type of imbalance in resource provision and dependence for the various parties to act upon. These findings contribute to research on RDT and network relationships through pointing at relationships as phase-specific. They contribute to research into business networks through showing that business relationships may develop, yet also expire, as a consequence of an innovative firm’s PDPs. In addition, the chapter contributes to research on innovation through showing how these phases include different needs and dependencies on network parties. This chapter further contributes to the field of RDT, through its discussions on negative resources in terms of connected relationships and how such relationships need to be incorporated to fully understand the development of dependence, resource provision and balance/ imbalance between them.

200

FUTURE RESEARCH DIRECTION This chapter is based on a literature review and empirical findings of four case studies on innovative firms of software solutions. For future research, it would be interesting to perform complementary studies related to other products and services. It would further be of interest to measure innovation performance related to various parties’ participation, to conclude whether or not certain parties are more important than others.

REFERENCES Agarwal, R., Sarkar, M., & Echambadi, R. (2002). The conditioning effect of time on firm survival: An industry life cycle approach. Academy of Management Journal, 45(5), 971–994. doi:10.2307/3069325 Alajoutsijärvi, K., Möller, K., & Tähtinen, J. (2000). Beautiful exit: How to leave your business partner. European Journal of Marketing, 34(11/12), 1270–1290. doi:10.1108/03090560010348434 Baldwin, C., Hienerth, C., & von Hippel, E. (2006). How user innovations become commercial products: A theoretical investigation and case study. Research Policy, 35, 1291–1313. doi:10.1016/j. respol.2006.04.012 Chandra, B., & MacPherson, A. (1994). The characteristics of high-technology manufacturing firms in a declining industrial region: An empirical analysis form western New York. Entrepreneurship and Regional Development, 6, 145–160. doi:10.1080/08985629400000009 Christiansen, J. K., Varnes, C. J., Gasparin, M., Storm-Nielsen, D., & Vinther, E. J. (2010). Living twice: How a product goes through multiple life cycles. Journal of Product Innovation Management, 27(6), 797–827. doi:10.1111/j.15405885.2010.00753.x

Effects of Product Development Phases on Innovation Network Relationships

Doz, Y. L., & Hamel, G. (1998). Alliance advantage - The art of creating value through partnering. Boston, MA: Harvard Business School Press. Dul, J., & Hak, T. (2008). Case study research methodology in business research. Oxford, UK: Butterworth-Heinemann/Elsevier. Dwyer, F. R., Schurr, P. H., & Oh, S. (1987). Developing buyer-seller relationships. Journal of Marketing, 51, 11–27. doi:10.2307/1251126 Emerson, R. (1962). Power-dependence relations. American Sociological Review, 27, 31–41. doi:10.2307/2089716

Johnsen, T., Phillips, W., Caldwell, N., & Lewis, M. (2006). Centrality of customer and supplier interaction in innovation. Journal of Business Research, 59, 671–678. doi:10.1016/j. jbusres.2005.11.003 Katila, R., Rosenberger, J. D., & Eisenhardt, K. M. (2008). Swimming with sharks: Technology ventures, defense mechanisms and corporate relationships. Administrative Science Quarterly, 53(2), 295–332. doi:10.2189/asqu.53.2.295

Gomes-Casseres, B. (1996). The alliance revolution. London, UK: Harvard University Press.

Lee, C., Lee, K., & Pennings, J. M. (2001). Internal capabilities, external networks, and performance: A study on technology based ventures. Strategic Management Journal, 22, 615–640. doi:10.1002/ smj.181

Guba, E. G., & Lincoln, Y. S. (1989). Fourth generation evaluation. Newbury Park, CA: Sage.

Lehmann, D. R., & Winer, R. S. (2008). Analysing for marketing planning. Singapore: McGraw Hill.

Havila, V., & Salmi, A. (2000). Spread of change in business networks: An empirical study of mergers and acquisitions in the graphic industry. Journal of Strategic Marketing, 8(2), 105–119. doi:10.1080/096525400346204

Levitt, T. (1965). Exploit the product life cycle. Harvard Business Review, 43(6), 81–94.

Heide, J., & John, G. (1990). Alliances in industrial purchasing: The determinants of joint action in buyer-seller relationships. JMR, Journal of Marketing Research, 27(1), 24–36. doi:10.2307/3172548 Hertz, S. (1998). Domino effects in international networks. Journal of Business-To-Business Marketing, 5, 3–31. doi:10.1300/J033v05n03_02 Hirschman, E. C. (1986). Humanistic inquiry in marketing research: Philosophy, method and criteria. JMR, Journal of Marketing Research, 23, 237–249. doi:10.2307/3151482 Högberg, B. (1999). In McLoughlin, Damien, & Horan (Eds.), Research about inter-organizational relationships articles in Administrative Science Quarterly. 15th Annual IMP Conference, University College, Dublin.

Magnusson, P. R. (2003). Benefits of involving users in service innovation. European Journal of Innovation Management, 6(4), 228–238. doi:10.1108/14601060310500940 Moon, Y. (2005). Break free from the product life cycle. Harvard Business Review, 83(5), 86–94. Öberg, C., & Grundström, C. (2009). Challenges and opportunities in innovative firms’ network development. International Journal of Innovation Management, 13(4), 593–613. doi:10.1142/ S1363919609002431 Pfeffer, J. (1972). Merger as a response to organizational interdependence. Administrative Science Quarterly, 17, 382–394. doi:10.2307/2392151 Pfeffer, J., & Salancik, G. R. (1978). The external control of organizations - A resource dependence perspective. New York, NY: Harper & Row.

201

Effects of Product Development Phases on Innovation Network Relationships

Rink, D., & Swan, J. (1979). Product life cycle research: A literature review. Journal of Business Research, 7(3), 219–242. doi:10.1016/01482963(79)90030-4

Yin, R. K. (1994). Case study research - Design and methods (2nd ed.), Applied Social Research Methods Series, Vol. 5. Thousand Oaks, CA: Sage Publications, Inc.

Tellis, G. J., & Crawford, C. M. (1981). An evolutionary approach to product growth theory. Journal of Marketing, 45, 125–132. doi:10.2307/1251480

KEY TERMS AND DEFINITIONS

Thomke, S., & von Hippel, E. (2002). Customers as innovators - A new way to create value. Harvard Business Review, 80(4), 74–81. Thompson, J. D. (1967). Organisations in action - Social science bases of administrative theory. New York, NY: McGraw-Hill. Van De Ven, A. H., & Scott Pole, M. (1995). Explaining development and change in organizations. Academy of Management Review, 20, 510–540. von Hippel, E. (1978). A customer active paradigm for industrial product idea generation. Research Policy, 7(3), 240–266. doi:10.1016/00487333(78)90019-7 Welch, C. (2000). The archaleology of business networks: The use of archival records in case study research. Journal of Strategic Marketing, 8, 197–208. doi:10.1080/096525400346259

202

Innovation Network Relationships: Connections between companies that share or contribute in the development of new ideas and projects. Organization Networks: Group of companies connected through business relationship agreements. Per definition an organization network consists of three or more interrelated firms. Product Development Phases (PDP): As developed by Levitt (1965), PDP the stages of products and markets consisting of introduction, growth, maturity and decline. Resource Dependence Theory (RDT): A theory that explains why companies commit into long-term business relationships (Pfeffer & Salancik, 1978). RDT is based on ideas of power-dependence. The underlying idea is that companies want to decrease their dependence on other parties.

203

Chapter 12

Maturity in Innovation Network Management Caspar Van Rijnbach TerraForum Consulting, Brazil Gustavo de Boer Endo TerraForum Consulting, Brazil Suzana Monteiro Leonardi TerraForum Consulting, Brazil

ABSTRACT Companies are focusing increasingly on the creation and maintenance of external networks for innovation. The purpose of this chapter is to introduce the reader to the concept of network management and demonstrate the principal attributes that impact the formation and optimization of innovation networks, based on the network´s objectives, the combination of the characteristics of the network’s participants as well as the network’s organizational format to attract and maintain the partnership. To reach this purpose, we present the results of a benchmark study undertaken in Brazil, the United States of America and Europe between March and June 2009. In this study, we interviewed executives at 24 leading companies known as innovators in their industry. Through the results we were able to identify a maturity model consisting of four levels for innovation network management: initiators, explorers, established and world class.

INTRODUCTION The complexity of current Research, Development and Innovation activities (R,D&I), ever increasing cost of these activities, more sophisticated customer demands and shorter product life cycles, have raised the gap between the need for innovation and what companies can deliver internally. DOI: 10.4018/978-1-61350-165-8.ch012

This situation has stimulated companies to create innovation models based on collaboration with external sources, such as universities, clients, companies from other sectors, or even competitors, searching to improve their innovative capacity and performance. This new framework is being referred to as “Open Innovation”. With the concept of open innovation becoming common, companies are focusing increasingly on

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Maturity in Innovation Network Management

the creation and maintenance of external networks for innovation. Unfortunately, this often occurs without using a holistic approach to the architecture of networks and individual participants. Companies often look at specific competencies that need development and do not evaluate the network composition and its effectiveness based on the specific network’s objectives and its contribution to the overall company strategy. This can create malfunctioning of the networks, not being able to obtain the network’s goals and thereby not having the impact as expected on the companies strategic objectives. Much has been written about innovation networks and their management. Literature includes discussions of how management of external networks differs from the more traditional way of managing strategic alliances (a.o. Gulati, 1998) as well as how to measure the effectiveness of specific networks (a.o. Segil, 2004). We identified an opportunity to research more extensivily how organizations link different types of networks to organizational strategic goals and define methodologies to optimize network composition and architecture. It requires a portfolio view of networks, as already indicated by Vanhaverbeke e Cloodt (2006). For this research we developed a theoretic framework on the ways companies are managing the composition and structure of their innovation networks, measuring the fit between the network’s objectives and the management activities of the company in regards with the network. To develop this theoretical framework, we combined and adapted several theoretical models developed in books and articles from renown authors in this area. The main references we used were: “Alliance portfolios: designing and managing your network of business-partner relationships” (Parise & Casher, 2003), “Open innovation: researching a new paradigm” (Chesbrough & Vanhaverbeke, 2006) and “Effective practices for sourcing innovation” (Slowinski, 2009).

204

Our research was undertaken amongst 24 Brazilian, European and American based firms. Our method was based on testing our theoretical framework mainly through structured, partially qualitative, partially quantitive interviews. This study was for a large part concluded in 2009 and preliminary results of the research were presented during the International Society of Professional Innovation Management (ISPIM) conference in Austria in 2009. Our research amongst the 24 international organizations, showed that some common good practices exist among companies when it comes to open innovation management. Although some practices partly depend on the company’s industry or R,D&I investment levels, we see that many practices are common and their use depends on the company’s level of maturity regarding open innovation networks. The main results from our study therefore was the construction of a maturity model for open innovation, based on four dimensions: strategic, relational, support and organization. We hope this study will contribute to a better understanding of how innovation networks work and how to develop them. The maturity model should contribute to the debate around best practices in network management for open innovation.

INNOVATION NETWORKS Traditionally, Research and Development at large organizations have been handled internally. Large R&D organizations were seen as important assets to their companies and focused on discovering, developing and commercializing technologies and products internally. This type of R&D is called “closed innovation” (Chesbrough & Vanhaverbeke, 2006). However, the complexity of current Research, Development and Innovation activities, ever increasing cost of these activities, more sophisticated customer demands and shorter product

Maturity in Innovation Network Management

life cycles, have raised the gap between the need for innovation and what companies can deliver internally (Slowinski, 2009; Chesbrough, 2007; Van de Vrande, 2007). This situation has stimulated companies to create innovation models based on innovation networks: a set of external sources, such as universities, clients, companies from other sectors, or even competitors that collaborate to improve their innovative capacity and performance. This new framework is being referred to as “Open Innovation” (Chesbrough, 2007). Networks refer to inter-organizational relationships and can range from sparse dyadic, to dense multilateral relations where actors tend to cluster in alliance blocks (Lemmens, 2004). Innovation networks can be formed through various forms of cooperation, as stated by Terra (1999): • • • •

Joint ventures and research corporations Shared agreements for R&D Agreements for technology exchange Direct investments: minority shareholding driven by technology factors

• • • • •

• •

Licensing agreements Networks for Subcontracting Research associations Joint research programs sponsored by governments Computer databases and networks for exchanging technical and scientific information Informal networks Other networks

Since open innovation primarily refers to establishing of intra and inter organizational relationships, Vanhaverbeke e Cloodt (2006) suggest that the analysis of such relationships should be undertaken in five different levels, with growing degrees of complexity between them, as demonstrated in the following figure. The first level treats the relationship between individuals of the organization for innovation. This level permits us to understand how companies organize themselves internally to take the most advantage of external knowledge acquired and referes to the internal culture of the company which either stimulates or prevents the usage of

Figure 1. Complexity in intra and inter organizational relationships (Fonte: Vanhaverbeke e Cloodt (2006))

205

Maturity in Innovation Network Management

this knowledge and technologies from outside of the company. The second level treats the benefits that a company can obtain with open innnovation and is related to the types of partners and the company’s strategic objectives in relation to its open innovation model. The third level considers the benefits and interests between two or more companues to create links between them. This level is quite well discussed in academic literature about strategic alliances by authors like Gulati (1998), Parkhe and Miller (2000), Arino, de La Torre e Ring (2001), and Parise and Casher (2003). They discuss how to select partners for innovation, evaluate risks and returns, evaluate strategic alignment between two partners and how to generate a strategic alliance over time. The fourth level considers inter organizational networks and studies how a leading company integrates its external relationships within a coherent strategy and manages this over time. This level of analysis takes in consideration that every specific alliance is part of a network of interactions that can either optimize or restrict diadic relationships. Literature by authors such as Das and Teng (2002), Ozkan (2007), Wixted e Holbrook (2008), e Vanhaverbeke et al (2009, focuses on how to manage the portfolio of alliançes and partners. The fifth level consists of understanding how innovative companies are embedded in institutional arrangements and are able to leverage and optimize the innovative efforts of a group of companies gathered in an innovation system that can be can be of local, regional, national, supranational or sectorial dimension. When discussing innovation networks one should contemplate and manage relationships at all five levels, a systemic approach to open innovation. Some authors pledge that networks connect naturally, that they are emergent – a ‘network of organizations’ perspective, others argue that they are created intentionally and therefore can

206

be managed to some extent – a ‘network organization’ perspective (Moller & Rajala, 2007). Our research was undertaken based on the latter view and focuses specifically on the capabilities of the firm to manage its networks. We tried to use a more holistic approach to the management of networks, or what might be called a portfolio view, taking into consideration the five levels as described by Vanhaverbeke e Cloodt (2006), with emphasis on the fourth and fifth level, or what we called, a portfolio view.

A Portfolio View of Innovation Networks Different innovation processes and innovation activities demand different type of innovative capacities. Therefore, typically a company is involved with various partners in different alliances or contracts. Increasing sharing of knowledge and information between these different alliances is a great challenge. The various alliances with multiple partners, form interdependent networks that often compete with each other - both internally and externally - for limited resources (Parise & Casher, 2003). In this situation it will be necessary to develop a portfolio approach to successfully implement innovation network management. A portfolio of partners can be defined as a collection of direct partners of a company that are the central components of a collaborative network. In knowledge-intensive sectors, they have become significant drivers for innovation (Dyer & Nobeoka, 2000; Doz; Olk; Ring, 2000; Das; Teng, 2002; Oskan, 2007). To be able to define a preferred portfolio of partners one should answer the following questions: • •

For which part of the innovation process a partner is required? Which type of partners would be ideal to obtain the companies objectives within the specific part of the innovation process?

Maturity in Innovation Network Management

•

Which combination of partners and commercial type of relationships will optimize knowledge exchange and results within the network?

The portfolio approach provides a clear view of how to manage the network of partners - formed both by allies and rivals. It allows minimizing and diversifying portfolio risk and leveraging synergies of the network of partners as it permits the reflection on the future needs of potential partners and developing processes that enable the sharing of information and knowledge among the network participants.

MANAGING AND FORMATION OF INNOVATION NETWORKS Innovation network management refers to a systematic approach to work with external partnerships along the innovation processes. It includes monitoring and managing the network created by all these relationships, evaluating its performance and results and formulating strategies to improve their performance (Harbison & Pekar, 1998; Man; Duyster, 2002; Nielsen & Mahnke, 2003). With greater involvement and collaboration in the innovation process, a more strategic approach to management of innovation networks becomes necessary, since the agreements governing the relationship between the partners can bring significant risks to the company. There are many challenges of managing a network of collaboration among partners. According to Parise and Casher (2003) the principal challenges are to: • •

Understand the collaborative and competitive dynamics between partners Monitor and understand changes in the business environment which may alter these dynamics

• •

Establish different strategies for each type of network collaboration Understand how each partner selection and its position in the network will affect both individual relationship and overall network performance

When it comes to managing partner networks for innovation, and management of individual partnerships and alliances, one must take into account that these agreements lead to the creation of dense networks of partners linked by direct and indirect relations. External collaboration with different organizations brings with it a high level of complexity related to culture, organizational characteristics and trust. Partnerships are difficult to manage, especially when there are cultural differences between partners (Arino et al, 1997; Camisón; Boronat, Villar, 2007). Understanding the concepts and implications of the formation of strategic alliances to find the best setting and the appropriate partners for the innovation network is a major challenge for open innovation (Van de Vrande, 2007; Lichtenthaler, 2008). One of the factors of complexity in managing partnerships and alliances is that it involves nonhierarchical relations between different institutions and demands an unusual combination of skills from traditional managers: entrepreneurship, business intelligence, cross-cultural diplomacy, and the ability to establish mutual trust and interdependent relationships (Arino; De la Torre & Ring, 2001). In the next few paragraphs we will explore four dimensions of innovation network management one needs to take into consideration to guarantee that these critical and strategic factors are handled correctly: strategy setting, relationship management, support and services and organizational structure.

207

Maturity in Innovation Network Management

Dimension 1. Strategy Setting To make open innovation successful, it is necessary that its objectives are aligned with company strategy and innovation strategy. Five main business objectives are common in the development of partner networks for collaboration, as shown in the Table 1 (Chesbrough & Schwartz, 2007). There are some steps in developing the strategy for the formation of innovation networks (Schlange & Jüttner, 1996 apud OJASALO, 2008): • • •

• •

Understanding of the context: what is the strategic situation to be reviewed? Definition of the actors: which types of actors the network should focus on? Creation of an interdependent matrix: who determines the nature of network relationships? Creation of the desired portfolio of partnerships: where must each partner act? Creation of a strategic matrix: what potential must each actor possess for directing or leveraging the network?

Once having determined the strategic objectives for open innovation, companies should define what partners are best to reach their goals and targets. Some partners are better in helping to reduce risks whilst others are better in bringing cost of development down. Another decision that will direct which partners to choose, is the determination in which technology or business areas to collaborate for innovation. For example, some

firms might be reluctant to open up their innovation process in technologies that are strategic to the company, while others do exactly the opposite with the objective to diminsh risks. External collaboration can be used in different parts of the innovative process, from the generation of ideas through the development of solutions and commercialization of products and technologies, as shown in the following model adapted from Chesbrough (2003). Specific partners work better in different parts of the innovation process. For example, universities are good at scientific and basic research normally, but not considered the right partners for commercialization of technologies. Last, but not least, companies should take into consideration the strategic impact of adding certain partners to their portfolio. For example, a current partner could become a future competitor. It will be necessary to evaluate the risks that accompany the decision to involve this partner in once’s network. Also, companies will need to understand the dynamics and the potential issues that a combination of certain partners might bring (companies of different size, different culture etc.). Part of the innovation network strategy, is the decision on where to locate innovation activities. The logic behind the decision on where to locate is to be either close to innovation competencies, when one seeks more radical innovation and closer to manufacturing when it comes to incremental innovations (so as to be able to quickly deliver small improvements to existing products). Also, innovation activities could be near the customer

Table 1. Objectives for external collaboration in research, development and innovation Objectives

208

Business Requirement

Increase profitability

Lower cost

Shorten time to market

Incorporate already-developed component

Enhance innovation capability

Increase the number and variety of front-end technologies

Create greater flexibility

Share risks with partners

Expand market access

Broaden the pathways to market for products and services

Maturity in Innovation Network Management

Figure 2. Framework for open innovation

so to understand trends and needs. Therefore, the decision on where to locate innovation activities must take in consideration, besides the network strategy, some other factors, such as: access to research structure, ease of recruitment and selection of skilled labor, potential R&D cooperation with Universities, access to new consumers, access to equipment, promoting the image of the company, among others (Westhead & Batstone, 1999). So, defining clearly what the company objectives are and what it wants from its portfolio of partners is central to the success of the network, because only then the process for search and selection of partners can be successfully implemented (Slowinski, 2009). Defining the strategy forms the basis for the next steps, including the definition on how to manage relationships between company and its partners and between partners.

Dimension 2. Relational Diversified portfolios, rich in resources and diverse capabilities enhance the innovative capacity of a company (Ozkan, 2007; Vanhaverbeke et al., 2009). There is a positive relationship between the most innovative companies and the existence

of a complex portfolio of partnerships, with many different elements and geographic locations. In this sense the diversity of partners is even more important to the success of innovation than the number of partnerships (Duyesters & Lokshin, 2007). However, the greater the variety and number of elements in a portfolio of partners the complexity of their management increases (Duyesters & Lokshin, 2007). Although the criteria for inclusion of a partner in the network should be related to the company’s strategic objectives, it is also important to examine potential synergies between different partners that can be leveraged and how network limitations and conflicts can be reduced through development of partners or termination of partnerships. The objective behind these criteria is to ensure that the portfolio value is greater than the sum of the values created by each individual alliance (Parise & Casher, 2003). Mutual trust between partners is a central aspect in the management of partnerships (Parkhe & Miller, 2000; Arino, De la Torre & Ring, 2001; Suseno & Ratten, 2007). However, its constitution is not immediate, it occurs gradually, as the interactions between partners happens. This process of

209

Maturity in Innovation Network Management

building mutual trust is called “relational quality” and is considered the foundation of a successful partnership (Arino, de la Torre, Ring 2001). During the process of partner search and selection for participation in the innovation network and even before the partnership has really developed, confidence is more related to the sense of security, or reliability. Only with time and several interactions confidence will increase and take the full meaning of faith in one’s partner, or trust. The level of trust in a partnership is directly related to previous experiences of partners in other alliances, as well as their organizational capacities and technical skills. The relationship of integrity, reputation and ethical behavior are also extremely important in building trust between partners. This “relational quality” is constantly measured by participants and plays a significant role in the process of building mutual trust (Arino et al., 1997). Another attribution of portfolio management is to understand and manage synergies and constraints that may be generated by the relationship between the partners themselves, also called the interdependencies (Parise & Casher, 2003). Interdependencies exist when one partner is not fully in control of all the conditions necessary to achieve the expected result and is dependent on other partners to gain access to resources, capabilities and competencies. (Vasudevan et al., 2001). Interdependencies can be facilitators when they bring positive impacts to the network and are directly related to the success of the portfolio and can be restrictive and bring negative impacts on other partnerships. Table 2 shows possible facilitative and restrictive interdependencies. These reflections on the ideal design of a partnership portfolio and understanding of possible impacts of the relationship of partners between them should be the basis for the search and selection of partners. On the other hand, mechanisms for attracting and retaining participants should be created, enabling the development and maintenance of optimal innovation network. The need to attract and keep the partner interested to

210

continue participating in the network requires the analysis of other two dimensions for network management as shown next.

Dimension 3. Providing Adequate Support and Services for the Innovation Network Innovation practitioners constantly disagree about the importance of physical location for fostering innovation. Nevertheless, no one neglects the fact that innovation and knowledge transfers occurs in space (Polenske, 2007). Oerlemans, Meeus e Boekema (2003) when discussing the reasons why innovative companies involve themselves in innovation networks state the following motives: •

• •

Get access to complementary resources (knowledge, information, financial and physical resources); Share risks; Create synergies through the sharing of resources;

To be able to attain these goals, it is important that the company offers the potential partners the necessary conditions for sharing of knowledge and experience to happen smoothly (Kratzer, 2007). For this reason, leading innovative companies have ended up focusing on specific geographic areas, because proximity makes it easy and less expensive to provide access to physical space, components, machinery, personal and business services, knowledge and information and also offers quick access to institutions and public services. In addition, a population of companies and organizations geographically interconnected facilitates complementarity between the activities of network participants. It also facilitates the understanding of the needs of partners and increases face-toface contacts (Oerlemans, Meeus, & Boekema, 2003). In summary, geographic proximity affects

Maturity in Innovation Network Management

Table 2. Partners interdependencies Facilitative interdependencies

Restrictive interdependencies

Partners are part of the same collaboration network Partners provide additional resources Partners seek similar technology standard or infrastructure to innovation Partners see opportunity and have the desire to learn from each other Partners perceive other network members as a way to mitigate their own risks

Partners are members of competing networks of collaboration Partners are strong competitive rivals in the sector Partners seek rivals technology standards Exclusivity required by a particular partnership that prevent effective collaboration with other partners

the ability to receive and transfer knowledge and improve network performance. However, to attract potential partners for a specific geographic space, the arrangement should offer facilities and services that complement the partners’ capacities for innovation, to facilitate joint technology development and transfer of knowledge and enable the development and commercialization of innovations. The Support and Services dimension consists of defining the type of infrastructure and services necessary to attract and complement skills and capabilities of potential partners as well as to create conditions that facilitate learning, creativity and sharing of information and knowledge. In this dimension are included: the supply of buildings and facilities to host partners, laboratory infrastructure, equipment, communication systems, technical services, finance, management and technology. When taking into consideration the support and services dimension, companies will make sure that the physical and virtual structures are designed to encourage the flow of knowledge and creativity. To decide which set of infrastructure and support services to offer to their network partners, companies that lead innovation networks will need to consider: • • •

The network’s strategic objectives; Characteristics of the participants that they want to attract; Activities that they wish to facilitate or reinforce.

Table 3 shows some types of support services utilized to attract, develop and retain partners in innovation networks. Clearly, all these services and support, physical facilities, as well as the management of the individual and network relationships require processes, governance and legal structures, as we discuss in the following paragraph.

Dimension 4. Legal and Administrative Organization to Foster Innovation Networks After deciding which partners to work with, what for and where (Strategy), defining the working relationship with individual partners and the network as a whole (Relational), developing the services, physical structures and support required to attract and retain the preferred partners (Support and Services), a company needs to organize management of the network to guarantee systematic and sustainable results.

Governance Structures With a wide range of potential services available to support their network and with a number of partners located in the same area, it will be necessary to establish governance capable to manage relationships, offer services to partners and maintain the infrastructure created to support the network. According to Bibliardi et al (2006), a single model of governance does not seem appropriate,

211

Maturity in Innovation Network Management

Table 3. Types of support services Type of Service

Description

Technology services

Companies that lead innovation networks can offer a suite of technology services to its partners, such as support for testing and technical analysis and help for partners to obtain certifications or technical documentation, among others.

Access to capital

Given that funding for innovation is still faced as a challenge to companies, leaders of innovation networks can promote conditions for the partners to become fit and attractive to receive investment funds from Venture Capital (Romera, 1998) or government. To do so, the leading company offers aid to the development of business plans, business meetings and submissions of projects to government funds for innovation.

Intellectual Property support

Since the transfer of technology is a goal for the network, it is necessary that the network leader offers services to support such activity (Gower, Harris, 1996). Such services are usually performed by specialized partners such as offices or agencies for innovation. The objective is to assure the protection and commercialization of intellectual property for the network.

Training

The network leader can also provide business, technical or technology training directly or through partnerships with educational institutions, according to specific demands presented by the partners (Gower, Harris, 1996).

Support services for business development

Services such as management support - strategic planning, business plans, management, marketing, sales, finance and accounting, human resources management, project management and legal counseling can also be provided by network leaders in order to develop the business skills of its partners (Gargione; Lourenção; Plonski, 2005; Figlioli, 2007).

Operational facilities

Although there are many innovation networks that work without an established physical structure, the proximity of the partners facilitates knowledge and technology transfer and business development. In order to increase this capability it might be necessary to build a specific structure to host not only the partners, offering offices or structure for the operation of business, as well as spaces and infrastructure to conduct its projects and research.

since networks with different objectives and different players, such as the innovation network leaders, network partners, governmental institutions and investment companies, will have different characteristics and therefore different requirements. A large Innovation network with a lot of partners and innovation projects requires forms of governance capable of promoting the interests of the participants. The definition of governance for the network partners must take into account, primarily (Figlioli; Porto, 2007): • • • •

The partners’ leadership; The objectives of the partners; The intensity and importance of partnerships; The legal solution found to accommodate the interests of the actors of the initiative.

Important here is that, although the leader has a central role in the network, it should see itself as part of the network and therefore will need to

212

understand the objectives of the various participants, so to optimize gains for itself as well as for the network as a whole.

Legal Forms of Innovation Networks The legal form or arrangement between the players of the network is important because it will be able to influence and limit the strategic objectives of the network and influence directly the relations between partners. The type of legal form will also influence its governance, how the arrangement will be evaluated and the indicators to be used (Bigliardi et al, 2006). According to these authors, to facilitate leading and managing a company’s network, different types of legal structures might be required or preferred. Many legal and administrative formats are possible, such as: managing organizations without legal personality - being tied to a department of the organization leader - associations, foundations,

Maturity in Innovation Network Management

private companies (publicly traded and privately held) and public companies. The leader of the network might become the single shareholder of this separate legal entity or might divide the ownership with some of its principal partners, or even governmental institutions. All depending on the interest of the different parties involved, regional or national government incentives and regulations and optimization of long term value. The great variety of formal legal structures and consequently of governance in innovation networks is explained by Arranz, Fdez. de Arroyabe (2007) as a result of two main factors: the level of applicability of the type of activity (how easy it is to deploy the technology in the market) and the network’s goals. Activities as applied research and product development possess a high degree of applicability (easiness to deploy the technology in the market) and their evolvement through R&D networks can lead to opportunistic behaviors among the network participants. In this case, formal structures are established due to the fact that new products and patents can be implemented immediately. In the case of activities with low applicability such as basic research or pre commercial applied research, and activities related to the diffusion of knowledge such as training, scientific publications and research databases, formal structure mechanisms do not seem to be as important (Arranz, Fdez. de Arroyabe, 2007).

Processes and Roles in Managing Innovation Networks Networks should be governed by adequate mechanisms and roles to ensure the achievement of desired outcomes (Rampersad et al, 2010). Managing networks will require the implementation of a wide variety of processes and involve the following roles and responsibilities:

• •

•

•

•

•

Prospecting of potential partners; Managing partnerships in R&D projects including issues of intellectual property and commercialization of technology generated by the project; Managing partnerships, including evaluation, feedback, development and eventual disconnecting from partners Management of support services offered - such as management services, finance, marketing and project management to the participants of the network; Management of technology services offered to network members and support for intellectual property protection, the valuation and transfer of technology. Management of the innovation network portfolio – aligning the partner portfolio with corporate and innovation strategy.

Funding of Network Projects In general, financing of innovation networks in literature discusses cases of projects promoted by public institutions, either directly or through universities, foundations, among others. According to Rosenblum (2004), the most common sources of funding for innovation networks are universities, banks, government grants, philanthropic funds and venture capital. Regardless of the nature of the promoter of the venture, opportunities for financing of innovation is influenced by both the legal framework that supports innovation network and by the goals, business model and the results expected by the network: the prospect of future income, the guarantees offered and the revenue stream (Figlioli, 2007).

213

Maturity in Innovation Network Management

Communication, Marketing and Promotion of the Innovation Network In order to attract potential new partners, to receive government support and community approval, it is desirable to promote the innovation network through marketing actions. These might include propaganda via different media, but also promoting debate around the networks objectives at regional or national level, as well as sponsoring of specific events and initiatives related to the networks’ focus. Also, efficient communication between players is crucial to the effectiveness of the innovation network. It can be obtained making information and knowledge available to all network collaborators (Rampersad et al, 2010), besides promoting collaborative forums and network meetings.

Innovation Network Management Model The important aspects discussed above led to the construction of a theoretical model which summarizes the main points for the formation and maintenance of networks for innovation. This model, with four dimensions is shown in Figure 3. The dimensions Strategy, Relational, Support & Services and Organizational were used in our research to determine how companies and institutions organize their innovation networks.

OUR RESEARCH Objectives of the Study The study aimed to determine how companies and institutions organize management of their innovation networks within the four dimensions. We visited and interviewed managers responsible for innovation networks to describe the practices of companies in Brazil, Europe and the United States, verifying the network strategy of the group

214

leader, the structure of the network of partners, their physical infrastructure and services and the solutions used for organizational governance, roles and responsibilities of actors and their legal, managerial and financial formats. During our research we searched to understand the following questions: • •

•

How do renowned companies form and develop their networks for innovation? Are there common practices among the companies that lead to success (a common ground)? Are there logical phases when building one’s open innovation practices (common building blocks)?

The Companies Selected for our Research Our study was undertaken between March and June 2009. The study involved 24 companies, of which twelve in Brazil (three Brazilian companies, nine Brazilian based foreign multinationals), five based in Europe and seven based in the United States of America. The companies for our research were selected based on the following criteria: • • •

Known as innovators in their industry; Possess their own research center; and Work together with several partners.

All of them where large companies and they invested between 1,5% and 6,5% of their revenue in R,D&I. Various sectors were represented in the research, such as the energy, agribusiness, automotive, computer, chemical, electronic consumer goods and telecommunications sectors. These companies, in 2008, all together spent more than US$ 18 billion on R,D&I, employed around 85,000 people in technology development and worked together with over 2,000 partners in their R,D&I processes. Four of the companies (Philips, Nokia, Siemens and DuPont) were ranked among

Maturity in Innovation Network Management

Figure 3. Innovation network management model

the most innovative companies as selected by Business Week (2008). Although our selection process focused on companies with research facilities and large networks, very few companies in Brazil have a long history of extensive and intensive external collaboration. All Brazilian based companies showed a tendency towards more investment in research and more intensive external collaboration along the various phases of the innovation process, even outside Brazil within the near future.

RESULTS Strategy In this dimension we endeavored to understand the role of innovation in a company, the objectives for partnering in R,D&I, the areas in which the company partnered and the type of technology

deployed in the partnership. Furthermore, we discussed where the company located its R,D&I activities and the rationale for such placement.

The Role of Innovation in Strategy In each of the companies we examined, innovation plays a key role. The purpose of innovation is sometimes to support current operations; more often, though, companies have loftier purposes for innovation. For many, innovation is the motor of the company’s future, with pioneering innovations being sought to generate groundbreaking, high-impact products and services that facilitate entering new markets. Partnering plays a vital role in this process.

Open Innovation Objectives Objectives for corporate partnering are myriad, but one stands out: companies partner to obtain

215

Maturity in Innovation Network Management

specific competencies and technologies that they do not possess. The reasons are twofold. In some cases, companies seek outside competencies and technologies because they do not recognize any strategic reason to develop them internally. On the other hand, there are technological competencies that companies want to master but do not possess. By partnering, a company can acquire these competencies and knowledge. The second-most cited objective for partnering is to enhance the execution capacity of the company’s R,D&I. It is well known that companies seek partners to aid them in bringing technologies and products to market more rapidly. This partnering practice is closely related to another significant driver: the search for complementary capabilities in the R,D&I value chain. We touch more upon this below, but for now we can confirm that, as companies position themselves within the R,D&I value chain, they focus their partnering activities mostly on less-strategic parts in that chain. Firms mentioned risk reduction as another partnership objective, but did so less often than expected, given that it is well established that partnering can reduce risk substantially. However, this may be because most interviewees are not especially capital-intensive in their R,D&I investments and no pharmaceutical companies, which ordinarily make major investments in R,D&I, were included in the study. A more surprising outcome from our findings was that various companies recognized important benefits in partnering with universities and institutes, such as being known as an innovative and collaborative company. This reason was especially cited by Brazilian companies, where collaboration in the innovation process is still reasonably new to many. The reasons for partnering and the frequency they were mentioned can be seen below, distinguishing between Brazilian based companies and European and American based firms.

216

Open Innovation Strategy Over the course of our study, we used the basic definition of research and development as set forth by the OECD, which includes basic research, applied research, and experimental development. To that definition we added scientific research while also expanding the other side of the R&D equation to include advanced development and commercialization. This brings together all the fundamental aspects of the technology innovation process. In examining the stages of the innovation process in which companies opt to partner, we discovered that all interviewees collaborate with partners in various parts of the R,D&I process, with most focusing on basic and applied research to develop breakthrough technologies. Some interviewees focus on partnering in development and testing to accelerate implementation of technologies. A few partner with competitors in technology research in the pre-competitive stage but not in the more competitive developmental stages. One of the companies interviewed mentioned that its approach to initiating research is to join or partner with research being conducted at one of the major research institutes to see what is “hot”. That way, the company shares the risk while working on research projects that are industry-strategic. None of the companies interviewed collaborates in scientific research, nor does any even contemplate investing in this type of research with third parties (or at least none explicitly acknowledged doing so). Only a few interviewees partner in the stages of commercialization and licensing of technologies. In terms of partnering in technology, companies largely do not outsource research and development of strategic technologies because of the potential risk in loosing legal control and technological know-how. However, there is one particular exception: companies do outsource research and development of their strategic technologies so

Maturity in Innovation Network Management

Figure 4. Main reasons for partnering

long as their staffs monitor their partners closely, allowing the firms to acquire beneficial knowledge while maintaining control of intellectual property matters related to their technologies.

Defining Strategic Location Our interviewees revealed that the location of their R,D&I activities differs widely. Some companies’ R,D&I locations have been determined historically, usually near their production facilities. Other companies take a more deliberate approach, preferring development to be close to their factories in order to be able to fine-tune solutions for production, and research to be close to world renown universities or world-class technology parks. Technology monitoring normally occurs closer to the end customer. For example, one of the companies interviewed spoke about its “antennas” across the globe to monitor what local competitors are developing in their field and what local universities are working on.

In general, most companies distribute their R,D&I activities over multiple locations. Some have created their own technology parks beside their own research laboratories. These companies are doing more than just searching for competencies worldwide; they prefer to have them located nearby, thus creating their own local technology innovation systems with third parties close at hand. It seems counterintuitive in today’s highly connected world with ready access to people and information anywhere around the globe, but research, development and innovation still seem to function best with face-to-face real-time interaction. The strategy dimension gives direction to all other key dimensions. For instance, partnering objectives define the type of partners sought, the infrastructure and services necessary to support them, and the format for collaboration. The configuration of the other three dimensions depends on what is practiced in this dimension.

217

Maturity in Innovation Network Management

It can be concluded that all the interviewed companies seek to optimize their decision making based on strategic objectives, business constraints (such as budget) and open innovation logic. Not every company has the opportunity to define exactly how to set up its Open Innovation System, but all are well aware of the many potential opportunities.

Relationship In this dimension we explored the composition of the R,D&I networks, specifically with how many and which type of partners the companies collaborate, the role and location of partners and the nature of the partner relationship, and the handling of intellectual property rights.

Network Composition Companies work with a wide range of partners. The firms we interviewed cited partnerships with universities, research institutes, clients, suppliers, consultancies, specialists in technology development, companies that commercialize technologies and governments. Several companies also leveraged “virtual” networks, such as Innocentive, as partners. The most common partners are universities and research institutes. Collaboration with other types of partners often depends on the length of time the company has been working with open innovation. Firms that have a longer history of open innovation collaborate with partners across a wider range of categories. Firms tend to have an abundance of partners when they collaborate in several different stages of the R, D&I process and when they outsource research and development activities for a range of technologies. Our research unveiled some companies that accumulate hundreds of partners, with one company even boasting more than 1,000 partners (including international research programs). Although a vast quantity of partners may seem very impressive, having many partners does

218

not necessarily ensure a more effective network. On the contrary, some interviewees mentioned the importance of having fewer network partners with whom they could execute a wider range of projects. One can argue for either many or few partners. Many partners can facilitate direct access to technologies by creating more choices and fewer difficulties in targeting specific competencies when needed. But a larger network also brings the complex task of managing many relationships. On the other hand, a network with fewer partners gives the firm more control over its network, allowing for more fine-tuned relationships and less intellectual property risks. Although both models have their advantages and disadvantages, collaborating with fewer partners is preferable for strategic technologies because trust and control are critical in such situations. Less strategic technologies can be outsourced to a wider range of potential partners to capture more extensive benefits In terms of the location of partners, even though some companies prefer a local country partner, most partners are global. Companies seek partners that are “best in class” and may in fact be on the other side of the globe. To locate the best partners, our findings indicate that various interviewees use patent and article databases to initiate their searches. Based on their initial findings, they converse via telephone to secure worldwide recommendations in the target technologies. Nevertheless, most of the interviewees reiterated the importance of being close to their partners. One of the interviewees claimed that interaction with the university improved significantly when they moved close to the university, instead of having to travel 20 miles, because of the ease of having face-to-face meetings with students and professors. This again indicates the relevance of proximity and real-time interaction.

Maturity in Innovation Network Management

Figure 5. Types of partners

Role of Partners in Open Innovation Partners can play varied roles in the R,D&I process. As expected, universities and research institutes are increasingly utilized for basic and applied research. Universities are primarily sought for their infrastructure, their exceptional competencies in research, and their ability to generate graduates with master’s degrees and PhDs. Institutes are targeted for their specialization and expertise on general technological industry challenges. In research partnerships, companies also turn to major corporations as development partners. In the context of pre-competitive research, these partners at times may even be competitors. In such cases, the overriding objective is to share risks. Competitors also are selected as partners at national or international consortia that are convened to set industry standards. Companies exhibit certain strong preferences in collaborative habits. One of our interviewees explicitly mentioned that it prefers working with other multinationals, since it finds them more reliable than universities. When partnership objectives are more profit-oriented, partnerships seem to be more effective. Nevertheless, there remain those

that still prefer universities for their deep-rooted research expertise. Partners also are sought as potential sources for ideas and insights, although very few companies in our study rely on this approach. They are more focused on searching for solutions to their research or operational challenges than receiving new ideas from their partners. Virtual networks, like Innocentive, increasingly are being leveraged to solve specific, targeted problems in applied research and early development. Suppliers also play a role by providing new instruments for laboratories and at times can be co-developers. In a few instances clients themselves are co-developers. Consultancies also are enlisted at various stages of the process, depending on their expertise in R,D&I. Companies that partner in the commercialization of technologies rely on a wide variety of actual and virtual partners. Firms that are more advanced in open innovation go further and utilize “supporting” partners, such as venture capitalists, intellectual property agencies, and the government in support of a broader open innovation effort.

219

Maturity in Innovation Network Management

Type of Relationships The types of relationships vary widely: there are one-off contracts, master agreements, joint development contracts, licensing agreements, equity participation and co-participation in national and international programs, among others. The type of commercial relationship logically is defined by the type of relationship sought (for example, strategic or non-strategic, formal or informal) and the objective of the relationship (such as research, solution provisioning, investment, commercialization of technology, etc.) A valuable insight here is that some companies seek out a close relationship with their strategic partners not only through master agreements but also through involvement in their daily affairs in order to facilitate their partner’s understanding of their business. In fact, one of our interviewees calls together its key suppliers to share its strategic “top needs list.”

Intellectual Property Rights All companies generally place great importance on protecting intellectual property rights. Companies that are more sophisticated in their open innovation efforts not only have clear policies in place but also have educated their employees on these policies. This reduces R,D&I employees’ hesitation to participate in open innovation and helps them define what to share and what to withhold. In terms of distributing intellectual property rights, most companies focus on protecting only strategic property rights. According to one of the interviewed firms, “We must guard strategic technology, but non-strategic technology can be made available to generate extra value for the network.” Finally, patents also play a role in negotiating co-development projects when the various parties are expected to leverage some of their own patents to develop a new technology. Best practices in this dimension are mainly a function of a corporation’s maturity (time and

220

experience) in partner relationships. Therefore, the more mature a company is in its relationships, the more types of relationships it normally will have in the various stages of the process, the better it usually defines its relationships and its intellectual property policies, and the more it will broaden its horizons in search for potential partners.

Support and Services In this dimension we discussed with the companies how they attract partners and develop the network as a whole. What support and services do they offer their partners? Do they give partners access to their laboratories and/or invest in their partners’ infrastructure? Do they provide business support and other services to their partners? Do companies proactively manage their networks? And do companies stimulate collaboration and learning between participants in the networks?

Partner and Network Management To attract new partners, the interviewed companies generally rely on their strong reputations, which they all possess in their respective industries. Some use their top-tier facilities to attract partners, whereas others attract partners via ongoing public relationships, for instance through articles authored by individuals within the company. Some companies also open their research departments to interns during the summer months of school vacation. Companies rarely invest in the development of their partners. Except for investing in infrastructure and sponsoring some research projects, there is little evidence that they intentionally aid in developing their partners’ capabilities. Longerterm relationships certainly benefit partners, but even those companies that seek out longer-term relationships remain reluctant to set up plans for developing their partners. Nevertheless, companies in more advanced stages of open innovation occasionally possess a

Maturity in Innovation Network Management

clear partner-development strategy that usually encompasses infrastructure projects, IP policies, business services and other activities, as explained below.

Infrastructure All companies generally support their partners with some degree of access to their laboratories. This seems to be a basic, given provision in partnership agreements. Most also offer engineering know-how or other expertise to assist partners in executing their projects. One of the interviewees trains its customers in its laboratory so that they learn to use the laboratory on their own. Many companies invest in the infrastructure of their partners, especially universities. Some firms also invest directly in their partners’ equity, mostly in the case of technology-based companies. During our study in Brazil, several companies mentioned to face some problems with investing in Universities, since many of the universities do not have the funds for maintenance of the investments.

Business Support and Services Business support and services is the area in which companies most differ in innovation management. On one hand, there are companies that only provide their partners with basic access to laboratories. On the other hand, there are companies that construct a comprehensive local technology innovation system by bringing together, within one physical space, suppliers, consultants, patent offices, venture capitalists, governmental research organizations, contractors, research specialists, etc. In an example of the latter case, one interviewed company offers its partners office space (for a fee), an incubator for technology startups, and a laboratory to conduct experiments and test equipment (in the case of suppliers). In addition, some companies also provide access to a restaurant, a fitness center and childcare facilities to

stimulate a sense of community and to facilitate collaboration and well-being onsite. Other companies also provide partners with apartments and comprehensive support for foreign specialists. Overall, however, the majority of companies do not provide advanced business support and services to their partners.

Collaboration Incentives In terms of partner collaboration, companies that are focused more on generating a network than on a simple set of individual relationships generally maintain, at a minimum, periodic meetings often informal meetings with their network partners. Most companies invite their partners annually, but some companies organize events several times a year. Also, some companies have “technical meetings” in which a technical expert on a certain subject gives a presentation to the partnership network. Some firms even go further by promoting “Dream Days” with their partners, prompting them to think together about the types of products that might be relevant to the future. Some firms – two in this study – specifically attempt to stimulate collaboration through the physical layout of their facilities and campus regulations. Since transportation on campus is on foot or by bicycle because cars are not permitted, the partners benefit from interaction through spontaneous encounters. Furthermore, with only a single central restaurant, because restaurants are not allowed in other buildings, people inevitably meet one another. Similarly, large, centrally located meeting rooms also promote collaboration and interaction. Encouraging participation in and leading regional, national and international research initiatives is another approach companies employ to stimulate collaboration among partners. One of the interviewees, for example, encourages the formation of groups to collaborate on important societal priorities, with the objective of promoting knowledge exchange among partners. These

221

Maturity in Innovation Network Management

groups assemble in meeting rooms and virtual spaces, and their work often earns the approval and appreciation of the government. Another firm gives their partners access to wikis and other collaborative tools to stimulate interaction and knowledge exchange via a virtual platform. Overall, companies provide basic support to their partners and networks. The major distinction between companies that give strong support and companies that do not appears to be a function of their experience and confidence in open innovation, their ambition and their resources to invest. Certain best practices, such as access to laboratories and office space and periodic meetings, are practices to which any firm can commit. However, firms that aspire to offer a higher level of partner support will need to invest not only financial but also human resources and possess a passion to strengthen their open innovation systems.

Organizational In this dimension we focused on the various organizational structures to support the innovation networks as well as governance and processes to manage open innovation. We also looked briefly at how companies promote their open innovation initiatives.

Organizational Structure & Governance for Open Innovation There appear to be basically two different types of legal organizational structures. Some R,D&I organizations are a department within their mother company while others are a separate legal entity but remain part of the business group. There are reasons for choosing a specific format. One is the quest for tax benefits; another is the desire for the R,D&I organization to function as a profit center; and a third relates to the organization’s objective to serve a variety of clients. There does not appear to be a single preferred practice, because the choice depends on national laws and corporate structures and policies. 222

Only a few companies have specific organizational structures with open innovation objectives. Organizational structures to seek and select partners and manage and support partnership networks are generally rare. Most companies embed roles in their routine R,D&I organizational chart. In organizations with larger structures and headcounts, searching for partners seems to attract more focus (i.e., more staffing resources) than managing partnerships. The latter seems to be handled principally through project relationships. In order to identify new partners, some companies deploy a dedicated team. Technical experts inside the firm, for example, can be responsible for targeting potential new partners in their fields. One of the interviewed companies, in fact, has set up a scouting group that searches globally for new technologies and, consequently, new partnerships. Another firm has developed a worldwide network through which it seeks external partners to complement and accelerate its innovation efforts. In addition, there are companies that have established a dedicated M&A department to invest in technology-based firms. Few companies allocate exclusive full-time resources to partnership management. One company that has partnered with a university provides extensive staff to facilitate the relationship between the university, the company’s internal business units, and students by offering technical support to all parties in the partnership. The strategic management of open innovation, including open innovation strategy and partners selection, normally rests with the Chief Technology Officer, with business unit heads maintaining a degree of involvement as well.

Innovation Processes Very few companies have official open innovation management processes. With the exception of contractual and legal processes, the selecting, developing and evaluating of partners and the network as a whole are all done informally.

Maturity in Innovation Network Management

Selecting partners is normally done on a case by case basis. Companies can sometimes be selected for an individual project, but as well to build long term relationships. However, our interviewees did not mention that they selected their partners based on a portfolio view of their network, specifically where one evaluates if the current network supports the company’s strategy, not only in technical terms, but in structure, culture and results. A good management practice, as stated by one of the interviewees, is mapping the entire R,D&I partnership’s requirements for a technology, not just by partner for an individual project. This company, when starting a new research project, looks practically from the start at what partners might be involved in development and commercialization. The evaluation of partners is generally done quite informally by companies. Most companies have year-end reviews with their partners, often discussing informally their project(s), the progress and results. There also are companies that conduct a more formal review on agreed upon objectives and results within contracts. But it appears rare that a company (only one company interviewed) would evaluate their partner using a quantitative approach, such as based on grades. This company also put a high premium on cultural alignment as an important evaluation point.

Funding Regarding the funding origins, much of the funding for projects developed by the network of innovation comes from their own network leader. Although few would consider the use of venture capital, the search for subsidized funding and local government incentives were quite common in both surveys. The participation in national and international research programs is quite common, especially in innovation networks outside Brazil.

THE MATURITY MODEL OF INNOVATION NETWORKS The result of this study shows different practices adopted by companies in regard to open innovation around the world. The analyses of these results were consolidated and the practices observed adopted a pattern. Therefore, with the data gathered on this study was possible to develop a Maturity Model regarding Open Innovation activities grouping and classifying the practices around the world into four different maturity stages. The maturity stages describe good practices adopted by companies’ taking in consideration the different stages of development considering four groups: beginners, explorers, established, world class. These stages are described next.

Figure 6. Maturity model in innovation networks

223

Maturity in Innovation Network Management

Beginners These companies are at the very beginning of open innovation. They are at times reluctant to advance with Open Innovation Systems because of worries about intellectual property rights, a strong belief in the old closed innovation model, or only waking up to the benefits of open innovation. It does not mean that these companies have never worked with partners, for they never did this deliberately to systemically explore external knowledge and competencies. The objective of the companies in this stage is to create cheaper and faster ways to generate incremental innovation for their current markets. Characteristics of companies in this stage: • •

• • • • • • •

Partnering focus on improvement in existing products; Using partners for particular knowledge, mainly suppliers, and sometimes clients or universities; Engaging when required (per project) with few partners; Worrying excessively about loss of Intellectual Property; Majority are one-off contracts; Some partner access to company infrastructure; Resistance from within the company to the open innovation model; No specific governance model set up to manage partners; Searching for external funding just starting.

Explorers These companies are deliberately searching to utilize all the opportunities of open innovation to their advantage, seeking partnerships in their various technology needs, especially focused on being able to generate innovation with an impact on the company. The objective of these companies is to search for partners that help them create

224

technologies that are substantially or even radically innovative to support the company’s future competitiveness. Characteristics of companies in this stage: • • • • • • • •

Using open innovation to search for substantial and radical innovations; Partnering mainly with universities and research institutes; Mapping technology needs and potential partners (technology strategy); Adapting umbrella contracts are increasingly common; Intellectual Property policies clearly defined and shared with staff; Accessing infrastructure and some engineering support; Setting up the management for individual partnerships; Looking across borders for potential partners (outside the country).

Established These companies use open innovation as a strategic tool in their technology development process. They manage their open technology innovation system in an organized and structured manner, utilizing a number of strategic partnerships in the various parts of the R&D& I process. The objective of these companies is to maximize value generation from a wide range of partnerships. Characteristics of companies in this stage: • •

• • •

Searching for breakthrough technologies together with partners; Partnering in long-term contacts with universities, research institutes and other partners; Pre-competitive research with competitors, suppliers and universities; Investing in the infrastructure of partners; Use of external venture funds to invest in technology based companies;

Maturity in Innovation Network Management

• •

• •

Business support for partners, including management and patent advisory; A governance structure in place with individual partnership management and development, while scouting for new partners; Commercializing technology with partners; Participating in national and international research programs.

World Class These companies are the leaders in open (technology) innovation, managing their systems deliberately to grow in value over time. These companies look beyond their own short-term benefit, instead searching to optimize the value of the whole system by giving strong support to their partners and encouraging constant collaboration and learning within the system. In this manner they are creating a self-regenerating and expansive system that interconnects across other innovative networks. Characteristics of companies in this stage: •

• • • • •

•

Creating their own physical structure instead of just participating in collaborative systems and infrastructure; Leading national and international research programs; Maintaining strong services to attract, support and develop new partners; Stimulating constantly the collaboration and learning between participants; Searching for network expansion, services and clients of the R,D&I center; Governance to manage partner portfolio, besides individual partnership development; Strong feedback mechanisms and evaluation.

CONCLUSION The results of the research show a diversity of approaches, practices and maturity levels between the interviewees, but we are able to identify some key findings. There are some common practices utilized by the interviewed companies, in all very much in line with what one can find in published literature about open innovation. There were clear differences, however, among companies concerning the following: the business model for a partnership; the location of research and development facilities; the processes outsourced; the number and type of partners; the working format; the commercial relationship with partners; the investment in partners or base technology companies; the use of intellectual property rights; the business support for partners and access to infrastructure; the legal format and level of organizational preparation to manage the partnership networks. We found that the differences were primarily related to the following forces: Maturity in open innovation practices (the time period in which open innovation has been practiced); Need for open innovation (how much the company needs to involve 3rd parties in the innovation process); • • •

•

Due to quick and major changes in the technological environment; Relevance of technology as a competitive differentiator; Nominal investments in technology innovation or the ability to invest more in innovation and thereby open innovation. Ambition to be a technology innovation leader.

225

Maturity in Innovation Network Management

In summary, we found that the longer the company works with open innovation, the more the company needs to innovate, the more money the company has available to innovate and the more ambitious the company is in relation to innovation. Consequently these companies invest more in open innovation, involve more partners in more parts of the R,D&I process, and develop better support and governance structures. It all sounds logical, but it became more explicit after our research. Using the results of this research we can identify four different levels of development of innovation networks: initiators, explorers, established and world class. The initiators are, as the name implies, reasonably new to open innovation and are only waking up to its opportunities; the explorers try to find the best model to work for them; the established are companies that have been working with open innovation for some time and are using it to their advantage; and the world class are those that lead the practices in open innovation, breaking paradigms. Most of our interviewees are explorers and established, whereas only a few can be considered world class and only one can be viewed as a beginner. We need to point out that these classifications are entirely conceptual and should not be used in a rigid manner, but rather be used to help one understand the complex world of open innovation management. An advanced stage of open innovation is not necessarily better, for it can depend on the company’s characteristics: size, market and availability of resources. In some cases, the world class stage is too far stretching for companies, since it requires large investments and complex organizational structures. It may even be unnecessary given the competitive environment in which the company is working. And if well managed, companies can obtain benefits from all of the stages.

226

ACKNOWLEDGMENT This research was developed for the “Companhia Paulista de Força e Luz” (CPFL), within the Aneel R&D Programme in Brazil.

REFERENCES Anprotec, S. (2002). Glossário dinâmico de termos na área de tecnópolis, parques tecnológicos e incubadoras de empresas. Brasília: ANPROTEC. (in Portuguese) Arino, A., Abramov, M., Skorobogatykh, I., Rykounina, I. & Vila, J. (1997). Partner selection and trust building in west European-Russian joint ventures. International Studies of Management & Organization, 27(1). Arino, A., de la Torre, J., & Ring, P. S. (2001). Relational quality: Managing trust in corporate alliances. California Management Review, 44(11), 109–131. Arranz, N. Fdez., & De Arroyable, J. C. (2007). Governance structures in R&D networks: An analysis in the European context. Technological Forecasting and Social Change, 74, 645–662. doi:10.1016/j.techfore.2006.05.009 Camisón, C., Boronat, M., & Villar, A. (2007). Technical strategic alliances and performances: The mediating effect of knowledge-based competencies (Working Paper). Castellon, Spain: Instituto Valenciano de Investigaciones Economicas SA, Universitat Jaume I. Chesbrough, H. (2007). Why companies should have open business models. MIT Sloan Management Review, 48(2), 22–28. Chesbrough, H., & Schwartz, K. (2007). Innovating business models with co-development partnerships. Research Technology Management, 50(1), 55–59.

Maturity in Innovation Network Management

Das, T. K., & Teng, B. (2002). Alliance constellations: A social exchange perspective. Academy of Management Review, 27(3), 445–456. Doz, Y. L., Olk, P. M., & Ring, P. S. (2000). Formation processes of R & D Consortia: Which path to take? Where does it lead? Strategic Management Journal, 21, 239–266. doi:10.1002/(SICI)10970266(200003)21:3<239::AID-SMJ97>3.0.CO;2K Duysters, B., & Lokshin, B. (2007). Determinants of alliance portfolio complexity and its effect on innovative performance of companies (Working Paper). Holland: Maastricht Economic and Social Research and Training Centre on Innovation and Technology, United Nations University. Dyer, J. H., & Nobeoka, K. (2000). Creating and managing a high-performance knowledge-sharing network: The Toyota Case. Strategic Management Journal, 21, 345–367. doi:10.1002/(SICI)10970266(200003)21:3<345::AID-SMJ96>3.0.CO;2N Figlioli, A. (2007). Perspectivas de financiamento de parques tecnológicos: Um estudo comparativo. Mastery Dissertation, Faculdade de Economia, Administração e Contabilidade de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, 2007. (in Portuguese) Figlioli, A., & Porto, G. S. (2007). Perspectivas de financiamento de parques tecnológicos: Um estudo comparativo. Ribeirão Preto: FIPASE. (in Portuguese) Gargione, L. A. Lourenção, Paulo, T. M. & Plonski, G. A. (2005). Fatores Críticos de Sucesso para Modelagem de Parques Tecnológicos Privados no Brasil. In: XI Seminário Latino Americano de Gestão Tecnológica- Altec 2005- 25-28 oct. (in Portuguese)

Gower, S., & Harris, F. (1996). Evaluating British science parks as property investment opportunities. Journal of Property Valuation & Investment Bradford, 14(2), 24. doi:10.1108/14635789610112646 Gulati, R. (1998).Alliances and networks. Strategic Management Journal, 19, 293–317. doi:10.1002/ (SICI)1097-0266(199804)19:4<293::AIDSMJ982>3.0.CO;2-M IASP. (2009). Key challenges for Science Parks Managers. In Learning by sharing: Book 2. Málaga, Spain: IASP. Kratzer, J., Leenders, R. Th. A. J., van Engelen, J. M. L., & Kunst, L. (2007). InnovationNet: The art of creating and benefiting from innovation. Assen, The Netherlands: Royal Van Gorcum. Lemmens, C. E. A. V. (2004). Innovation in Technology Alliance networks. Cheltenham: Edward Elgar Publishing Limited. Lichtenthaler, U. (2009). Integrated roadmaps for open innovation. Research -Technology Management, 52(1), 27-34. Moller, K., & Rajala, A. (2007). Rise of strategic nets – New modes of value creation. Industrial Marketing Management, 36, 895–908. doi:10.1016/j.indmarman.2007.05.016 Nielsen, L. E., & Mahnke, V. (2003). Managing R & D alliance portfolios: The case of mobile service providers (Working Paper). Denmark: Department of Informatics, Copenhagen Business School. Oerlemans, M., Meeus, T. H., & Boekema, F. W. M. (2003). Innovation, organisational and spatial embeddedness: An exploration of determinants and effects (Working Paper). Holland: Eindhoven Centre for Innovation Studies. Ojasalo, J. (2008). Management of innovation networks: A case study of different approaches. European Journal of Innovation Management, 11(1), 51–86. doi:10.1108/14601060810845222

227

Maturity in Innovation Network Management

Ozkan, P. (2007). What networks do to companies and what companies do to networks: Evolution of alliances portfolios in networked markets (Working Paper). Spain: IESE Business School, Universidade de Navarra.

Suseno, Y., & Ratten, V. (2007). A theoretical framework of alliance performance: The role of trust, social capital and knowledge development. Journal of Management & Organization, 13(1). doi:10.5172/jmo.2007.13.1.4

Parise, S., & Casher, A. (2003). Alliance portfolios: Designing and managing your network of business-partner relationships. The Academy of Management Executive, 17(4), 25–39. doi:10.5465/AME.2003.11851824

Terra, J. C. (1999). Gestão do conhecimento – Aspectos conceituais e estudo exploratório sobre as práticas de empresas brasileiras. São Paulo, Brazil. (in Portuguese)

Parkhe, A., & Miller, S. R. (2000). The structure of optimal trust: A comment and some extensions. Academy of Management Review, 25(1), 10–11. doi:10.5465/AMR.2000.15876047 Petree, R., Petkov, R., & Spiro, E. (2000). Technology parks - Concept and organization. Center for Economic Development. Polenske, K. R. (2007). The economic geography of innovation. Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9780511493386 Rampersad, G., Quester, P., & Indrit, T. (2010). Managing innovation networks: Exploratory evidence from ICT, biotechnology and nanotechnology networks. Industrial Marketing Management, 39, 793–805. doi:10.1016/j.indmarman.2009.07.002 Romera, F. (1998). Technocells. In Delivering innovation: Key lessons from the world wide network of Science and Technology Parks. IASP. Rosenblum, L. (2004). Profiting from research. American School & University, 77(3). Segil, L. (2004). Measuring the value of partnering. New York, NY: AMACOM. Slowinski, G. et al. (2009). Effective practices for sourcing innovation. Research -Technology Management, 52(1), 27-34.

228

van de Vrande, V., de Jong, J. P. J., Vanhaverbeke, W., & de Rochemont, M. (2007). Open innovation in SMEs: Trends, motives and management challenges. Rotterdam, Holland: Department of Strategic Management and Business Environment Working Paper Series, RSM Erasmus University. Vanhaverbeke, W., & Cloodt, M. (2006). Open innovation in value networks. In H. Chesbrough, W. Vanhaverbeke, & J. EST (Eds.), Open innovation: Researching a new paradigm. New York, NY: Oxford University Press. Vanhaverbeke, W., Gilsing, V. A., Beerkens, B. E., & Duysters, G. (2009). The role of alliance network redundancy in the creation of core and non-core technologies. Journal of Management Studies, 46(2), 215–243. doi:10.1111/j.14676486.2008.00801.x Vasudevan, A. (2001). The changing face of alliance management: Managerial imperatives for the network economy. In de Man, A.-P., Duysters, G., & Vasudevan, A. (Eds.), The allianced enterprise: Global strategies for corporate collaboration. London, UK: Imperial College Press. doi:10.1142/9781848161405_0002 Westhead, P., & Batstone, S. (1999). Perceived benefits of a managed science park location. Entrepreneurship and Regional Development, 11, 129–154. doi:10.1080/089856299283236

Maturity in Innovation Network Management

Wixted, B., & Holbrook, J. A. (2008). Conceptual issues in the evaluation of formal research networks (Working Paper). Burnaby, Canada: Centre for Policy Research on Science and Technology, Simon Fraser University.

Zhang, Y. (2004). Critical factors for science park management: The North American and European experience. International Journal of Entrepreneurship and Innovation Management, 4(6), 575–586. doi:10.1504/IJEIM.2004.005849

229

230

Chapter 13

Science Parks and Their Role in the Innovation Process: A Literature Review for the Analysis of Science Parks as Catalysts of Organizational Networks Renata Lèbre La Rovere Federal University of Rio de Janeiro, Brazil Leonardo de Jesus Melo Federal University of Rio de Janeiro, Brazil

ABSTRACT This chapter investigates the contributions of Science Parks (SPs) to innovation. In particular, we discuss whether the literature on innovation and SPs consider the fact that SPs can be catalysts of Organizational Networks (ONs). We consider that ONs are elements of knowledge production and can contribute to the development of core competencies to pursue dynamic innovation and sustainable competitive advantage. This chapter is based on a literature review of scientific papers and theses which are included in indexed databases related to SPs and their contributions to innovation. Preliminary analysis of the literature shows that SPs have been mostly studied as part of innovation systems, and that less attention has been given to the role of ONs and SPs in the processes of technological learning and innovation.

DOI: 10.4018/978-1-61350-165-8.ch013

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Science Parks and Their Role in the Innovation Process

INTRODUCTION In accordance with the International Association of Science Parks (2002), a Science Park is an organisation managed by specialised professionals, whose main aim is to increase the wealth of its community by promoting a culture of innovation and the competitiveness of its associated businesses and knowledge-based institutions. To enable these goals to be met, a Science Park stimulates and manages the flow of knowledge and technology amongst universities, R&D institutions, companies and markets; it facilitates the creation and growth of innovation-based companies through incubation and spin-off processes; and provides other value-added services together with high quality space and facilities. The SPs literature considers those institutions as ways of organizing enterprises in a territory that foster innovative activities (Squicciarini, 2008). Innovation in SPs is related to positive externalities that result from geographical proximity. Nevertheless, the fact that firms are close to other firms and universities in a Science Park does not necessarily mean that interactions among them will occur. Furthermore, the fact that the Science Park promotes the development of organizational networks among its firms does not mean that firms located in the Park will develop relations only with other firms in the Park. Rather, SPs should be viewed as spaces that not only allow for the creation of organizational networks but also strengthen organizational networks that existed before firms moved to the Park. As organizational networks have a role in promoting and organizing interactions between firms and institutions, they should be considered in studies of SPs, especially because organizational proximity may be as, or even more, important than geographical proximity in the development of innovations. Networks can be formed by clusters of firms in the same territory or in different territories. Despite the variety of concepts and low level of accuracy of studies about clusters of firms (Hasenclever &

Zissimos, 2006), all the authors who have analyzed these agglomerations have pointed to the benefits that companies may obtain. Proximity provides economies of scale, possibilities for development of production chains, accumulation of knowledge and innovative activities, reduces transport costs and, in the case of urban areas, provides access to sophisticated clients. We define proximity not only as geographical proximity but also as relational proximity. Therefore, the research question addressed in this chapter is the extent to which SPs, as spaces that can combine benefits related to geographical and relational proximity, contribute to the generation and strengthening of organizational networks for innovation and how these networks deal with the processes of creation, dissemination and appropriation of knowledge in order to develop sustainable competitive advantage. This subject is directly related to the theme of innovation, since in the current techno-economic paradigm the ability to create and sustain competitive advantages in a particular territory is related to learning ability, the quality of products and processes, productivity, and companies’ capacity for technological development. In this paradigm, companies seek to meet requirements for flexibility and speed by involving themselves in networks. Studies of local development highlight a variety of forms of association and network integration of these networks in global markets. Networks are key elements for the creation and diffusion of knowledge that underlies the generation of innovations. The processes of creation, dissemination and appropriation of knowledge are enhanced when organizations are linked in a network and develop mechanisms for governance and management aimed at coping with the knowledge assets generated and traded in their context. After a review of the literature on business networks, Britto (2002) identifies three possible types of network: subcontracting networks, where a company outsources part of its activities; Marshallian industrial districts, where the interaction between

231

Science Parks and Their Role in the Innovation Process

the components of the network allows for the acquisition of static and dynamic advantages related to geographical proximity, and technology networks, where the interaction between the components takes place with the specific purpose of developing innovations. In SPs the actors involved are located in the same area and they are influenced by an institutional initiative whose main objective is to foster technology networks. In this type of network geographical proximity is not necessarily more important than organizational proximity. This chapter assumes that SPs, as innovation environments, stimulate and manage flows of knowledge and technology between universities, research institutions, companies and markets, and are presented by current literature as a mechanism for local development capable of catalyzing the generation of organizational networks that act as means of articulation among the principal agents of innovation. The methodology used is a review of the literature. This chapter will present the main results of a search in scientific papers and theses included in indexed databases related to SPs and their contributions to innovation. Our discussion will be based on concepts drawn from the Evolutionary and New Institutional Schools, which have made the most significant contributions to the literature regarding innovation and regional development in the Post-Fordist period. The study of the relationship between SPs and organizational networks will primarily contribute to the debate about the role of organizational proximity and geographical proximity in the creation of sustainable competitive advantages. Secondly, we will analyze the existing potential and the main challenges involved in the generation of networks capable of dealing with the processes of creation, dissemination and ownership of knowledge assets; in addition, we also aim to understand the challenges and opportunities faced by companies regarding the management of their resources and cooperation with other members of the network.

232

BACKGROUND: SCIENCE PARKS AND THEIR ROLE IN INNOVATION The theoretical framework of this chapter is in line with the Evolutionary Studies approach. These studies assume that firms have limited rationality and asymmetric information, so their decisions concerning innovative activities and production will be affected by the decisions of other firms and institutions. The interactive processes that shape the decisions of the firms are self-organizing and will determine the properties of local networks (Vicente, 2000). The chapter also draws on literature from the New Institutional School, as it assumes that networks of companies and their worlds of production can be organized in different ways with different impacts on territory (Markusen, 1996). Furthermore, we assume that the interaction between companies, institutions and local community in a given territory affects the spread of knowledge and innovation (Storper et al., 2007, Storper, 2008). SPs originated in the United States during the 1950s, as a consequence of the emergence in the postwar period of a large number of high-tech companies, many of which were created to support ongoing research activities in universities. In accordance with IASP (2007), the second half of the 1980s was the period when the largest amount of SPs was created (23%), as Figure 1 shows. But one can see that the curve rises steeply in the first decade of the 21st century; this period of just five and a half years is responsible for 26% of all the SPs in the sample. According to IASP (2007), Science Parks are mostly an urban (or semi-urban) phenomenon, with 66% of the Parks surveyed being within a city and 27% being quite close to one (25 km or less). Furthermore, 36% of SPs worldwide are located on a university campus or adjacent to one, while 8% are located on land owned by a university, although not on a campus or adjacent to it. However, the majority of SPs (53%) are located outside university campuses and on land not owned

Science Parks and Their Role in the Innovation Process

Figure 1. Global creation of science parks (%) (Source: IASP)

by a university. In Brazil the physical spaces chosen for the deployment of SPs usually comes from public agencies or universities (ANPROTEC, 2007). SPs may be analyzed as clusters that are deliberately promoted by local institutions to enhance innovation and learning in a particular territory. Therefore, to discuss the role of these institutions as catalysts of networks we must first look at the literature on the benefits of proximity for firms. Zander (2004) argues that entrepreneurs prefer to be geographically close to their clients, suppliers and competitors for several reasons. First, they need to identify their competitors and learn to prepare adequate competitive strategies from their competitors’ movements. Second, there is a demonstration effect on the territory, whereby successful enterprises influence local entrepreneurs’ perceptions of socially desirable businesses. Third, the educational level of entrepreneurs, conditioned by the territory, will affect local entrepreneur choice of business. Fourth, when recognizing an opportunity local entrepreneurs will establish new businesses by assimilating local knowledge and recruiting members of their social network.

Clusters are also institutional forms in which loyalty relations are easily built, because, according to Frigant (2001), agents have a sense of embeddedness. Therefore the territory is relevant as a locus of social capital and entrepreneur action. Positive effects of entrepreneurship and agglomeration on innovation were verified by Acs and Varga (2005), in an econometric study using data from the European Union. They came to the conclusion that knowledge spillovers are positively related to clustering and entrepreneurship. This is why SPs are built: institutions promoting them expect that Parks will generate benefits in terms of the stimulation of new businesses, development of innovative activities and generation of local knowledge. Studies of innovation that emphasize the role of territory suggest that enterprises are rooted in institutional arrangements consisting of social relationships that feed creativity and adaptability. Innovation is seen by these studies as an “island of activities” determined locally (Amin & Cohendet, 2005). The formation of clusters of firms is seen as the result of a selective mechanism that provides favorable conditions to meet the demands posed by technological change. Growth opportunities are

233

Science Parks and Their Role in the Innovation Process

shaped by the legacy of accumulated knowledge and learning that is geographically determined (Iammarino & McCann, 2006). More recent studies, however, propose the concept of another type of proximity, which is independent of territory: relational proximity. Amin and Cohendet (2005) argue that relational proximity, whose concept was developed from the text of Nonaka and Konno (1998) on space-sharing relationships (ba) is fueled by travel, common routines, databases and common software and provision of training to communities through temporary project groups and task forces. Relational proximity can be achieved through a variety of regional mobilizations. Some authors, such as Lemarié et al. (2001), use the term ‘organizational proximity’ to describe relational proximity. They contrast geographical proximity, which is space-related, with organizational proximity - related to affiliation (same relational area) and similarity (from an organizational point of view). For these authors, both forms (geographical and organizational proximity) increase the sharing of tacit knowledge in the innovation process (Davenport, 2005). Kaufmann et al. (2003) carried out a study of innovative firms in Austria with similar purposes. They argue that, as the principles that guide innovative process are learned, face to face communication is no longer a prerequisite for innovation, and geographic proximity may be replaced by relational proximity. The authors suggest that geographical proximity is important in the beginning of the innovation process (in design) and in its end (in testing phase), whereas in the intermediate stages of development and prototyping communication can take place remotely. Amin and Cohendet (op.cit.) note, from a review of previous studies, that the same attributes of networks of firms identified as success factors for innovation, such as flexible learning expectations, commitment to partnership, trust of partners, excessive tolerance, ability to manage conflicts, cancellation of myopia linked to performance

234

at all costs, and acceptance of partnership as a long-term investment, are also the ones identified as success factors for territorial agglomerations. The authors then conclude that knowledge is not confined to particular sites, as networks may be formed with firms in different locations. Adherence (stickiness) of knowledge to specific places derives from unique combinations and interactions of bodies, minds, languages, technologies and objects that can be found in territories, crystallized in attitudes. Thus, a specific cluster is not restricted regionally, but it is rather a container of relations that combine and transmit knowledge, which may come in pieces, with a number of different distances and directions. Clusters with high rates of innovation are characterized by the existence of dense relations among different professional communities (engineers, entrepreneurs, financing professionals, computer professionals). The growth of these clusters results from the successful management of diverse knowledge assets of the local professional community. Relationships between these communities occur in certain places, but the networks of these communities extend beyond the territory, therefore the knowledge developed within the territories depends on internal and external mobility and connections. Davenport (2005) confirms Amin and Cohendet’s propositions and shows the results of a survey of innovative firms in New Zealand. He observes that firms do not draw on local or national knowledge to be innovative; since they provide competitive solutions their products are designed to meet customer needs and building knowledge comes from strong relationships with networks of customers, distributors, employees of international companies, consultants with complementary skills, as well as with networks of ‘sister’ (similar) companies. He suggests that companies which seize opportunities presented by the external market go through a process of rapid internationalization and present few linkages with the territory.

Science Parks and Their Role in the Innovation Process

The existence of relational proximity may help to explain why clusters of firms differ. Markusen (1996), in her work on industrial districts, identifies four types of agglomerations of firms, each one with different configurations of firms and governance structures: hub-and-spoke districts, satellite platforms, state-anchored districts and Marshallian districts. She contests the idea that Marshallian districts will prevail as the dominant form of clusters and points out that in hub-and spoke districts and satellite platforms, knowledge diffusion among members of the cluster is very limited. Iammarino and McCann (op.cit) also propose three forms of agglomeration of firms: the first is pure or Marshallian agglomeration, where firms do not have market power, continuously change their relations with other firms and exploit market opportunities. Entry and exit costs in this market are low, and these agglomerations often occur in urban spaces. The second is the industrial complex, characterized by long-term relations between stable and predictable firms in the cluster. Access to this cluster is limited by entry and exit barriers, and their location is regional but not necessarily urban, and dependent on transport costs. The third form is the cluster that arises from a social network with ties of trust and cooperation among enterprises. Geographical proximity is necessary in this type of agglomeration, but access is limited by the relations of trust, built on a common culture. Iammarino and McCann suggest that all agglomerations may have characteristics of the three models, but one model will always prevail over the others. Arguments about the spillover of knowledge between firms implied by the models of pure agglomeration and social networking are not always applicable when dealing with multinational or oligopolistic firms with many affiliates. This argument is confirmed by Crespo and Fontoura (2007), who made an extensive review of literature on the externalities generated by multinational companies and showed that there is not enough empirical evidence to argue that these externalities will in fact occur. In particular, the impact

on local enterprises will depend largely on their capacity to absorb technology, thus conditions in each site will differ. It should also be noted that if the company decides to locate in a given territory to be close to other companies, it will generate positive externalities that will benefit other companies (free riding effect). According to Meyer-Stamer (2005), companies, particularly large ones, take into account free riding when making location decisions, and seek to limit it through contracts. Contracts may limit the diffusion of knowledge to local firms that is highlighted as one of the advantages of clusters. Studies of relational proximity and of different types of knowledge diffusion related to diverse types of clusters support our proposition that to understand how innovation takes place in a territory, analysts have to consider networks of firms. Lawson et al. (2009) point to the relevance of networks for innovation with their study of knowledge sharing in inter-organizational product development teams. These authors did an empirical study of 111 manufacturing organizations in the UK and found that relationships between firms, buyers and suppliers are crucial in new product development. Furthermore, the inter-organizational teams that are formed to develop new products are strongly influenced by informal socialization mechanisms, therefore face-to-face contacts are crucial to share sticky and tacit knowledge. To summarize, the available literature on the benefits of territorial agglomerations of firms explains the reasons why SPs are viewed as spaces for innovation and thus are promoted by institutions that want to enhance learning and knowledge production in a territory. However, if we consider that what is relevant for innovation is not the territory per se but the networks that are located in the territory, an analysis of SPs governance structures (including the hierarchy structure of local networks and contracts) is needed to assess whether SPs are catalysts of organizational networks. Our survey

235

Science Parks and Their Role in the Innovation Process

of scientific papers on SPs found that few authors have been working in this direction. Recent literature on SPs may be divided in two broad categories: studies that focus on firms as the main object of analysis and studies that focus instead on the Science Park as an institution located in a region, using therefore a Meso approach. While in the former view innovative activity is seen as a competitive tool for firms and traditional indicators are focused on, such as productivity of firms, job creation and value generation, the latter view focuses on a particular region, policy or technology. In relation to methodology, studies use statistical models, case analysis or a combination of both. Studies focusing on firms investigate whether SPs generate spillovers (Squicciarini, 2009), if they have significant patenting activity (Squicciarini, 2008), how they compare with firms located outside the Park (Squicciarini, 2008, Yang et al., 2009), and identifying the conditions for their growth (Link & Link, 2003, Lofsten & Lindelof, 2005, Yu et al., 2009). These issues are explored because, as Squicciarini (2009) and Hansson (2004) observe, empirical evidence on the effectiveness of SPs regarding the development of technology is mixed. The mixed results may derive from the fact that the traditional indicators such as revenue, survival of firms, job generation and patents used in most analysis fail to properly measure knowledge creation in the Park and related benefits (Hansson, 2004). Dettwiler et al. (2006) tried to measure knowledge creation by comparing firms located inside a Park with firms located outside it and concluded the former have a slightly superior performance. Squicciarini (2009) suggests that knowledge creation may be assessed by comparing the patenting activity of firms before and after entering a Science Park and by analyzing patenting activity of incubated firms. Her model used a database of Finnish firms and confirms that size, sector and time elapsed before joining the Park are all relevant for patent capacity. She also suggests that there is a path

236

dependency in Park activities that creates firstmover disadvantages. SPs, in her words, “look unable to learn and improve their performance over time” (Squicciarini 2009:187). This result may be explained by the fact that Park management must define their objectives in goals that are measurable. Therefore, they use the same traditional measures of performance mentioned above (Link and Link 2003). If directors use traditional measures, the governance structure of the Park will have a limited scope concerning the creation of knowledge. Papers that take a Meso approach focus on different countries and present results complementary to the findings of those focused on firms. Dettwiler et al (2006) indicated that cost of facilities is an element considered by firms in deciding to locate in a Park, a result also found by Sun et al. (2009) and Hu (2007). Tan (2006) found evidence of aging in a Beijing Science Park that gives further support to Squicciarini’s ide (2009) that Park management must take into account the Park’s path dependency. Bigliardi et al. (2006) suggest that, in addition to the life cycle of firms, Park managers must also consider proximity to universities and legal conditions. Proximity of universities and adequacy of management are considered crucial by Ratinho and Henriques (2010). Zhang (2004) found that the critical factors for the success of a Park are location and management. Chen et al. (2006) also consider the importance of the sector in the performance of firms located inside a Park. Whether the focus is on the firm or the Park, what appears to be the common element in all the studies reviewed is that they try to investigate Park efficiency by assuming that innovation depends on active interaction between universities, industry and government, a concept known as the Triple Helix (Etzkovitz & Leydesdorff, 1997). As Hansson (2004) and Wicksteed (2004) observe, the dimension of knowledge creation and networking – crucial for innovation in the creative economy – is frequently lost in these studies. Some studies of knowledge creation in SPs use patents as a proxy

Science Parks and Their Role in the Innovation Process

for knowledge creation. However, patents measure only codified knowledge. Case studies like those of Grassler and Glinnikov (2008) provide better insights into codified and tacit knowledge diffusion in SPs. Nevertheless even case studies may not take into consideration organizational networks as spaces for knowledge creation and diffusion, which are essential to understand growth and innovative activities of firms inside Science Parks. Grassler and Glinnikov (2008), for instance, mention in their work that partnerships found in their case “are far from exploiting promising options”. This result may be explained by the fact that firms, in establishing partnerships, take into consideration their organizational networks to set the boundaries of these partnerships. Also revealed by the literature review was that in making the choice to locate in SPs, firms tend to prioritize physical infrastructure and financial and tax incentives, to the detriment of the creation and strengthening of organizational networks which can generate sustainable competitive advantages. When networks are mentioned in studies, they are seen as providers of specific advantages to the firm. This observation is supported by Manella (2009) in a study of factors that limit the attractiveness of Science Parks for innovative firms. The investigation of these factors in five Brazilian SPs in highlighted certain factors of attraction, such as main source of capital accessibility, partnership with universities, transportation facilities, infrastructure and common services, local incentives. Of the fifteen most important factors considered, seven were directly related to the arrangement of financial support by the Park and the rest were directly or indirectly linked to locational factors. The companies surveyed gave little importance to the presence of universities and R&D, with the establishment of research projects in partnership with research centres being an uncommon practice. The analysis of the SPs literature shows that although they have been studied as part of an innovation system, little attention has been given to

the role of organizational networks in the process of technological learning and the generation of innovation. The result of this analysis involves a series of issues relevant to the theoretical field of organizational networks. The first issue is that within the literature it appears that companies in Science Parks, while noting the possibility of establishing and strengthening networks as a factor of attractiveness, use Parks mainly to obtain benefits related to financial/operational issues and not as a differentiating factor related to the ability to create and disseminate knowledge and promote (environmental, social and economic) sustainability. As mentioned above, the self-organizing process that shapes firms’ decisions concerning innovation and production limits the ability of firms to have independent long-term strategies that may ensure sustainability of activities. Firms tend to recognize more easily static advantages of location, such as access to financial benefits, than dynamic advantages, such as knowledge generation. The second issue is that understanding that we must go beyond the use of networks to achieve certain and specific short-term goals implies that we must understand them as mechanisms for generating business opportunities, relationships and learning. Therefore, to study networks that are formed within a Science Park analysts have to look not only at the number of networks and the number of interactions each firm has in the network, as suggested by the authors from the New Institutional literature that we reviewed. Network analysis must also look at the specific sector of the firms in question to assess the potential of the creation of business opportunities and the learning generated by the network to develop innovation. Osajalo (2009) mentions other elements, such as duration, planning, control and trust, as being essential to the analysis of innovation networks. The third issue is that the current evaluation of firm performance located in SPs is based on traditional indicators such as patenting and value-added

237

Science Parks and Their Role in the Innovation Process

generation and does not consider intangible assets, such as organizational networks. This is because, as noted above, authors implicitly assume in their analysis that the presence of institutions that form the Triple Helix in the Park will be a sufficient condition to develop innovation. This may be true in those cases where geographical proximity is sufficient to develop the necessary interactions required for innovation, but as observed above the literature on clusters suggests that relational proximity must be considered as well. Finally, more studies are needed not only to understand the role of the relational proximity of the firms located in Science Parks for their innovation activities, but also to contribute to the development of SP governance mechanisms that ensure their sustainability. Although the literature confirms that Science Parks are environments for the development of skills aimed at building sustainable competitive advantage, few studies point to the need to develop mechanisms that allow the use of the benefits generated by intangible assets. In this sense, Zhang (2004:1) calls attention to the fact that “intangible aspects of Science Park management such as marketing, services and the quality of Park management team emphasized were in the third decade of Science Park development.” Hansson (2004) suggests that the concept of ba, which combines three central elements of knowledge creation – process, learning and complexity, should be used in the Science Park literature. However, we found few recent studies dealing with knowledge creation or about how the tacit and social elements of knowledge creation pose challenges to SPs governance structures. These results are not surprising. Grandori (1997, 2001) indicates that there is some neglect of governance mechanisms as antecedents of knowledge processes (creation, dissemination and appropriation). Developing this argument, the author analyzes the different types of governance mechanisms and management that contribute to the coordination of knowledge sharing and

238

integration between networks and organizations within their own companies, suggesting they are important elements when proposing some form of governance knowledge. Nooteboom (2009) also observes that governance and competencies are complementary and essential for innovation. Therefore, more research is needed on Science Parks with the aim of assessing the contribution of organizational networks to the creation of knowledge and how SPs can develop governance mechanisms that contribute to the creation and strengthening of organizational networks. As Hansson et al (2005) observe, a possible role for SPs is the development of the social capital necessary for enabling and facilitating entrepreneurship in networks.

ANALYSIS OF SCIENCE PARKS AS CATALYSTS OF ORGANIZATIONAL NETWORKS To conduct an analysis of Science Parks as catalysts of organizational networks, certain research steps must be followed. The first step is the assessment of the role that organizational networks play in the generation of business opportunities, learning, training and empowerment in the specific sectors of the firms that are located in the Science Park being analyzed. This can be done by a literature review, to understand differences and similarities between experiences based in specific contexts, and also to assess how organizational isomorphism is related to involvement in institutions with global representativeness (Dimmagio & Powell, 2005). The second step is an assessment of organizational networks prevalent in the Science Park. This can be done by applying a questionnaire to firms in the Park. The relevant research questions in this step are: do the firms in the Science Park belong to networks? If yes, how many? Are the networks local, national or global? Do networks

Science Parks and Their Role in the Innovation Process

involve formal or informal contacts? What are their aims? What is the frequency of relationships? How interactions take place (emails, meetings, workshops, videoconferences, social events etc.). What are the results of interactions? Did the firm enter new networks after entering the Park? Is the purpose of new networks different? To understand the process of network creation and strengthening is crucial for Park managers, because they can enhance this process by tapping their own networks and extending benefits of networks to all organizations located in the Park. The third step is an assessment of the role of Park services in the fostering of organizational networks. This can be done by interviewing Park managers. The relevant research questions in this step are: what are the specific services provided by SPs to disseminate knowledge? What is the role of each Park agent in the provision of these services? The services provided will differ according to the stage of maturity of the firm. For instance, services provided to mature firms such as research laboratories of transnational companies will focus on the strengthening of networks that already exist so that risks associated with the entrance of new partners attracted by their location in the SP are mitigated. The fourth step is an assessment of the governance mechanisms and their relation to knowledge generation in the Park. This can be done through interviews with firms and Park managers. The relevant research questions in this step are: how are information flows in the network organized? How are the results of interactions disseminated through networks? How is it possible to control results of interactions and their appropriateness? These questions are important because the demand for high speed and quality businesses deals generated by existing networks. Clear and efficient governance mechanisms can provide a significant reduction of transaction costs for the enterprises and for the Park itself.

SUMMARY AND CONCLUSION By having a systemic profile, Parks present a great challenge for their managers: to intensify their role in coordinating activities related to the processes of the creation, dissemination and protection of knowledge, and developing governance mechanisms that take into account the creation and strengthening of organizational networks. Based on a review of cluster characteristics, we suggested that organizational networks are important to develop innovation since they allow for benefits that stem from relational proximity. Therefore, the research question dealt with here was how SPs, as innovation focused clusters, can contribute to the generation and strengthening of organizational networks and how these networks deal with the processes of knowledge creation, dissemination and appropriation in order to develop sustainable competitive advantages. We tried to answer these questions by reviewing in scientific indexed papers studies of Science Parks. As clusters are created with the specific goal of innovation development, we expected to find papers that included in their analysis an assessment of organizational networks as core competencies that sustain the organization in the pursuit of dynamic innovation. However, the analysis of the SPs literature showed that although they have been studied as part of an innovation system, little attention has been given to the role of organizational networks in the process of technological learning and generation of innovation. Science Park literature, therefore, should broaden its scope. While studies focusing on performance of firms and the attractiveness of SPs are important to assess their relevance as tools for regional development, studies of knowledge creation inside the Parks are needed to assess whether SPs provide a relevant contribution to innovative activities and can thus meet the original objectives of the Park. As Parks seem to have a path dependency and can present signs of aging

239

Science Parks and Their Role in the Innovation Process

with declining performance, understanding how innovation is created inside the Park may provide tools for actions that can guarantee their sustainability. The contributions of the New Institutional and the Evolutionary Schools are important in this effort. As observed by Foss (1994), the contributions of these two schools provide analytical tools to understand agent rationality, change and learning processes, and the role of institutions. The analysis of the literature also allowed us to identify a series of issues relevant to the theoretical field of organizational networks. Based on a discussion of these issues, we then proceeded to suggest a step-by-step method to analyze Science Parks as catalysts of organizational networks. We hope that this method contributes to the literature on organizational networks by stimulating more studies on specific cases as well as comparative studies.

Britto, J. N. P. (2002). Cooperação interindustrial e redes de empresas. In Kupfer, D., & Hasenclever, L. (Eds.), Economia Industrial. Fundamentos Teóricos e Práticas no Brasil. Rio de Janeiro, Brasil: Campus.

REFERENCES

Dettwiler, P., Lindelof, P., & Lofsten, H. (2006). Utility of location: A comparative survey between small new technology-based firms located on and off Science Parks—Implications for facilities management. Technovation, 26, 506–517. doi:10.1016/j.technovation.2005.05.008

Acs, Z. J., & Varga, A. (2005). Entrepreneurship, agglomeration and technological change. Small Business Economics, 24, 3232–3334. doi:10.1007/ s11187-005-1998-4 Amin, A., & Cohendet, P. (2005). Geographics of knowledge formation in firms. Industry and Innovation, 12(4), 465–486. doi:10.1080/13662710500381658 ANPROTEC. (2006). Parques tecnológicos no Brasil: Estudo, análise e proposições. Brasília (in Portuguese). Bigliardi, B., Dormio, A. I., Nosella, N., & Petroni, G. (2006). Assessing science parks’ performances: Directions from selected Italian case studies. Technovation, 26, 489–505. doi:10.1016/j.technovation.2005.01.002

240

Chen, C. J., Wu, H. L., & Lin, B. W. (2006). Evaluating the development of high-tech industries: Taiwan’s Science Park. Technological Forecasting and Social Change, 73, 452–465. doi:10.1016/j. techfore.2005.04.003 Crespo, N., & Fontoura, M. P. (2007). 30 anos de investigação sobre externalidades do IDE para as empresas nacionais – Que conclusões? [Out-Dez]. Estudos Economicos, 37(4), 849–874. doi:10.1590/S0101-41612007000400006 Davenport, S. (2005). Exploring the role of proximity in SME knowledge-aquisition. Research Policy, 34(5), 683–701. doi:10.1016/j. respol.2005.03.006

Dimaggio, P. J., & Powell, W. W. (2005). A gaiola de ferro revisitada: Isomorfismo institucional e racionalidade coletiva nos campos organizacionais. [RAE]. Revista de Administração de Empresas, 45(2), 74–89. Etzkowitz, H., & Leydesdorff, L. (Eds.). (1997). Universities in the global knowledge economy: A triple helix of university-industry-government relations. London, UK: Cassell. Foss, N. J. (1994). Why transaction cost economics needs evolutionary economics. Revue d`Économie Industrielle, 68,(2ème trimester), 7-25.

Science Parks and Their Role in the Innovation Process

Frigant, V. (2001). Une lecture hirschmanienne de la coordination: Le loyalisme dans les Systèmes Productifs Territorialisés. Revue d’Economie Regionale et Urbaine, 5, 743–762.

International Association of Science Parks - IASP. (2002). About Science and Technology Parks. Retrieved July 3, 2010, from www.iasp.ws/publico/ index.jsp?enl=8

Grandori, A. (1997). Governance structures, coordination mechanisms and cognitive models. Journal of Management and Governance, 1, 29–42. doi:10.1023/A:1009977627870

International Association of Science Parks - IASP. (2007). Worldwide Statistics on SPs 2006-2007. Retrieved August 10, 2010, from http://www.rtp. org/ files/ iasp_survey_on_SPs.pdf

Grandori, A. (2001). Neither hierarchy nor identity: Knowledge governance mechanisms and the theory of the firm. Journal of Management and Governance, 5, 381–399. doi:10.1023/A:1014055213456

Kaufmann, A., Lehner, P., & Todtling, F. (2003). Effects of Internet on the spatial structure of innovation networks. Information Economics and Policy, 15, 402–424. doi:10.1016/S01676245(03)00005-2

Grassler, A., & Glinnikov, R. (2008). Knowledge transfer in Science Parks. MSc Thesis, Baltic Business School, University of Kalmar.

Lawson, B., Petersen, K. J., Cousins, P. D., & Handfield, R. B. (2009). Knowledge sharing in interorganizational product development teams: The effect of formal and informal socialization mechanisms. Journal of Product Innovation Management, (26): 156–172. doi:10.1111/j.15405885.2009.00343.x

Hansson, F. (2004). Science Parks as knowledge organizations – The ’ba’in action? Working Paper 15/2004, Department of Management, Politics and Philosophy, Copenhagen Business School. Hansson, F., Husted, K., & Vestergaard, J. (2005). Second generation Science Parks: From structural holes jockeys to social capital catalysts of the knowledge society. Technovation, 25, 1039–1049. doi:10.1016/j.technovation.2004.03.003 Hasenclever, L., & Zissimos, I. R. M. (2006). A evolução das configurações produtivas locais no Brasil: Uma revisão da literatura. [in Portuguese]. Revista de Estudos Econômicos, 36, 407–433. Hu, A. G. (2007). Technology Parks and regional economic growth in China. Research Policy, 36, 73–87. doi:10.1016/j.respol.2006.08.003 Iammarino, S., & MacCann, P. (2006). The structure and evolution of industrial clusters: Transactions, technology and knowledge spillovers. Research Policy, 35(7), 1018–1036. doi:10.1016/j. respol.2006.05.004

Lemarié, S., Mangematin, V., & Torre, A. (2001). Is the creation and development of biotech SMEs localised? Conclusions drawn from the French case. Small Business Economics, 17(1), 61–76. doi:10.1023/A:1011197616151 Link, A. N., & Link, K. R. (2003). On the growth of U. S. Science Parks. The Journal of Technology Transfer, 28, 81–85. doi:10.1023/A:1021634904546 Lofsten, H., & Lindelof, P. (2005). R&D networks and product innovation patterns—Academic and non-academic new technology-based firms on Science Parks. Technovation, 25, 1025–1037. doi:10.1016/j.technovation.2004.02.007 Manella, B. F. P. (2009). Atractiveness factors of innovative firms for Technology Parks. MSc. Thesis Universidade de São Paulo, Ribeirão Preto.

241

Science Parks and Their Role in the Innovation Process

Markusen, A. (1996). Sticky places in slippery space: A Typology Of Industrial Districts. Economic Geography, 72(3), 294–314. doi:10.2307/144402 Meyer-Stamer, J. (2005). Local economic development: What makes it difficult; What makes it work. In Giordano, P., Lanzafame, F., & Meyer-Stamer, J. (Eds.), Asymmetries in regional integration and local development (pp. 215–225). Washington, DC, USA: Inter-American Development Bank. Nonaka, I., & Konno, N. (1998). The concept of ‘Ba’: Building a foundation for knowledge creation. California Management Review, 40(3), 40–54. Nooteboom, B. (2009). A cognitive theory of the firm – Learning, governance and dynamic capabilities. Cheltenham, UK: Edward Elgar. Ojasalo, J. (2008). Management of innovation networks: A case study of different approaches. European Journal of Innovation Management, 11(1), 51–86. doi:10.1108/14601060810845222 Ratinho, T., & Henriques, E. (2010). The role of Science Parks and business incubators in converging countries: Evidence from Portugal. Technovation, 30, 278–290. doi:10.1016/j.technovation.2009.09.002 Squicciarini, M. (2008). Science Parks’ tenants versus out-of-Park firms: Who innovates more? A duration model. The Journal of Technology Transfer, 33, 45–71. doi:10.1007/s10961-007-9037-z Squicciarini, M. (2009). Science Parks: Seedbeds of innovation? A duration analysis of firms’ patenting activity. Small Business Economics, 32, 169–190. doi:10.1007/s11187-007-9075-9 Storper, M. (2008). Community and economics. In Amin, A., & Roberts, J. (Eds.), Organising for creativity: Community, economy and space (pp. 37–68). Oxford, UK: Oxford University Press. doi:10.1093/acprof:o so/9780199545490.003.0003

242

Storper, M., Lavinas, M. H., & Mercado-Celis, A. (2007). Society, community and development: A tale of two regions. In Polenske, K. (Ed.), The economic geography of innovation (pp. 310–339). Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9780511493386.015 Sun, C. C., Lin, G. T. R., & Tzeng, G. H. (2009). The evaluation of cluster policy by fuzzy MCDM: Empirical evidence from HsinChu Science Park. Expert Systems with Applications, 36, 11895– 11906. doi:10.1016/j.eswa.2009.04.019 Tan, J. (2006). Growth of industry clusters and innovation: Lessons from Beijing Zhongguancun Science Park. Journal of Business Venturing, 21, 827–850. doi:10.1016/j.jbusvent.2005.06.006 Vicente, J. (2000). Interactions economiques et coexistence spatiale des modes de coordination. Doctoral Dissertation, University of Toulouse, France. Wicksteed, B. (2004). Elements of attractiveness in the knowledge economy – Reflections from Cambridge and Singapore. Presented at the International Association of Science Parks´ Annual Conference, Bergamo. Retrieved September 20, 2010, from http://www.sqw.co.uk/ file_download/31 Yang, C. H., Motohashi, K., & Chen, J. R. (2009). Are new technology-based firms located on Science Parks really more innovative? Evidence from Taiwan. Research Policy, 38, 77–85. doi:10.1016/j.respol.2008.09.001 Yu, J., Stough, R. R., & Nijkamp, P. (2009). Governing technological entrepreneurship in China and the west. Public Administration Review, (Special Issue), 95–100. doi:10.1111/j.15406210.2009.02095.x Zander, I. (2004). The microfoundations of cluster stickiness – Walking in the shoes of the entrepreneur. Journal of International Management, 10, 151–175. doi:10.1016/j.intman.2004.02.002

Science Parks and Their Role in the Innovation Process

Zhang, Y. (2004). Critical factors for Science Park management: The North American and European experience. International Journal of Entrepreneurship and Innovation Management, 4(6), 575–586. doi:10.1504/IJEIM.2004.005849

Organizational (Relational) Proximity: Ensemble of relationships between organizations which have similar objectives and therefore foster exchange of information and knowledge. Science Parks: Spaces institutionally designed to host high-tech companies, science laboratories and other innovative organizations.

KEY TERMS AND DEFINITIONS Clusters: Agglomerations of enterprises in a same territory that may develop relations between them.

243

Section 3

Entrepreneurship and Innovation

245

Chapter 14

Entrepreneurial Learning and Innovation:

Building Entrepreneurial Knowledge from Career Experience for the Creation of New Ventures Jonas Gabrielsson Lund University, Sweden Diamanto Politis Halmstad University, Sweden

ABSTRACT The relation between entrepreneurial learning and innovation is poorly understood – especially with respect to how entrepreneurs build up their capability to create new ventures. In this chapter we employ arguments from theories of experiential learning to examine the extent to which entrepreneurs’prior career experience is associated with entrepreneurial knowledge that can be productively used in the new venture creation process. We relate entrepreneurial knowledge to two distinct learning outcomes: the ability to (1) recognize new venture opportunities, and (2) cope with liabilities of newness. Based on analysis of data from 291 Swedish entrepreneurs, we provide novel insights into how and why entrepreneurs differ in their experientially acquired abilities in different phases of the new venture creation process.

DOI: 10.4018/978-1-61350-165-8.ch014

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Entrepreneurial Learning and Innovation

INTRODUCTION The important role of entrepreneurs in bringing innovations into the economic system has been emphasized at least since the workings of Schumpeter (1934). A question that still intrigues scholars is why some individuals are more successful than others in the practice of entrepreneurship. Past research has shown that it is difficult – if not impossible – to point out a single factor that explains entrepreneurial success. The most widely acknowledged viewpoint, however, is that successful entrepreneurs have acquired relevant and valuable experiences throughout their professional careers (e.g., Minniti & Bygrave, 2001; Rae & Carswell, 2001; Shane, 2003). This experiential base in turn enables the development of personal and unique knowledge structures and insights that can be put into productive use in the new venture creation process (Politis, 2005; Corbett, 2007). Yet despite this general inference, there have been very few empirical studies that have examined the extent to which various career experiences lead to entrepreneurial knowledge that can be used in the practice of starting up and managing new innovative ventures. So far, the bulk of past research has instead primarily been concerned with examining associations between entrepreneurs’ career experience and the performance of their new ventures (e.g., Cooper, Woo & Dunkelberg 1989; Brüderl, Preisendorfer & Ziegler 1992; Reuber & Fischer 1993; Butt & Khan 1996). The focus in past research has thus primarily been on firm-level outcomes, while learning outcomes among individual entrepreneurs on the other hand have been largely neglected. Scholars with an interest in learning and knowledge accumulation in entrepreneurial contexts have recently started to explore individual-level learning outcomes (e.g., Harrison & Leitch, 2008). The main argument emphasized for doing this is that previous studies have made great inferential leaps from career experiences directly to firm performance, without any attention to the

246

intermediate learning processes that link inputs to outputs (Reuber & Fischer, 1999; Minniti & Bygrave, 2001; Corbett, 2005; Politis, 2005). Although convenient, such an approach treats the important issues of knowledge accumulation in entrepreneurial contexts as a “black box” and thus overlooks both the sources and outcomes of entrepreneurial learning. As a result, there is hitherto limited scholarly understanding of how enterprising individuals can build up their ability to spot and seize opportunities for entrepreneurial profit throughout their professional careers. A change in focus towards individual-level learning outcomes, however, necessitates a distinction between ‘experience’ on the one side and ‘knowledge’ on the other. One way to distinguish between the two is to follow Reuber, Dyke and Fischer (1990) and consider ‘experience’ as a direct observation of, or participation in, events – while the practical wisdom resulting from what an individual has encountered represents the ‘knowledge’ derived from this particular experience (see also Kolb, 1984). If we accept this, then a relevant question is to what extent there is an association between particular career experiences and the acquisition and development of valuable knowledge that can be put into productive use in the process of new venture creation. Prior studies are unfortunately of little help to answer this question. The two concepts ‘experience’ and ‘knowledge’ have instead most often been used interchangeably with an implicit assumption that entrepreneurs’ prior career experience automatically leads to entrepreneurial knowledge. Whether this implicit assumption bears some (or any) truth is however an empirical question and something which up to date has received very limited empirical attention despite its relevance for both theory and practice. Based on the discussion above, the purpose of this chapter is to examine the extent to which entrepreneurs’prior career experience is associated with entrepreneurial knowledge that can be put into productive use in the process of new venture creation. In the study we treat entrepreneurial

Entrepreneurial Learning and Innovation

knowledge as a theoretical construct proxied by two distinct learning outcomes that have been emphasized in recent entrepreneurship research: their ability to (1) recognize new venture opportunities and (2) cope with liabilities of newness. Through our literature review we identify four career experiences that can be expected to lead to these two learning outcomes: industryspecific experience, small business management experience, varied management experience, and cross-functional experience. Based on statistical analysis of empirical data gathered from 291 practicing entrepreneurs in Sweden, we find that entrepreneurs differ in their ability to perform in different phases of the new venture creation process depending on their prior career experience. In all, the findings support our conjecture that there is a need to distinguish between the two concepts “experience” and “experientially acquired knowledge” in future research on entrepreneurial learning. The rest of the chapter is structured as follows. The next section presents the background where we review relevant literature and define our key concepts. The literature review is followed by a section where we present the hypotheses guiding our study. Once the hypotheses are outlined, we present the method section with a description of the sample and variables used. Thereafter follows the analysis and a presentation of the results. The study ends with a discussion of the findings and suggestions for future research.

BACKGROUND Innovation involves a complex evolutionary process, where many actors and institutions interact in the creation of new entities of economic significance (Edquist, 1997) – from the initial embryonic pieces of information and knowledge that create opportunities for doing novel things, to the innovation’s ultimate diffusion in society (Fagerberg, 2005). Entrepreneurs play a crucial

role in this process as they are the ones who make ideas for new or better ways of serving customers and markets come into existence by identifying and acting on opportunities for entrepreneurial profit (Shane & Venkataraman, 2000). Several scholars emphasize the role of knowledge for the pursuit of entrepreneurial activities, by relating the opportunities that people recognize and exploit to information and knowledge asymmetries in the economy (e.g., Venkataraman, 1997; Shane, 2000; Ardichvili, Cardozo & Ray, 2003; Shane, 2003; De Clercq & Arenius, 2006; see also Kirzner, 1973). A common argument in their writings is that only a few people have knowledge about inventions, inefficiencies or resources that currently are not put to their best use, and that by making productive use of this knowledge they are able to spot and seize opportunities for entrepreneurial profit. This knowledge is moreover based on the education and accumulated career experience they have obtained throughout their professional lives (Shane, 2000). In this study we have set out to examine the extent to which entrepreneurs’ prior career experience is associated with entrepreneurial knowledge. By this, we mean knowledge that entrepreneurs can put into practical use to produce or create a desirable outcome in the process of new venture creation. Shane and Venkataraman (2000) delineate entrepreneurship as an activity that involves the discovery, evaluation and exploitation of opportunities to introduce new goods and services, ways of organizing markets, processes and raw materials through organizing methods that previously have not existed. This definition helps us to identify two distinct phases in the new venture creation process – the first being opportunity recognition where opportunities for new ventures are discovered and subsequently evaluated (Ardichvili et al., 2003), and the second being opportunity commercialization where a new venture is formed and established (Delmar & Shane, 2004). Individuals may in reality engage in both phases simultaneously, for example if they

247

Entrepreneurial Learning and Innovation

are involved in several concurrent projects that are in different stages of development. However, the initial organizing and development of a new venture centers on a new venture opportunity that must have been recognized and evaluated at some earlier point in time. Thus, from a theoretical point of view, opportunity commercialization cannot take place without prior opportunity recognition. In line with this discussion, we relate entrepreneurial knowledge to two distinct learning outcomes that have been emphasized in recent entrepreneurship research (Politis, 2005; Huovinen & Tihula, 2008). The first learning outcome refers to knowledge that increases entrepreneurs’ ability to effectively recognize new venture opportunities. A successful entrepreneur is in this respect often described as an alert person who is aware of, or receptive to, unevenly distributed information about market imperfections (Kirzner, 1973; Shane & Venkataraman, 2000). This personal and highly localized information can then be used as a basis for developing the first entrepreneurial insights into a more developed idea of how the market need might be served and resources deployed to yield profit (Ardichvili et al., 2003). The second learning outcome refers to knowledge that increases entrepreneurs’ ability to organize and manage new ventures, which in practice means coping with “liabilities of newness” (Shepherd, Douglas & Shanley, 2000). The term was originally coined by Stinchcombe (1965) who in his seminal study reported that the risk of business closure is highest at the point of founding of an organization, and decreases with growing age of the organization. The reasons for this risk were certain liabilities that newcomers suffer compared to already established players, such as the lack of a stable portfolio of clients and the time required for learning new organizational roles to be performed by their members. In sum, entrepreneurial knowledge can from this discussion be conceptualized as knowledge facilitating the ability to recognize new venture opportunities, and to effectively cope

248

with liabilities of newness when organizing and managing new ventures. Extant research points toward the importance of personal first-hand work experience for developing the ability to recognize and exploit new venture opportunities (Politis, 2005; Corbett, 2007). For example, empirical studies suggest that experienced business founders throughout their career develop a unique “knowledge corridor” through which they interpret the outside world, which in turn enhances their ability to recognize and evaluate additional new venture ideas (Ronstadt, 1988; Venkataraman, 1997). It is this knowledge corridor that enables them to use their experientially acquired knowledge base to assess the potential benefit in an opportunity in either a positive or negative light (Park, 2005). The ability to make sense and use of new information to find ideas for new venture opportunities, to assimilate them and apply them to commercial ends can hence to a large extent be seen as a function of an individual’s prior experience (Cohen an&d Levinthal, 1990; Rae, 2000; Shane, 2000). Based on the reasoning above, it seems fair to argue that the extent to which individuals are effectively involved in recognizing and exploiting new venture opportunities can be expected to be highly dependent on their prior career experience. A conceptual foundation for understanding how individuals acquire and develop knowledge based on their career experience can be found in theories and models of experiential learning (for applications of experiential learning theory in entrepreneurship studies, see e.g. Bailey, 1986; Johannisson, Landström & Rosenberg, 1998; Baum et al., 2003; Corbett, 2007). A key tenet in theories of experiential learning is the need to draw a distinction between the experience of an individual and the knowledge he or she acquires from that experience (Reuber et al., 1990; Politis, 2005). This observation can be related back to Kolb (1984) who argues that experiential learning requires at least two interrelated dimensions, namely the grasping of experience, and then some

Entrepreneurial Learning and Innovation

transformation of this particular experience into knowledge. Hence, the simple perception of an experience is not sufficient for learning to happen, which requires that something must be done with it. Similarly, transformation alone cannot represent learning for there must be something to be transformed, some state or experience that is being acted upon. This distinction means, at least conceptually, that the experience of an individual will not automatically represent the knowledge derived from this particular experience. Further, it can be conjectured that some career experiences are more beneficial than others for the acquisition and development of entrepreneurial knowledge. Thus, the conceptual distinction between experience and knowledge that is made in theories of experiential learning intensifies the question of how different kinds of career experiences may lead to the development of entrepreneurial knowledge that can be productively used by entrepreneurs in the process of new venture creation.

DEVELOPMENT OF HYPOTHESES In the following section we will develop hypotheses which associate particular career experiences with the two learning outcomes that were previously identified. For this discussion we have deliberately chosen career experiences that have received limited empirical attention in past research, even though they are often expected to be conducive to entrepreneurial learning. Theoretically, the hypotheses are grounded in the conceptual discussion above together with empirical literature and research on entrepreneurial learning and development.

Industry-Specific Experience Past research suggests that prior industry-specific experience can facilitate the development of valuable knowledge that enhances entrepreneurs’ ability to both spot and seize new venture

opportunities and to organize and manage new ventures. For example, studies have shown that entrepreneurs tend to start businesses in industries in which they were previously employed, because this allows them to take advantage of important information and knowledge gained during this period (Aldrich, 1999). Entrepreneurs with prior industry experience also generally have a better understanding of how to meet demand conditions in the market place (Shane, 2000). Moreover, the products, services, customers and suppliers of surviving ventures have been found to be more closely related to the products, services, customers and suppliers of the entrepreneurs’ previous employers, compared to non-surviving ventures (Cooper, Dunkelberg & Woo, 1988; Bates & Servon, 2000). Industry-specific experience can hence be expected to provide entrepreneurs with valuable insights about relevant contacts, reliable suppliers, viable markets and product availability, all of which could influence their ability to recognize new venture opportunities and cope with liabilities of newness (Cooper et al., 1993; Politis, 2005). Based on these arguments, the following hypotheses are proposed: H1a: Prior industry-specific experience is positively associated with a higher number of recognized new venture opportunities. H1b: Prior industry-specific experience is positively associated with an ability to better cope with liabilities of newness.

Small Business Management Experience Another kind of career experience that has been highlighted in research on entrepreneurial learning is management experience (Cooper, Woo & Dunkelberg, 1989; Duchnesneau & Gartner, 1990; Reuber & Fischer, 1994). Management experience may in this respect provide entrepreneurs with knowledge of markets, ways to serve markets, and customer problems, all of which are impor-

249

Entrepreneurial Learning and Innovation

tant dimensions in the process of entrepreneurial discovery (Shane, 2000). A consistent finding from previous reviews of management studies is however that managerial work is contextually dependent, rather than task-dependent (Hales, 1986; Whitley, 1989). This implies that managerial work requirements vary considerably, depending on functional area, management level, and organizational attributes such as type, structure, size and industry (Reuber, 1997). Empirical studies suggest that small firms are the most typical setting where entrepreneurs carry out their managerial work (Butt & Khan, 1996; Cooper et al., 1989; Gimeno et al., 1997; Lee & Tsang, 2001; Reuber & Fischer, 1994). Previous experience from managing a small business can thus be expected to provide budding entrepreneurs with training in many of the skills needed for recognizing and acting on entrepreneurial opportunities, including negotiating, leading, planning, decision-making, problem-solving, organizing and communicating (Romanelli & Schoonhoven, 2001; Shane, 2003). Entrepreneurs with previous management experience are moreover generally found to have a higher likelihood of success, implying that they are better prepared to cope with traditional obstacles facing new ventures (Cooper et al., 1989; Duchnesneau & Gartner, 1990; Stuart & Abetti, 1990). Based on these arguments, the following hypotheses are proposed: H2a: Prior small business management experience is positively associated with a higher number of recognized new venture opportunities. H2b: Prior small business management experience is positively associated with an ability to better cope with liabilities of newness.

Varied Management Experience In addition to small business management experience, there are also indications that varied management experience may be beneficial for individuals that are involved in new venturing

250

activities (Reuber 1997; Reuber & Fischer 1994). Varied management experience refers to experience from managing people in different firm contexts. Individuals with such experience are for example generally used to dealing with subordinates in the organization and it may also bring valuable knowledge about a wider set of potential customers and reliable suppliers, as well as valuable social contacts with important stakeholders (Baucus & Human 1994; Hambrick & Crozier 1985). Moreover, varied management experience may provide exposure to a wider variety of situations and problems, and it is often through surviving and understanding such novel situations that learning takes place (Fiol & Lyles, 1985; Reuber, 1997). Varied management experience from firms with different sizes may in this respect increase entrepreneurs’ ability to handle problems that are “taken for granted” in the small firm context, as diversity in cognitive inputs often reduces the risk of home-blindness, path-dependence and lock-in (e.g., Krueger, 2009). Thus, having management experience from businesses of varied sizes can be an additional dimension that also may be fruitful to consider when investigating sources of entrepreneurial knowledge (Dyke, Fischer & Reuber, 1992). Hence, the following hypotheses are proposed: H3a: Varied management experience is positively associated with a higher number of recognized new venture opportunities. H3b: Varied management experience is positively associated with an ability to better cope with liabilities of newness.

Cross-Functional Experience Another experience dimension that has attracted scholarly interest is the functional experience of the entrepreneur (Cooper, 1985; Reuber & Fischer, 1994; Stuart & Abetti, 1990; Sykes, 1986; Vesper, 1980). This type of experience relates to professional experience from various functional areas,

Entrepreneurial Learning and Innovation

such as management, production, product development and R&D, marketing and selling, accounting, finance, etc. Previous research has failed to find any consistent associations between particular types of functional experience and new venture performance (Stuart & Abetti, 1990). Rather, the empirical findings indicate that entrepreneurial learning stems from having functional experience across different kinds of business functions. In a study of success factors of new ventures, Vesper (1980) found that experience from different functional areas was an indicator of better new venture performance. In line with these findings, Cooper (1985) found that the participation in or observation of a wide range of business functions was an experience relevant to successful venture formation in his study of incubator organizations. Moreover, Sykes (1986) found a very strong correlation between new venture financial success and having both previous management and sales experience. Experience from a broad array of functional areas seems consequently to result in the consideration of more alternatives and more careful evaluation of alternatives – cognitive processes that generally also are considered to contribute to the quality of decision-making in uncertain environments (Milliken & Vollrath, 1991). Based on these arguments, the following hypotheses are proposed: H4a: Cross-functional experience is positively associated with a higher number of recognized new venture opportunities. H4b: Cross-functional experience is positively associated with an ability to better cope with liabilities of newness.

RESEARCH METHOD Sample To answer the research question and test the hypotheses developed in this chapter, we designed

the empirical study as a questionnaire survey. The measures were derived from a careful review of previous theoretical and empirical work on experiential and entrepreneurial learning. Before sending out the questionnaire, it was pilot-tested on a smaller group of practicing entrepreneurs and entrepreneurship scholars. Based on this feedback, the questions were honed and clarified for the final research instrument. The initial sample included 1000 randomly selected entrepreneurs who each started an independent new firm in 1998-2002. We collected information about contact addresses from Statistics Sweden and the questionnaire was sent out in early fall 2004 addressed to the CEOs of the targeted firms. To verify that the person who answered the questions had experience of starting up a new firm, we included a control question in the questionnaire. After the first mailing round we immediately received 15 envelopes in return, due to problems of finding the individual entrepreneur (unknown address, ownership changes, liquidation etc.). This reduced the total number of cases to 985. After one postal follow-up we received 303 complete questionnaires, corresponding to a valid response rate of approximately 30.8%. This response rate compares favorably to similar studies of entrepreneurial learning (e.g. Dyke, Fischer & Reuber, 1992; Reuber & Fischer, 1994; Ucbasaran, Westhead & Wright, 2008). Before making the final analyses we excluded responses from 12 individuals who had no experience of starting up a business. This led to a final sample of 291 cases. We conducted chi-square and t-tests to assess whether the results from the sample could be generalized to the population. These tests revealed no statistically significant differences between respondents and non-respondents with regard to industry, geographical location, firm size and age of their current business. In addition, we conducted chi-square and t-tests to examine if there were any differences between first-round (69.6% of total responses) and second-round (30.4% of total responses) respondents. No significant dif-

251

Entrepreneurial Learning and Innovation

ferences could be found between the early and late responses with respect to the same variables. Moreover, no significant differences were found between early and late respondents with regard to the variables used in the study (see next section below). Hence, on these criteria we have no reason to suspect that there are any significant response biases in our sample.

Variables and Measures Dependent Variables In the study we treat entrepreneurial knowledge as a theoretical construct, proxied by the self-assessed ability to recognize new venture opportunities and cope with liabilities of newness. In line with our frame of reference, the first learning outcome variable was constructed by an item measuring the number of new venture ideas which the entrepreneur had in the last year and which could lead to a potential new business or a significant part of a business. This conceptualization is consistent with previous research on opportunity development, suggesting that the process starts with the perception of opportunities for recombining resources on the market that the entrepreneur believes will yield profit, and where the idea for a new venture continually develops as individuals shape these elemental insights into a notion of an emerging business concept (i.e., Bhave, 1994; Ardichvili et al., 2003; Klofsten, 2005). We validated the measure against an item measuring the number of business opportunities (defined as unmet customer needs) that the entrepreneur had seized during the last five years. The result shows that the two items are positively and significantly associated at p <.01, which also supports our conceptualization of the opportunity development process described above. A higher score on this item indicates a higher number of recognized new venture opportunities. Due to a skewed distribution, the variable was transformed using a logarithmic transformation. We acknowledge that this item is biased towards

252

the quantity rather than the quality of new venture opportunities. However, in a larger pool of new venture opportunities there is greater likelihood that one or some of them can develop into a viable business concept (Ucbasaran, Westhead, & Wright, 2008). Based on this argument, we thus posit that there is a value in generating more rather than fewer new venture opportunities. The second learning outcome variable was the entrepreneur’s self-assessed ability to cope with liabilities of newness. This variable was constructed using the mean of four items on a Likert-type scale, where respondents were asked to rate the extent (1 = very low extent, 5= very high extent) to which they would consider the following obstacles as problematic if they were currently involved in creating and organizing a new venture: (1) convincing potential clients about the new venture, (2) uncertainty regarding the market potential for the product or service, (3) lack of stable relationships with key stakeholders, and (4) uncertainty regarding roles and functions in the organization that a new venture would require. The responses were then reverse-coded so that a higher score on the scale indicates an ability to better handle liabilities of newness. These questions were developed expressly for this research based on prior theoretical work on the liabilities of newness (Aldrich, 1999; Shepherd et al., 2000; Starr and Bygrave, 1992; Stinchcombe, 1965). Cronbach’s alpha (α) for this construct was.59. However, as α can be a relatively weak indicator of internal consistency when few variables are employed in a composite measure, we also checked item-to-total correlations by applying the rule-ofthumb procedure suggested by Hair et al. (1998). Here we found that the item-to-total correlations were between.59 and.71, which was well above the suggested limit of above.50. Moreover, to assess whether our measure could be associated with any firm-level performance advantages when exploiting new venture opportunities, we initially set out to collect information about firm survival. These data were collected in 2007 by identifying

Entrepreneurial Learning and Innovation

the number of firms in the sample that were still operating during 2006. However, we could locate only a handful of firms (n=27) that had closed down. This rendered us unable to correlate our liability of newness measure against a measure of survival. Instead, we made analyses with respect to firm sales growth (the year-to-year average change in sales). Through this procedure we found that entrepreneurs with a higher reported ability to handle liabilities of newness to a significantly higher extent were in a high-performing group (with a sales growth which was 2.5 or higher, p. >.05), which may be a sign of an ability that the entrepreneur can cope with traditional obstacles more effectively in the early development of a firm.

Independent Variables The research model involves four main independent variables. “Industry-specific experience” was measured as the entrepreneurs’ total number of years of experience from the industry they now operate in. “Small business management experience” was measured as the number of years that the entrepreneur has had a management position in a small firm. Here, we followed the EU definition of a small firm as a firm with less than 50 employees. “Experience from varied management positions” was measured as a dichotomous variable, indicating if the entrepreneur had experience also from management positions in medium-sized or large firms (0= no, 1= yes). “Cross-functional experience” was measured as the number of different business functions that the entrepreneur had experience from. Based on the work of Stuart and Abetti (1990), McGee, Dowling and Megginson (1995) and Entrialgo (2002), we used six functional areas to identify and distinguish between different work functions: (1) general management, (2) R&D, (3) manufacturing/production, (4) sales/ marketing, (5) finance, and (6) law.

Control Variables We also included three control variables in the research model. The first control variable was related to the individuals’ experience of discontinuing their earlier ventures due to bankruptcy. We included this control as research has shown that owners often believe they learn significantly from a business closure process so that they are better equipped to run businesses in the future (Stokes & Blackburn, 2002; Politis & Gabrielsson, 2009). Experience from business closure may moreover affect the entrepreneur’s ability to attract further resources in his or her subsequent venturing activities (Cope, Cave and Eccles, 2004). Bankruptcy experience was measured as a dichotomous variable, indicating if the respondent had previous experience from discontinuing an earlier venture due to bankruptcy (0= no, 1= yes). The second control variable was the prior start-up experience of the respondent. We included this control as it is widely acknowledged that prior experience from starting a new venture increases the probability that an individual will continue to identify and exploit new venture opportunities (Duchesneau & Gartner, 1990; Shane, 2003; Shane & Khurana, 2003). The primary reason for this expected association is that the experience gained from starting up one business enables the entrepreneurs to recognize and act on further entrepreneurial opportunities they could neither see, nor take advantage of, until they had started their initial venture (Ronstadt, 1988; see also Shepherd, Douglas & Shanley, 2000; Starr & Bygrave, 1992 for similar findings). Prior start-up experience was measured as a dichotomous variable, indicating if the respondent had previous experience from starting up a new venture (0= no, 1= yes). The third control variable was related to the entrepreneur’s experience from working in high-growth industries, i.e. sectors of the economy that experience a higher-than-average growth rate (Storey, 1994). High-growth industries are generally characterized by rapid changes and fast technological progress,

253

Entrepreneurial Learning and Innovation

which in turn can influence the level of opportunity present in those industries (Shane, 2003). New business opportunities are hence more likely to occur in growing markets. Studies of managers operating in high-growth industries have moreover suggested that these individuals often are more alert in acting on opportunities while repressing environmental threats (Covin & Slevin 1989). Studies have furthermore indicated that the environment can be highly heterogeneous both within and across industries (Keats & Hitt, 1988; Zahra, 1993). Therefore we chose to measure the entrepreneur’s perception of this type of experience, rather than to classify specific industries that we thought could be considered high-growth industries. We measured industry growth as the entrepreneur’s experience from working in highgrowth industries on a Likert-type scale (1=minor experience, 5=major experience).

Sample Characteristics The individuals in the final sample represent a broad cross-section of entrepreneurs. Their mean age was 47.3 years (min=24, max=73), and the average total years of work experience was 25.4 (min=4, max=50). About 12% of the entrepreneurs had compulsory school education (7 or 9 years) as their highest education level, 33.7% had education also from gymnasium/senior high school, and 50.8% had some sort of higher education (university studies). The majority of these individuals (68.7%) were moreover entrepreneurs with multiple start-up experience, so-called “habitual entrepreneurs” (MacMillan, 1986; Westhead & Wright, 1998). The average number of start-ups was 2.51 (min=1, max=15), and the average total work experience of self-employment was 12.8 years (min=1, max=41). The most common industry-specific experience was from consulting and other business services (49.3%), followed by wholesale and retail (28.5%), and construction (28.2%). About 69% of the entrepreneurs had experience from

254

working in two or more industries. About 85% had experience from having a management position in a small firm (i.e., firms with less than 50 employees), and the average number of years in this position was 9.6 years (min=0, max=35). About 62% of the entrepreneurs had experience from three or more functional areas of expertise, where functional expertise in general management, marketing/sales and accounting/finance was the most common. The number of years of experience from these three functional areas were highly correlated with the number of years from working as a small business manager (r.=69, r.=45, and r.=44 respectively). Over two thirds of the entrepreneurs (69.6%) had experience as board members, and 34.5% of the entrepreneurs had experience from investing their own money as risk capital in unlisted firms in which they have no previous family connections.

ANALYSIS AND RESULTS In our research model we have metric measures as dependent variables and several metric or dichotomous independent variables, so we considered linear multiple regression analysis as an appropriate statistical technique (Hair et al., 1998). A description of the variables used in the analysis (correlations, means and standard deviations) is displayed in the table in Figure 1. We expected some difficulties with using variables connected to entrepreneurs’ career experience in the study. For example, individuals with prior start-up experience also generally have experience from managing these ventures. As we expected, there were inter-correlations among some of the independent variables even though they are well below threshold levels for multicollinearity problems. All correlation coefficients are less than r =.70, which according to Nunnally (1978) is the standard threshold used to determine high correlation. Moreover, all explanatory variables in the regression analysis had

Entrepreneurial Learning and Innovation

Figure 1. Pearson correlation matrix, means and standard deviations

VIF’s between 1.02 and 1.35, which lead us to conclude that no problems of multicollinearity exist in our data set. To identify the separate effects of the control variables and the four experience variables, we conducted a stepwise multiple regression. First we entered the control variables (Step 1). This step is presented as Equation I. Then we included the four experience variables (Step 2). This step is presented as Equation II. Additional analyses of the data controlled for the possibility that the control variables moderate the relationship between independent and dependent variables, but these tests did not reveal any significant results. The results of these analyses will therefore not be reported. The result of the final multiple regression analysis is presented in Figure 2. The final regression model (Equation II) shows that there is no association between industryspecific experience and a higher number of recognized new venture opportunities. There is also no association between industry-specific experience and the ability to cope with liabilities of newness. Hence, the empirical data do not support either Hypothesis 1a or 1b. We can also see in Figure 2 that Hypothesis 2a is not supported, showing no association between small business management experience and a higher number of recognized new venture opportunities. However,

Hypothesis 2b is supported as there is a positive and significant association between small business management experience and the ability to cope with liabilities of newness (p <.05). There is no significant association between varied management experience and a higher number of recognized new venture opportunities, indicating no support for Hypothesis 3a. The data in Figure 2 support Hypothesis 3b, however, as there is a positive and significant association between varied management experience and the ability to cope with liabilities of newness (p <.01). The data in Figure 2 also support Hypothesis 4a, as crossfunctional experience was positively associated with a higher number of recognized new venture opportunities (p <.01). But there was no significant association between cross-functional experience and coping with liabilities of newness, indicating no support for Hypothesis 4b.

DISCUSSIONS AND CONCLUSION Entrepreneurial learning is a key ingredient in successful innovation, as it supports the production and transformation of knowledge into the creation of new ventures. It is in this respect widely acknowledged that different career paths create knowledge asymmetries which in turn lead

255

Entrepreneurial Learning and Innovation

Figure 2. Regression analysis

individuals to value resources differently (Shane, 2000). Opportunities for entrepreneurial profit occur on the basis of such asymmetries when some people, throughout their careers, learn to discover and develop ideas for new products or processes that other people are willing to pay for. The ability to make productive use of their personal stock of knowledge that entrepreneurs develop from career experience is thus a key ingredient in the overall process of innovation where new ideas are commercialized and diffused in society. In this study we add to past research on entrepreneurial learning and innovation by showing that entrepreneurs differ in their ability to make productive use of their knowledge in the new venture creation process, depending on their prior career experience. The value of different kinds of career experience can in this respect be related to different phases in the process of new venture creation (Shane & Venkataraman, 2000). Professional experience from various functional areas is of value for the entrepreneur before the formal establishment of the new venture, as it influences his or her ability to come up with entrepreneurial ideas and insights. Small business management experience and varied management

256

experience, on the other hand, are of value for the entrepreneur after the formal establishment of the new venture, as they influence his or her ability to effectively cope with liabilities of newness. Our empirical findings contribute to current research on entrepreneurial learning where ‘experience’and ‘knowledge’ often have been used interchangeably with the implicit assumption that career experience automatically leads to entrepreneurial knowledge. The findings thus suggest that there is a need to reconsider this implicit assumption, and future research will hopefully use these insights to advance our understanding of how entrepreneurs develop knowledge from experience. In addition, our findings provide valuable insights into the practice of new venture creation, specifically suggesting that different career experiences may lead to different kinds of knowledge advantages among entrepreneurs. As such, our study supports the importance of experiential learning for the development of knowledge that can be productively used by entrepreneurs in the new venture creation process.

Entrepreneurial Learning and Innovation

Limitations Some potential limitations of the present study should be mentioned. First, we have used a simplified model with the aim of examining personal experience-related factors that are located extensively in the entrepreneur. However, new venturing activities are in many ways also a social exchange process (Pittaway & Cope, 2007), and entrepreneurs have frequently been found to base their decisions on personal and professional advice through their personal networks (Birley, 1985; Aldrich & Zimmer, 1986; Brüderl & Presiendorfer, 1998). Their personal networks seem in this respect to provide them with critical and essential information, and also expose them to new and different ideas and worldviews (Johannisson, 2000; Singh, 2000; Ozgen a&d Baron, 2007). Our findings are hence only part of the story, and further research should also consider dimensions of experience related to entrepreneurs’ social surroundings when investigating the relationship between prior career experience and entrepreneurial knowledge. Second, our two measures of entrepreneurial knowledge were based on the self-assessed ability to recognize new venture opportunities and cope with liabilities of newness respectively. Although self-perceptive measures can be a fairly good indication of an individual’s ability to perform certain tasks (Gist, 1987), this is not necessarily the same as the actual long-run performance of these tasks. To examine this issue further we suggest developing, combining and comparing both subjective and objective measures in future studies. Third, we should also like to mention that we are aware of the potential limitations in measuring only the amount or quantity of career experience of entrepreneurs. The reason why we bring this up is that we could observe that some entrepreneurs derived greater, and others less, benefit from their career experience. Hence, even though the regressed mean in our analyses showed significant associations between some particular career expe-

riences and learning outcomes, there were some entrepreneurs who seemed to learn “more” than others from the same amount of career experience. Interestingly, this may suggest that there exist not only knowledge advantages depending on differences in their prior career experience, as we point out in this study, but also some kind of learning advantages among entrepreneurs with similar amounts of career experience. If so, this would imply that some entrepreneurs are more effective in transforming their experience into knowledge that can be productively used in the practice of starting up and managing new ventures. However, this discussion is highly speculative and an examination of these issues would require additional variables and more rigorous statistical analyses. Nevertheless, it provides some interesting and relevant ideas for further research which may increase the explanatory power of our theoretical model.

Implications Despite the above-mentioned potential limitations, we believe our study has some important implications for the practice of entrepreneurship. A general conclusion that can be drawn from our findings is the important role that an individual’s prior career experience plays for the successful acquisition and development of entrepreneurial knowledge. The professional career seems in this respect to expose enterprising individuals to distinct learning opportunities (van Gelderen, van de Sluis & Jansen, 2005) that can enhance their ability to recognize and exploit new venture opportunities. In addition, the findings suggest that different kinds of career experience lead to different kinds of entrepreneurial knowledge (Politis, 2005). Cross-functional experience seems to provide individuals with productive knowledge that improves their ability to recognize new venture opportunities. Small business management experience and varied management experience seem on the other hand to provide individuals

257

Entrepreneurial Learning and Innovation

with productive knowledge that increases their ability to handle liabilities of newness in the new venture creation process. Interestingly, the empirical findings also show that there are no significant associations between the ability to effectively recognize new venture opportunities and the ability to effectively cope with liabilities of newness. This implies that individuals who have developed one kind of knowledge advantage have not necessarily developed the other type of knowledge advantage. This should be kept in mind, as it implies that an individual entrepreneur is generally not able to cover all the skills and knowledge areas necessary to successfully develop and pursue an identified opportunity through the different phases in the entrepreneurial process. It also speaks in favor of new venture teams (e.g., Chandler, Honig & Wiklund, 2005; Foo, Sin & Yiong, 2006) for successfully handling the process of developing a new venture from initial conception to establishment. Empirical findings, for example, point to a positive relationship between team size and new venture growth, especially in cases where the team possesses diverse educational and professional backgrounds (Lüthje & Prügl, 2006). Hence, even if entrepreneurs do not possess all relevant kinds of experience and knowledge themselves, they may have access to valuable knowledge resources through a well-composed new venture team.

Conclusion Recent studies have highlighted the need to better understand the relationship between entrepreneurial learning and innovation by examining how individuals learn to act entrepreneurially in different contexts (e.g., Harrison and Leitch, 2008). In this chapter, we add to this growing body of literature by presenting an empirical study of the extent to which entrepreneurs’ prior career experience is associated with their productive use of knowledge in the new venture creation process. Based on theories of experiential learn-

258

ing, we provide empirical evidence suggesting that different career experiences are associated with different kinds of knowledge, which in turn provide the basis for performance differentials in the new venture creation process. Conceptually, we also argue that there is a need to distinguish between “experience” and “knowledge” in future studies of entrepreneurial learning. In all, we believe that our arguments and findings in this study contribute a more detailed understanding of entrepreneurship as an experiential learning process, which also provides some general implications for future research.

REFERENCES Aldrich, H. E. (1999). Organizations evolving. London, UK: Sage. Aldrich, H. E., & Zimmer, C. (1986). Entrepreneurship through social networks. In Sexton, D., & Smilor, R. (Eds.), The art and science of entrepreneurship (pp. 3–23). Cambridge, MA: Ballinger. Ardichvili, A., Cardozo, R., & Ray, S. (2003). A theory of entrepreneurial opportunity identification and development. Journal of Business Venturing, 18(1), 105–123. doi:10.1016/S08839026(01)00068-4 Bailey, J. (1986). Learning styles of successful entrepreneurs. In Ronstadt, R., Hornaday, J., Peterson, J. R., & Vesper, K. (Eds.), Frontiers of entrepreneurship research (pp. 199–210). Wellesley, MA: Babson College. Baucus, D. A., & Human, S. E. (1994). Secondcareer entrepreneurs: A multiple case study of entrepreneurial processes and antecedent variables. Entrepreneurship Theory and Practice, 19(2), 41–71.

Entrepreneurial Learning and Innovation

Bhave, M. (1994). A process model of entrepreneurial creation. Journal of Business Venturing, 9(3), 223–242. doi:10.1016/08839026(94)90031-0 Box, T. M., White, M. A., & Barr, S. H. (1993). A contingency model of new manufacturing firm performance. Entrepreneurship Theory and Practice, 18(2), 31–45. Butt, A., & Khan, W. (1996). Effects of transferability of learning from pre start-up experiences. In Reynolds, P. D., Birley, S., Butler, J. E., Bygrave, W. D., Davidsson, P., Gartner, W. B., & McDougall, P. P. (Eds.), Frontiers of entrepreneurship research (pp. 108–116). Wellesley, MA: Babson College. Chandler, G. N., Honig, B., & Wiklund, J. (2005). Antecedents, moderators, and performance consequences of membership change in new venture teams. Journal of Business Venturing, 20(5), 705–725. doi:10.1016/j.jbusvent.2004.09.001 Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152. doi:10.2307/2393553 Cooper, A. C. (1985). The role of incubator organizations in the founding of growth oriented firms. Journal of Business Venturing, 1(1), 75–86. doi:10.1016/0883-9026(85)90008-4 Cooper, A. C., Woo, C. Y., & Dunkelberg, W. C. (1989). Entrepreneurship and the initial size of firms. Journal of Business Venturing, 4(5), 317–332. doi:10.1016/0883-9026(89)90004-9 Cope, J., Cave, F., & Eccles, S. (2004). Attitudes of venture capital investors towards entrepreneurs with previous failure. Venture Capital, 6(2/3), 147–172. doi:10.1080/13691060410001675965

Corbett, A. C. (2005). Experiential learning within the process of opportunity identification and exploitation. Entrepreneurship Theory and Practice, 29(4), 473–491. doi:10.1111/j.15406520.2005.00094.x Covin, J. G., & Slevin, D. P. (1989). Strategic management of small firms in hostile and benign environments. Strategic Management Journal, 10, 75–87. doi:10.1002/smj.4250100107 De Clercq, D., & Arenius, P. (2006). The role of knowledge in business start-up activity. International Small Business Journal, 24(4), 339–358. doi:10.1177/0266242606065507 Delmar, D., & Shane, S. (2004). Legitimating first: Organizing activities and the survival of new ventures. Journal of Business Venturing, 19(3), 385–410. doi:10.1016/S0883-9026(03)00037-5 Duchesneau, D. A., & Gartner, W. B. (1990). A profile of new venture success and failure in an emerging industry. Journal of Business Venturing, 5(5), 297–312. doi:10.1016/08839026(90)90007-G Dyke, L. S., Fischer, E. M., & Reuber, A. R. (1992). An inter-industry examination of the impact of owner experience on firm performance. Journal of Small Business Management, 30(4), 72–78. Edquist, C. (Ed.). (1997). Systems of innovation: Technologies, institutions and organizations. London, UK: Pinter/Cassell. Entrialgo, M. (2002). The impact of the alignment of strategy and managerial characteristics on Spanish SMEs. Journal of Small Business Management, 40(3), 260–270. doi:10.1111/1540-627X.00056 Fagerberg, J. (2005). Innovation: A guide to the literature. In Fagerberg, J., Mowery, D. C., & Nelson, R. R. (Eds.), The Oxford handbook of innovation. Oxford, UK: Oxford University Press.

259

Entrepreneurial Learning and Innovation

Fiol, C. M., & Lyles, M. A. (1985). Organizational learning. Academy of Management Review, 10(4), 803–813. Foo, M., Sin, H., & Yiong, L. (2006). Effects of team inputs and intra-team processes on perceptions of team viability and member satisfaction in nascent ventures. Strategic Management Journal, 27(4), 389–399. doi:10.1002/smj.514 Gimeno, J., Folta, T., Cooper, A. C., & Woo, C. Y. (1997). Survival of the fittest? Entrepreneurial human capital and the persistence of underperforming firms. Administrative Science Quarterly, 42, 750–783. doi:10.2307/2393656 Gist, M. E. (1987). Self-efficacy: Implications for organizational behaviour and human resource management. Academy of Management Review, 12, 472–486. Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, New Jersey: Prentice Hall. Hales, C. P. (1986). What do managers do? A critical review of the evidence. Journal of Management Studies, 23(1), 88–115. doi:10.1111/j.1467-6486.1986.tb00936.x Hambrick, D. C., & Crozier, L. M. (1985). Stumblers and stars in the management of rapid growth. Journal of Business Venturing, 1(1), 31–45. doi:10.1016/0883-9026(85)90005-9 Harrison, R., & Leitch, C. (Eds.). (2008). Entrepreneurial learning: Conceptual frameworks and applications. London, UK: Routledge. Huovinen, J., & Tihula, S. (2008). Entrepreneurial learning in the context of portfolio entrepreneurship. International Journal of Entrepreneurial Behaviour & Research, 14(3), 152–171. doi:10.1108/13552550810874673 Johannisson, B. (2000). Networking and entrepreneurial growth. In Sexton, D. L., & Landström, H. (Eds.), Handbook of Entrepreneurship (pp. 368–386). Oxford, UK: Blackwell Business. 260

Johannisson, B., Landström, H., & Rosenberg, J. (1998). University training for entrepreneurship – An action frame of reference. European Journal of Engineering Education, 23(4), 477–496. doi:10.1080/03043799808923526 Keats, B., & Hitt, M. (1988). A causal model of linkages among environmental dimensions, macro organizational characteristics, and performance. Academy of Management Journal, 31, 570–598. doi:10.2307/256460 Klofsten, M. (2005). New venture ideas: An analysis of their origin and early development. Technology Analysis and Strategic Management, 17(1), 105–119. doi:10.1080/09537320500044776 Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, New Jersey: Prentice Hall. Krueger, N. (2009). The microfoundations of entrepreneurial learning and…education, In E. Gatewood, E. and G.P. West (Eds) Handbook of cross campus entrepreneurship, Cheltenham, UK: Edvard Elgar. Laitinen, E. K. (1992). Prediction of failure of a newly founded firm. Journal of Business Venturing, 7(4), 323–340. doi:10.1016/08839026(92)90005-C Lee, D., & Tsang, E. (2001). The effects of entrepreneurial personality, background and network activities on venture growth. Journal of Management Studies, 38(4), 583–602. doi:10.1111/14676486.00250 Lüthje, C., & Prügl, R. (2006). Preparing business students for co-operation in multi-disciplinary new venture teams: Empirical insights from a businessplanning course. Technovation, 26(2), 211–219. doi:10.1016/j.technovation.2004.10.010 MacMillan, I. C. (1986). To really learn about entrepreneurship, let’s study habitual entrepreneurs. Journal of Business Venturing, 1(3), 241–243. doi:10.1016/0883-9026(86)90001-7

Entrepreneurial Learning and Innovation

McGee, J. E., Dowling, M. J., & Megginson, W. L. (1995). Cooperative strategy and new venture performance: The role of business strategy and management experience. Strategic Management Journal, 16(7), 565–580. doi:10.1002/ smj.4250160706 Milliken, F., & Vollrath, D. (1991). Strategic decision making tasks and group effectiveness: Insights from theory and research on small group performance. Human Relations, 44, 1–25. doi:10.1177/001872679104401201 Minniti, M., & Bygrave, W. (2001). A dynamic model of entrepreneurial learning. Entrepreneurship Theory and Practice, 25(3), 5–16. Nunnally, J. C. (1978). Psychometric theory. New York, NY: McGraw-Hill Book Company. Ozgen, E., & Baron, R. A. (2007). Social sources of information in opportunity recognition: Effects of mentors, industry networks, and professional forums. Journal of Business Venturing, 22(2), 174–192. doi:10.1016/j.jbusvent.2005.12.001 Park, J. S. (2005). Opportunity recognition and product innovation in entrepreneurial hi-tech startups: a new perspective and supporting case study. Technovation, 25(7), 739–752. doi:10.1016/j. technovation.2004.01.006 Pittaway, L., & Cope, J. (2007). Simulating entrepreneurial learning: Integrating experiential and collaborative approaches to learning. Management Learning, 38(2), 211–233. doi:10.1177/1350507607075776 Politis, D. (2005). The process of entrepreneurial learning: A conceptual framework. Entrepreneurship Theory and Practice, 29(4), 399–424. doi:10.1111/j.1540-6520.2005.00091.x

Politis, D., & Gabrielsson, J. (2009). Entrepreneurs’ attitudes towards failure – An experiential learning approach. International Journal of Entrepreneurial Behaviour and Research, 15(4), 364–383. doi:10.1108/13552550910967921 Rae, D. (2000). Understanding entrepreneurial learning: A question of how? International Journal of Entrepreneurial Behaviour and Research, 6(3), 146–159. Rae, D., & Carswell, M. (2001). Towards a conceptual understanding of entrepreneurial learning. Journal of Small Business and Enterprise Development, 8(2), 150–158. doi:10.1108/ EUM0000000006816 Reuber, R. A. (1997). Management experience and management expertise. Decision Support Systems, 21, 51–60. doi:10.1016/S0167-9236(97)00017-1 Reuber, R. A., Dyke, L. S., & Fischer, E. M. (1990). Experiential acquired knowledge and entrepreneurial venture success (pp. 69–73). Academy of Management Best Paper Proceedings. Reuber, R. A., & Fischer, E. M. (1993). The learning experiences of entrepreneurs. In Churchill, N. C., Birley, S., Bygrave, W. D., Doutriaux, J., Gatewood, E. J., Hoy, F. S., & Wetzel, W. E. (Eds.), Frontiers of Entrepreneurship Research (pp. 234–245). Wellesley, MA: Babson College. Reuber, R. A., & Fischer, E. M. (1994). Entrepreneurs’ experience, expertise, and the performance of technology-based firms. IEEE Transactions on Engineering Management, 41(4), 365–374. doi:10.1109/17.364560 Reuber, R. A., & Fischer, E. M. (1999). Understanding the consequences of founders’ experience. Journal of Small Business Management, 37(2), 30–45.

261

Entrepreneurial Learning and Innovation

Romanelli, E., & Schoonhoven, K. (2001). The local origins of new firms. In Schoonhoven, K., & Romanelli, E. (Eds.), The entrepreneurial dynamic (pp. 40–67). Stanford, US: Stanford University Press.

Starr, J. A., & Bygrave, W. D. (1992). The second time around: The outcomes, assets, and liabilities of prior start-up experience, In S. Birley, & I. C. MacMillan (Eds.), International perspectives on entrepreneurship research, 1991, 340-363.

Ronstadt, R. (1988). The corridor principle. Journal of Business Venturing, 3(1), 31–40. doi:10.1016/0883-9026(88)90028-6

Starr, J. A., Bygrave, W. D., & Tercanli, D. (1993). Does experience pay? Methodological issues in the study of entrepreneurial experience. In Birley, S., & MacMillan, I. C. (Eds.), Entrepreneurship research global perspectives (pp. 125–155). Amsterdam, The Netherlands: Elsevier Science Publisher.

Sapienza, H. J., & Grimm, C. M. (1997). Founder characteristics, start-up process, and strategy/ structure variables as predictors of shortline railroad performance. Entrepreneurship Theory and Practice, 23(1), 5–24. Schumpeter, J. A. (1934). The theory of economic development. Oxford, UK: Oxford University Press. Shane, S. (2000). Prior knowledge and the discovery of entrepreneurial opportunities. Organization Science, 11(4), 448–469. doi:10.1287/ orsc.11.4.448.14602 Shane, S. (2003). A general theory of entrepreneurship. The individual – Opportunity nexus. Cheltenham, UK: Edward Elgar. Shane, S., & Khurana, R. (2003). Bringing individuals back in: The effects of career experience on new firm founding. Industrial and Corporate Change, 12(3), 519–543. doi:10.1093/ icc/12.3.519 Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. Shepherd, D. A., Douglas, E. J., & Shanley, M. (2000). New venture survival: Ignorance, external shocks, and risk reduction strategies. Journal of Business Venturing, 15(5-6), 393–410. doi:10.1016/S0883-9026(98)00032-9 Singh, R. P. (2000). Entrepreneurial opportunity recognition through social networks. New York, London: Garland Publishing.

262

Stinchcombe, A. (1965). Social structure and organizations. In March, J. (Ed.), Handbook of organizations (pp. 142–193). Chicago, IL: Rand McNally. Stokes, D., & Blackburn, R. (2002). Learning the hard way: The lessons of owner-managers who have closed their businesses. Journal of Small Business and Enterprise Development, 9(1), 17–27. doi:10.1108/14626000210419455 Storey, D. (1994). Understanding the small business sector. London, UK: Routledge. Stuart, R. W., & Abetti, P. A. (1990). Impact of entrepreneurial and management experience on early performance. Journal of Business Venturing, 5(3), 151–162. doi:10.1016/0883-9026(90)90029-S Sykes, H. B. (1986). Lessons from a new ventures program. Harvard Business Review, (May/June): 69–74. Thornhill, S., & Amit, R. (2003). Learning about failure: Bankruptcy, firm age, and the resourcebased view. Organization Science, 14(5), 497–509. doi:10.1287/orsc.14.5.497.16761 Ucbasaran, D., Westhead, P., & Wright, M. (2006). Habitual entrepreneurs. Aldershot, UK: Edward Elgar.

Entrepreneurial Learning and Innovation

Ucbasaran, D., Westhead, P., & Wright, M. (2008). Opportunity identification and pursuit: does an entrepreneur’s human capital matter? Small Business Economics, 30, 153–173. doi:10.1007/ s11187-006-9020-3 Van Gelderen, M., van de Sluis, L., & Jensen, P. (2005). Learning opportunities and learning behaviours of small business starters: Relations with goal achievement, skill development and satisfaction. Small Business Economics, 25, 97–108. doi:10.1007/s11187-005-4260-1 Venkataraman, S. (1997). The distinctive domain of entrepreneurship research. In Katz, J. A. (Ed.), Advances in entrepreneurship, firm emergence, and growth (pp. 119–138). Greenwich, Connecticut: JAI Press. Vesper, K. (1980). New venture strategies. Englewood Cliff, NJ: Prentice Hall. Westhead, P., & Wright, M. (1998). Novice, portfolio, and serial founders: Are they different? Journal of Business Venturing, 13(3), 173–204. doi:10.1016/S0883-9026(97)90002-1 Whitley, R. (1989). On the nature of managerial tasks and skills: Their distinguishing characteristics and organization. Journal of Management Studies, 26(3), 209–224. doi:10.1111/j.1467-6486.1989. tb00725.x Zahra, S. A. (1993). Environment, corporate entrepreneurship, and financial performance: A taxonomic approach. Journal of Business Venturing, 8(4), 319–340. doi:10.1016/08839026(93)90003-N

KEY TERMS AND DEFINITIONS Career Experience: The experience gained during an individual’s total working life. Entrepreneur: An individual who establishes and manages a new business venture. Entrepreneurial Knowledge: Knowledge that can be used in the practice of starting up and managing new ventures. Often, it is related to two distinct learning outcomes; the ability to recognize new venture opportunities and cope with liabilities of newness (Politis, 2005). Experiential Learning: The process of making meaning from direct experience (Kolb, 1984). Liability of Newness: This term relates to the different risks of closure or termination during the course of development of an organization, where the risk of closure is highest at the point of founding and thereafter decreases with growing age (Stinchcombe, 1965). New Venture Creation: The identification and commercialization of an opportunity (for definition, see above), leading to the birth of a new business venture. Opportunity Recognition: The discovery and evaluation of an opportunity (for definition, see above), resulting in a new profit potential (Ardichvili, Cardozo & Ray, 2003). Opportunity: Those situations in which new goods, services, raw materials and organizing methods can be introduced and sold at greater than their cost of production (Shane & Venkataraman, 2000).

263

264

Chapter 15

Innovation and Corporate Reputation: Britain’s Most Admired Company Surveys 1990-2009 Michael Brown Birmingham City University, UK Paul Turner Anglia Ruskin University, UK

ABSTRACT As much as 75% of a company’s value derives from its intangible assets. One of the most important of these intangible assets is corporate reputation. The Britain’s Most Admired Company surveys into corporate reputation includes nine characteristics, one of these is a company’s ‘capacity to innovate’. Surveys between 1990 and 2009 show that a good reputation for innovation does not guarantee a good overall reputation; nor does a reputation for innovation lead to business success. However, where a company has a reputation for innovation and is able to manage other characteristics, there is a better chance that this company will develop its innovation capability into long-term competitive advantage and profitability. Central to this conclusion is converting innovation into enhanced processes, products or services through effective implementation. The research identifies key attributes of companies that combine a reputation for innovation, with a good corporate reputation overall and business success.

DOI: 10.4018/978-1-61350-165-8.ch015

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovation and Corporate Reputation

INTRODUCTION This chapter discusses the relationship between innovation and corporate reputation. It analyses peers’ perceptions of the ‘capacity to innovate’ as measured in the Britain’s Most Admired Company (BMAC) surveys of corporate reputation, against other measures of reputation such as leadership or financial soundness. Between 1990 and 2009, the surveys produced data on nine measures of reputation from 761 British companies. The perceptions of business leaders who participated in BMAC surveys provide a perspective on the value of innovation in determining a company’s overall reputation; and offer insights into the practices of those companies that achieve a high rating in the surveys. We use Fombrun’s (1996) definition of corporate reputation as the ‘net affective reactions of customers, investors, employees and the general public’. Reputation is an internally owned, externally evaluated, intangible asset that emanates from a company’s history, location, culture, and from its distinctive capabilities or competencies. (Kay 1993). One of these competencies is the capacity to innovate.

BACKGROUND The Schumpeterian assumption that ‘static firms rapidly face losses and thus bankruptcy,’ (Kurz 2007) provides a compelling case for organisations to be innovative. However, Repenning’s (2002) view that ‘the history of management practice is filled with innovations that failed to live up to the promise suggested by their early success’ is indicative of the case against. Hawn (2004) echoes the view suggesting that; ‘some of the most innovative companies in the history of American business have been colossal failures’. Innovation alone is insufficient; it does not guarantee delivery of corporate objectives, competitive advantage

or a superior, sustainable, corporate reputation, either in the medium or long term. The analysis of the relationship between innovation and corporate reputation is intended to provide insight into the paradox between the objective of innovation as a route to prosperity and the actuality of innovation practice, which can be fraught with difficulty (Dougherty & Heller, 1994). Do those companies that achieve a high reputation for innovation have philosophies or practices that can help in the solution to this paradox? There has been research into the relationships between innovation and profitability (Xin, Yeung & Cheng, 2010); firm performance (Artz, Norman & Cardinal, 2010) and the role of institutional investors (Kochhar & Parthiban, 1996). Other areas of interest include the relationships between innovation and the dynamics of organisational innovation (Monge, Cozzens & Contractor, 1992; the effectiveness of knowledge management (Vaccarro, 2010) cooperation and collaboration (De Faria Lima & Rui, 2010); and organisational change and renewal (Dougherty, 1992). Tzeng (2009) identified three classifications, or schools of thought about innovation from this research, namely those of capability, corporate entrepreneurship and culture. There is less research into the linkages between innovation and corporate reputation. The findings from the BMAC surveys suggest that there are elements from each of Tzeng’s three classifications.

BRITAIN’S MOST ADMIRED COMPANIES SURVEYS INTO CORPORATE REPUTATION (BMAC) The Methodology of the BMAC Surveys Since 1990, the BMAC survey has polled senior executives in companies with the highest market capitalisation on the British Stock Exchange. This process has provided data over a 19-year period

265

Innovation and Corporate Reputation

producing approximately 3 million observations. The BMAC surveys provide continuity of data since 35% of the companies that have taken part were in both the first (1990) and the latest (2009) survey. These data offer insights as to how a reputation for innovation (an intangible asset) translates into the practice of innovation, leading to successful business performance and hence profit (a tangible asset). Heil (2008) makes the case for an ontological enquiry with respect to organisational reputation, identity and innovation, whilst Courtright and Smudde (2009) propose a process of ‘identity, image and reputation that situates message design in the context of diffusions of innovations theory.’ In both cases, there is an implied link between innovation and corporate reputation, though empirical evidence does not consistently support this relationship at the company level’. (Brito, Brito & Morganti, 2009). Senior executives of each participating company provided their perceptions for other companies in the sector in which they operated (e.g. finance, retailing, engineering) across each of nine characteristics that determine a company’s reputation. namely; the quality of management (QM); financial soundness (FS); the quality of products (QP); the ability to attract retain and develop top talent (AADRT); value as a long term investment (VLTI); the capacity to innovate (CI); the quality of marketing (QMar); community and environmental responsibility (Cer); and the use of corporate assets (UCA). A company’s characteristics are scored on a Likert scale of 0-10, (0 = poor, 5 = average and 10 = excellent). Bipolar scales in the form of opposite adjectives, poor to excellent, capture the respondents’ attitudes towards each company within the sector, for each of the characteristics. The results are a most admired company for each of the characteristics, and for each sector and a ‘Britain’s Most Admired Company’ overall.

266

A Longitudinal Analysis of the ‘Capacity to Innovate’ Characteristic in the BMAC Survey: A Period of Stasis Figure 1 shows the average ratings of each of the nine characteristics measured in the BMAC surveys from 1990-2009. Financial soundness, the quality of goods and services and the quality of management are the three characteristics that have consistently received the highest ratings. Financial soundness has finished in number one position for 12 out of the 19 years of the survey and the quality of goods and services on six occasions; and both shared the highest position in 2000. The quality of management is normally in second or third place. At the other extreme community and environmental responsibility is consistently the lowest rated of the reputation characteristics. British executives and business analysts who contribute to the BMAC surveys rate the capacity to innovate as less important than other business attributes. For most of the period between 1990 and 2009, the relative performance of innovation as a perceived strength in British companies was consistently low. In 1990 the capacity to innovate was in the bottom third of the characteristics and remained so for most of the years of the survey. There have been few periods when innovation achieved a high ranking or high performance ‘scores.’ The notable exception was during the dot.com boom of 1999-2001 when the capacity to innovate was a more desirable objective for businesses than it had been in previous years and British companies raised their performance. The innovation characteristic was 4th out of nine in 2001. This was the highest position in the history of the surveys. However, by 2003, capacity to innovate again rated sixth or lower. From 2006-2009, only the quality of marketing and community and environmental responsibility ranked below the capacity to innovate in the BMAC survey.

Innovation and Corporate Reputation

Figure 1. Average ratings for the nine BMAC characteristics 1990-2009

There is further evidence for ‘innovation stasis’ when reviewing executive responses to the importance of BMAC characteristics between 2000 and 2008. Table 1 shows responses concerning the importance of the nine characteristics in the BMAC surveys in two years and, whilst the innovation score has increased marginally, it has remained in sixth position.

The Correlation between Innovation and Other Characteristics in the BMAC Survey The rating of innovation in the BMAC surveys appears counter to the belief in the importance of innovation. An explanation for this may be to do with perceptions of actual performance rather than a critique of innovation as an objective for the future. Nevertheless, the BMAC surveys offer insights as to how an organisation can convert its innovativeness onto practical value added. They do this by showing the characteristics most closely associated with innovation. Table 2 identifies

the relationship between innovation and other characteristics using a series of survey correlation coefficients. The table shows the correlation results at two points in time, 1992 and 2009. In the first year of the analysis, (Saunders, Brown & Laverick, 1992) innovation (CI) is shown to be most strongly associated with the ability to attract talent and the quality of marketing. At this time, a reputation for innovation was dependent upon having innovative people in the company rather than having innovative processes. In addition, the association between innovation and quality of marketing, the second highest correlation in 1992, points to innovation being recognised through a company’s external projections, its advertising or PR or through other aspects of the marketing mix such as distribution. In the second year, however (2009), the relationships had changed. The capacity to innovate is associated strongly with the quality of a company’s products though once again having a strong people relationship. Given that employee engagement and participation in innovation implementation

267

Innovation and Corporate Reputation

Table 1. The importance of BMAC characteristics 2000 and 2008 Senior executives – importance of BMAC characteristics - 2000

1

BMAC Characteristics

Score

Quality of Management

8.83

Senior executives – importance of BMAC characteristics - 2008 BMAC Characteristics

Score

1

Quality of Management

8.79 8.23

2

Quality of Products/Services

8.20

2

Ability to Attract, Develop and Retain Top Talent

3

Financial Soundness

7.99

3

Financial Soundness

8.13

4

Ability to Attract, Develop and Retain Top Talent

7.84

4

Quality of Products/Services

8.12

5

Value as a Long Term Investment

7.53

5

Value as a Long Term Investment

7.63

6

Capacity to Innovate

7.23

6

Capacity to Innovate

7.30

7

Use of Corporate Assets

6.78

7

Use of Corporate Assets

7.03

8

Quality of Marketing

6.76

8

Quality of Marketing

6.78

9

Community & Environmental Responsibility

5.67

9

Community & Environmental Responsibility

6.36

Average

7.43

Average

7.60

Standard deviation

0.94

Standard deviation

0.79

Table 2. Comparison of correlation coefficients between BMAC characteristics in 1992 and 2009 1992

2009 QM

FS

QP

Aat

Vlti

CI

QMr

CER

QM

FS

QP

Aat

Vlti

CI

QMr

CER

QM FS

0.75

0.77

QP

0.64

0.58

AAT

0.83

0.71

0.70

VLTI

0.80

0.89

0.63

0.76

CI

0.58

0.40

0.64

0.71

0.46

QMr

0.61

0.41

0.69

0.69

0.48

0.75

Cer

0.41

0.45

0.61

0.45

0.52

0.35

0.40

UCA

0.85

0.73

0.57

0.77

0.79

0.52

0.55

0.45

0.72

0.67

0.83

0.80

0.81

0.79

0.83

0.76

0.86

0.74

0.65

0.80

0.80

0.75

0.68

0.61

0.73

0.77

0.66

0.79

0.50

0.54

0.57

0.65

0.59

0.60

0.66

0.79

0.77

0.72

0.79

0.79

0.73

0.67

0.62

QM = Quality of management, FS = Financial Soundness, QP = Quality of Goods and Services, AAT= Ability to attract, develop and retain top talent, VLTI = value as a long term investment, C2I = Capacity to innovate, QMr = Quality of Marketing, Cer = Community and Environmental Responsibility, UCA = Use of corporate assets

268

Innovation and Corporate Reputation

is a complex role (Cadwallader, Jarvis, Bitner & Ostrom, 2010) there is sense in seeing the strength of the relationship between the people characteristic and innovation. Furthermore, Fidler and Johnson (1984) argued that: ‘The capacity of a decision unit to induce innovation implementation within an adoption unit is crucial to organizational success. Risk and complexity are characteristics of innovations that can lead to resistance within organizational adoption units. Communication costs, types of power, and communication channels are structural characteristics that can be used by a decision unit to overcome this resistance. The interaction of these factors can determine the degree of successful innovation implementation within organizations.’ The results of the BMAC surveys suggest that effective people management, culture and communication are critical success factors to successful innovation. Indeed, Klein and Sorra (1996) proposed that ‘implementation effectiveness, the consistency and quality of targeted organizational members’ use of an innovation, is a function of (a) the strength of an organization’s climate for the implementation of that innovation and (b) the fit of that innovation to targeted users’ values.’ The increasing strength of association between innovation and people management in the BMAC survey between 1992- 2009 is further recognition on the importance of this association on the part of those executives who participated in BMAC surveys. There are two other areas where the association appears to be strong. In the first, the correlation between innovation and value as a long-term investment has increased markedly (an increase in correlation from 0.4 to 0.7). Secondly, the association between innovation and the quality of management characteristic has also increased markedly (from 0.5 to 0.7) thereby giving support to Michaelis, Stegmaier and Sonntag’s (2010) view that ‘companies should invest in transformational leadership training and in the selection of supervi-

sors with this leadership style before initiating the implementation of innovations.’ The BMAC data give further credence to this finding. The following sections will test some of the changes in strength of association by highlighting the type of company and business sectors that have performed well in the innovation characteristic and drawing lessons from their experiences.

The Ranking of Companies and Business Sectors in the Capacity to Innovate Characteristic in the BMAC Survey Since 1990, only two companies that finished top in the innovation characteristic of the BMAC survey also came top overall (Tesco and BSkyB). Others have fared less well. The 1995 innovation winner for example, British Land, came in 20th in the overall positions for corporate reputation and Burford, 1997’s most innovative company, came in 36th overall. Technology company ARM Holdings, the 2006 innovation characteristic winner also came in 36th in the overall assessment of corporate reputation. The American Most Admired Company surveys mirror the discrepancy between a reputation for innovation and overall reputation performance. In 2007, for example, Apple, Google and FedEx were the top three in the innovation category but did not make the top five overall. In 2006 only Apple and in 2005 only FedEx from the top three most innovative companies made the top 20 overall in the America’s Most Admired Company surveys. The conclusion from these comparisons is that a reputation for innovation is no guarantee of a reputation for overall business reputation. There is further evidence of this ambivalence when looking at sector analysis for innovation reputation. Between 1994 and 2009, innovativeness was a feature of many industries rather than just one showing a broad sweep of innovation in the British economy. On the other hand, there is the negative connotation that few industries appear to

269

Innovation and Corporate Reputation

have built a sustained competitive position through innovation. For example, the finance sector’s share of vote for innovation over the period 1996–2006 increased from 1% to 13%. However, after 2008, there was a collapse in the sector’s reputation for innovation. This may have been a backlash at too much innovation and too little governance or financial control, especially in the area of dealing with sub- prime mortgage financing and derivative products. The highest rated Bank in the BMAC survey in 2009 was Banco Santander at 44th place for innovation. Royal Bank of Scotland was the 170th most innovative company in Britain in 2009 (29th in 1999); Lloyds Banking Group was the 176th most innovative company (24th in 1998). The British financial services sector, once perceived as one of the most innovative of all the business sectors was, by 2010, an innovation laggard. Other sectors have been able to build more sustainable reputations for innovation. The chemicals and engineering sectors have had high reputations for innovative practices. The technology sector, on the other hand has had a variable performance, though in recent times, BSkyB has enhance that reputation considerably. Telecommunications increased its share of the innovation ‘vote’ reflecting developments in the mobile business and recently there was recognition for Autonomy (4th in 2009) and Qinetiq. Both the media and retail sectors, however, saw their shares of innovation votes fall over the period of the survey. In the period 2000-2002 Tesco, Iceland, Dixons, Next, Selfridges, French Connection and Morrisons were amongst those retailers rated highly for their innovative qualities (retailers received 23% of the votes for innovation.) By 2009, only Tesco, from the retailing sector, made the top 20 companies, though some of their suppliers Britvic, Diageo and Cadbury were all in high positions in this year. Results of the BMAC survey from 1990-2009 show that a reputation for the capacity to innovate is difficult to sustain and furthermore is not a guarantee of a reputation for overall business performance. Whilst Tesco and BSkyB have

270

shown excellence for reputation in innovation, overall and backed this up with strong financial results, British Banks, and other business sectors failed to convert innovation into business success with any consistency (and the banks’ failure was dramatic).

The Challenges of Innovation in Larger Companies Why is innovation such a challenge? The evidence from the BMAC surveys seems counter to perceived wisdom about the importance of innovation in organisations. There are several possible explanations for this. First, executives regarded innovation in the lower range of critical management activities and therefore not deserving of the higher scores given to, say, financial management or quality of management. Second, they regarded innovation as important, but did not rate the performance of British companies as being particularly innovative. A third possibility however, is that the executives had insights about the challenges of innovation in the type of large organisation that made up the constituents of the BMAC surveys and this was reflected in their assessment. There is research evidence to support this hypothesis. On the one hand, there are arguments in favour of the scale advantages of large companies and innovation success. Research has shown, for example, that ‘the financial rewards of innovation vary dramatically across firms and are tied closely to firms’ resource base. Firms that provide higher per-product levels of marketing and technology support obtain much greater financial rewards from their radical innovations than do other firms’ (Sorescu, Chandy & Prabhu, 2003). Those organisations that have resources to back up innovation are more likely to reap the benefits. Large organisations, though not exclusively, would feature in this category. On the other hand, research has also shown that there are barriers to innovation in large established firms. (Dougherty & Heller, 1994)

Innovation and Corporate Reputation

and that ‘fostering innovation and supporting a culture in practice...is easier said than done’ (Jassawalla & Sashittal, 1993). In addition, even when a company was successful in innovation and had achieved a reputation for innovation, there was no guarantee that this would filter through to the company’s wider reputational standing. Further analysis of the performance of specific companies that have featured in BMAC surveys may shed some light onto the subject of innovation and its conversion into business success.

INNOVATION AND PERFORMANCE: KEY LESSONS FROM THE RESULTS OF THE BMAC SURVEYS Innovation Stasis Research from BMAC data has suggested that innovation is not as highly regarded as other business attributes such as financial soundness or quality of management in determining a company’s reputation. Moreover, over the period of the BMAC surveys, the results for innovation remained in stasis. Why should this be the case given the strong assumption that innovation is such a critical aspect of sustained performance? One hypothesis is that the challenge of converting innovation reputation and, by implication, innovation actuality into business performance is difficult. There are exceptions, such as Tesco, Rolls Royce and Johnson Matthey, but other companies are not able to sustain a reputation for innovation, nor are they able to develop a wider reputational or indeed a better business performance, There are further insights when deconstructing the total reputation score and analysing the capacity to innovate component against other components that make up total reputation. Two companies, Pilkington Glass and BSkyB, provide key lessons. Both companies were repeatedly top within their respective sectors (Building Materials and Media) in terms of their capacities to innovate.

Deconstructing the total reputation into its constituent parts provides an opportunity to undertake a more detailed analysis of the performance of these two companies.

Innovation Paradox: The Case of Pilkington Glass Pilkington Glass is a successful company that achieved sustained recognition for its capacity to innovate between the years 1990-2006 in the BMAC surveys. However, their experience also confirms that achieving an excellent reputation in a single characteristic will not necessarily filter through to an excellent overall reputation. The reason behind this may be that a good deal of the company’s strategic effort and resource is perceived as being allocated to a single area. Such focus may well detract from other important business activity, whether this is through a dilution of management effort or an imbalance in resource allocation. This observation supports Teece’s (1988) finding that the competitive potential embedded in new technology is difficult to capture. The experience of Pilkington demonstrates this point to some extent and we refer to this as the Pilkington Paradox. Pilkington Glass was established in 1826 and, during the years of the BMAC survey from 1990, achieved an international reputation for innovation. Figure 2 outlines its composite scores. Over each of the years of the survey, Pilkington achieved high ratings from executives within the business sector in which the company operated for both the capacity to innovate and the quality of its products. The company’s innovations included developing a universal process for the manufacturing of flat glass, the development of K glass with coatings, automotive glass, laminated glass, fire resistant glass, bullet proof glass, energy saving glass, solar controlled and thematic insulation glass and self cleaning glass. Because of this combination of invention and innovation, Pilkington Glass was highly regarded. The company was able to

271

Innovation and Corporate Reputation

translate this innovation into quality of products backed by successful marketing. However, whilst acknowledging an outstanding performance for innovation, executives and analysts in the BMAC survey did not rate Pilkington highly for other important business attributes, the most notable of which were value as a long-term investment and financial soundness. The Financial Times carried an article reinforcing this point: ‘The company’s inventions include energy-saving and fire-resistant glass and advanced processes for making car windscreens in complex shapes. But, like many UK companies, Pilkington had failed to turn its inventiveness into financial success’ (Skapinker 2001). Whilst being at the forefront of innovation in the sector, and whilst achieving international recognition for the advances made, difficulties remained in converting these successes into financial

gain. In 2001, the company’s profits fell 38 per cent to £132m, and between 1996 and 2000; Pilkington shares underperformed the market by more than 50 per cent. Pilkington Glass is an example of a company that had excelled in innovation but less so in its reputation for financial management. Figure 3 shows that the two financial characteristics were consistently amongst the lowest rated. Pilkington Glass was acquired by Nippon Sheet Glass in June 2006 for £2,2bn (Blitz, 2006), thereby ending a long run in which the company had attempted to stave off takeover. A focus on economies of scale and scope for innovation enabled Pilkington to increase its Group revenues to ¥ 588bn in 2010, with a profit of ¥ 0.9bn. Pilkington were able to report that, ‘controlled cash management and cost reduction continue to mitigate the impact of the challenging conditions in our markets’ (Pilkington Group, 2010).

Figure 2. The composite scores of Pilkington Glass in BMAC surveys 1990-2006

272

Innovation and Corporate Reputation

BSkyB: A Holistic Approach to Innovation and Business Management BSkyB had similar recognition to Pilkington as a company rated by executives in the BMAC surveys for its capacity to innovate. In 1997, the company was in tenth position behind such companies as Orange, Glaxo, Reuters and Tesco, but the following year BSkyB was in third position and in 1999 at number one in the survey. In 2000, 2001 and 2004 and again in 2007, 2008 and 2009, BSkyB was the most innovative company in Britain. The philosophy of the company is to tie in innovation to customers’ needs. ‘This isn’t innovation for its own sake. It’s first, last and always about our customers. It’s about what new technology can do for them and how we can use it to make Sky better’ (BSkyB, 2006). The impact of these innovations on the rating by executives in BMAC surveys is shown in Figure 3. Other facets of the company’s performance include collaborative partnerships to maximise a broad range of innovation capability and continuous improvement as part of the innovation process (Brown & Turner, 2008). A critical success factor in achieving a reputation for innovation is the ability to execute ideas effectively and to allocate sufficient resources to enable innovation in practice. BSkyB has this capability (Huston & Sakkab, 2006; Lafley & Charan, 2008; Brown & Turner, 2008). Often this requires a company to be very specific about which innovations it decides to back. As Steve Jobs, of Apple, put it, success comes from ‘saying no to 1,000 things’ so as to concentrate on the ‘really important’ creations’ (Burrows, 2004). Figure 4 shows the performance of BSkyB in each of the characteristics from its introduction into the BMAC survey until 2009. In a similar way to Pilkington, BSkyB is highly rated for its capacity to innovate. The company was Britain’s Most Admired Company for innovation in 2007, 2008 and 2009 ahead of such companies as Rolls

Royce, Autonomy, Unilever, GSK, Tesco and Marks and Spencer. BSkyB has also achieved high ratings in the important ‘stabilising’ characteristics of financial soundness and value as a long-term investment, even though in the early years of their existence the company suffered poor perceptions in both. In 2000, for example, BSkyB’s highest score in the BMAC survey was for its capacity to innovate; its lowest was for financial soundness. BSkyB’s performance was similar to that of Pilkington (see Figure 2) at the time, i.e. it was highly regarded as being a company with a propensity to innovate but not one with a strong financial performance. Both BSkyB and Pilkington Glass had the challenge of balancing reputation for innovation with the financial characteristics of financial soundness and value as a long-term investment. Of the two companies, only BSkyB were able to address this challenge to the satisfaction of executives and analysts and ultimately shareholders. By 2009, both innovation and financial soundness were highly ranked. In addition, value as a long-term investment was also on an upward trajectory. In this latter year, BSkyB was a company that was able to be both innovative and profitable.

CONCLUSION The analysis of peer perceptions of the innovation data from the BMAC surveys between 1990 and 2009 gives interesting insights. On the one hand, achieving a good reputation for innovation does not guarantee a good overall reputation; nor does a reputation for innovation lead to business success. However, where a company has a reputation for innovation and is able to manage stabilising characteristics - such as financial soundness and value as a long-term investment, there is a better chance that this company will be able to develop its innovation capability into long-term competitive advantage and profitability. A key facet of this conclusion is a focus on converting innovation into

273

Innovation and Corporate Reputation

Figure 3. BSkyB innovations and CEO’s, plus their capacity to innovate scores on BMAC surveys, and comparison with average innovation scores for all companies

Figure 4. The composite scores of BSkyB in BMAC surveys 1997-2009

274

Innovation and Corporate Reputation

enhanced processes, products or services through effective implementation. Our research identifies key attributes of companies that combine reputations for innovation, with good overall reputations and business success (Brown & Turner, 2008): •

•

• •

• •

They have CEO’s who play active parts in driving and supporting innovation and who elicit the support of the Board for investment. They ‘get the balance right between the big ‘I’ of invention and the little ‘I’ of innovation, and they view innovation as continuous improvement as well as dramatic invention’. They focus on key innovations and do not diffuse their efforts. They include many people in the innovation process - hence, the important correlations between people management and culture and innovation. They make sure that innovation is customer-focused and relevant to end-users. Finally, they make sure innovation adds value to the bottom line.

FUTURE RESEARCH DIRECTIONS Corporate Reputation is an important intangible asset that increasingly affects a company’s stock market evaluation. Since a reputation for the capacity to innovate contributes to overall reputation, there may be linkage between innovation reputation, corporate reputation and company value. The findings from the BMAC surveys suggest that those companies that are able to forge this link benefit through both revenue and profit. However, many companies find this challenge difficult to meet. Further research into this area can add to academic understanding and has implications for competitive performance.

REFERENCES Artz, K. W., Norman, P. M., & Cardinal, L. B. (2010). A longitudinal study of the impact of R&D, patents, and product innovation on firm performance. Journal of Product Innovation Management, 27(5), 725–774. doi:10.1111/j.15405885.2010.00747.x Blitz, R. (2006). Japanese break through a glass barrier, The Financial Times, June 23. British Sky Broadcasting (2006). Annual Report. Brito, E. P. Z., Brito, L. A., & Morganti, F. (2009). Innovation and corporate performance: Profit or growth? RAE Electronica, 8(1), 34. Brown, D. M., & Turner, P. A. (2008). The Admirable Company. London, UK: Profile Books. Burrows, P. (2004). The seed of Apple’s innovation, Business Week, October 12. Cadwallader, S. J., Bitner, C. B., & Ostrom, A. L. (2010). Frontline employee motivation to participate in service innovation. Journal of the Academy of Marketing Science, 38(2), 219–239. doi:10.1007/s11747-009-0151-3 Courtright, J. L., & Smudde, P. M. (2009). Leveraging organisational innovation for strategic reputation management. Corporate Reputation Review, 12(3), 245–269. doi:10.1057/crr.2009.18 De Faria, P., Lima, F., & Rui, S. (2010). Cooperation in innovation activities: The importance of partners. Research Policy, 39(8), 1082–1093. doi:10.1016/j.respol.2010.05.003 Dougherty, D. (1992). A practice-centred model of organisational renewal through product innovation. Strategic Management Journal, 13, 77–92. doi:10.1002/smj.4250131007 Dougherty, D., & Heller, T. (1994). The illegitimacy of successful product innovation in established firms. Organization Science, 5(2), 200–218. doi:10.1287/orsc.5.2.200

275

Innovation and Corporate Reputation

Fidler, L. A., & Johnson, J. D. (1984). Communication and innovation implementation. Academy of Management Review, 9(4), 704–711. Fombrun, C. J. (1996). Reputation: Realizing value from the corporate image. Boston, MA: Harvard Business School. Grant, R. M. (2008). Contemporary strategy analysis. London, UK: Blackwell Publishing. Hall, R. (1993). A framework linking intangible resources and capabilities to sustainable competitive advantage. Strategic Management Journal, 14(8), 607–618. doi:10.1002/smj.4250140804 Hawn, C. (2004). If he’s so smart...Steve Jobs, Apple, and the limits of innovation, Fast Company, 78(1 January), 35-44. Heil, D. (2008). Strategic innovation and organisational identity. Journal of General Management, 33(4), 23–35. Huston, L., & Sakkab, N. (2006). Connect and develop: Inside Procter & Gamble’s new model for innovation. Harvard Business Review, 84(3), 55–66. Jassawalla, A. R., & Sashittal, H. C. (1993). Building collaborative cross-functional new product teams. The Academy of Management Executive, 13(3), 50–63. doi:10.5465/AME.1999.2210314 Kay, J. (1993). Foundations of corporate success. Oxford, UK: Oxford University Press. Klein, K. J., & Sorra, J. S. (1996). The challenge of innovation implementation. Academy of Management Review, 21(4), 1055–1080. Kochhar, R., & Parthiban, D. (1996). Institutional investors and firm innovation: A test of competing hypothesis. Strategic Management Journal, 17(1), 73–84. doi:10.1002/(SICI)10970266(199601)17:1<73::AID-SMJ795>3.0.CO;2N

276

Kurz, H. D. (2008). Innovations and profits, Schumpeter and the classical heritage. Journal of Economic Behavior & Organization, 67, 263–278. doi:10.1016/j.jebo.2007.08.003 Lafley, A. G., & Charan, R. (2008). The game changer: How you can drive revenue and profit growth with innovation. New York, NY: Crown Business. Michaelis, B., Stegmaier, R., & Sonntag, K. (2010). Shedding light on followers’ innovation implementation behavior: The role of transformational leadership, commitment to change, and climate for initiative. Journal of Managerial Psychology, 25(4), 408–429. doi:10.1108/02683941011035304 Monge, P. R., Cozzens, M. D., & Contractor, N. S. (1992). Communication and motivational predictors of the dynamics of organizational innovation. Organization Science, 3(2), 250–274. doi:10.1287/orsc.3.2.250 Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company. New York, NY: Oxford University Press. Pilkington Group Company Website. (2010). Press Release, ‘Group Announces Full Year Financial Results,’ 14 May. Repenning, N. P. (2002). A Simulation approach to understanding the dynamics of innovation implementation. Organization Science, 13(2), 109–127. doi:10.1287/orsc.13.2.109.535 Saunders, J., Brown, D. M., & Laverick, S. L. (1992). Research notes on the best of British companies - A peer evaluation of Britain’s leading firms. British Journal of Management, 3(4), 181–196. doi:10.1111/j.1467-8551.1992. tb00044.x Skapinker, M. (2001). A clear-cut vision of how to make profits: Interview Paolo Scaroni, Pilkington, Financial Times, 15(July 19).

Innovation and Corporate Reputation

Sorescu, A. B., Chandy, R. K., & Prabhu, J. C. (2003). Sources and financial consequences of radical innovation: Insights from pharmaceuticals. Journal of Marketing, 67(4), 82–102. doi:10.1509/ jmkg.67.4.82.18687 Teece, D. J. (1988). Capturing value from technological innovation: Integration, strategic partnering and licensing. Interfaces, 18(3), 46–61. doi:10.1287/inte.18.3.46 Tzeng, C. H. (2009). A review of contemporary innovation literature: A Schumpeterian perspective. Management Policy and Practice, 11(3), 373–399. doi:10.5172/impp.11.3.373 Vaccaro, A. (2010). Knowledge management tools, inter-organisational relationships, innovation and firm performance. Technological Forecasting and Social Change, 77(7), 1076–1089. doi:10.1016/j.techfore.2010.02.006 Xin, J. Y., Yeung, A. C. L., & Cheng, T. C. E. (2010). First to market: Is technological innovation in new product development profitable in health care industries? International Journal of Production Economics, 127(1), 129–136. doi:10.1016/j. ijpe.2010.05.004

KEY TERMS AND DEFINITIONS Britain’s Most Admired Companies: Survey (BMAC) is a survey of companies’ corporate reputation. It is a peer perception survey undertaken annually, initially with The Economist between

1990-1992 and then with Management Today from 1994 onwards. The survey aims to capture the tacit views of UK companies’ senior executives and sector investment analysts towards nine characteristics that contribute towards the measure of reputation, across a number of sectors. Corporate Reputation: The contribution of a multitude of stakeholders who, by how they think and feel about a company, determine how it is seen, by themselves and others. Capacity to Innovate: One of the nine constituents that make up the measure for corporate reputation. It is the perceptions of senior executives and analysts’ as to competing companies’ ability to innovate. Innovation: Not only creates competitive advantage, it provides a basis for overturning the competitive advantage of other firms. It is typically thought of in its technical sense: the new products or processes that embody new ideas and new knowledge. In business however innovation includes new approaches to doing business (Grant, 2008). Intangible Assets: Include the intellectual rights of; patents, trademarks, copyright and registered designs; as well as contracts, trade secrets and databases. The intangible resource of reputation may also be classified as asset due to its characteristic of “belongingness” (Hall, 1993). Tacit Knowledge: Rncompasses individuals’ ideals, values, experiences and actions. “Tacit” is something not easily visible or expressible, is very personal, is difficult to communicate to others, is subjective, based on hunches, feelings or insights (Nonaka & Takeuchi, 1995).

277

278

Chapter 16

Natural Resource Dependency and Innovation in the GCC Countries Thomas Andersson Jönköping University, Sweden & The Research Council, Sultanate of Oman

ABSTRACT Whether the current strong performance displayed by the Gulf Cooperation Council (GCC) countries proves sustainable for the long term will cast new light on the extent to which natural resource abundance can be turned into a “blessing”, rather than a “curse”, and then the requirements for that. This chapter synthesizes new evidence on the conditions for innovation in these economies, including through examination of innovative performances at firm level, collected through the first Community Innovation Survey (CIS) carried out in the GCC countries. Whereas strengths are recorded in some respects, e.g., Information and Communication Technology (ICT), education and some conditions for start-up activity, challenges remain in others, including with regard to governance. The chapter ends with recommendations what further action is required to enable better conditions for innovation both in the natural resource sector itself, and broadly in the economy.

INTRODUCTION Explaining the determinants of cross-country variation in economic growth has proven a severe challenge for economists. The availability of capital, land or labour contributes only marginally DOI: 10.4018/978-1-61350-165-8.ch016

to the productivity performance of a particular country relative to others. Although there has been somewhat more convincing outcomes of the analysis of education and human capital, the unexplained residual in studies of productivity growth has continued to account for the bulk of cross-country variation. This residual, or so-called

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Natural Resource Dependency and Innovation in the GCC Countries

total factor productivity growth (TFP)1, has been interpreted as associated with “technical progress” (Solow, 1957). Economists traditionally viewed natural resources as an essential building bloc for development. Once systematic empirical work was undertaken, however, most evidence pointed to a significant negative impact. A good deal of research has subsequently been devoted to further substantiating whether such a “curse”, as opposed to a “blessing”, actually exists, and what then might explain it, worsen it, or make it go away. The conditions that may create such a negative relationship will be further reviewed below. Gradually, however, the performance of several so-called Natural Resource-Rich Economies (NRE), has led to questioning whether it is actually correct to speak of a curse for growth. At least, it has been demonstrated that no universal negative relationship exists. The starkest examples of exceptions are now to be found within the category of the oil & gas producers, notably among the GCC countries2. This is because this country grouping, despite exceptional dependence on their natural resource base, has displayed very high economic growth over the last couple of decades. Over a relative short time span, they have all moved beyond the middle-income economy status. A few of them now rank among the richest and most stable economies in the world. On the whole, these countries have advanced from a state of hardly populated “Middle Age desert land” into an era marked by modern infrastructure and institutions, notably in urban areas but also, in several cases, with wealth diffused to the countryside as well. The GCC region now stands out as the world’s second most important source of excess savings and capital exports, after East Asia. Although there are also significant downsides to their development, and yet outstanding challenges, the performances displayed must be viewed as nothing short of spectacular. This development would clearly not have been possible, had it not been for their oil & gas

richness. This is despite the fact that the prime initial outlier in terms of economic expansion in the region, the Emirate of Dubai, is basically lacking a natural resource base. More recently, on the other hand, Dubai has been saved from the outlook of economic collapse, brought about by the radically altered conditions for real estate investment, by the helping hand of the oil-rich Emirate of Abu Dhabi, which also represents the capital of the United Arab Emirates (UAE). The question remains, however, whether the economic surge of the GCC countries is sustainable, and what wider implications their record will have for our understanding of the role played by natural resources in economic growth. The answer to such questions will much depend on their ability to create conditions that are conducive to innovation in a genuine sense, beyond reliance on already established winners and brand names, both as a basis for furthering their performance in and around the incumbent (natural resource related) industry, and for the rise of new high-value added goods and services. According to mainstream perspectives, innovation is the more or less linear output of expenditures on Research and Development (R&D). With the recent exception of Qatar, the GCC countries are known to have invested only scanty resources in R&D thus far. It cannot be taken for granted, however, that R&D is the main source of innovation, neither in these countries nor elsewhere. On the contrary, there is by now plenty of evidence that innovation does not emanate from investments or actions undertaken by individuals or firms in isolation, but that, linkages between different kinds of often complementary actors and competencies are greatly important.3 So far, the lack of data has prevented any systematic examination of the situation in the GCC countries when it comes to innovative performance beyond R&D. In this chapter, after having reviewed more general aspects of the link between natural resource abundance and economic performance, we take stock of relevant conditions and policies related

279

Natural Resource Dependency and Innovation in the GCC Countries

to innovation in the GCC countries. While starting out with the available aggregate statistics, we extend by drawing upon a unique set of micro data reporting innovative behaviour and practices at firm level. This data, which has become available through the first Community Innovation Survey (CIS) carried out in the GCC countries, covers a representative sample of enterprises in Abu Dhabi. On this basis, we attempt to broadly characterize the state and nature of innovation in the GCC countries today, and how their performances relate to natural resource abundance. We take note of outstanding issues, and what may be crucial for these countries to go the whole way in overcoming the looming risk of ending up with a natural resource curse after all. In this, we argue the GCC countries need to take further action both so as to generate innovation which can increase their returns from the hydrocarbon sector itself, and as a source of diversification and renewal of the wider economy.

A CURSE OR A BLESSING? Whereas traditional development theory viewed natural capital as a cornerstone for development (Nurkse, 1953; Rostow, 1960), a number of studies later concluded that natural resource wealth serves as a drag rather than a facilitator (Auty, 1990; Sachs & Warner, 1995; Gylfason, 2001; Jones, 2002). The notion of the so-called “Dutch disease” was placed at the centre of the stage from the outset. As natural resource abundance boosts foreign exchange earnings, it tends to result in an appreciation of the exchange rate and the subsequent crowding out of other activities in the open and tradable part of the economy, while benefiting public sector growth and non-tradable. Adding to this, because the production of most natural resources is capital intensive, high fixed costs tend to be required. At the same time, commodity prices are generally volatile, bringing the risk of severe macroeconomic fluctuations,

280

including periods of low returns. Not only may this in itself hurt growth performance (van der Ploeg & Poelhekke, 2010). High volatility further undercuts the support of long-term investment, such as R&D. Gradually, it has become clear that considerations of macroeconomic aspects, while relevant in many situations, convey only part of the story. Influences on the directions of human effort are critical. Rich natural resources serve as a lure for rent-seeking, i.e. for gaining privilege and a share of the gains through political clout rather than economic achievement, as well as complacency when it comes to pushing for competition and economic efficiency (Corden, 1984; Auty, 1990; Sachs & Warner, 2001). Even where regimes make the effort to distribute the returns more widely among the population at large, there is the danger of picking up the habits of a “cosy life”. Because natural resource riches tend to accrue directly to the government, the latter may obtain an inflated status relative other stakeholders. The proportion of national income that flows to the population at large will tend to be smaller as a consequence. Further, since government revenue is not collected through taxes of the general public, there is less accountability and pressure on government to make best use of its financial muscle, and less strive for use of public resources to support societal objectives (Devarajan et al. 2010). Also when it comes to the resource basis itself there is generally a lack of investment in supportive knowledge generation, both because of the noted bias against long-term R&D, and because of a common failure to inspire the set-up of specialized educational institutions and programmes that can support its upgrading. In short, there is a risk of natural resource wealth translating into poor governance. Some have argued this leads to less incentive to develop democratic institutions, although that notion has been defused in other studies, and the relationship to economic growth in this case appears unclear in any event.

Natural Resource Dependency and Innovation in the GCC Countries

A number of studies have concluded the curse operates through institutional factors (Isham et al., 2005; Sala-i-Martin & Subramanian, 2003; Bulte et al., 2005; Arzeki & Bruckner, 2009). Part of the impact may emanate from less pressure to undertake needed structural reforms, such as those aimed to open up for more competition, sharper frameworks for education, learning and merit-based promotion, and the establishment of new enterprises (Amin & Djankov, 2009). Because natural resource generated revenues invariably boost the public sector, they tend to inflate the status and rewards associated with public service. There is thus a distinct risk of weak incentives and drive for institutions as well as for individuals to engage in private sector development more generally, and in risk-taking, entrepreneurship, and start-up activity specifically. The causal link between natural resource abundance and growth remains contestable, however. If natural resources earnings, as a share of Gross Domestic Product (GDP), are used as proxy for natural resource assets, the group of NRE will by definition include agriculture-dependent and undiversified economies. These would probably be better defined as “innovation and human capital poor”, and a high share of natural resource in the economy is then as much an outcome of slow growth, and a proven inability to diversify, as the opposite (Smith, 2007). Others have questioned to what extent natural resource abundance really can be observed to act as a drawback for a given economy. Lederman and Maloney (2002), for instance, found Sachs’ and Warner’s results not to hold given a different specification of the studied time period, although they did conclude that high export concentration exerts a robust negative effect on growth. Gylfason’s result also depends on a few outliers that have achieved high growth without natural resources. Herb (2005) and Alexeev & Conrad (2009) evaluate a range of recent statistical studies and conclude against the presence of a natural resource curse, especially when it comes to oil and

mineral wealth. As for volatility, a well developed financial system will cushion the impact (van der Ploeg & Poelhekke, 2009). The recent experience of several countries, especially within the group of the GCC countries but also among some other NRE across the Middle East, Africa, Latin American and East Asia, has demonstrated there is no generally applicable notion of a curse (Fasano, 2002: Sturm et al., 2008; Frankel, 2010). 4 Lending support in this regard is also the experience of several (by now) developed countries, including Australia, Canada, Finland, Norway and Sweden. Of these, Finland and Sweden displayed important spillovers and spinoffs emanating around the paper/pulp industry, benefiting the long-term growth potential of these economies as a whole (Blomström & Kokko, 2007). The GCC countries nevertheless represent the most compelling case, which is due both to the exceptionally rapid growth they achieved over a sustained period of several decades by now, coupled with their remaining extreme dependence on their natural resource, in this case oil & gas. Whereas their advance has not been unaffected by the financial crisis of recent years, on the whole there has only been some temporary moderation of their performance. The equity and real estate positions of the GCC countries in debt-struck overseas markets took a toll on their accumulated net wealth. Several of them, including Bahrain, experienced painful recession. Still, the only economy suffering from a severe lasting impact is probably that of Dubai, which had been exceptionally dependent on capital imports motivated by accelerating real estate assets. While the stabilizing counterweight of oil revenue in this case has been lacking at the regional level, that factor has been at force in the national economy of the UAE. Thus, Dubai too keeps muddling through, aided by the support of lending and some unconventional internal transfers of equity and intangible investments by Abu Dhabi.5

281

Natural Resource Dependency and Innovation in the GCC Countries

As seen from Figure 1, several of these countries have now attained an income level above that of a “comparable high income” European segment (here labelled EU 12+3)6. The converse distance to prominent other Middle East and North Africa (MENA) countries, such as Egypt, Morocco and Jordan, is stark.7 At the same time, as seen from Figures 2 and 3, the GCC countries continue to stand out as markedly undiversified economies. The share of high tech exports in total exports is particularly low, suggesting the presence of a strong “Dutch disease” effect, i.e., the crowding out of an open tradables sector. Some observers of the governance models applied in the Gulf argue that they suffer from particularly severe obstacles to instituting needed micro economic reforms, suggesting that changing the curse into a blessing stands a better chance elsewhere, e.g., in Africa (Devarajan et al., 2010). Further examination is needed to gain a better understanding of the way in which NRE encounter special issues, why that is the case, and what it may take for a rich supply of natural resources to be turned away from a hindrance towards becoming a source of long-term strength. The GCC countries may define the ultimate test case in this regard, due to their high level of natural resource dependence, combined with their proven strong growth record.

THE SCOPE FOR RESEARCH AND INNOVATION At the cost and income level now attained by the GCC countries, their ability to shift from a traditional industrial model based on the availability of natural resources, combined with routinized and mature technologies, to one that is nimble, knowledge-intensive and capable of generating economic activities with higher value-added, is of central importance to their total factor productivity (TFP). This implies that education and training, R&D, innovation, private enterprise develop-

282

Figure 1. GDP per capita (Source:World Bank (2010a). Data are from 2008 or latest available.

ment and entrepreneurial activities relevant to the creation and use of knowledge in new ways, require high attention, so as to pave the way for competitiveness in potential high-growth new market-niches and sectors. With regard to aggregate expenditures on R&D, Figure 4 draws on a combination of data sources to present an estimate as good as we can get. As noted in previous studies (Aubert & Reiffers, 2002), in most cases the GCC countries demonstrate scanty activity levels. Except for the

Figure 2. Economic diversification (share of the largest sector in total value added) (Source:World Bank (2010a). Data are from 2008 or latest available.

Natural Resource Dependency and Innovation in the GCC Countries

Figure 3. High tech exports as percent of GDP (Source:World Bank (2010a). Data are from 2008 or latest available.

noteworthy exception of Qatar, whose estimated level is based on unofficial sources8, they are way below the EU-comparator. The figures imply the GCC countries have lagged in R&D growth relative GDP per capita. Put differently, in the context of impressive economic growth, R&Dintensity has failed to keep up, even compared to the meagre numbers recorded by their peers in the MENA region. The low level of R&D spending is mirrored in weak scores on traditional measures of research output, such as scientific publications or patents. Table 1 indicates the GCC countries do marginally better than the MENA peers, but with an insignificant lead, compared to the gap recorded in the most advanced industrialized countries. Here, the implication is higher public investment did translate into some strengthening in performance, although not to an extent that corresponds to the rise in income levels. Naturally, historical and institutional factors, along with economic structure, need to be taken into account. Despite remarkable scientific contributions in the Middle Ages, the MENA region as of late has been basically disconnected from the rapid evolution of the globalizing research

community. As universities have developed poorly outside the educational agenda, a vibrant research community, including science-industry interface, is largely lacking. In the present situation, it will take time before publicly funded research starts benefiting the overall economy. Meanwhile, the weight of capital intensive industries and services weakens private sector rationale for investing in R&D. This does not mean that R&D is irrelevant, but other factors such as customer relations, the mobility and means of incentivizing skilled labour (domestic and expatriate) and the advance of knowledge brokering and inter-firm collaboration in innovation may also matter greatly (Milbergs & Vonortas, 2004: Andersson & Formica, 2007). Innovation may also draw on research in other countries and locations, at least when combined with other factors that help raise absorptive capacity. On the other hand, own R&D activity at firm level, or in the wider economy, matters for the ability to source the output of R&D elsewhere (Andersson, 2009). In order to gauge their actual situation, and how the current R&D effort should be interpreted, let us take a closer look at some

283

Natural Resource Dependency and Innovation in the GCC Countries

Figure 4. R&D expenditures as percent of GDP (Source: World Bank (2010a), except Oman and Qatar (unofficial estimates). Data are from 2008 or latest available.

additional factors of relevance for innovation in the GCC countries. It is well understood today that meaningful benchmarking of science, research and innovation must take into account the status of complementary and enabling factors (UNCTAD, 2010b). Policymakers must similarly address a broader

Table 1. Innovation output (Source: Estimates based on World Bank (2010b). S&E Journal Articles/Mil. Peole 2005

Patents Granted by USPTO/Mil. People avg 2003-2007

EU 12+3

634

75.5

Kuwait

92

2.3

UAE

56

1.1

Jordan

51

0.2

Bahrain

46

0.1

Oman

44

0.1

Saudi Arabia

25

0.8

Egypt

23

0.1

Morocco

15

0.1

Algeria

11

0.0

Yemen

0

0.0

284

portfolio, if they are to be effective in enacting improved conditions. Among such related factors, human capital assumes particular importance. Figures 5 to 8 present a few relevant cross-country comparisons in this area. Judging from the aggregate numbers, the rate of primary school enrolment, displayed in Figure 5, does not appear to have been much affected by the resource abundance of the GCC countries, neither compared with the EU nor within the MENA region. This reflects the fact that the rate of school enrolment at primary level has increased strongly in more or less all the countries considered here, reaching close to 100 percent across-the-board. Examining enrolment at secondary level, on the other hand, the GCC countries lead the MENA country peers consistently, and with a wide margin in most cases. Adding to the latter observation, Figure 6 indicates the GCC countries have escaped the gravity of the illiteracy problems that continue to plague the wider MENA region. No doubt, the hydrocarbon-generated finances have helped fed increased effort in both primary and secondary schooling, in some cases showing up in enrolment numbers, in others as improved results.

Natural Resource Dependency and Innovation in the GCC Countries

Figure 5. Primary and secondary school level enrolment (as percent of relevant age group) (Source:World Bank (2010a). Data are from 2008 or latest available.

Figure 6. Illiteracy rates (percent of adult population, 15+) (Source:World Bank (2010a). Data are from 2008 or latest available.

Expenditures on tertiary education vary markedly, as seen from the comparison between Oman and Kuwait with the EU-comparator in Figure 8. Here, Kuwait is at a much higher level, while Oman is behind. Figure 9 shows there are limited differences in expenditure per student at secondary and primary level within the MENA region, whereas the EU is at a much higher level, especially in secondary education. These figures suggest that the hydrocarbon economy has fed only a slight increase in the share

of national resources that has gone into education, whereas the sharply increased size of the economy nevertheless means that education has benefited, at least proportionately, and also a little bit more than that. Needless to say, any quantitative considerations of the amount of resources devoted or the number of students enrolled, applying to primary, secondary to tertiary education, vocational training, or other forms of investment in human capital, are unable to fully capture essential aspects of the quality of education and learning, or how human resources are put to use. Multiple studies point to the continued presence of outstanding challenges in this area for the GCC countries, including those that are associated with labour market distortions caused by political motives and market segmentation between indigenous and foreign labour (Andersson et al., 2010a; Djeflat, 2010). Nevertheless, it appears the availability of more resources has fed not only the allocation of greater investment to education, and the provision of a greater number of teachers, but also created a drive for raising the quality and relevance of education as well as to put in place better workplace training across the GCC countries. To what extent there has been genuine progress thus far on this basis, including when it comes to raising TFP, requires further evaluation and examination. The development of the media industry adds further to the picture, as there has been a marked opening for more competition through new establishments followed by soaring, diversified content in public service communication. Related to the latter, modern Information and Communications Technology (ICT), applying to infrastructure as well as services, is now crucial for enabling the successful advance of a knowledge-based economy. Figure 10, which shows a relatively low presence of secure servers in the GCC countries, indicates a “digital gap” between the advanced European countries and the MENA region. Figure 11, on the other hand, conveys a more complex picture. The number of Internet

285

Natural Resource Dependency and Innovation in the GCC Countries

users is higher in the UAE and Bahrain than the EU. Even more impressive, the number of mobile subscriptions is considerably higher in several of the GCC countries compared to the EU. The peers in the MENA region are much behind, with considerably lower levels of mobile penetration. The surge in mobile subscriptions is particular neither to the GCC nor to NRE more broadly, but applies to a diverse set of emerging and developing economies (UNCTAD, 2010a). However, cross-country variation in the penetration of either Internet use or mobile telephony is clearly reflective of price levels, which in turn hinge on the extent to which regulatory reforms have been enacted to break the privileges of (current, or the legacy of) state monopolies, and open for competition in the development and launch of new, rivalling services. To examine the situation in this respect, Figure 12 compares country scores derived through an index that weighs together prices for fixed telephony, mobile and Internet services. As can be seen, prices in the GCC countries are, in most instances, highly competitive compared to the MENA peers (Yemen is included as well here, to demonstrate the discrepancy to many other developing countries). They are also on par with the European comparator. In the case

of ICT, oil and gas wealth has clearly not stood in the way of reforms. While a comprehensive examination of regulatory reform goes beyond this work, international ranking of public procurement practices resulted in a strong upgrading of the GCC countries in recent years (World Bank, 2008: World Economic Forum, 2010). It is also worth taking note of a proxy variable for red type, in this case when it comes to hindering the establishment of business. This is the number of days it takes to start up a new company, shown in Figure 13. Here, most of the GCC countries offer less burdensome conditions than the MENA peers, although the difference is modest. Most of them compare favourably with the EU-comparator. Kuwait is an outlier in this respect.

INNOVATIVE ACTIVITIES AT FIRMLEVEL Whereas the GCC countries do not appear to have increased expenditures on R&D significantly, we do not know whether this ought to be interpreted as a sign of complacency and lack of support for innovation. It may be the status of their innovation

Figure 7. Gross tertiary enrolment (as percent of relevant age group) (Source:World Bank (2010a). Data are from 2008 or latest available.

286

Natural Resource Dependency and Innovation in the GCC Countries

Figure 8. Expenditure per student, as percent of GDP per capita, primary, secondary and tertiary level (Source:World Bank (2010a). Data are from 2008 or latest available.

Figure 9. Expenditure per student, as percent of GDP per capita, primary and secondary level (Source: World Bank (2010a). Data are from 2008 or latest available.

system, e.g. the dominance of the hydrocarbon sector and shortage of qualified researches, makes R&D difficult to justify. In the areas of human resource development, ICT, and conditions for starting a new business, the previous sections pointed to signs of progress in regulatory reform and also, in some cases, associated economic performances. It is worth taking a closer look at the status of innovation more broadly in the GCC countries.

A fundamental problem in this regard is the lack of data on R&D and innovation. In the following, we thus examine the single source of quantitative information that is currently available on innovative activity at the micro level in these countries. This is the data generated by the first Community Innovation Survey (CIS)9 carried out in the region, namely on a population of statistically representative enterprises in Abu Dhabi.10 While not necessarily applicable to other GCC countries, this allows us to examine the state of firm behaviour in regard to innovation within a regional economy (the Emirate level) that is as natural resource dependent (and undiversified) as any of the national economies (Andersson et al., 2010a). 11 On this basis, the innovation landscape is seen to be dominated by three sectors: manufacturing, mining and petroleum, and business services. We find the highest share of innovation active firms within manufacturing and also the mining and petroleum sector (Figure 14). Interestingly, on the whole there is a distinctly higher prevalence of innovation in new services (38.5 per cent) relative to new goods (27 per cent), which applies to mining and petroleum as well. Manufacturing firms, along with those in trade and utilities, on the other hand, focus on innovation in goods (Figure 15). Innovation active firms draw on various kinds of investments, as shown in Figure 16. In-house R&D represents merely one kind among others, mirroring the situation in other countries where CIS surveys have been conducted. Customers are important partners in innovation, particularly when it comes to sharpening design, and for testing new or improved products and services. Among firms indicating collaboration with other partners, customers and suppliers feature prominently as partners along the value chain. Specialised sources of expertise are sourced from consultants and universities (around 30-35 per cent of times identified as partners). Meanwhile, manufacturing and the mining and petroleum sectors are reported to represent

287

Natural Resource Dependency and Innovation in the GCC Countries

Figure 10. Secure internet servers, per million people (Source:World Bank (2010a). Data are from 2008 or latest available.

the most important drivers of innovation in other sectors, as measured via the influence of customer-producer relationships. Firms with a main customer in these two sectors tend to be innovative to a higher degree than firms with main customers from other sectors (Figure 17). Retail and construction come across as particularly unimportant in customer-led innovation, which is in line with the evidence from other countries. These two sectors have a general tendency to be relatively sheltered from foreign competition, and lack of openness tends to be accompanied by less pressure for generating innovative activity. On the other hand, the great weight of mining and petroleum in aggregate innovative activity clearly distinguishes the Abu Dhabi innovation system from those of other economies for which CIS data is available. While we cannot confirm the situation in the rest of the GCC countries, due to the lack of data, there is good reason to believe the situation is similar to that of Abu Dhabi in this respect, especially to the extent hydrocarbon weighs heavily in the economy. Figure 18 illustrates the relationship between the main market of the firm and the degree to

288

which firms are innovative or not. The greater the international exposure, the higher the innovativeness. Figure 19 demonstrates that the same relationship holds with regard to innovations of different calibre. Firms that export play a more prominent role especially for innovations that are new to international markets, although they are also more active in introducing innovations that are new to the domestic market. While the above applies to innovation in general, Figure 20 highlights how firms across the different sectors generate innovations that are new to the domestic market and to international markets respectively. As can be seen, manufacturing primarily plays a role as gate-opener to innovation in the local market, applying to a lesser extent to business services, trade and transport. The clearcut exception is the mining and petroleum sector, which displays a markedly higher activity level when it comes to introducing innovations that are new to the international market. This suggests that the natural resource sector not only represents the most internationally exposed component of the Abu Dhabi economy, but that it is also the leader in regard to the capacity to innovate in international markets.

Natural Resource Dependency and Innovation in the GCC Countries

Figure 11. Internet users, per 100 people (Source:World Bank (2010a) and UNCTAD (2010a). Data are from 2009 or latest available.

Figure 12. ICT Price Basket (Source: UNCTAD (2010a)

Figure 13. Number of days needed to start a new business (Source: World Bank (2010a). Data are from 2008 or latest available.

289

Natural Resource Dependency and Innovation in the GCC Countries

Meanwhile, in the other leading sectors, such as manufacturing and business services, the high percentage of innovations that are new to the national market suggests innovation activities are value chain centred to a high degree. Abu Dhabi innovation active firms tend to serve as suppliers of goods and services to other firms, rather than end-consumers. This is verified by Figure 21, which shows that 65 per cent of innovation active firms focus on the business-to-business segment. With regard to ownership, Figure 22 shows that subsidiaries of Abu Dhabi or UAE firms have a higher propensity to innovate than foreign-owned firms. However, foreign-owned subsidiaries have a higher propensity to introduce international market novelties. Subsidiaries of Abu Dhabi or UAE groups are thus more likely to focus on national markets, whereas foreign-owned firms tackle international markets to a higher degree. Foreign-owned firms further have a higher propensity to co-operate in innovation. This probably reflects the presence of stronger, already established connections between such firms and research institutes, universities or partner firms in their countries of origin, as well as in third markets where their parent companies may have been present for a long time. On the other hand, domestic firms might have been expected to possess better knowledge of viable co-operation partners and enjoy better access to national networks. In terms of frequencies, as can be seen from Figure 23, the average share of large firms that collaborate with partners in generating innovation shows up as relatively low in Abu Dhabi compared to other countries, based on statistics reported by Eurostat. There is a smaller share of co-operating firms in Abu Dhabi than in most European countries. As already noted, foreign-owned firms and firms in mining and the petroleum sector are at the high end in this respect. Keeping in mind the above data refer only to a set of representative firms in Abu Dhabi, the following conclusions stand out:

290

•

•

• •

• •

Innovation active firms tend to be concentrated in three sectors: mining and petroleum, manufacturing, and business services. Abu Dhabi firms pursue a mix of investments related to innovation, with some emphasis on R&D and the acquisition of new technology. There is a high degree of innovation generated via the supply-chains. Innovation in mining and petroleum is more directed to international markets and display relatively high levels of collaboration, and a higher degree of services innovation, compared to manufacturing. Foreign-owned firms collaborate more in innovation. For innovating firms on average, international collaboration is at a relatively low level.

CONCLUDING REMARKS AND RECOMMENDATIONS FOR ACTION In this chapter, we have taken stock of the apparent natural resource “curse” for development, as well as of divergent views in the literature on its nature and generality across countries. We have noted that certain countries managed to perform well based on rich natural resources, and set off lasting growth processes on that basis. While some today developed economies, such as Australia, Canada, Finland, Norway and Sweden, may belong to this camp, as they were able to benefit from rich natural resources in early stages, the GCC countries now represent the most compelling case challenging the notion of a curse. The reason why the performance of the GCC countries attracts special attention in this context is two-fold. On the one hand, they have attained an exceptionally strong economic position, based on basically just oil & gas (the prime exception, the Emirate of Dubai, has recently been bailed out

Natural Resource Dependency and Innovation in the GCC Countries

Figure 14. Share of innovative firms across sectors (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

Figure 15. Share of new goods and services innovations across sectors (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

Figure 16. Investment by innovative firms (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

291

Natural Resource Dependency and Innovation in the GCC Countries

Figure 17. Share of innovative firms according to customer (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

with the help of the oil riches of Abu Dhabi). On the other hand, in line with the “Dutch disease”, whereas costs and incomes of the indigenous population have increased sharply, to date they remain heavily dependent on the hydrocarbon sector. Regardless of the time they have left before this source of revenue will start subsiding, continued excessive dependence on oil & gas will not do as a basis for sustainable prosperity, in part because it will perpetuate public sector dominance and costly labour market distortions. Success with regard to innovation is now essential for the development and production of competitive high value added goods and services in the GCC countries. Whether they create conditions that are genuinely conducive to innovation will be crucial for their ability to ultimately break away from the natural resource curse. So far, in most cases they display a weak standing when it comes to R&D. As for wider reforms, we have taken note of strengths in ICT infrastructure and services, educational effort, public procurement, and some conditions of importance for the start-up of new enterprises.

292

All the GCC countries have, however, launched their special efforts to boost R&D and/or advance complementary means for generating innovations. This applies both to those economies, such as Kuwait, Qatar, Saudi Arabia and the UAE, which have plenty of time left before their oil & gas revenues subside, as well as Bahrain and Oman which have much less time to go. To cite and comment briefly on a few examples of pursued policies, Qatar has put massive resources aside for R&D funding, according to unofficial data, while also engaging in an ambitious range of science park activities. Oman has initiated a call for open research grants, and has taken special initiatives to boost research capacity in prioritized niche areas, such as enhanced oil recovery, road safety, and biodiversity and genetic resources. Within the UAE, Abu Dhabi has launched an ambitious agenda to generate cluster-based development, spurred by Mubadala as a publicly-supported but business-minded investment agency, e.g., in renewable energy and cultural activities. Adnoc Technical Institute and the Petroleum Institute have been directed to raise the supply of prioritized technical skills.

Natural Resource Dependency and Innovation in the GCC Countries

Figure 18. Share of innovative firms according to geographical market (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

Figure 19. Market of the firm and novelties (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

The Khalifa Fund has also raised support for opportunity-based entrepreneurship, although so far limited to the Emirati population, and not freed of the complicating labour market distortions noted above. A research foundation has been introduced, although its establishment phase was prolonged due to bureaucratic hurdles. In Dubai, work has been going on to strengthen and upgrade the Technopark. Kuwait has launched an ambitious centre

on diabetes and related diseases research. Saudi Arabia, finally, has invested massively in several new knowledge cities and research universities. In several of these efforts, the GCC countries rely heavily on imported expertise, but they also attempt to ensure domestic capacity building for the long-term, especially in Oman. At firm level, keeping in mind the limitations in generalizing the results, we have observed a

293

Natural Resource Dependency and Innovation in the GCC Countries

Figure 20. Share of firms across sectors with products new to international and domestic markets (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

strong drive for innovation in the oil & gas sector itself. Here, innovative firms are relatively active in collaboration, and firms innovate at a relatively high level. R&D is clearly not sufficient for measuring their innovativeness, since several other activities serve as important sources of innovation as well. Further, according to our results, which draw on observations from the population of firms in Abu Dhabi, the mining and petroleum sector takes the lead in pulling innovation more broadly. This situation is likely to be more (less) applicable elsewhere in the GCC countries, the more (less) the dominance of the hydrocarbon sector in the economy. Sectors that are relatively more oriented towards the domestic market, and to a high degree sheltered from foreign competition, meanwhile, show clear signs of complacency, and are marked by low levels of collaboration in innovation as well as less potent innovation output. Whereas we can refute the idea that there would be a lack of political support for undertaking required policy action, the lack of tangible evidence of enhanced innovation and actual economic

294

diversification at aggregate level indicates the presence of remaining hindering factors, which keep frustrating and delaying tangible progress. Here, the dominance of public sector activities and employment is likely to be a key factor, especially as it is interrelated with serious labour market distortions following from the political motive of favouring the indigenous population. This applies especially to those GCC countries where the locals are in minority, including the UAE and Qatar, which in fact possess the largest natural resource pool relative the size of the population, resulting in special disincentives for genuine risk-taking, entrepreneurship and private sector development in the most well-off natural resource exporters. The current situation can probably not be overcome merely through regulatory adjustment, no matter how pervasive. Substantive action to exert radical and lasting mindset change, as regards the merits of public sector and established institutional brands and structures relative those of experimenting with and developing new enti-

Natural Resource Dependency and Innovation in the GCC Countries

ties and solutions, needs to be enacted. In order to enable a substantive impact, measures should be synchronized across several policy domains. Examples of what would most likely form important components of such an agenda include those that would increase mobility between the public and the private sector, reinforce merit-based career paths in the labour market, enable income transfers through other means than labour market distortions, support a long-term approach to R&D, facilitate the establishment particularly of potential high-growth knowledge intensive start-

ups, and engineer an upgraded appreciation of entrepreneurship in education and labour market institutions. There is also the task of furthering the oil & gas sector itself, as well as its linkages to other sectors, including by spurning spin-offs, not least as this is where a lot of the already existing professional expertise and most dynamic innovativeness no doubt resides. Universities and research institutes belong to those that should be incentivized to invest and partake more in combined knowledge creation and knowledge use, by specializing and developing diverse approaches

Figure 21. Innovation along the value-chain (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009))

Figure 22. Innovative behaviour of firms with international versus domestic ownership (Source: CISIKED Pilot Data Innovation Survey, SCAD (2009))

295

Natural Resource Dependency and Innovation in the GCC Countries

Figure 23. Proportion in the economy of large co-operating firms (Source: CIS-IKED Pilot Data Innovation Survey, SCAD (2009), and Eurostat))

to science-industry interface and the kinds of knowledge brokering that can work out in their specific context. All this requires an approach to governance that allows for innovation to attain a high priority in public and private decision-making across the board. An effective and consistent approach to fostering innovation is greatly facilitated by constructive engagement of all the key stakeholders, in such a way as to enable a widely spread buy-in and room for bottom-up initiatives. Already enacted successful policy reforms, e.g., in ICT when it comes to the UAE and Qatar, may be built upon to solidify the momentum for such engagement. The improved access to new tools and services in ICT can also be used to help raise greater interest in, and acceptance of, new solutions in other areas. Will the GCC countries succeed, and thus ultimately demonstrate that the natural resource curse is not cast in stone but can be turned around to realize a blessing? This we obviously do not know, and further observations and research work are thus warranted. The clock keeps tick-

296

ing, however, with the natural resource riches of these countries extracted and consumed for fewer gains than could potentially be generated, because insufficient effort is going into long-term R&D and skills accumulation aimed to carve out a sustainable edge, and also into developing the competencies that are required for diversifying into those neighbouring and complementary activities that could still last after the current resource basis is gone. The later in the day it gets, the stronger the drive will be for the GCC countries to do what it takes to make their growth record sustainable. In this sense, there will be a race between the forces calling for reforms in support of long-term capacity building, and those that keep exploiting what can be relatively effortlessly consumed today. While that is not unique to NRE, but applies rather universally, more is at stake for these societies than for most. Finally, we argue that the empirical evidence and conclusions on innovation in the GCC countries presented in this chapter lend some insights into what is crucially important for breaking away

Natural Resource Dependency and Innovation in the GCC Countries

from the natural resource curse. At the same time, further studies are required on a number of issues. This includes the actual state and nature of innovation in natural resource based economies, the linkages between innovation in natural resource related industries and other parts of the economy, the quality issues in their educational systems and labour market institutions, how they can develop a vibrant university sector and research community that is also capable of generating productive science-industry interface, how to generate successful knowledge-intensive potential high-impact start-ups, and how to succeed in implementing governance reform in support of a comprehensive innovation system in such economies.

REFERENCES Alexeev, M., & Conrad, R. (2009). The elusive curse of oil. The Review of Economics and Statistics, 3(91), 586–598. doi:10.1162/rest.91.3.586 Amin, M., & Djankov, S. (2009). Natural resources and reforms. Washington, DC, USA: The World Bank, Financial and Private Sector Vice Presidency. doi:10.1596/1813-9450-4882 Andersson, T. (2009). The changing role of technology & knowledge transfer and the need of institutional change, special feature: Globalisation of technology transfer. Tech Monitor. March-April. Andersson, T., Carayannis, E., Formica, P., Johansson-da Silva, S., & Mahroum, S. (2010a). Towards innovation policy in Abu Dhabi: Indicators, benchmarking, and natural resource rich economies. Abu Dhabi: General Secretariat of the Executive Council. Andersson, T., Curley, M., & Formica, P. (2010b). Knowledge-based entrepreneurship, the driving forces behind social and economic transformation. New York, NY: Springer Verlag.

Andersson, T., & Formica, P. (2007). The formation of international start-ups and mobility as an international public good. Industry and Higher Education, 2(21), 125–127. doi:10.5367/000000007780681049 Arzeki, R., & Bruckner, M. (2009). Oil rents, corruption, and state stability: Evidence from panel data regressions, IMF Working Papers 09/267, Washington, International Monetary Fund. Aubert, J. E., & Reiffers, J.-L. (2002). Knowledge economies in the Middle East and North Africa: Toward new development strategies. Washington, DC, USA: World Bank Institute. Auty, R. (1990). Resource-based industrialization: Solving the oil in eight developing countries. Oxford, UK: Clarendon Press. Blomström, M., & Kokko, A. (2007). From natural resources to high-tech production: The evolution of industrial competitiveness in Sweden and Finland. In D. Lederman, & W. Maloney (Eds.), Natural resources: Neither curse nor destiny. Washington, DC., USA: the World Bank. Bulte, E., Damania, R., & Deacon, R. (2005). Resource intensity, institutions and development. World Development, 7(33), 1029–1044. doi:10.1016/j.worlddev.2005.04.004 Carayannis, G. E., & Campbell, D. F. J. (2009). Mode 3 and Quadruple Helix: Toward a 21st century fractal innovation ecosystem. International Journal of Technology Management, 3/4(46), 201–234. doi:10.1504/IJTM.2009.023374 Corden, M. W. (1984). Booming sector and dutch disease economics, survey and consolidation. Oxford Economic Papers, 36, 359–380. Devarajan, S., Minh Le, T., & Raballand, G. (2010). Increasing public expenditure efficiency in oil-rich economies. Washington, DC, USA: World Bank, Africa Region, Chief Economist Office.

297

Natural Resource Dependency and Innovation in the GCC Countries

Djeflat, A. (2010). Building knowledge economies for job creation, increased competitiveness, and balanced development, individual country overview: the UAE. Background Report of the High Level International Conference. ISESCO, World Bank, Tunisian Government, Carthage, Tunisia, forthcoming.

Lederman, D., & Maloney, W. (2007). Neither curse nor destiny: Introduction to natural resources and development. In Lederman, D., & Maloney, W. (Eds.), Natural resources, neither curse nor destiny. Palo Alto, California & Washington, DC: Stanford University Press and World Bank, Latin American Development Forum Series.

Fasano, U. (2002). With open economy and sound policies, U.A.E. has turned oil curse into a blessing. IMF Survey. International Monetary Fund, 21(October), 330–332.

Lundvall, B.-Å. (1992). National innovation systems: Towards a theory of innovation and interactive learning (Ed.). London, UK: Pinter.

Frankel, J. (2010). The natural resource curse: A survey. Cambridge, MA: Harvard Kenny School, Faculty Research Working Paper Series, February. Freeman, C. (1987). Technology policy and economic performance: Lessons from Japan. London, UK: Pinter. Gylfason, T. (2001). Natural resources, education and economic development. European Economic Review, 4/6(45), 847–859. doi:10.1016/S00142921(01)00127-1 Herd, M. (2005). No representation without taxation? Rents, development and democracy. Comparative Politics, 3(37), 297–317. Isham, J., Woolcosk, M., Pritchett, L., & Busby, G. (2005). The varieties of resource experience: Natural resource export structures and the political economy of economic growth. World Bank Economic Review. Oxford, UK: Oxford University Press. Jones, C. I. (2002). Introduction to economic growth. New York, NY: Norton. Kojo, N. C. (2010). Diamonds are not forever, Botswana medium-term fiscal sustainability. Policy Research Working Paper 5480. Washington, DC., USA: World Bank.

298

Milbergs, E., & Vonortas, N. (2004). Innovation metrics: Measurement to insight. Center for Accelerating Innovation and George Washington University, National Innovation Initiative 21st Century Working Group, 22 September. Nurkse, R. (1953). Problems of capital formation in underdeveloped countries. Cambridge, UK: Cambridge University Press. Porter, M. E. (1990). The competitive advantage of nations. New York, NY: The Free Press. Rostow, W. W. (1960). The stages of economic growth: A non-communist manifesto. Cambridge, UK: Cambridge University Press. Sachs, J., & Warner, A. M. (1995). Natural resource abundance and economic growth. In Meier, G., & Rauch, J. (Eds.), Leading issues in economic development. New York, NY: Oxford University Press. Sachs, J., & Warner, A. M. (2001). Natural resources and economic development: The curse of natural resources. European Economic Review, 45, 827–838. doi:10.1016/S0014-2921(01)00125-8 Sala-i-Martin, X., & Subramanian, A. (2003). Addressing the natural resource curse: An illustration from Nigeria. IMF Working Paper, 3(139). (2009). SCAD. Abu Dhabi, Abu Dhabi: Statistics Center.

Natural Resource Dependency and Innovation in the GCC Countries

Smith, K. (2007). Innovation and growth in resource-based economies. Hobart: Australian Innovation Research Centre, University of Tasmania. Solow, R. (1957). Technical progress and the aggregate production function. The Review of Economics and Statistics, 99, 312–321. doi:10.2307/1926047 Sturm, M., Adolf, P., & Peschel, J. (2008). The Gulf Cooperation council countries. Economic structures, recent developments and role in the global economy. European Central Bank, Occasional Paper Series, 92, July. UNCTAD. (2010a). Information economy report. Geneva, Switzerland: UNCTAD. UNCTAD. (2010b). Science, technology and innovation indicators for policymaking in developing countries: An overview of experiences and lessons learned. Geneva, Switzerland: UNCTAD. Van der Ploeg, F., & Poelhekke, S. (2009). Volatility and the natural resource curse. Oxford Economic Papers, 4(61), 727–760. doi:10.1093/ oep/gpp027 Van der Ploeg, F., & Poelhekke, S. (2010). The pungent smell of Red Herrings: Subsoil assets, rents, volatility and the resourcer curse. Journal of Environmental Economics and Management, 1(60), 44–55. doi:10.1016/j.jeem.2010.03.003 World Bank. (2008). Middle East and North Africa region, 2007 economic developments and prospects. Washington, DC, USA: World Bank. World Bank. (2010a). World development indicators. Washington, DC, USA: World Bank. World Bank (20010b). World bank knowledge assessment methodology data. Washington, DC., USA: World Bank. World Economic Forum. (2010). Global competitiveness report. Geneva, Switzerland: World Economic Forum.

KEY TERMS AND DEFINITIONS Community Innovation Survey (CIS): Today CIS represents a standard practice for collection of information on innovation performances at enterprise level, spanning both product innovation (goods or services) and process innovation (organizational and marketing), through a series of harmonised surveys. A CIS is undertaken regularly (typically on a bi-annual basis) by European Union Member States but also by many other countries around the world.12 Digital Divide: The gap between individuals, households, businesses and geographic areas at different socio-economic levels with regard to both their opportunities to access ICTs and their use of the Internet for a wide variety of activities.13 Dutch Disease: The negative impact on an economy of anything that gives rise to a sharp inflow of foreign currency, and thereby currency appreciation, such as the discovery of large oil reserves.14 Typically the concept is used to refer to the shrinking of other sectors producing tradable goods in economies with large natural resource exports. Economic Diversification: The process through which an economy produces a growing range of economic output, across different sectors or kinds of products. It can also refer to the diversification of markets for exports or the diversification of income sources away from domestic activities.15 Merit-Based Promotion: The promotion and remuneration of staff based on merit and competencies of relevance to their ability to carry out a particular job, rather than based on other ad hoc factors or connections. Resource Curse: It has been observed that economies with rich endowments of natural resources tend to underperform economically relative to what one would expect based on other factors.16 Total Factor Productivity (TFP): TFP growth is the share of productivity growth that cannot be

299

Natural Resource Dependency and Innovation in the GCC Countries

ascribed to capital or labor or any other particular production factor. Thus, TFP is in effect measured as the unexplained residual, the source of which is associated with technical progress, organisational change, or “new ways of doing things”. Vested Interest: Special privileged groups that carry own economic benefit from exerting a political influence on regulations or other policies.

5



6



7



8



ENDNOTES 1



2



3



4



300

Also sometimes referred to as multifactor productivity, TFP reflects the overall efficiency with which capital and labour is put to use. It is boosted by generally improved ways of producing goods and services, and tends to be driven by technical progress and innovation. The GCC (Gulf Cooperation Council), whose members are the Kingdom of Saudi Arabia, the Kingdom of Bahrain, Kuwait, the State of Qatar, the Sultanate of Oman, and the United Arab Emirates (UAE), has as its objective to promote cooperation between its members to achieve unity. At the aggregate level, the importance of such linkages has been expounded in the notion of national innovation systems (Freeman, 1987; Lundvall, 1991). Impetus for innovation may also draw on linkages between individual firms, or between firms interacting within or between specific industries or industrial clusters (Porter, 1990). The most impressive case in Africa is that of Botswana, which has demonstrated stable high growth over the last decades, pulled by substantive revenue from mining, notably of diamonds. Exceptionally high price stability for this commodity has helped fuel predictability in public revenue and underpin constant growth. Looking ahead, however, conditions may well become less favourable. As Botswana remains highly dependent on

diamond production and exports, conditions for extraction are set to become increasingly demanding (Kojo, 2010). The last-minute name change of the world’s tallest building, Burg Khalifa (named after the ruler of Abu Dhabi), should be seen in this light. The continuous negotiated influx of resources from Abu Dhabi is set to gradually tie the regional economies, as well as the governance, of the two prime Emirates, more closely together. The situation will nevertheless hardly do away with the natural competition between them, and the room for diversified development, reflecting their different historical origins as well as economic structures. In order to enable benchmarking that is relevant to the GCC countries, as comparator we use KAM data, and specifically “Aggregate Western Europe”, here relabelled “EU12+3”. This measure excludes the largest EU-economies and members of G7 (France, Germany, Italy, UK) but includes high-income “old” EU countries, and also the three advanced non-EU high-income European countries (Iceland, Norway, Switzerland). The measure is thus calculated as the average for: Austria, Belgium, Cyprus, Denmark, Finland, Greece, Iceland, Ireland, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, and Switzerland. Throughout this chapter, the GCC countries are benchmarked against each other, the defined high-end European comparator, and the selected peers in the wider Middle East and North Africa (MENA) region. The level attained by Qatar, following political decisions to put funding aside in foundations and capacity-building programmes, is not yet recorded in official R&D statistics. The investment is not matched by domestic research activity, but rather stimulates international linkages and provides incentives for future research.

Natural Resource Dependency and Innovation in the GCC Countries

9



10



CIS were first developed in European countries but have gradually been carried out in an extensive number of other countries, both in the OECD and elsewhere. The main statistical unit for CIS is the enterprise, notably in the following market activities: mining and quarrying (NACE 10-14), manufacturing (NACE 15-37), electricity, gas and water supply (NACE 40-41), wholesale trade (NACE 51), transport, storage and communication (NACE 60-64), financial intermediation (NACE 65-67), computer and related activities (NACE 72), architectural and engineering activities (NACE 74.2) and technical testing and analysis (NACE 74.3). Run by the Statistics Center - Abu Dhabi (SCAD), under the guidance of the International Organisation for Knowledge Economy and Enterprise Development (IKED), the

11



12



13



14



15



16



CIS-IKED survey succeeded in obtaining a 93% response rate (Andersson et al., 2010a). The weight of oil & gas in the GDP of Abu Dhabi stands at about 60 percent. In Saudi Arabia, for instance, the share is below 50 per cent. http://epp.eurostat.ec.europa.eu/statistics_ explained/index.php/Glossary:Community_ innovation_survey_(CIS) http://stats.oecd.org/glossary/detail. asp?ID=4719 http://lexicon.ft.com/Term?term=dutchdisease http://unfccc.int/adaptation/nairobi_work_ programme/programme_activities_and_ work_areas/items/3994.php http://www.eoearth.org/article/Resource_ curse

301

302

Chapter 17

Innovation in Scenario Building: Methodological Advancements and a Foresight Study of the Automotive Industry in Brazil Ariane Hinça Schneider Industry Federation of Parana, Brazil Laila Del Bem Seleme Industry Federation of Parana, Brazil Felipe Fontes Rodrigues Federal University of Parana, Brazil Marilia de Souza Industry Federation of Paraná, Brazil Helio Gomes de Carvalho Federal Technological University of Parana, Brazil

ABSTRACT Situated in Paraná state in southern Brazil, the Metropolitan Region of Curitiba (MRC) is home to an automotive sector which plays a major role in the local and national economy. In order to expand the development of the automotive sector and to create new local and worldwide opportunities, the Federation of Industries of Paraná (FIEP) developed and employed an innovative scenario building methodology to analyze the automotive industry’s potential for innovation and attendance of new market demands for 2020; which is Sector Foresight. Therefore, results allow the players to have a clearer managerial view of the industry’s possible future. This chapter seeks to publicize the experience as well as the results of this innovative project by focusing on the methodology and tools. Data sources included a review of the literature, document analysis, direct observation, semi-structured interviews and two rounds of questionnaires. This experience contributed to innovate the organizational and methodological processes of FIEP, and to improve the perspective of innovation in the automotive sector through a new approach to scenario building. Results also shown this methodology can be applied to other industries in future studies. DOI: 10.4018/978-1-61350-165-8.ch017

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovation in Scenario Building

INTRODUCTION The automotive industry plays an important role in the economies of over 40 countries, and is a benchmark for innovation and application in management and production technologies. Brazil is one of the world’s key automotive players and ranks fifth worldwide in vehicle assembly (OICA, 2010). Paraná state is home to one of Brazil’s leading auto industry clusters, with more than 6,000 related companies located in the Metropolitan Region of Curitiba (MRC). Due to the industry’s importance to Paraná, in 2008 and 2009 the Federation of Industries of Paraná (FIEP) oversaw a foresight study conducted by its Industrial Development Observatory (ODI). It was designed to contribute to the MRC automotive industry by improving the sector’s growth and development, and create new opportunities worldwide. Scenario building was chosen as the key tool to assess the industry, while the project’s timeframe was set for the year 2020. This chapter examines the innovative experience and results of the project, specifically the methodology developed and the tools applied. The region’s automotive industry is relatively new compared to other Brazilian clusters, and as such it was somewhat unorganized, which hindered its view of the sector’s future. Accordingly, this project was driven in part to promote interaction among its key players and develop synergies within the sector. The innovation of this experience is seen in the creation of a new organizational method (OECD, Oslo Manual, 2005): Sector Foresight. It was developed by FIEP to significantly improve its industrial relations through an enhanced view of the industries’ possible futures. This also contributed to the acquisition of non-transactional assets, paramount to the automotive industry scenario building exercise. This methodology involves a process of assessing and analyzing opinions from the public and private sectors, universities and research centers, and was conducted in a structured,

collaborative, coordinated and synergistic way. When making decisions about the automotive industry’s future as a whole, a systematic view of this environment is employed, as it considers the needs and wants of all participants. This scenario building activity, based on the foresight methodology developed by FIEP, differs from other methods as it enables the participation of different players within an industry, thanks to FIEP’s impartiality in overseeing the entire process. It is regarded as an innovative methodology as it includes the perspectives and opinions of multiple stakeholders, not to the organizations individually, but to the industry as a whole, leading to the collection and analysis of strategic information regarding the views of all participants. This new approach to scenario building provides managers of different organizations with a forward-looking, systematic look at the need to innovate in technology, processes and products to meet future conditions. It can also contribute strategically to organizational planning. It not only provides significant improvements for scenario building, but is also an innovative new service provided to industry by FIEP.

FORESIGHT AND SCENARIO BUILDING Foresight is a methodology to collect and assess expert opinions about the future from the public and private sectors, universities and research centers, through a structured, interactive, participative, coordinated and synergistic process (Godet, 2001). It is used to build strategic views that can spur competitiveness and the development of a country, territory, company or public institution and as shown below, an industrial sector or a productive chain. The University of Manchester defines foresight as a process of anticipation that assesses expert opinion to set priorities regarding certain assumptions about the future which are constrained by

303

Innovation in Scenario Building

the external environment. These assumptions are limited to the development of interfaces with customers, suppliers and regulatory bodies, allowing foresight to give meaning to the environment by defining strategic views and reducing uncertainties. For Coates (1985), foresight is a process for a deeper understanding of the factors that drive the design of the long-term future, and should be taken into account in policy, planning and decision making. Horton’s (1999) approach asserts that foresight is “a process of developing views on possible ways in which the future can be built: by understanding that present actions will contribute to the future’s best scenario”. On the other hand, Hamel and Prahalad (1995) feel that foresight should reflect the idea that predicting the future must be predicated on a detailed perception of trends in lifestyle, technology, demography and geopolitics, but is equally based on imagination and prognosis. Similarly, Martin et al (1998) define foresight as a process for systematically analyzing the long-term future for science, technology, the economy and society. They add however, that the research should be able to identify fields of strategic study, development and emerging technologies that would most likely create the best economic and social benefits. Cristo (2000) takes foresight further, seeing it as the process of anticipating and exploring the opinion of experts from social networks in order to build strategic views. According to Schwartz (2000), scenario building is one of the activities that comprise the foresight methodology. Scenarios are tools for helping long-range views in a world of great uncertainty. Such tools can promote the recognition of change processes in the current environment. The author also says they can be seen as alternative stories or “tales” about the future. More than recognizing changes, they allow preemptive responses in order to fully adapt to them (Schwartz, 2000).

304

According to Godet (1987), scenarios are the consistent description of a future situation and leading events from the present onto that future. From an industrial perspective, Porter (1989, p. 413) states that scenarios are: “an internally consistent view of the future structure of an industry. They are based on a set of plausible assumptions regarding important uncertainties that could influence the industrial structure, taking into account their implications for the creation and support of competitive advantage. A complete set of scenarios, and not the most probable one, is then used to design a competitive strategy”. Scenario building involves a systematic procedure to detect trends and identify the social forces that could alter them (Rattner, 1979). For this exercise one must define a timeframe, the key structures and parameters for the analysis, and the scenario building objectives. According to Simpson (1992) and Schoemaker and Heijden (1992), the results from scenario building lead to a broader view of the external environment, thereby improving the decisionmaking process, as it enhances management’s perceptions and ensures faster decisions. Quinn and Mason (1994) complement this idea by stating that the scenario building practice triggers strategic thought, which prepares one to face important changes. The techniques for prospective scenario building date from the twentieth century and have subsequently been refined. The methods are many - (Godet, 1993, 2000a, 2000b; Porter, 1992; Schoemaker, 1995; Ringland, 1998; Wilson, 1998; and Schwartz, 2000): Logical-Intuitive; the GBN Model; Schoemaker; Michel Godet; Arthur D. Little; the Mitchell Method, Tydeman and Georgiades; Michel Porter’s Competitive Strategies; Impact and Trends Analysis; Comprehensive Situation Mapping, Future Mapping, Crossed Impacts and Grumbach.

Innovation in Scenario Building

Of this sample of 12 methods only three are described in this study, as they are basis to the methods used by FIEP’s ODI/PR for this case study: Michel Godet’s Method (1993), Global Business Network – GBN (Schwartz, 2000) and Grumbach’s (1997) Methodology. All use foresight as a theoretical basis. However, each has distinctive features which can help meet specific demands of varying situations. All three methods are also variable-based, taking into account the behavior of the players and the consistency of the multiple scenarios that can emerge. These results are used in strategy building in response to the object of study. Nevertheless, the number of variables and their possible outcomes can make the process lengthy and time consuming, requiring know-how and adaptability from the researchers. The three methods are briefly described below.

Michel Godet’s Methodology Godet’s (1993) scenario building methodology begins with a diagnosis of the external environment to further support strategic decision making. The author believes that every action in the present will reflect on the future scenario, making it possible to predict possible scenarios and take actions to achieve desirable results. This anticipation to action helps deal with the growing effects of uncertainties and interdependency, plus changes in certain areas and inertia in others. The objectives of the scenario building under this perspective are: •

•

Identifying key variables through a global analysis that can establish relationships among the variables related to the object of study; Identifying, from these key variables, the main players, their strategies and the means they have to reach their goals. The analysis of these elements, as well as the evolution of the relationships among players, can provide indicators towards possible scenarios; and

•

Building possible scenarios through the evolution of the system under study by taking into account the most likely outcomes of the key variables, and then assessing the variables’ hypotheses.

Scenario building, under Godet’s methodology, begins with defining the scope of study, and then listing the relevant variables and players. A structural analysis is conducted to identify the influence/dependence of each variable between them. Games are then used to identify the strength of the relations among the players, as well as their objectives, strategies, behavior, uncertain elements and trends. All of these can cause ruptures in the scenario’s environment. Thus, the analyses help define the futures’ main drivers, allowing further hypotheses to be made that will be used later on, in the “morphological analysis”. Accordingly, Godet’s Methodology consists of eight stages: 1. Definition of the scope and the environment 2. Retrospective analysis of the environment and current situation 3. Structural analysis of the system and environment 4. Selection of futures’ drivers 5. Design of alternative scenarios 6. Consistency tests 7. Establishment of polices and strategies 8. Strategic monitoring

Global Link Network Methodology (GBN): Peter Schwartz (1988) The Global Link Network Methodology, known as GBN, was created by Peter Schwartz, who sees scenarios as an instrument of long-range strategic planning that considers macro-environmental uncertainties. These qualitative or quantitative uncertainties require that multiple future scenarios be generated during the planning process. This method tries to identify those issues with the most

305

Innovation in Scenario Building

effect on decision making, based on what he calls the “strategic urgency” in a given system. These issues can be accessed through interviews, panels or expert discussions that deepen the understanding of a subject. After defining the most relevant aspects of a given system, one should identify the driving forces with the most influence on the macro-environment. From these driving forces one can identify the critical uncertainties that will be the required inputs for scenario building. This scenario building methodology is unique as it begins with the micro-environment of the system and grows towards the outside, or the external macro-environment. The goal is to highlight the most likely significant changes in the future of such a system. Therefore, the system should be analyzed from the inside-out, focusing on the most significant differences that can occur in its future scenarios. It can be considered a learning process of a specific system’s nature as it allows the players involved to have a shared view of the possible outcomes. It also enables managers to learn how to cope with the unexpected. The GBN methodology features eight steps: 1. Identification of the focal issue or decision 2. Identification of key factors (micro-environment) 3. Identification of driving forces (macro-environment) 4. Ranking of pre-determined uncertainties 5. Selection of scenario logics 6. Description of the scenarios 7. Selection of key indicators and signalers 8. Analysis of the implications and options

Grumbach’s Methodology The initial version of Grumbach’s (1997) methodology was a tool for making and analyzing prospective scenarios. However, it evolved into a future view-based strategic planning process anchored in prospective scenarios. The method

306

uses an open system approach, meaning that the object of analysis can either influence or be influenced by its environment. From this point of view, it seeks to model the key strategic questions and the players’ behavior, and only then build the prospective scenarios. For Grumbach, one should ideally build four alternative scenarios: “the more likely”, “the ideal”, “the optimistic” and “the pessimistic”. Grumbach’s method relies on various tools to complete its scenarios: brainstorming, Delphi rounds, cross-impact analysis, Bayes’ theorem, Monte Carlo Simulation and game theory. Its use is made simpler through the development of two software programs: Puma, a system for strategic planning and prospective scenarios; and Lince, a future management and simulation system. The method consists of three stages: 1. Understanding the problem 2. Assessing the alternatives 3. Evaluating and interpreting the alternatives for decision making

THE AUTOMOTIVE INDUSTRY The automotive industry is a global economic powerhouse. Vehicle assembly alone generates over US$3 trillion in revenue worldwide. Auto manufacturing plants operate in more than 40 countries, including six South American countries, of which Brazil is the leader. The industry consumes massive amounts of raw materials and has invented production systems from Ford’s traditional mass-volume assembly line to today’s advanced approaches such as the Toyota Production System and Lean Manufacturing, to name a few. The plants have become increasingly effective and are the de facto creators of today’s global supply-chains. Over 70 million vehicles are produced globally each year, and this number has grown despite the 2008 economic crisis (OICA, 2010). The tradi-

Innovation in Scenario Building

tional industrial leaders have played little part in this growth, as new markets have emerged in the past decade, namely China, India and South Korea. These countries already represent well over 20% of worldwide production, while South America represents about 5% (3.5 million vehicles). Production on this scale requires a massive labor force: the automotive industry accounts for eight million direct jobs, which represent 5% of total world employment in manufacturing (ILO, 2008). It is also estimated that every direct job accounts for five other indirect jobs worldwide. Among manufacturers, the auto industry is the Research & Development leader, investing 4% of its revenue into R&D. However, the nature of R&D has changed. It has gradually been passed down from the automakers to Tier 1 auto parts suppliers, mainly due to the latter’s thriving specialization in high technology parts and high value-added assembly sets (London School of Economics, 2006). The market became relatively saturated by the early 2000s, after a period of high growth in the industry’s traditional markets: Japan and the developed countries in Europe and North America. This saturation is thought to be mostly due to the vehicle/population ratio as well as negative demographic trends. The industry’s current focus has shifted to a restructuring of production capacity, parts replacement and new markets, in the face of sharp increases in prices of raw materials, and a rapid rise of new players in Asia. Among the markets that present the greatest potential are the so-called BRICs: Brazil, Russia, India and China. These emerging economies have a low vehicle/population ratio, vast territorial dimension and significant increases in purchasing power. These factors led to an increase in demand for personal and cargo mobility (PWC, 2006). An underdeveloped multimodal transport infrastructure actually favored road transportation, which is more flexible and adaptable to these countries’ rapid economic growth.

This recent growth cycle of the BRIC countries attracted new assembly plants which can supply domestic and neighboring markets. These countries are primarily seen as the answer to continued growth in the industry. After all, they not only boast growing demand, but also offer lower production costs, mostly favorable exchange rates and heavy government incentives. Recent investments made by auto makers and parts suppliers back up this trend. To exploit these opportunities, North American, European and Asian countries have invested in emerging economies, which are estimated to generate up to half the growth in worldwide production, and which are responsible for around 80% of the industry’s growth in sales. On the other hand, added pressure is being placed on the mature markets, as there has been an increase in product life-cycle. This is the result of higher value-added technology and superior production assembly. It also allows for longer ownership and a higher average age of the fleet. A lower repair frequency in the European Union has been reported, while at the same time the average maintenance value remains the same. Even more pressure can be felt from the supply and demand side. High price sensitivity among consumers, rising production and raw material costs and the emergence of new competitors are already a reality. China and India have started up exporting programs, mainly in light commercial and low cost vehicles, and plan to export up to one million vehicles per year (including the new ultra-low-cost segment). The auto parts segment has also become a key factor in emerging countries, and will become even more so. Although it represents only 5% of the auto makers’ revenues, it generates up to 50% of their profits. Apart from some regional manufacturers (Tata, Mahindra & Mahindra in India, FAW and Chery in China, and GAZ in Russia), the bulk of the world’s domestic car and heavy vehicle markets is distributed among the major American, European, Japanese and most recently, Korean multinationals. Nevertheless, a lower market concentration

307

Innovation in Scenario Building

can be found in the auto parts business. The 30 largest companies in Europe are responsible for providing almost all the parts and assemblies for the manufacturers which operate in the European Union (London School of Economics, 2006). Despite its contribution to economic development and mobility, the industry faces challenges that directly affect its sustainability. Internal combustion engines and tailpipe emissions are major public opinion topics, despite being responsible for only a small amount of total emissions from human activities (VDA, 2007). Heavy metals and other materials are also pollutants and a fundamental part of today’s automotive technology. The automotive industry infrastructure also causes environmental impacts, while the use of cars has a strong social impact. The industry’s response to these findings has been a crusade to produce safer, quieter vehicles with embedded clean technologies and a comprehensive assessment of the product’s life cycle. (WBCSD, 2004). This position demands that automakers – in fact, the industry as a whole – to organize itself around a supply chain that is more sustainable and governed by best social, labor and environmental practices. In view of the global warming phenomenon, the industry has made it a top priority to significantly reduce its emissions (ACEA, 2007). This commitment has become a reality for automaker associations such as ACEA (European Automobile Manufacturers Association), JAMA (Japanese Automobile Manufacturers Association) and KAMA (Korean Automobile Manufacturers Association). These groups have all adopted greenhouse gas emissions caps. Automakers and suppliers seek to help reduce CO2 emissions, mostly through better designs, lighter materials, alternative fuels and more fuel-efficient engines. They have also invested heavily in emission control technologies. According to the “Well-to-wheel” report, edited by the European Union Commission, switching to alternative-fuel sources, either renewable or less polluting, could bring huge reductions in emissions. However, the high costs in R&D, the need

308

for synergies among different companies along the supply chain and the many energy-intensive technologies can offset such savings significantly. The automotive industry has been faced with numerous challenges, whether threats or opportunities. Diverse strategies are well underway, taking into account the specific conditions of each regional market. Likewise, comparative advantages and disadvantages of each locale have preeminent importance regarding the role they will play in the industry’s future. On this basis, following is a look at the automotive industry in Brazil, showing its current role in the domestic economy and the challenges it faces, which underscored the efforts taken to research possible futures for the industry in Brazil and the state of Paraná.

The Automotive Industry in Brazil Vehicle production in Brazil began in the late 1950s with the establishment of Volkswagen, Toyota and Ford plants (the latter also produced light trucks) in the town of São Bernardo do Campo, in São Paulo state. Scania and Mercedes-Benz set up truck and bus plants in São Caetano do Sul in São Paulo, where General Motors later established a diversified plant. The city of São Paulo also received a Ford truck plant shortly thereafter. Later investments by Fiat in the state of Minas Gerais and others in the states of Rio de Janeiro, Paraná and Rio Grande do Sul comprised the basis of the automotive industry in Brazil until the 1990s. With the opening of the Brazilian economy to foreign markets and the concurrent economic stabilization that took place in the 1990s, the industry received a push with the retooling of existing plants and the building of new plants by Renault, Peugeot-Citroen, Nissan and Mitsubishi, to name a few (BNDES, 1999). In 2006 the automotive industry in Brazil turned 50 years old, with over 24 automakers, over 500 parts suppliers and an endless number of service providers (ANFAVEA 2007). Over the

Innovation in Scenario Building

previous ten years domestic production and sales of vehicles had increased significantly. The Brazilian auto market is characterized by the production of small and medium-sized vehicles. In 2005, 55% of sales came from cars with engines no larger than 1000cc. Such vehicles have government incentives - such as tax waivers, first introduced in the 1990s - to encourage the market for these so called “popular” cars. High demand and competition push the need for costcutting, large-scale production and low margins. A unique feature of the Brazilian market is the predominance of flex-fuel vehicles (which run on gas, ethanol or any mix of both), whose technology has helped reduce the country’s dependence on foreign oil. Successive hikes in the price of oil worldwide have led several markets to further research the Brazilian experience and assess the potential benefits of flex-fuel technology. In fact, automakers and parts suppliers of flex-fuel technologies hope to exploit this interest through exports or technology licensing. By the early 2000s the domestic market had trouble meeting the industry’s initial forecasts of high-volume growth, and so shifted its focus to exports to better utilize excess capacity. Exchange rate policy changes and a strengthening local currency, which occurred by mid-decade, showed up the weaknesses of this strategy. As in other countries, Brazil couldn’t sustain its role in the international market until its domestic market boosted demand. It wasn’t until the late 2000s that the market flexed its muscles and began its long awaited growth path. Other automakers took notice and competitors have now arrived to challenge the established players, through direct investments in new plants and via favorable exchange-led imports. The main foreign markets for Brazil’s automotive industry are Latin American countries with similar features to Brazil (high concentration in small hatchbacks), and lower income countries such as Mexico, China, India, Russia and South Africa.

One of the challenges of operating in Brazil is the higher–than-expected production cost, seen mostly in its cumbersome and complex tax system. Even among other developing countries, Brazil’s taxation is a heavy burden. The value-chain is strained by fiscal regulations, outdated laws and union issues. In fact, tax and labor concerns might jeopardize future foreign direct investments by automakers. On top of that, the fragile and undersized logistics infrastructure only helps increase the cost of operating in Brazil. Although the country posts moderate growth when compared to other developing economies, the automotive industry has a more positive outlook for the short and medium-term. Downturns in the global economy have had limited effect on Brazil’s automotive industry, which has managed to retain an export base and meet domestic demand. It is not widely known that Brazil and Argentina combined represent 92% of Latin American production. Brazil’s automotive market alone (around two million vehicles) is at least four times that of Argentina and dwarfs those of Venezuela, Chile, Colombia, Paraguay and Uruguay, which have a combined market of less than 600,000 vehicles. This brief background on the automotive industry in Brazil and around the world clearly shows that it plays a key role in the economies where it operates. There are many challenges to be tackled, particularly related to uncertainties over factors such as competitiveness, alternative fuels, new production models, technologies, markets, governments and a qualified labor force. Through understanding and assessing these variables, specific actions can be directed towards a thorough development of the industry and the communities affected by it. Foresight studies such as scenario building become essential for collective long-range thinking. The industry can also undertake collective actions leading to the desired outcomes it seeks.

309

Innovation in Scenario Building

RESEARCH METHODOLOGY Based on its goals, this research is descriptive by nature (Vergara, 2005), as it describes the various stages and tools employed during the scenario building exercise for the MRC automotive industry. It is also a qualitative case study, and according to Yin (2001), was designed to comprehensively and empirically approach a contemporary phenomenon in its real-life environment. To achieve this, multiple sources of empirical evidence were required not only from a review of the literature, but also through questionnaires, semi-structured interviews, direct observation and analysis of the FIEP document database. The literature review was designed to identify the leading scholars and practitioners of scenario building, such as Michel Godet (1987), Grumbach (1997) and Peter Schwartz (2000). Primary data collection was conducted through semi-structured interviews applied to the FIEP scenario building project personnel. The aim of the interviews was to establish the scenario building practice at FIEP. At the same time, direct observation was used to obtain more detailed information regarding the respondents’ experience with the automotive industry. Secondary data was obtained through documentation assessment, which included methodology files, notes, videos, project reports and minutes of meetings. These documents demonstrate the procedures and results of the project. The interviews were submitted for content analysis, along with the secondary data. The goal was to approximate Bardin’s (1977) regularity identification and develop a model that could be used in further practice and research.

SCENARIO BUILDING FOR THE MRC AUTOMOTIVE INDUSTRY The Federation of Industries of Paraná (FIEP) “produces research and reports on economic issues, suggests and discusses strategies related to

310

its many industrial sectors, defends the interests of the industry and provides tools for the development of business associations, fosters international partnerships, and eases the access to credit lines and innovation” (SISTEMA FIEP, 2010). The help meet these goals, the FIEP System started a project called Rede de Competências (Competences Network), which sought to mobilize the automotive industry’s knowledge base to generate growth within the industry and consequently for Brazil. This project was carried out by the National Industry Confederation (CNI) – which coordinates all state Industry Federations – and is supported by the federal government through the Studies and Projects Funding Agency (FINEP). One of the innovative mechanisms created by the Competences Network is the Industrial Development Observatory think tanks (ODIs). Six Brazilian states have implemented local ODIs: Bahia, Minas Gerais, Paraná, Pernambuco, Rio Grande do Sul and Santa Catarina. The central goal of the ODIs is to create strategic knowledge regarding the economy, technology and societal changes and trends which occur globally, nationally and locally. It anticipates the impacts of these changes and trends on numerous industries, and seeks to identify and support possible pathways for innovation and sustainable industrial development. Each ODI selected an industry which was economically important and of local strategic interest. These were then the subject of a foresight pilot project. The FIEP System, through the ODI/ PR, chose Paraná’s automotive industry because it has national and regional importance, it employs over 51 thousand workers in Paraná (Brazil, 2006), and is a regional benchmark in technology and innovation. Through its ODI think-tank, FIEP led the prospective scenario project from 2008 to 2009, with the goal of further developing the state’s automotive industry and bringing in new opportunities worldwide by the year 2020. To build the scenarios, certain steps had to be taken: defining

Innovation in Scenario Building

the scope of the project; establishing the Strategy Board and determining its responsibilities; diagnosis and trend analysis; and lastly, the scenarios themselves. As this was a pilot project, these stages were defined during the working process, and were continuously tested and reassessed until the final format was determined. As part of defining the scope, the key problem and main goals were also set. This stage also finetuned the range of the project (industry sector vs. production chain), geographical area (the MRC) and the project timeframe: the year 2020. Choosing the automotive sector posed the challenge as foresight studies mostly relate either to individual organizations or territories. Adding to the challenge the main goal was defined as “to contribute to strengthening the automotive industry in the MRC and fostering new opportunities worldwide under the scope of 2020”. The Strategy Board was made up of key players that could benefit from the development of the project, namely senior managers and decisionmakers from leading companies and organizations linked to the industry. These individuals are the ones that could contribute the most to the improvement of the industry if they chose to be part of a foresight study. Diagnosis and trend analysis began with gathering the main reports and market studies published by think-tanks, associations and consulting firms around the world. The diagnosis was divided into global and local market structures, trends and industry core competences. From the diagnosis the main variables of the system were extracted and cross-impacted into a structural analysis that allowed for the key variables at stake to be identified, which were used throughout the project. For the scenario building, each at stake variable resulted in hypotheses or possible outcomes. Based on combinations of hypotheses, possible scenarios were built considering the pre-set time frame. Following is a description of the main steps and sub-steps that will result in scenario building for the MRC automotive industry.

Defining the Scope of the Project According to Godet’s methodology (2000b), the first and one of the most important steps is to define the scope, as it provides the basis from which the theme/problem of the study can be determined, as well as the main goals. It also leads to decisions over using the industrial sector or its production chain, the geographical area and the time frame. The choice for the automotive industry as the object of research arose from the economic findings of its importance to the state of Paraná. Upon analyzing the state’s industrial base by manufacturing value, the five main industrial sectors represented 53.5% of total industry in 1996, rising to 63.1% by 2005, namely: food processing, oil refining, and automotive assembly, equipment manufacturing and chemical products. (Instituto Paranaense de Desenvolvimento Econômico e Social [IPARDES], 2005). Automotive assembly (division 34 of Brazil’s national economic activity classification system - CNAE) rose 320% in monetary terms from 1996 to 2005. This same growth is also seen in the number of businesses, which increased from 373 to 462 in the same period (Brazil, 2006). The automotive industry was also a leader (together with the food industry) in job creation during those same years. However, only the automotive industry increased in each of manufacturing added value, job creation and number of businesses. Also, the state’s largest automakers and related firms (Volkswagen, Renault/Nissan, Volvo and Bosch) generate 20% of the state’s international trade (Brazil, 2008). The auto industry’s manufacturing chain covers everything from raw materials to the most complex electronics components, as well as sales and maintenance-related services. Considering the size and complexity of the manufacturing chain, the study was limited to the sectors shown in Table 1. An assessment of economic fundamentals revealed that most of the automotive industries

311

Innovation in Scenario Building

Table 1. Research profile for the study of the MRC automotive chain Automakers

• Passenger cars and light commercial vehicles • Trucks and buses

1st Level (TIER 1)1

• System Suppliers • Auto parts

in Paraná are located in the MRC, thus setting the study’s geographical scope. Discussions among FIEP management resulted in the year 2020 timeframe and the drafting of the research problem. The former was due to the lengthy maturation process of the automotive business, while the latter was defined by the Strategy Board as2: “To contribute to strengthening the automotive industry in the MRC and fostering new opportunities worldwide under the scope of 2020”.

Establishment of the Strategy Board The main actors interested in the development of a foresight study for the MRC’s automotive industry were identified in the second stage, referred to as the Establishment and Modus Operandi of the Strategy Board. The main activities the Strategy Board had to develop were to define the scope, direct activities, articulate resources, and monitor the work and its results. Following the methodology assumptions (GODET, 2000a), the FIEP System considered an approximation to the MRC automotive industries very important; so that all decisions related to the project could be made together. A survey was first taken of both the companies and experts in the automotive industry located in the MRC. Sources used were: the FIEP industrial database, news bulletins, newspapers, associations, unions and the “Lattes research platform” of Brazil’s National Council of Research, the

312

2nd Level (TIER 2)

• Auto parts • Tires • Auto bodies

3rd Level (TIER 3) • Forged metal • Cast metal • Die cast • Plastic • Rubber parts • Glass • Non-metallic parts

CNPq, company sites, amongst others. Selection criteria were selected from this survey in order to establish the “Strategy Board.” The search for strategic actors for the industry was handled respecting the industry’s delimitations, by selecting 3 representatives from each segment selected, such as automakers, 1st level companies (system suppliers), 2nd level (auto parts, pneumatics and auto bodies) and 3rd level (basic parts). The actors were first categorized according to their work category: associations and unions, governments, industries and research. They were also classified according to their position in the company: management positions, strategic decision making jobs, operational positions and sales. The search for products and services was both efficient and useful and was complemented with customer, competitor and supplier research. Bits of information such as ongoing or concluded projects and scientific publications or opinions, related to the subjects of the industry, were added especially for the actors connected to research centers. In short, the criteria used for choosing strategic actors were: the company’s size, number of employees, its capital source (national/multinational), and the company’s position in the chain as well as its field of operation. After the strategic companies were selected, their CEOs were invited to be a part of the Board. This process was done through a formal document signed by the FIEP System’s president. The companies were then contacted by telephone so that each one’s importance in the project was reaffirmed as well as making sure that the com-

Innovation in Scenario Building

pany was interested in taking part of the project. Those who showed interest in taking part in the project were visited by a technical team from FIEP which was able to explain the project and talk about the expectations regarding each company’s participation. The first official Board meeting took place in August 2008, at the International Innovation Center of the Federation of Industries of Paraná. In this meeting the members’participation was confirmed during the building of the Strategy Board and a bimonthly agenda of meetings was accepted, in order to put into action the activities proposed. In agreement with the chosen methodology, all the stages of the foresight scenario building were directed and validated by the Strategy Board so that the project’s results had credibility. The initial idea was to have the participation of approximately 10 companies. Currently the Board companies are: Bosch, Brose, Denso, Fiat Powertrain, Hubner, Igasa, Johnson & Controls, Perkins, Renault, Treves, Volvo and Volkswagen. There were a total of 12 important companies from the MRC automotive industry, as well as a development and innovation agency.

Diagnosis and Trend Analysis An information survey regarding the automotive industry was conducted in this stage of Diagnosis and Trend Analysis. The survey conducted this diagnosis on a global and local level, running trends analysis and sought out current competences identified as necessary for the industry’s development. Later came the structural analysis, which allows for the identification of variables considered relevant for the next stage of the project. The structural analysis technique was used to do a survey regarding the structuring variables for the automotive industry. According to Godet (2004), this is a tool used for diagnosing the influence and dependence relations between the variables of a system. The variables were classified according to their dimension (global, regional and local) and

subject (environment, economics, energy, MRC, government, automotive industry, infrastructure, market, automotive products, technology and society.) From a list of 250 variables, the research team consolidated them into 46, which are: global economic growth, automobiles’ life cycle, productive systems, mobility services, interest rates, international commerce policies, tax legislations, alternative fuels and public transport. The 46 variables chosen were organized in a matrix. The objective was to establish the influence and dependence relations of a certain variable over another. From this variables confrontation, a matrix was obtained: the Cross-Impact Matrix (Figure 1), in which the placement of the variables of the system is determined. This procedure was done with all 46 variables which are considered the most important for the automotive industry. With this matrix established, a “plan of influences” (Figure 2) was built which allowed for better visualization of the variable’s role in the system. The spatial character of the plan of influences is fundamental for understanding the system under study and is of great value in defining future scenarios. The variables of this influence plan are classified into influence variables, variables at stake, dependable variables, excluded variables and borderline variables, according to Table 2.

Figure 1. Example of a cross-impact matrix

313

Innovation in Scenario Building

The 46 variables from the automotive industry were placed on this influence plan, as shown in Figure 3. The most relevant variables in this plan were selected to define the scenarios. Thus this allowed a synthetic analysis and at the same time allowed a deep systems analysis. This selection was made in a Scenario Building Workshop where the variables were shown to a Technical Board consisting of 32 participants, such as senior engineers, analyst researchers and other automotive professionals. This Technical Board analyzed the variables shown and was able to incorporate, transfer or exclude the variables from quadrants, always focusing on the variables at stake. This process was conducted with the consensus of each sub-group of participants. They elected a “spokesperson” to communicate their decision to the spokespersons that represented the other groups. Consequently the spokespersons from all groups were able to reach a general consensus among them and then share their common decision with everyone. According to Godet’s “prospective” methodology (GODET; 1993, 2001), the “variables at stake”, that are the simultaneously very influential and dependable variables, should be given higher priority than the other ones. These variables

Figure 2. Types of variables of the plan of influences

314

have an “ambiguous” behavior and can interfere in all the other system variables. They are “at stake” because their system structure positioning is uncertain, as well as, the position that they can assume. Consequently, the scenarios can be built according to the different positions that these variables at stake can assume. The experts raised likely hypothesis for each variable after the consensus was made of which variables at stake would be suitable for the prospective scenarios in the industry. These hypotheses represent the likely states that the variables would assume within the prospective scenario target. The results were that 24 variables and their hypotheses were chosen. These variables and their respective hypothesis were used as a basis for the scenario building. An example of a chosen variable was “alternative fuels” and their hypotheses were: an increase in regulations and a reduction of alternative fuels available; and also a reduction in the regulations as well as an increase in the different types of alternative fuels offered.

Scenario Building Once the step of choosing variables and their respective probable hypothesis was concluded, the specialist’s query process and the variables probability were started. The hypotheses were presented as semi-structured questionnaires conducted through interviews with members of the Strategy Board of the MRC’s Automotive Industry. The hypotheses that best represented the opinions of the strategic MRC’s board members, regarding the most propitious events, were consolidated in a scenario referred to as a “desirable scenario”. The hypotheses that represented the “trend” behavior, that is, the most likely to occur, were consolidated in the “most likely scenario”. The hypothesis combinations, that seemed the most likely/desirable for the foresight study, triggered the scenario building - Probable and Desirable – that aimed at contributing to the MRC’s Automotive Industry consolidation for

Innovation in Scenario Building

Table 2. Classification of variables in the influence plan VARIABLE TYPES

DESCRIPTION

Influence Variables

• They are very influential and not very dependable variables. • They are variables that explain the system’s dynamics due to their high impact capacity over it.

Variables at stake

• They are simultaneously very influential and dependable variables. • They have an unstable nature and are capable of producing great changes in the system’s dynamics • They are generally considered as challenges and must be constantly controlled.

Dependable Variables

• They are not very influential but are very dependable variables. • They have little impact or no impact at all on the system, but they are part of the results of its dynamics. • Their development is explained by the variables performance in quadrants 1 and 2.

Excluded Variables

• They are not very influential and not very dependable variables. • They are independent factors of the system having only a few connections with it. • Their importance lies in the fact that they can constitute system trends, ie. Factors that have little or no influence nowadays; however, they can represent elements that will have impact on the subject/problem dynamics in the foresight study.

Borderline Variables

• They are moderately influential and dependable variables • A priori, these variables may not indicate anything in a consistent way as its location is not well defined • Variables on this specific area deserve attention in the way of research efforts in order to better understand their performance.

Source: SENAI (2010)

the development of new opportunities worldwide around 2020. This stage had 17 experts participating from the MRC industry, all of which were members of the Strategy Board. They were interviewed using a prospective questionnaire. 10 major themes were touched on, as follows: (1) economics, (2) energy, (3) government, (4) automotive industry, (5) infrastructure, (6) market, (7) automotive products, (8) MRC (9) social and (10) technological. In the end, 24 variables and 83 possible hypotheses were considered. The interviews contributed to variable filtering and this resulted in 23 variables that were considered to have the most impact on the MRC’s industry, as can be observed on Table 3. The Strategy Board considered it paramount to conduct a broader survey in order to obtain more details about the hypotheses and even create their probabilities. A Delphi survey was conducted online especially for this study. Structured questionnaires were sent to experts countrywide, both upstream and downstream along the automotive supply chain; 125 questionnaires were filled out.

The expert’s survey was done in two rounds via the internet. The first round was open for 47 days. After analyzing the data from the first round, a reasonable 12 question consensus approach was reached. The remaining 11 questions that presented either irregular central tendencies or where there was no consensus among the respondents were re-submitted to the 2nd round with the same 125 experts that had already answered the first round questions. The 2nd round was conducted a month after the consolidation of the first round results. This was available on the internet for 13 days, resulting in 68 valid responses. In the second round, relative consensus or central tendencies were reached, allowing for a more robust analysis of the experts’ opinions regarding the automotive industry scenarios for the MRC. A morphological analysis tool was used after obtaining the hypothesis probability and was able to analyze and consolidate the most representative prospective scenarios – Probable and Desirable. According to Godet (2004), the morphological analysis term comes from “morphology” which means the study of forms. It is a tool that can be

315

Innovation in Scenario Building

Figure 3. Influence and Dependence Plan for the MRC Automotive Industry

used to build scenarios from the parts that compose it. In a “prospective” study this tool aims at providing a systematic scanning of possible futures within a given foresight timeframe, through a set of combinations from different scenarios prepared for each variable at stake. The paths for the two main scenarios were: the desirable scenario, or what was referred to as the “Sustainable Future”, and the most likely scenario, that was referred to as the “Future Contingency”. Those trajectories were a good exercise on how changes and ruptures could happen in the near future and therefore, be anticipated. Thus the industry or chain could be better prepared for challenges and opportunities from the competitive environment in which they are located.

316

Regarding achieved results, the study suggests one “likely scenario” for the MRC automotive industry that includes Brazil’s economic growth through trade agreements and lower trade barriers in the external market. It also facilitates the Brazilian companies’ access to supply chains and distribution channels abroad, and includes at least some improvements in logistics infrastructure and the maintenance of the Brazilian automotive industry as a key industry in Brazil’s trade balance. The scenario shows the growth of renewable fuels in the energy matrix as well as new business models such as rental services. It is believed that in this study the industry would specialize in technology according to its core competences; MRC is known as an important local production cluster.

Innovation in Scenario Building

Table 3. Themes and variables Themes

Variables 1. Positive trend in Exports

Economy

2. Increase in GNP per capita 3. Economic importance of the automotive industry in the RMC

Energy

4. Brazil’s transport matrix

Government

5. Brazil’s tax load 6. Industrial policy 7. Probability of reduction in barriers of entry

Automotive industry

8. Trends in the supply chain 9. Industry growth strategies 10. Vehicle Production share 11. Positioning of newcomers

Infrastructure

Market

12. Improvement of Brazil’s transport infrastructure 13. Cost/benefit ratio of vehicle ownership in Brazil 14. Vehicle density in Brazil 15. New vehicle sales in Brazil

Product

16. Average fleet age in Brazil

MRC

17. Relative production costs of MRC compared to other clusters in Brazil 18. Qualified workforce in MRC

Social

19. Probability of alternative transport use among vehicle owners 20. Shift in employers/employees Union relations 21. Productivity gains in the automotive industry

Technology

22. New productive arrangements in the automotive industry 23. Location and intensity of R&D activities in the automotive industry

The “desirable” scenario or the “Sustainable future” includes the MRC as an important worldclass production center as it becomes an agent of technology transformation, not only for the industry but also the State. The scenario suggests a lower logistics cost in Brazil due to better use of the multi-modal system as well as a more important role in Brazil’s exports. Higher investments in education would reflect in a better qualified workforce, trained in universities and technical

colleges that are well integrated into the industry. The scenario boils down to a new automotive industry, based on a greater use of public transportation and alternative means of transportation for vehicle owners and are directly linked to the use of alternative fuels and fleet renewal.

RESULTS: STAGES AND TOOLS Based on the previously stated experience of industrial scenario building and in rigorous accordance to the literature - highlighting Godet (1993), Grumbach (1997) and Schwartz (2000) - the research team at FIEP’s Industrial Development Observatory (ODI/PR) was able to develop a stage-based framework comprising the necessary steps for such an exercise, as well as the best fit tools for its application in industrial scenario building (Table 4). The main stages can be summarized as follows: scope definition; establishment of Strategy Board; diagnosis and trend analysis; and scenario building per se. Scope definition was considered the paramount stage since it defines the problem of research and its goals. It also sets the geographic area, the approach (industry/sector vis-à-vis production chain), and the project’s timeframe. The establishment of the Strategy Board is the stage in which the researchers identify the key players that would be most interested in the development of this type of foresight study. Among its most important activities, one would highlight assisting in scope definition, guidance for the activities according to its relevance to the industry and the validation of the research’s work and results. The project, as it was developed by the ODI/ PR, included a great amount of work on diagnosis and trend analysis. It enables researchers to fully understand the object of study as well as gather the upmost critical information regarding the industry in reference. From this stand point, both global and local diagnosis and trend analysis take place as

317

Innovation in Scenario Building

Table 4. Stages and tools for scenario building stages

SUB-STAGES

TOOLS

SCOPE DEFINITION

• Definition of topic or problem for foresight study • Assignment of chain or industry • Geographic delineation • Definition of foresight timeframe • Definition of objectives • Assessment of Stakeholders

• Perceived ideas workshop • Change, rupture and inertia workshop • Retrospective and prospective questionnaires

STRATEGY BOARD

• Assignment of Strategy Board members • Appointment of attributions of the Strategy Board • Operation and procedures of the Strategy Board

• Perceived ideas workshop • Change, rupture and inertia workshop Retrospective and prospective questionnaires

diagnosis/ trend analysis

• Global and Industry-specific diagnosis • Trend analysis • Assessment and analysis of key players in the industry • Structural analysis and Stakeholder’s game • Research and Assessment of industry’s indicators

• Retrospective and prospective questionnaires • Perceived ideas workshop • Change, rupture and inertia workshop • SWOT analysis • Structural analysis

scenario building

• Identification of uncertainties • Formulation of hypotheses • Hypotheses presumption • Scenario assembly

• Retrospective and prospective questionnaires • DELPHI • Hypotheses probability presumption • Morphologic analysis

well as identifying the core competences necessary for the industry’s development. Moreover, this is when the key variables are first gathered that will be applied throughout the research. Finally, the “scenario-building” stage consists of the identification of possible hypotheses for each variable “at stake” within the system. The likely combinations of hypotheses are, thus, the basis for the possible scenarios considering the given timeframe. The applicable tools for the foresight studies should be those that contribute the most to gathering and analyzing strategic information during the multiple stages of prospective scenario building. They should also assure relevant results not only for the industry but also for the organizations individually. These tools are: •

318

Retrospective and prospective questionnaires: They help the research team obtain information from the players about changes, ruptures, inertia related to past, present and future that are related to a given research topic.

•

•

•

Change, rupture and inertia workshops: Group dynamics aimed at the acknowledging perceptions, behavior and mental representations that experts have in regards to the theme and research problem. Through this exercise, one can identify the changes foreseen, desired or feared by the players during a given timeframe. It can trigger the formulation of alternative responses to the changes previously identified. Perceived ideas workshops: It aims at identifying the experts conceived ideas or behavior that has an impact on the dynamics of the theme or given research problem. As such ideas are taken for granted; they have a powerful impact on the player’s behavior in a given system. Structural analysis: Technique which structures the collective thinking about the variables of a foresight study, thus reducing its complexity. It offers one the possibility of describing any given system with the help of a matrix and a chart that establishes the relationships of all its constituent elements.

Innovation in Scenario Building

•

•

•

•

•

Stakeholder’s game: As is the case with the structural analysis, the stakeholder’s game aims to reduce the complexity of the competitive movements of a given system’s players. Through systematically gathering information on the strategies of stakeholders, one can position the players according to their interests in the system. SWOT analysis: This well known technique helps the industry to take advantage of the opportunities and avoid external threats. It also explores the strengths and weaknesses of the players helping them to make the best of both. Its application makes it possible to obtain and process relevant information for scenario building as well as to plan strategies for the players involved. Morphologic analysis: This tool provides a systematic exploration of possible futures within a given timeframe, through the likely combinations between hypotheses variables. Hypotheses’ probability presumption: Aims to identify the set of hypotheses most likely to occur in order to put together the possible prospective scenarios. It complements morphological analysis as it quantifies the probability of the occurrence of each set of hypothesis. Delphi: Based on the elaboration, submission and resubmission of a given questionnaire to a group of experts, thus allowing them to acknowledge the group’s collective opinion about a research problem. The consecutive rounds of responses also promote reflection on the individual respondents as they have access to the group’s general trends. As such, this technique verifies the degree of convergence/divergence of knowledge about a given set of hypotheses so they can be applied in the scenario building.

It is important to note that the stages and their tools are non exclusives as in some cases; they can be re-arranged or even excluded from the foresight research. The combination of stages, substages and their tools will depend on the theme, time available and resources, personnel, level of understanding of the tools, budgeting and other factors peculiar to the effort of foresight research.

INNOVATION PROCESS IN SCENARIO BUILDING: A NEW SERVICE FOR THE INDUSTRY Scenario building based on “prospective” helps players in acquiring relevant knowledge, competences and tools that allow them to raise the player’s foresight skills, which in turn fosters short-term innovation capability as well as increases competitive performance while adding value to the processes, products and services in the long run. Attesting to the innovation in the modusoperandi of scenario-building at FIEP, Table 5 gives one a comparison of methods anchored in the “prospective” for scenario-building. The last column is focuses on outlining the elements exclusive to FIEP’s model. FIEP’s model is the result of the significant improvement of other methods and is currently offered as a new service for the Paraná State Industrial base. Some testimonies of key stakeholders explicitly state innovations that were triggered in the industry. According to Mr. Yoshio Kawakami, President of Volvo Construction Equipment Brazil: “The research FIEP conducted via ODI/PR was surprising due to its ability to mobilize and coordinate strategic actions. The exercise significantly added value to the entire local automotive industry as it led to the establishment of the automotive engineering graduate program in Curitiba. This opportunity is beneficial to Volvo Brazil not only because it is increasing the professional growth of

319

Innovation in Scenario Building

Table 5. Stages and tools for scenario building Feature

Methods Godet

Schwartz

Grumbach

FIEP

Problem definition

Yes

Yes

Yes

Yes

Historical analysis

Yes

Yes

Yes

Yes

Description of present situation

Yes

Yes

Yes

Yes

Variable Identification

Yes

Yes

Yes

Yes

Stakeholder’s Identification

Yes

Yes

Yes

Yes

Consistency check

Yes

Yes

Yes

Yes

Multiple-variable hardship

Yes

Yes

Yes

Yes

Expert consultancy

Yes

Yes

Yes

Yes

Competitor behavior monitoring

No

No

No

Yes

Qualitative and quantitative variables

Yes

Qualitative

Qualitative

Yes

Detailed technical presentation

Yes

No

Yes

Yes

Cross-impact analysis

Yes

No

Yes

Yes

Delphi method

No

No

Yes

Yes

Probabilistic hierarchy

Yes

No

Yes

Yes

Managers’ mental map

No

Yes

Yes

Yes

Multiple exploratory scenarios

Yes

Yes

No

Yes

Strategy Board’s involvement with multiple chain competitors

No

No

No

Yes

Source: adapted from Marcial (1999) and the authors

its engineers, but also because it provides the same opportunity for many of its suppliers in specialized product development engineering services.” Mr. Alain Tissier of Renault Brazil’s executive management adds: “Such collective work could have never been done by my company’s strategic planning team, mostly due to the heavy workload needed and for not being able to mobilize that many key players […] there is no such service in the market. Scenario building is important for defining courses of action, and FIEP proved it has the know-how to pull it off. The result is that we now have input for our strategic planning. We dominate the market, but need more information from the external environment, which FIEP

320

was able to deliver through its scenarios. A good example is the variable that proxies hybrid-electric vehicle production for the year 2020 which will total 5% of the vehicle production. This is the sort of information that I cannot find nor buy in the market and was only possible through FIEP’s work […] it is an important parameter for defining new products by Renault.” As shown above, the stakeholder involved in the exercise is able to take advantage of the opportunities and benefits of the structural tendency analysis, better understand the industry and the individual organizations and assess the market’s future needs. Furthermore, the collective is able to anticipate the industry’s possible opportunities and threats, thus enabling faster and more robust responses to environmental changes. Another benefit would also be in the development of

Innovation in Scenario Building

raising and managing key information for the development of new products, services, concepts and business models.

CONCLUSION This foresight study can be seen as a methodology for building the future, which contributes to the conception and implementation of new economic development and innovation strategies for a country, region, organization, or as shown in this chapter, an industry or supply chain. Based on articulated and cooperative efforts, this kind of research encourages entrepreneurs to think about the relevance of future studies, prospective views, of medium and long-term planning as well as collective action, with the aim of achieving innovation and sustainable competitive advantage for firms, industries, local and national economic sectors. With the goal of strengthening the MRC’s automotive industry, the Federation of Industries of Paraná (FIEP), through ODI/PR, led a sector foresight project, a truly innovative service, aimed at adding to the industry’s development and creating new opportunities in the worldwide arena. The project took over two years of research with over 200 experts directly involved, including scholars, researchers, businessmen, managers and government agents. This initiative was a pioneer effort to bring together an industry known for its individuality and independence, focusing on collective thinking as a means for joint competitive gains. This exercise allowed for the comprehensive consolidation of the necessary methodological stages and sub-stages for a sector foresight study. In fact, it resulted in an innovative methodology for scenario building, as it requires an industry view as well as cooperative involvement of the industry’s players both in the process and results. Aside from that, tools that were suggested throughout literature were tested in the different study phases and were confirmed according to the particular industrial focus analysis. In short,

FIEP’s methodology consisted of 4 stages, 18 sub-stages in total and 9 different tools that could be replicated in studies for different industries. This methodological advancement works not only as means of raising the awareness of a given industry’s competitive global, regional and local environment, but also spurs the individual and group innovative responses towards critical uncertainties. Scenario building under the strategic “prospective” school developed by Michel Godet’s seminal papers (1993) was traditionally used by either enterprises or territories. By adding stakeholder’s governance as a neutral partner to legitimate scenario building for stakeholders and multiple research techniques, the foresight methodology was greatly inhanced allowing an entire industry to conduct its common strategic thinking in an innovative and collaborative way. This research contributed by proposing a methodological framework for “sector foresight”, which can hereafter be applied to other local industries as well as to other auto industries located in other regions and nations. The exercise promoted communication between the MRC’s automotive industry players, enabling collective thinking about the industry’s future as well as the building of the “most likely” and “desired” scenarios. The delivery of those consolidated scenarios is the main product offered to the industry, allowing the players to have a global view of the industry’s impacting variables and critical uncertainties. In turn, they can follow their own paths which best suit their desired future. Furthermore, the appropriation of this content allows for a clearer managerial view of the industry’s possible future. This overview allows technologies, products, processes and enterprises to be anticipated in a way that meets the necessary responses to future demands shown in the scenarios. Thus, the scenarios become the local managers’ decision making support platform as it offers premiere strategic information for all players in the industry.

321

Innovation in Scenario Building

The local automotive industry benefits from the communication channels now established through FIEP’s ODI/PR. The exchange and sharing of strategic information fosters innovation and innovative responses as it triggers anticipative intelligence and research as well as development engagement for the sector. As FIEP developed the most needed resources for this connection – know-how, credibility, trust, legitimacy and impartiality – an innovative service became available for the first time in Paraná State’s industry. This service can significantly contribute to the enhancement of the industry’s competitiveness - not only in products, but also services and processes. This new model that FIEP has developed has supported the industry by embedding this futuristic exercise in the player’s thinking patterns, an essential step for industrial innovation processes. The next stage of this research would be to monitor the variables at stake and the players’ repositioning, as they respond to the different scenarios or not. Those responses to variable shifts, competitive policies and institutionalized actions that interfere in the industry would ultimately result in feedback on how the players apply the knowledge that was transmitted by each strategic scenario. This is not only collectively, but also as to foster innovation in their companies and so continuing the scenario building exercise.

REFERENCES ACEA (2007). European Automotive Industry Report 07/08. Bruxelas: European Automobile Manufacturers Association. ANFAVEA. Anuário estatístico da indústria automobilística brasileira. ANFAVEA, 2007. (in portuguese) Banco Mundial. (2006) World Development Indicators. Retrieved Oct 07, 2008, from http://devdata.worldbank.org/ wdi2006/contents/ cover.htm

322

Banco Mundial. (2007). World Development Indicators. Washington: Banco Mundial. Bardin, L. (1977). Análise de Conteúdo. Lisboa: Edições 70. (in portuguese) BNDES. (1999) Pólos Automotivos Brasileiros. BNDES Setorial, Rio de Janeiro, n. 10, p. 173200, set. (in portuguese) BRASIL. Ministério do Trabalho e Emprego (TEM). (2006). Relação Anual de Informações Sociais (RAIS). Brasília. Série histórica disponível em CD pelo Ministério do Trabalho e do Emprego. (in portuguese) BRASIL. Ministério do Desenvolvimento, Indústria e Comércio Exterior (MDIC). Ministério do Desenvolvimento, 160 cenários da indústria automotiva: Região Metropolitana de Curitiba 2020 indústria e comércio. Série histórica estatística do fluxo de comércio internacional do Brasil. Retrieved Mar 10, 2008, from http://www.mdic. gov.br(in portuguese) Coates, J. (1985). Foresight in federal government policy making. Futures Research Quartely, 1, 29–53. Cristo, C. (2000). Programa brasileiro de prospectiva tecnológica–industrial, Secretaria de Tecnologia Industrial, Ministério do Desenvolvimento, Indústria e Comércio Exterior, Brasília. (in portuguese) European Automobile Manufacturers Association (ACEA). European Automobile Industry Report 07/08. Retrieved Mar 19, 2008, from http://www.acea.be/ images/uploads/ ind/ ind_0004.pdf do Petróleo, A. N., & Natural e Biocombustiveis, G. (2008). Anuário estatístico. Retrieved April 01, 2009, from http://www.anp.gov.br/ petro/ dados_estatisticos.asp. (in portuguese) dos Fabricates de Veículos Automotores, A. N. (ANFAVEA) (2007). Anuário da indústria automobilística brasileira. São Paulo. (in portuguese)

Innovation in Scenario Building

dos Fabricates de Veículos Automotores, A. N. (ANFAVEA) (2008). Anuário estatístico da Associação Nacional de Fabricantes de Veículos Automotivos. São Paulo, 2008. (in portuguese) Economics, L. (2006). Developments in car retailing and after-sales markets under Regulation no. 1400/2002. Brussels: European Commission. Godet, M. (1987). Scenarios and strategic management. London: Butterworths Scientific. Godet, M. (1993). From Antecipation to Action. Paris: Unesco. Godet, M. (1993). Manual de prospectiva estratégica: da antecipação a acção. Lisboa: Publicações Dom Quichiote. (in portuguese) Godet, M. (2000a). A Caixa de Ferramentas da Prospectiva Estratégica. Lisboa: CEPES. (in portuguese) Godet, M. (2000b). The Art of Scenarios and Strategic Planning: Tools and Pitfalls. Technological Forecasting and Social Change, 65, 3–22. doi:10.1016/S0040-1625(99)00120-1 Godet, M. (2001). Manuel de prospective stratégique 1: Une discipline intellectuelle. 2 ed. Paris: Dunod. (in french) Godet, M. (2004). Manuel de prospective stratégique 2: L’art et la méthode. 2 ed. Paris: Dunod. (in french) Grumbach, R. J. (1997). Prospectiva: a chave para o planejamento estratégico. Rio de Janeiro: Catau. (in portuguese) Hamel, G., & Prahalad, C. K. (1995). Competindo pelo futuro: estratégias inovadoras para obter o controle do seu setor e criar os mercados de amanhã. 3 ed. Rio de Janeiro: Campus. (in portuguese)

Horton, A. (1999). Foresight: how to do simply and successfully. Foresight, v. 1, n.1. Retrieved Ago 18, 2009, from http://www.ibge.gov.br/ home/presidencia/noticias/ noticia_visualiza. php?id_noticia=1330&id_pagina=1 ILO. Global employment trends: January 2008. Retrieved Set 09, 2009, from http://www.ilo.org/ wcmsp5/groups/public/ ---dgreports/---dcomm/ documents/ publication/wcms_090106.pdf Instituto Brasileiro de Geografia e Estatística (IBGE). Censo demográfico 2000. Disponível em . Acesso em: 10 mar. 2008. (in portuguese) Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Industrial Anual (PIA). Retrieved Mar 10, 2008, from http://www.ibge.gov. br(in portuguese) Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Industrial Anual: empresa. Série Relatórios Metodológicos do IBGE, n. 26. Retrieved Oct 07, 2008, from http://www.ibge. gov.br(in portuguese) Instituto Brasileiro de Geografia e Estatística (IBGE). Projeção de população. Retrieved Abril 01, 2009, from http://www.ibge.gov.br/ home/ estatistica/populacao/ projecao_da_populacao/2008/ default.shtm(in portuguese) Instituto Euvaldo Lodi. Núcleo Central (IEL/ NC). (2009) Dinâmicas e tendências do setor automotivo: Região Metropolitana de Curitiba. Brasília: IEL/NC. (in portuguese) Instituto Euvaldo Lodi. Núcleo Central (IEL/ NC). (2009) Estudos de futuro setoriais: guia metodológico. Brasília: IEL/NC. (in portuguese) Instituto Euvaldo Lodi. Núcleo Central (IEL/NC). (2009) Estudos de futuro setoriais para a indústria brasileira. Brasília: IEL/NC. (in portuguese)

323

Innovation in Scenario Building

Instituto Paranaense de Desenvolvimento Econômico e Social (IPARDES). (2005). Arranjo automotivo da Região Metropolitana Sul: Curitiba no Estado do Paraná. Curitiba. (in portuguese) International Organization of Motor Vehicle Manufacturers (OICA). Site. Retrieved Oct 07, 2008, from http://www.oica.net/ IPEADATA. Série histórica do sistema de contas nacionais disponibilizada pelo Instituto Brasileiro de Geografia e Estatística. Retrieved Mar 10, 2008, from http://www.ipeadata.gov.br(in portuguese) Japan Automobile Manufacturers Association (JAMA). The Motor Industry of Japan2007. Japan, 88 p. Retrieved Mar 14, 2008, from http:// www.jama-english.jp/ publications/MIJ2007.pdf Marical, E. C. (1999). Aplicação de Metodologia de Cenários no Bando do Brasil no Contexto da Inteligência Competitiva. Dissertação de Mestrado, Université de Droite et des Sciences d’aix, Marseille, France. (in portuguese) Martin, B. R., Anderson, J., & Maclean, M. (1998). Identifying research priorities in public-sector funding agencies: mapping science outputs onto user needs. Technology Analysis and Strategic Management, 10, (n.d.). Porter, M. E. (1989). Vantagem competitiva: criando e sustentando um desempenho superior. Rio de Janeiro: Campus. (in portuguese) PWC. (2007). Global Automotive Financial Review – Industry Outlook: A Focus on BRIC. PricewaterHouseCoopers, 2006. Disponível em: Office of Aerospace and Automotive Industries, U.S. Department of Commerce: The Road Ahead for the U. Washington: S. Auto Market. Rattner, H. (1979). Estudos de futuro: introdução à antecipação tecnológica e social. Rio de Janeiro: FGV. (in portuguese)

324

Receita Federal do Brasil. Arrecadação ano base2008. Retrieved Abril 01, 2009, from http:// www.receita.fazenda. gov.br/ Arrecadacao/ default.htm(in portuguese) Ringland, G. (1998). Scenario Planning: Managing for the Future. Chichester: John Wiley & Sons. Schoemaker, P. J. H. (1993). Multiple Scenario Development: Its Conceptual and BehavioralFoundation. Strategic Management Journal, 14, 193–213. doi:10.1002/smj.4250140304 Schoemaker, P. J. H. (1995). Scenario Planning: a Tool for Strategic Thinking. Sloan Management Review, winter, p.25-40. Schoemaker, P. J. H., Heidjen, C. A. J. M., & van der,. (May. (1992, June). Integrating scenarios into strategic planning at Royal Dutch Shell. Planning Review, 20, 41–46. Schwartz, P. (2000). A Arte da Visão de Longo Prazo. São Paulo: Nova Cultural. (in portuguese) SENAI. (2010). Estudos de Futuro Setoriais: Guia Metodológico. Curitiba: SENAI. (in portuguese) Simpson, D. G. (May/ June 1992). Key lessons for adopting scenario planning in diversified companies. Planning Review. p. 10-17. Sindicato Nacional da Indústria de Componentes para Veículos Automotores. (SINDIPEÇAS.). Site. Retrieved Oct 07, 2008, from http://www. sindipecas.org.br(in portuguese) Sistema Federação das Indústrias do Estado do Paraná (FIEP). FIEP - Federação das Indústrias do Estado do Paraná. Retrieved Jul 10, 2010, from http://www.fiepr.org.br/ FreeComponent9437content68759.shtml(in portuguese) United States Department of Labour. Productivity report2008. Retrieved Abril 01, 2009, from http:// www.bls.gov/ data/ #productivity

Innovation in Scenario Building

VDA. (2007). VDA: Annual Report 2007. Frankfurt am Main: Verband der Automobilindustrie e. V. (VDA). Retrieved Jun 03, 2009, from http:// www.vda.de Verband der Automobilindustrie (VDA). (2007). Auto Annual Report, 2007. Frankfurt, 232p. Retrieved Mar 14, 2008, from http://www.vda.de/ en/ service/ jahresbericht/ files/VDA_2007_en.pdf Vergara, S. C. (2005).Métodos de pesquisa em administração. São Paulo: Atlas. (in portuguese) WBCSD. (2004). WBCSD: Mobilitity Report 2030: Meeting the Challenges to Sustainability. Hertordshire, England. Yin, R. K. (2001). Estudo de caso: planejamento e métodos. 2. ed. Porto Alegre: Bookman. (in portuguese)

KEY TERMS AND DEFINITIONS Automotive Industry: The industrial chain that covers everything from project, engineering, assembly and distribution of new passenger and commercial road vehicles, its parts and pieces, as well as its sales and maintenance-related services. Foresight: Methodology to collect and assess expert opinions about the future from the public and private sectors, universities and research centers, through a structured, interactive, participative, coordinated and synergistic process (Godet, 2001). It is used to build strategic views that can spur competitiveness and the development of a

country, territory, company, public institution, industrial sector or a productive chain. Innovation: An organization’s process of applying an idea or invention and successfully taking it into its practice or to its market. Prospective Scenarios: Alternatives futures or “tales” about possible future outcomes of a given system built according to Godet’s “prospective” methodology (GODET; 1993, 2001). Scenario Building: A systematic procedure to detect trends and identify the social forces that could alter them (Rattner, 1979); a process for long-range views in a world of great uncertainty, leading to a broader view of the external environment (Schwartz, 2000). Strategic Planning: An organization’s structured process for taking relevant and sometimes irreversible action in anticipation or in response to its competitive environment as well as for assessing its actions vis-à-vis its very existence. Trend Analysis: Collection and assessment of quantitative and/or qualitative historic data in attempt to establish patterns or behaviors as means to establish possible forward-looking outcomes.

ENDNOTES 1



2



TIER: term used by the automotive industry to determine the place in the chain occupied by a certain industry. The project’s goal was presented and validated by the MRC automotive industry Strategy Board, which was formed afterwards.

325

Section 4

Knowledge Management and Innovation

327

Chapter 18

Toward a More Pragmatic Knowledge Management: Toyota’s Experiences in Advancing Innovation Steven Cavaleri Central Connecticut State University, USA

ABSTRACT Managers often conceive knowledge management processes in ways that unduly limit its potential. Toyota has avoided falling into this narrow paradigm trap by creating its own version of knowledge management that is well suited to its culture. They have woven their knowledge management strategy together with process improvement and innovation methods. Toyota’s knowledge management system is a theoretically sound, yet practical, business approach built on a set of scientific principles based on a philosophy known as Pragmatism. This chapter examines how Pragmatic principles used by Toyota can achieve superior innovation results. The chapter concludes by explaining why the Pragmatic approach delivers superior performance at lower cost than conventional knowledge management methods.

INTRODUCTION Some researchers see organizational innovation as a product of individual skills, such as creativity and imagination. Conventional wisdom regards it as being an art, not a science. Still others, such DOI: 10.4018/978-1-61350-165-8.ch018

as many management theorists, regard innovation as being the organizational outcome of a properly designed business strategy. In their eyes, strategy becomes the activator of predictable organizational processes where ‘B’ follows ‘A’ - as if a clockwork. They envision a tightly controlled system capable of driving innovative ideas through a pipeline

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Toward a More Pragmatic Knowledge Management

flowing through various phases of development toward an outcome - releasing a product or service to market. For example, Bacon and Butler (1998:11) define innovation as a commercially successful use of invention, and invention as being a “solution to a problem (unmet needs)”. Similarly, Davila et al (2006), propose that innovation IS a management process – one requiring specific tools, rules, and discipline. This chapter’s purpose is to explore an alternate paradigm for innovation. It suggests a strategy based in the logic of scientific reasoning and experimentation. Specifically, this alternative spurs innovation by radically improving the quality of knowledge held by an organization’s members. Its theoretical basis is a system designed to improve the quality of scientific discoveries known as Pragmatism. Pragmatism’s founder, scientist Charles Sanders Peirce, set forth a number of principles for being pragmatic in improving the effectiveness of one’s action. Many management theories, such as Total Quality Management, incorporate pragmatic principles. Peirce’s (1958:293) approach to scientific discovery begins with the pragmatic maxim that holds we should always, “Consider what effects, that might conceivably have practical bearings, we conceive the object of our conception to have. Then, our conception of these effects is the whole of our conception of the object.” This maxim is the basis for an innovation strategy that focuses on conducting frequent mini-experiments throughout an organization. For example, Spear (2009:215) cites an example of how plant-floor workers at Aisin−a first-tier supplier for Toyota – routinely use such an experimental approach to improving the quality of their common knowledge. “Problem solving is done in a disciplined fashion. Assumptions about cause and effect are made explicit and stated clearly, then they are tested in

328

rigorous fashion so improvement efforts both make processes better and deepen process knowledge.” To Peirce, the key to creating high quality knowledge is through rigorous experimentation and the integrated application of three types of inferential reasoning, namely deduction, induction, and abduction. Abduction produces radical insights of the sort that companies seek for gaining competitive advantage. The chapter proposes an innovation strategy based on pragmatic principles designed to leverage the power of abductive reasoning (Wiener, 1958). Toyota is one of the leading companies in both applying pragmatic principles for increasing knowledge quality, experimentation, and innovation. This chapter examines Toyota’s methods for increasing knowledge quality and innovation and their origins in pragmatic philosophy.

WHAT IS INNOVATION? What is innovation? Research by Baregheh (2009:1334) found the term innovation describes, “the multi-stage process whereby organizations transform ideas into new/ improved products, service or processes, in order to advance, compete and differentiate themselves successfully in their marketplace.” By contrast, such flow-oriented definitions oppose those that focus on identifying the sources of knowledge necessary to produce innovations. For example, scholars, such as Peirce and noted economist Joseph Schumpeter (1950), view knowledge as being the primary force behind innovation. Peirce’s main interest in studying knowledge was in discovering how it drives processes of scientific discovery, whereas Schumpeter’s primary interest was in how knowledge influences the entrepreneurial economic potential of a firm. Peirce studied how scientists conduct research and how their methods lead to breakthrough innovations. He concluded that scientific innovations often happen suddenly, but

Toward a More Pragmatic Knowledge Management

usually occur after prolonged periods of analysis and many experiences. A surprising find was that these scientists often employed a special type of reasoning called abduction to achieve these radical innovations. The process of abductive inferential reasoning builds on conclusions gained from extensive analysis followed by a period of rearranging perceived facts in the minds of the scientist. Burks (1946) interprets Peirce’s claims about abduction’s power to drive innovation as depending on two key elements. First, abduction relies on inferences taken from a body of data used to explain prior hypotheses, and second, in contrast to inductive methods of testing hypotheses, abduction provides a way of discovering new, broader, hypotheses. Martin (2009) interprets abduction as being a synthetic way of thinking that integrates many of the lessons of experimentation into new ideas of what might be possible. He concludes that synthetic thinking can fuel innovations in firms, such as new products like Research in Motion’s Blackberry communications device. Peirce’s approach to innovation is very systematic. It views innovations as resulting from a combination of extensive analysis and experience, followed by abduction, synthesis and breakthrough. He proposes, “abductive suggestion comes to us like a flash. It is an act of insight, although extremely fallible insight. It is true that the different elements of the hypothesis were in our minds before; but it is the idea of putting together what we had never before dreamed of putting together which flashes the new suggestion before our contemplation.” (Peirce, 1988:227) In other words, innovation is the result of a kind of mental

synthesis that rearranges previously diverse ideas now joined together. While Pragmatic analysis alone does not stimulate radical innovation, it sets the stage for the abductive process where breakthrough discoveries are often the result. Today, many organizational processes such as Total Quality Management, strategic management, KM and innovation, include pragmatic principles in their designs. Peirce wrote over forty volumes dedicated to presenting his core principle that innovation was mainly a scientific process resulting from integrating three different types of scientific reasoning that conclude in abduction. These three types of logic include (1) Deduction; (2) Induction; and (3) Abduction. Each of these types of logic enable decision-makers to draw inferences from evidence gained observation and experience. Management processes employ one of more of these types of reasoning. Ideally, these forms of reasoning become part of an integrated whole system and used together. (Table 1) Each of the first three methods listed focus on one type of inferential reasoning, whereas 5-Point Dynamic Mapping (Cavaleri & Seivert, 2005) is an integrative strategic management process designed to improve the quality of shared knowledge in an organization. By using scientific reasoning in an integrative manner, it progressively reveals the mechanisms by which actions produce expected effects under specific conditions. This is not only a scientific way of achieving expected outcomes it is also sets the stage for enabling knowledge to be created and improved.

Table 1. Approaches and forms of scientific reasoning APPROACH

TYPE OF LOGIC

PROCESS

THEORIST(S)

Total Quality Mgmt.

Deduction

Control

Deming

Quality Improvement

Induction

Policy Making

Firestone & McElroy

Research & Develop.

Abduction

Innovation

Martin

Strategic Management

Integrative

Planning

Cavaleri & Seivert

329

Toward a More Pragmatic Knowledge Management

THEORETICAL BACKGROUND Pragmatism relies on the scientific method to drive the process of experimentation necessary to improve the quality of knowledge. The founder of the discipline of knowledge management, Karl Wiig (2004:213) sets forth four basic premises as the foundations of modern knowledge management. (1) Knowledge is the primary driver of enterprise performance; (2) Knowledge affects performance through people; (3) Effective Knowledge Management must be people-focused; and (4) Personal knowledge effectiveness. He concludes that in doing knowledge management “we must facilitate and strengthen the knowledge-related processes, activities, and practices that make it possible for people and organizational entities to make effective actions.” Some knowledge management advocates claim that information technologies should be the focus of KM initiatives. Yet, there is little evidence to support the effectiveness of such technologies in the types of business environments where knowledge management is most important – complex, dynamic ones. (Malhotra, 2005) Stewart (2002) also questions the effectiveness of technology-enabled KM approaches, noting they neglect to ask ‘what knowledge should be managed and toward what end?’ Firestone and McElroy (2005) argue that it is moot to seek a precise meaning of the term ‘knowledge management’ and more important seek the answer to question - Has KM has ever actually been done? They argue that unless KM is formulated using clear, non-contradictory ideas, it is impossible to lay any claims to its effectiveness or value. They see KM more simply as being a set of processes designed to enhance an organization’s present pattern of knowledge processing to improve organizational outcomes. Fahey and Prusak (1998) have voiced a similar skepticism about the way KM has been defined expressed as what they term the ‘eleven deadly sins of KM’. Pragmatic KM’s focus is on managing knowledge processes to improve the quality of knowl-

330

edge in organizations. Knowledge processes are the task-focused social interactions among team members designed to formulate, evaluate, and validate knowledge claims. (Firestone & McElroy, 2003) Knowledge claims are conjectures, assertions, arguments, or theories proposing which action are most likely to lead to expected states of affairs. Here, knowledge is, reiteratively, improved and refined, over time, through many cycles of experimentation. Experimentation means not only taking new actions, but also looking at the same situation through new eyes, and interpreting performance feedback differently. To the pragmatic manager, knowledge is a storehouse of rules for actions under various specific situations to achieve an expected outcome. Simply, knowledge is a type of contingency plan for action that is based upon on a set of situational cues and lessons learnt from experiences. Due the apparent fallibility of knowledge, it requires continuous improvement and validation to increase its value in generating effective action. Over time, knowledge’s main use is to solve problems and its effects become the basis for conclusions about the value of that knowledge. It becomes iteratively refined through the lessons learnt during these problem-solving episodes. This is a hallmark of Toyota’s approach to KM. Knowledge is continuously improved based on lessons learned from its application in various problem solving initiatives throughout the company. Firestone and McElroy (2003) propose that knowledge matures over the course of a knowledge life cycle when organizations take systematic steps to improve knowledge quality. Improvements in knowledge quality also owe to the continuous problem solving processes used to drive knowledge processes. Unlike conventional KM approaches used to supply knowledge to workers based on its availability, pragmatic KM employs what McElroy (2003: xxiv) terms supply-side knowledge management. This stands in contrast to demand-side KM which “instead of focusing on the supply of existing knowledge to a workforce, seeks

Toward a More Pragmatic Knowledge Management

instead to enhance their capacity to produce it.” Firestone and McElroy designed their Knowledge Life Cycle model of knowledge management in a manner that “owes much to Karl Popper’s ideas on problem solving (1972, 1994) and the role of problems: detecting them (while engaged in business processing), arriving at tentative solutions (knowledge claim formulation), and performing error elimination (knowledge claim evaluation) to produce knowledge.” (2003: 197) The Life Cycle KM approach is significant for many reasons, but most importantly, it improves both the quality of knowledge and rate of innovation in organizations. Such developmental knowledge strategies have significant advantages over conventional static KM strategies due to their impetus to continuous improvement in the quality of knowledge that results from its use. The essence of the Life Cycle KM approach is the formulation, evaluation, and validation of knowledge claims by subjecting them to the scrutiny of subject matter experts within the team or organization. Each time a problem emerges, it becomes viewed as being an experiment to select the potentially most effective course of action and study its effects for future codification. At Toyota, this becomes a self-organizing process where potentially interested workers, from around the company, receive invitations to view how a problem is being addressed -- so they may participate in problem solving and learn. In the true spirit of pragmatic knowledge processing, it is not sufficient to solve the problem, the quality of knowledge needs improvement too. Spear (2009:217) cites an example at the Toyota Supplier Support Center where a problem-solving team had solved a problem by getting better-than-expected results, yet failed in terms of learning outcomes. “It was true they had succeeded, but not completely. Yes, they had made the changeover process much better than it had been. Their shortcoming was not that they had failed to reduce the changeover further. It was that they had failed to learn from reducing it further.”

Toyota is one of the most highly effective knowledge management and innovation-based companies in the world. Even though Toyota has often received the MAKE Award as one of the best KM companies in the world, it rarely ever uses the term ‘knowledge management’ in its literature. One of the features of Toyota’s strategy is the pragmatic methods it uses for driving knowledge and innovation. This formula for innovation did not occur merely as the result of happenstance. Nearly half a century ago, Toyota’s leaders learned about a scientific approach to operating a company based on pragmatic principles from quality guru W. Edwards Deming. Deming’s system not only emphasized continuous improvement in quality, it also taught the value of knowledge and learning for innovation. Toyota has seamlessly interwoven knowledge processes directly into its business processes and systemic problem-solving initiatives. Designing work this way not only amplifies the value of existing improvement processes, such as TQM, but it also improves the quality of shared knowledge within the company. Why do such knowledge-based processes work so well at Toyota? The core of the Toyota’s high-performing knowledge-based system is a highly interactive collective form of scientific experimentation based upon the tenets of Pragmatism. The implications of adopting such a comprehensive organizationwide strategy in business and commerce are indeed profound.

CASE: TOYOTA’S PRAGMATIC KNOWLEDGE MANAGEMENT SYSTEM Management scholars, such as Liker (2004) have closely studied Toyota, yet despite this extensive analysis, the theoretical sources of many of the improvement principles were relatively unknown. The founder of the famed Toyota Production System, Taiichi Ohno (1978) attributes many of the core ideas used in the framework to Henry

331

Toward a More Pragmatic Knowledge Management

Ford. On the other hand, various members of the founding Toyoda family have credited the influence of the founder of the Total Quality Management (TQM) approach, W. Edwards Deming, with having a major impact in shaping the company. Today, there is little doubt that many of the pragmatic principles, first advocated by Deming, now play an important role in innovation processes at Toyota. However, less obvious is the influence of Deming’s teachings on the firm’s structured approach to scientific experimentation and leveraging knowledge gained for improving business performance. MIT researcher, Steven Spear, describes Toyota’s approach to scientific experimentation in these terms, consider what the Toyota people are attempting to accomplish. They are saying before you (or you all) do work, make clear what you expect to happen (by specifying the design), each time you do work, see that what you expected has actually occurred (by testing with each use), and when there is a difference between what had actually happened and what was predicted, solve problems while the information is still fresh. (Johnston, 2001) Near the end of his life, Deming wrote about the importance to companies of developing profound knowledge of how their improvement systems operate. What is far less well known is that Deming’s views were derivatives of Peirce’s Pragmatism. Some scholars, such as Towns, (1997) have argued that Deming himself was a Pragmatist who employed the pragmatic framework as a practical tool for effecting change in organizations. Similarly, Barton (1999) notes “a set of touchstones exist which allow us to interpret systems and systems thinking in terms of Peirce’s pragmatism. (p. 7). Pragmatism, at its very core, is an approach that employs the scientific method to determine the possible future effects of actions to taken by understanding how past actions have produced particular outcomes. Pragmatism embraces the scientific method of inquiry toward improving the quality of knowledge-in-use in firms. Its methods ask managers to pay careful

332

attention to understanding the mechanisms that enable their actions to produce effects. Over time, such analysis not only improves the quality of knowledge available for use in the organization, but it also prompts innovation. The Global MAKE (Most Admired Knowledge Enterprises) Award Hall of Fame has honored Toyota as one of the top twenty-six Knowledge Management firms in the world. Yet, Toyota executives rarely have used the term knowledge management. Toyota’s leaders have avoided using the types of KM techniques that are so popular in the Western countries, in favor of building their own custom knowledge-centric processes. Doing so enables them to interface seamlessly with its internal business and improvement processes. Toyota’s most well known knowledge-based approach is its yokoten system. Yokoten is Toyota’s way of propagating new ideas and promoting improvement in other past of the company in conjunction with its quality, Lean, and problem solving approach. Toyota’s approach to KM is essentially a pragmatic one. What makes it pragmatic? At it simplest, yokoten follows many of the same principles of kaizen, such as a mindset based on experimentalism, and the focus on causal analysis found in TQM. Pragmatism employs the scientific method to the question: How do we make actions more effective? Is it coincidental that Toyota’s approach to KM originates in the same philosophical doctrine as its quality improvement process? MIT professor Steven Spear (2004:7) spent many years observing Toyota’s workers and production systems in operation at various plants in Japan and the United States. He discovered at the core of Toyota’s vaunted Production System is a single-minded drive to engage in continuous rigorous scientific experimentation. “At Toyota, the focus is on many quick simple experiments rather than on a few complex lengthy ones. This is precisely that Toyota workers practice process improvement. They cannot “practice” making change, because a change can only be made once.

Toward a More Pragmatic Knowledge Management

But, they can practice the process of observing and testing many times.” These are essential ingredients in Toyota’s yokoten system that integrates problem solving with knowledge management. Toyota’s yokoten system focuses on creating and sharing knowledge that arises during problem solving initiatives. This focus on creating knowledge applied in problem solving initiatives is an example of what McElroy (2003) calls demand-side KM in action. Liker (2008:164) explains yokoten as being not merely a way of communicating or sharing best practices. Rather, it is a way to engage in collective problem solving and use the resulting innovations to propagate even more innovations in other parts of the company. He distinguishes yokoten from conventional ways of sharing best practices by tracing the origins of yokoten. Toyota takes an organic, non-mechanical, view of it business. “It is not just ‘go, see and then copy’. For Toyota, it is ‘go, see, and improve upon.’” Inside Toyota, the backbone of the improvement process is a self-organizing collective problem solving process. Their justification for investing heavily in problem solving initiatives is that there are significant cost savings from eliminating the effects of problems before they become deeper and more widespread in their influence on performance. A key tenet of the Toyota system is that everyone has two jobs, first to perform a specific set of tasks, and secondly, to improve the job. The reason for employing this approach is deeply rooted in Toyota’s culture. The company’s focus on kaizen and continuous improvement is well known, but a more fundamental philosophy embedded in the fabric of Toyota’s culture is the belief people can never know in detail what will happen in the future. (Liker 2008:154) Consequently, the chief priority of managers is the training of operational employees in the techniques of problem solving to address unexpected problems that result from unforeseen changes in the organization before they become serious issues. This approach exemplifies Firestone and McElroy’s Life Cycle knowledge-processing methods discussed earlier

in this chapter. The intellectual roots of this approach originated in Charles Peirce’s notion of a community of committed inquirers first conceived over a century ago. At Toyota, identifying problems is more often the result of continuous reiterative problems solving and learning cycles. Research on Toyota’s problem solving approach by Spear & Bowen (1999:103) finds “…all managers are expected to be able to all jobs of everyone they supervise and also teach their workers how to solve problems according to the scientific method.” This is a systematic approach to concurrently both produce products and find problems. This process may seem inefficient to some, but it promises many benefits including reducing costs, and spurring innovation. Toyota’s approach stands in bold contrast to conventional Western manufacturing strategies. Critics wrongly assume its collaborative organic nature is inefficient because the focus on cost-reduction is indirect. In conventional mechanical production systems there is little actual learning, knowledge, or innovation that results among operators from running the system. By contrast, Toyota designs all of its training, problem solving, and improvement initiatives to interface seamlessly with yokoten processes. This is feasible due to using the same conceptual framework of pragmatic principles. (Fearon and Cavaleri: 2006) The yokoten process is simple. After identifying a problem, other employees throughout the plant receive a signal that a particular issue holding potential interest for them has surfaced. Then, the problem solvers send a brief description of the problem to all interested parties throughout the company. They are then invited to ‘come, look, and see’ the problem and to participate in the ongoing efforts to solve it. The ‘visiting’ co-workers can contribute their own insights to the problemssolving process as well as they may take away what lessons may be learned from the dialogues with their fellow problem solvers. This type of swarming activity attracts those other organization members who feel they may have something

333

Toward a More Pragmatic Knowledge Management

to learn and gain from participating in the problem solving effort because it may benefit them eventually. In accord with pragmatic principles, knowledge exists in a problem-focused context where the chief questions that arise focus on the design of the experiment to take place before the eyes of the workers and how they will measure the quality of their knowledge. This is a quite different approach from standard forms of KM in which various information technology systems send ‘information’ to employees – whether they perceive it may hold any value for them in solving problems they face. At Toyota, the shared culture supports simultaneous efforts to improve people, processes, and competitiveness as part of a complex system. In a long-term study of numerous Toyota plants, Spear & Bowen (1999: 103) found “All of the organizations we studied are managed according to the Toyota Production System and share an overarching belief that are people are the most significant asset and that investments in knowledge and skills are necessary to build competitiveness.” Further, leading, learning, and problem solving at Toyota are all what Spear (2009) calls ‘high velocity skills’. He notes that Toyota is one of a number of high velocity organizations able to differentiate and gain sustainable performance advantages by nurturing superior improvement, innovation, and invention processes. At Toyota, work is an ongoing experiment that, over time, yields accumulations of knowledge capable of driving innovation. Toyota goes to extreme lengths to design its experiments. It starts by establishing its control variables. They do this by specifying the exact processes with little room for variation in performing tasks. They set up rigid standards at the outset introducing a high level of standardization. This standardization often takes the form of following what is termed The Toyota Way (Liker, 2004) of doing things. The purpose of making such extreme prescriptions for work is not as a means to create a lock-step production system. Rather, it is to facilitate the process of experimentation by aiding problem

334

solvers in isolating causes of problems. The logic is simple – the fewer unknown variables, the simpler to isolate the causes of variation. While such a way of doing business may seem impractical, its pragmatic knowledge improvement value is subtle, yet critical. Let us revisit Spear’s example taken from the Toyota Supplier Support Center. The problem-solving team forgot its dual mission to improve both performance and the quality of knowledge. In Spear’s (2009:218) words, “Thus in falling short, they not only missed their target but missed the chance to push further to understand factors they had assumed to be true but that their experience had proved to be false. The process had gotten better, but their understanding of it had not improved as much as much as it might have had they made clear their expectations at the start and the assumptions underpinning them, thereby having something tangible to investigate when those assumptions were proven false.” Toyota provides the most visible instantiation of what a company looks like when it follows Pragmatic knowledge-based principles, and is deserving of further evaluation by scholars and practitioners alike.

KNOWLEDGE MANAGEMENT AND INNOVATION It is ironic that business leaders tend to perceive their ways of managing to be pragmatic when in fact they are far from it. This owes to the common misconception of being pragmatic as being goal-oriented rather than being scientific and experimental. Pragmatic business strategies include fundamental elements, such as abductive reasoning, inquiry, knowledge processing, experimentalism, and formal systems to improve the quality of learning and knowledge. At minimum, transforming business strategies toward being more pragmatic provides companies with a relatively simple way to boost innovation by improving the quality of shared knowledge within

Toward a More Pragmatic Knowledge Management

the firm. Haner (2002) proposes that innovation initiatives can produce varying levels of quality in innovation within a firm – depending on the expertise exercised in managing the effort. All innovations are not equal quality. Similarly, the conventional wisdom holds knowledge as being all of the same quality. It is axiomatic that breakthrough innovations can reliably flow from low quality knowledge. While leading economists, such as Nelson and Winter (2002), acknowledge the relevance and importance of organizational knowledge to the innovation process, they fail to define the specific mechanisms by which knowledge converts to innovation. Without recognizing the relevance of knowledge quality to the innovation process, many companies enthusiastically allocate significant resources to sharing low-quality knowledge. Low-quality knowledge imposes unnecessary limits on firms. Yet, such oversights are probable when firms do not have systems in place to evaluate the quality of knowledge-in-use. These oversights are traceable to the operational definition of the terms knowledge or knowledge management in use today. If managers assume knowledge and information are equal, then there is no need to be concerned about the issue of knowledge quality. This is because information is of singular quality in their minds. On the other hand, philosophers, such as Plato, Socrates, Dewey, Peirce, Popper, and Quine argue that all knowledge is fallible. If the knowledge were infallible then it could is considered a being truth rather than knowledge. Popper’s (1945) theory of fallibilism outlines an epistemology proposing that all knowledge is capable of containing errors. One means of identifying errors and improving knowledge quality is by using the Life Cycle Model of Firestone and McElroy, 2005. Here, innovation is the natural outcome of ongoing efforts to improve the quality of knowledge where it is both a cause of performance improvement efforts, and its effect. This is a con-

tinuous, incremental, knowledge-based approach where innovation breakthroughs result from the accumulation of scientific knowledge acquired over time. While this approach is compatible with the general economic theories laid out by notable economists, such as Schumpeter (1950) and Nelson and Winter (2002), it runs contrary to many of the popular management-oriented theories of innovation proposed by thought leaders, such as Burgelman (1983), Christensen, (2003), Von Hippel (1998), and Utterback (1996). These management-driven theories of innovation often ignore the critical role played by knowledge and knowledge processing in achieving breakthrough innovations. By contrast, Pragmatic theories of performance improvement advocate for ongoing experimentation and learning from experience as a means to heighten the organizations capacity for adaptation. How do Pragmatic knowledge management and innovation approaches actually work? Martin (2009) argues against overreliance on traditional measures of business success, and for the value of using abductive logic in developing new products and companies. He notes, While Motorola was projecting future sales volumes of “feature phones,” Mike Lazaridis, founder of Research in Motion, was imagining what executive life would be like if you could receive your emails on a handheld device. How compelling would an ordinary phone be if you could have a BlackBerry attached to your belt? He couldn’t “prove” that this would be a good idea. There was no data on the demand patterns for smartphones, because smartphones existed only in his imagination. But a mere 11 years after the launch of the product of his imagination, RIM leads Motorola by an ever-accelerating margin in sales, market share and profitability. Long ago, Peirce coined a term for the thinking that Lazaridis used to create the BlackBerry: abductive logic. Martin (2010)

335

Toward a More Pragmatic Knowledge Management

COMPLEXITY AND PRAGMATIC KNOWLEDGE MANAGEMENT Research by Sterman (1994) suggests that people’s capabilities of learning through experience diminish as the result of a variety of cognitive and perceptual limitations that exist within complex systems. These factors often render human problem solving capabilities ineffective. In a world defined by high levels of dynamic complexity, even the smartest leaders are incapable of accurately predicting the effects on performance of the strategies and policies they formulate. The forces of bounded rationality are often too strong to simply permit effective management by relying on conventional methods of managing (Simon, 1991).Yet, despite the limits on the cognitive processing abilities imposed on all executives by these forces, there is a general reluctance to even consider the possibility that limits exist. Executives often become skillfully unaware of their own inability to simulate solutions to complex problems in their minds. They prefer to try solving the wicked problems they face by simplifying them into ever-smaller components through a process of rational analysis. This strategy of reducing complex problems to their elements to find causes tends to produce more unintended consequences than the number of problems it resolves. Sterman (1989) studied the effects on managers and MBA students asked to play a computerized business simulation that incorporated delayed feedback of the effects produced by decisions the players made. The lengths of the feedback delays were comparable to those found in a low-moderate complexity business environment. The length of the feedback delay significantly reduced the game player’s performance in the simulation. In real life situations, unexpected ambiguities amplifying the complexities of learning from experience. Interpreting the exact meaning of feedback and in predicting its implications of for future performance becomes confounding for workers. In sum, the effects of delayed, confounding, and ambiguous feedback

336

comingle to create a dangerous soup of misperceptions with great potential to cause managers to misfire in making decisions -- even in less complex dynamic systems. When the limits of bounded rationality on decision making by managers are well understood it becomes clear that even the smartest of managers struggle to discern optimal strategies in a dynamically complex environment. Given the ubiquitous effects of bounded rationality and dynamic complexity, the importance of creating high quality knowledge, learning rich lessons from experience, and experimenting in systematic way is greater than ever. Designing knowledge management systems around the use of pragmatic principles promotes reflection, inquiry, and ways to improve the quality of knowledge in an organization. Alternately, an organizational culture rooted in a shared understanding of the value of experimentation driven by continuous learning, discovery, and innovation is likely to pay dividends for many organizations. Pragmatism provides managers with a scientific conceptual framework to guide their efforts to create and improve knowledge for innovation. One of the core tenets of Pragmatism is that the quality of knowledge improves directly in proportion to the level of insight gained from understanding the cause-effect mechanisms produce outcomes from actions. Pragmatic analysis studies how gaps between expectations and results trigger the inquiry process. Inquiry is a search for new solutions to improve performance and seeks to settle doubt over how future actions can generate desired results. Inquiry also opens the possibility of reconsidering the validity of gained through prior experiences. This sort of analytical process uses unexpected performance to evaluate the reliability and trustworthiness of the knowledgein-use at any point in time. This is one element of the double-loop learning process described by Pragmatic theorists, such as Argyris (1990) and Schon (1983). Double-loop learning is a process designed to reevaluate the validity of operative knowledge by contrasting past performance with

Toward a More Pragmatic Knowledge Management

expected results. This type of action learning ultimately depends on replacing or improving current knowledge. Ideally, the goal is to align such knowledge more closely with one’s expectations. In complex situations, where cause and effect are difficult to discern, the capacity to improve knowledge, beliefs, and assumptions becomes the fuel that drives adaptation, innovation, and other forms of intelligent action. Schon (1983:50) views simple technical rationality as being insufficient for solving the sort of complex problems faced today by professionals. “Once we put aside the model of Technical Rationality, which leads us to think of intelligent practice as an application of knowledge to instrumental decisions, there is nothing strange about the idea that a kind of knowing is inherent in intelligent action.” Above all, Pragmatism is a science for driving innovation by increasing the level of intelligence embedded in actions – thus increasing effectiveness. There is no intelligent action without reflection. At Toyota, the process of reflection receives much more attention than in most companies. Toyota’s 14th and final principle is to become a learning organization through relentless reflection (hansei) and continuous improvement (kaizen). Liker, (2004:251) studied Toyota extensively and notes that at Toyota reflection and learning drive innovation. “I believe Toyota is the best learning organization. The reason is that it sees standardization and innovation as two sides of the same coin, melding them in a way that creates great continuity.” Ultimately, the Pragmatic perspective defines knowledge as being the product of action, experimentation, prediction and reflection. When the polar forces of action and reflection comes into correct balance it opens the door to learning deeper lessons from experience. Technical rationality is incapable of adequately addressing the challenges posed by complexity or driving the innovation process forward in ways that may confer sustainable competitive advantages. One of the most fundamental assumptions that tend to derail knowledge management-driven innovation

is the belief that organizations are machines and innovation is a predictable, deterministic process. The belief that organizations are machines leads to the presumption that innovation is a mechanical process that flows through a company via controlled, simple, and sequential channels. The validity of such assumptions diametrically opposes much of the relevant academic literature that describes the basic nature organizations as being complex adaptive systems (Stacey, 1996). Forrester (1991:15) has an even harsher view of reductionist strategies designed to deal with the problems posed by complexity. “Complex systems defy intuitive solutions. Even a third order, linear differential equation is unsolvable by inspection. Important situations in management, economics, medicine, and social behavior usually lose reality if simplified to less than fifth-order nonlinear dynamic systems. Often the model representation must be twentieth order or higher.” Management strategies rarely are sufficiently sophisticated to adequately deal with the problems posed by complexity. Rothwell (2005) has taken a historical view of the innovation process and identified a series of progressively more complex theories to explain the innovation process that have evolved. He has identified five generations of innovation models ranging from linear models using technology-push systems to more flexible, customized, continuous innovation models. Similarly, Tidd (2006) claims that one of the most important challenges in managing innovation is to make clear sense of complex, uncertain and highly risky sets of phenomena. Yet, such dynamically complex domains tend to render traditional management strategies ineffective. All knowledge encompasses theories that predict some future state or expected outcome. Over time, accrued experiences can provide evidence to verify that theories-in-use and practices match well with reality. The next section of this chapter will explore this type of action-based view of knowledge and the tools that can help to raise the level of quality of this knowledge – including, inquiry, semiotics, and Pragmatic logic.

337

Toward a More Pragmatic Knowledge Management

ELEMENTS OF PRAGMATIC KNOWLEDGE MANAGEMENT From the Pragmatic perspective, knowledge is always contingent on situations. In particular, its basis is a triad of interconnected elements that define every problem situation. Collectively, these triads are known knowledge acts. Knowledge acts consist of the following three elements: 1. Case – A perceived problematic situation or ideal future state 2. Rule – Algorithms that serve as guides to action in various situations 3. Result – Expected outcomes follow consequent to prior actions.

Case A typical case defines a problem situation or an unmet purpose. For example, it might be one where sales of a computer software product are increasing fast, calls to the company’s toll-free technical support hotline are increasing dramatically, and the rate of employee turnover among technical is increasing at steep rate causing the quality of customer to support to decline markedly.

Rule A rule for action is a prescription of a series of steps or processes to follow in a given situation. Rules may range from being particular sets of algorithms to more general heuristics. For the manager of the technical support center is to follow the habit or routine for handling such situations in the past, such as to invest more money in recruiting new technical support personnel.

Results An expected result is a predicted outcome or ideal state of affairs. Whenever actions aim toward achieving a specific purpose, their design targets

338

an imagined outcome or pattern of behavior. The expected result is that hiring new technical support personnel will offset the turnover problem and return the quality of customer to an acceptable range. Here, a pragmatic manager envisions each possible problem-solving scenario as being an experiment. Experimentation fulfills dual purposes. It operates in the same way that managers at Toyota seek both to improve performance as well as the quality of knowledge about a situation. When a problem is recognized, then actions are taken in accord with specific rules -- based in knowledge – to attain a hoped for outcome. Such experiments seek to determine whether particular problem diagnoses and specific rules-for-action will produce expected outcomes. If results meet expectations -- then, the knowledge used to guide that action was valid for that particular case. Similarly, through a process of logical induction we may reinforce the rules for action used as being appropriate for use in this situation. Over time, as rules are repeatedly used, in becomes possible to ascertain their trustworthiness. In this scientific experiment, if expected results fail, then we may want to question the following: 1. How we interpreted a problem and what meaning we give to it. 2. Whether the rule for action we followed is appropriate to the situation. 3. The extent to which an expected future state is consistent with knowledge acts. In Pragmatism, the science of semiotics governs the formation of meaning given to a perceived symbol in a problem situation. For example, a decline in market share may symbolize many things ranging from dissatisfaction among customers to aggressive action taken by competitors. The problem we ultimately defined and the desired result will largely govern the type of rules for action we are likely to invoke to achieve that desired state. Over time, as we go through multiple iterations

Toward a More Pragmatic Knowledge Management

of following rules-for-action to achieve desired end states so as to resolve a perceived case -- we accrue knowledge of which actions work and which fail. Unlike simple theories of learning that address the importance of lessons learned, the Pragmatist uses the knowledge gained as feedback to measure the degree to which one’s beliefs mirror reality. Knowledge acts, not only become a basis for taking future actions, it also provides input for revising one’s belief systems. When expected performance fails, it triggers the irritation of doubt about the validity of our beliefs about how things work.

THE PERFORMANCEDOUBT-INQUIRY TRIAD Inquiry plays a critical function within the Pragmatic knowledge processes. It leads not only to improving the quality of existing knowledge, but to creating new knowledge as well. Inquiry often takes the form of exploring new ways of thinking about past knowledge and experience to settle one’s mind about why actions taken may not have produced the expected results in the past. The inquiry process is set in motion when actual performance fails to align with goals (expectations). When performance fails to meet expectations it causes doubts to arise about the validity of the hypothesized causal relationship between case, rule, and result. In other words, there might be doubts about whether the right rules-for- action are used or whether the way the diagnosis of the case provided a meaningful description of the situation or both. Figure 1 illustrates the dynamic relationship between performance, doubt, and inquiry. Whenever results fail to match expectations this precipitates what Peirce terms the ‘irritation of doubt’ to emerge. Figure 2 depicts how the unexpected declines in performance cause greater doubt in inverse proportion to the unmet expectations, which cause inquiry to increase. So here, the process of inquiry commences a search

Figure 1. The Performance-Doubt-Inquiry Triad

for new answers that typically might involve redefining the case or selecting new/different knowledge acts to follow or both. Once performance improves to expected levels then doubt will decline as will the amount of effort devoted to inquiry. Figure 2 depicts the three basic elements that compose knowledge as envisioned in the Pragmatic tradition. According to the Pragmatists, most explications of truth are defined, not only by how things work in reality, e.g. it is true that when a lead ball is dropped in the air it falls predictably toward the ground due to the effects of gravity, but there is also social component to defining what is true. Outside of the undeniable physical laws of the universe, in fields such as medical science, there are many interpretations as to the causes of disease based on the shared common beliefs of communi-

Figure 2. Situational Knowledge Act

339

Toward a More Pragmatic Knowledge Management

ties of committed practitioners and inquirers. Figure 3 demonstrates the reciprocal relationship between performance and inquiry as mediated by doubt. When performance declines and doubt grows, it causes our efforts to seek alternative explanations to expand through a process of inquiry. Inquiry is the driving force behind the science of discovery. Discovery can take many forms in organizations including invention and innovation

A SCIENCE OF DISCOVERY Historically, Charles Sanders Peirce developed the principles of Pragmatism to provide a general roadmap to increasing the capabilities of scientists to make important discoveries. Peirce’s approach to promoting discovery was to employ the synergistic use of all three forms of reasoning – deduction, induction, and abduction to build knowledge and use it to inform effective action. For example, the logical process of deduction enables practitioners to use the knowledge extracted from prior experiences and now embedded in rules-foraction to guide future conduct. The effectiveness of these actions in meeting expectations provides feedback on the validity of the knowledge in use. Similarly, induction draws upon the lessons learned from prior experience to further innovate

and revise rules for action thereby increasing their effectiveness. Finally, abduction synthesizes conclusions developed from prior deductions and inductions to create new hypotheses about how key governing relationships might exert their influence on some new initiative, such as releasing a new product or predicting changes in consumer buying habits. This logical process of recursively moving through continuous cycles of prediction and action is also the substrata of many process improvement systems. Most importantly, lessons learnt from revising rules-for-action, set the stage for creating improved knowledge for innovation. Knowledge gained from experience becomes the basis for enriching models of practice. Senge (1990: 176) argues, “The problems with mental models arise when the models are tacit – when they exist below the level of awareness.” Models based on false premises cannot produce highly effective outcomes reliably and in a sustainable manner. Quality experts, Box & Draper (1987:424) observed, “Essentially, all models are wrong, but some are useful.” Pragmatism enables managers to create causal models that will enable them to improve their knowledge, innovation, and performance.

Figure 3. The balance of the Performance-Doubt-Inquiry Triad

340

Toward a More Pragmatic Knowledge Management

Managing Knowledge by Improving Its Quality Quality guru, W. Edwards Deming created what has become became the centerpiece of virtually every TQM initiative -- the Plan-Do-Check-Act cycle. (Figure 4) Among the greatest influences on Deming’s thinking were ideas he learned from his mentor, Walter Shewhart. Shewhart was an avid reader of the writings of Harvard professor of pragmatic philosophy C.I. Lewis (Towns, 1997, Barton, 1999) and began to envision the implications of applying their principles to performance improvement and statistical process control. Deming proceeded to marry together quality, performance improvement, and knowledge into the rubric known as Total Quality Management. He also wrote of the importance profound knowledge in quality improvement initiatives. Deming (1993:102) identified four components of profound knowledge including a theory of knowledge. He argued management is a form of prediction and requires having a theory of knowledge about how things work causally so we can anticipate the future consequences of our actions. Deming’s theory of knowledge teaches that any statement, if it conveys knowledge, then predicts future outcomes. Here, Deming was speaking of the abductive qualities of knowledge. As the quality of knowledge improves -- through reiterative problem solving initiatives -- it provides opportunities for workers to find errors in their collective thinking, reach deeper insights into how cause produces effect, and enriches mental models with new possibilities. By rearranging facts and impressions to form new knowledge acts, it also enables abductive hypotheses to form. Such new speculations are the seed of innovation because they produce a type of design synthesis that heretofore failed to exist. In effect, a rational series of conclusions and inferences indirectly leads to creative insights that would be otherwise unlikely to form.

The PDCA cycle does not explicitly acknowledge how the quality of knowledge-in-use changes over time as a product of learning and experimentation. Incorporating the aforementioned pragmatic principles into the PDCA cycle there is a greater potential seeing more clearly how learning, reasoning, reflection, and experimentation, when integrated together, all contribute to improvements in the quality of knowledge. The four Pragmatic tools described earlier in this chapter directly govern the extent to which employees can fully realize the potential of the PDCA model to increase levels of organizational performance, adaptation, and innovation. Knowledge is the product of using these tools and is the second most important determinant of effective action – behind holding valid beliefs about how things work in practice. Figure 5 provides an integrative framework that unites knowledge, learning, and reasoning into a single perspective. The PDCA cycle often acts as a balancing feedback loop to determine the extent to which actual results match expected performance. If they do not match, then it sets off inquiry-driven search processes designed to reduce doubt by closing the performance gap by improving performance. The cycle achieves its learning purpose by enacting specific forms of inferential reasoning to drive each of the four elements in the loop. For example:

Figure 4. Deming’s PDCA Cycle

341

Toward a More Pragmatic Knowledge Management

Figure 5. Integrated Pragmatic Knowledge System

• •

•

The PLAN function seeks to determine the exact parameters of the case; The DO function seeks to select the Rule (rules for action) that will drive action to achieve a desired state; The CHECK function looks at both the expected result of anticipated action as well as the effects of prior action.

In Pragmatic logic terms, the various steps in the PDCA correspond to the specific types of reasoning necessary for creating new knowledge or improving existing knowledge. The process of deduction drives planning, while checking is primarily a process of induction. Finally, the Act function is largely a matter of abduction. (Reed, 2010) Each type of inferential reasoning builds on the conclusions that result from a logical sequence of considerations among the case-rule-result triad. The Pragmatic system of knowledge quality improvement operates as a rigorously scientific experimental framework designed to ensure that the quality of the knowledge-in-use is continu-

342

ously improved. It is more likely that knowledge built upon valid premises and using the logic of abduction will be capable of effectively driving the innovation process.

DISCUSSION Despite Toyota’s outstanding business performance in terms of quality and innovation, competitors tend to emulate its pragmatic methods far less often than one might expect. Arguably, Toyota’s organizational system is unique and difficult to imitate. It is a complex system composed of a mix of deeply held values, precise standards, relentless learning, scientific experimentation, and personal reflection by its employees. This sophisticated system has evolved over a half-century driven by adherence to the company’s fourteen basic principles. The difficulty other companies experience in imitating Toyota’s knowledge processes provide a competitive advantage to the firm. After all, typically the greatest sources of sustainable

Toward a More Pragmatic Knowledge Management

competitive advantage are unique applications of a firm’s intellectual capital reflecting their subtle ways of thinking and perceiving that remain less then apparent to outside observers. However, it is equally arguable that the barriers to imitation of Toyota’s strategy stems even more the extent to which its process are designed on the basis of pragmatic logic that often is nonsensical in the eyes of outsiders. For example, the notion of reducing costs, indirectly, through knowledge and innovation rather than by employing discrete costcutting initiatives is purely confounding to many competitors. Further, the pragmatic principles that uphold their yokoten system has little resemblance to the sorts of information technology-based KM approaches that proliferate around the world. Toyota’s KM system is a direct mirror of its own pragmatic principles that subscribe to idea that knowledge, action, feedback, and belief are inseparable. In the original pragmatic writings of Peirce there was a perspective expressed that all of these factors are parts of a larger dynamic system driven by inferential reasoning, inquiry, and reflection. In sum, Toyota’s quality, knowledge, and innovation processes are synergistic and operate seamlessly together. In other words, there is no Toyota ‘innovation system’ or ‘quality improvement system’ per se – rather there is the Toyota pragmatic way of doing business that embraces all of the processes that deliver superior performance for the company.

FUTURE DIRECTIONS Pragmatic knowledge-based systems stand in stark contrast to conventional knowledge management approaches in several important ways. Conventional KM approaches demand either a high investment in technology and/or employee time. Ironically, many of today’s employees already carry high responsibilities and resent the ‘add-on’ nature of typical KM processes. This is especially so when the direct benefits of doing

such types of KM are not readily apparent to them. The failure of such conventional KM approaches to spur innovation over the past decade has been unsurprising. First-generation KM approaches do not address the sort of knowledge-creation processes that innovation requires. Pragmatic KM innovates by seamlessly integrating knowledge with processes, such as problem-solving and quality improvement. However, today TQM has run out of steam in many companies as managers focus more on its cost-reducing benefits than on its innovation promise. To more effectively leverage the promise of knowledge-based innovation programs individual employees must become capable of changing their beliefs about how things work as the result of ongoing scientific experimentation. They must be taught to be open to evidence that may go contrary to habitual ways of thinking. Typically, such insights are the product of not only experimentation, but also reflection. While the notion of engaging in wide spread reflection among workers in companies has largely been rejected in North America as being inefficient, the need for it remains compelling. In the race among companies to achieve more sustainable forms of competitive advantage, a type of organization known as a high-velocity organization is winning the race (Spear, 2009). They achieve this by consistently investing heavily in developing employee capabilities in four areas: (1) systems design and operation; (2) problem solving and improvement, (3) knowledge sharing; and (4) developing high-velocity skills, such as leadership, in others.

CONCLUSION Amidst the hype of promises made about KM, among those many companies that claim to have used it, few of these promises have realized its potential benefits. Yet, there are significant advances by other companies, such as Toyota. Over the past twenty years, Toyota has been

343

Toward a More Pragmatic Knowledge Management

developing its own type of knowledge-based system to improve problem solving, quality, and innovation. This system relies on the Pragmatic principles embedded into the foundation of TQM by Deming. The main advantages of adopting a Pragmatic perspective is its focus on operational improvement at relatively low cost. Organizations that have already invested in building their capabilities in organizational processes, such as TQM, Lean, organizational learning, and systems thinking will find the transition to becoming more Pragmatic and innovative to be a relatively smooth journey. Yet, there is no escaping the principles laid out by Schumpeter (1950). He pointed out the importance of knowledge for innovation, and identified the principle that successful innovation results from the accumulated scientific knowledge that develops within a company over time. His use of the term scientific knowledge in innovation processes runs parallel to what Peirce described as being necessary for driving abductive reasoning. Innovation may occur in a flash – but it often results from incremental experimentation that has laid a foundation built on high quality knowledge.

REFERENCES Argyris, C. (2000). Overcoming organizational defenses. Boston, MA: Allyn & Bacon. Bacon, F., & Butler, T. (1998). Achieving planned innovation. New York, NY: Free Press. Baregheh, A., Rowley, J., & Sambrook, S. (2009). Towards a multidisciplinary definition of innovation. Management Decision, 47(8), 1323–1339. doi:10.1108/00251740910984578 Barton, J. (1999, July). Pragmatism, Systems Thinking and System Dynamics, In International System Dynamics Conference, Melbourne, Australia.

344

Box, G. E., & Draper, N. (1987). Empirical model-building and response surfaces. New York, NY: Wiley. Burgelman, R. (1983). Corporate entrepreneurship and strategic management: Insights from a process study. Management Science, 29(12), 1349–1364. doi:10.1287/mnsc.29.12.1349 Burks, A. (1946). Peirce’s theory of abduction. Philosophy of Science, 13(4), 301–306. doi:10.1086/286904 Christensen, C. (2003). The innovator’s dilemma. New York, NY: Harper. Davila, T., Epstein, M., & Shelton, R. (2006). Making innovation work: How to manage it, measure it, and profit from it. Upper Saddle River, NY: Wharton School Publishing. Deming, W. E. (1993). The new economics. Cambridge, MA: MIT Press. Fahey, L., & Prusak, L. (1998). The 11 deadliest sins of knowledge management. California Management Review, 40(3), 265–276. Fearon, D., & Cavaleri, S. (2006). Inside knowledge: Rediscovering the source of performance improvement. Milwaukee, WI: American Society for Quality Press. Firestone, J., & McElroy, M. (2003). Key issues in the new knowledge management. Boston, MA: Butterworth-Heinemann. Firestone, J., & McElroy, M. (2005). Doing knowledge management. The Learning Organization, 12(2), 189–212. doi:10.1108/09696470510583557 Haner, U. (2002). Innovation quality: A conceptual framework. International Journal of Production Economics, 80(1), 31–37. doi:10.1016/S09255273(02)00240-2

Toward a More Pragmatic Knowledge Management

Johnston, S. (2001). How toyota turns workers into problem solvers: Harvard Business School: Working knowledge. Retrieved on November 26, from http://hbswk.hbs.edu/ item/3512.html Liker, J. (2004). The Toyota way. New York, NY: McGraw-Hill. Liker, J. (2008). The Toyota culture. New York, NY: McGraw-Hill. Liszka, J. (1996). A general introduction to the semeiotic of Charles Sanders Peirce. Bloomington, IN: University of Indiana Press. Malhotra, Y. (2005). Integrating knowledge management technologies in organizational business processes: Getting real time enterprises to deliver real business performance. Journal of Knowledge Management, 9(1), 7–28. doi:10.1108/13673270510582938 Martin, R. (2009). The design of business: Why design thinking is the next competitive advantage. Cambridge, MA: Harvard Business School Press. Martin, R. (2010). Management by imagination, Harvard Business Review, January 19, Retrieved on October, 8, 2010 from http://blogs.hbr.org/martin/ 2010/01/ management-by-imagination.html

Peirce, C. S. (1988). Pragmatism as the logic of abduction, in Peirce Edition Project (Ed.), The essential Peirce: Selected philosophical writings, 1893-1913. Bloomington, IN: Indiana University Press. Perrow, C. (1999). Normal accidents. Princeton, NJ: Princeton University Press. Popper, K. (1945). The open society and its enemies. London, UK: Routledge. Reed, F. (2010). PDCA+, Unpublished manuscript in progress. Honey Brook, PA. Schon, D. (1983). The Reflective Practitioner. New York, NY: Basic Books. Schumpeter, J. A. (1950). Capitalism, socialism and democracy. New York, NY: Harper & Row. Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. New York, NY: Doubleday. Simon, H. (1991). Bounded rationality and organizational learning. Management Science, 21(February), 125–134. Spear, S. (2004). Learning to lead at Toyota. Harvard Business Review, (May): 1–9.

McElroy, M. (2009). Social footprints. The Netherlands: University of Groningen.

Spear, S. (2009). Chasing the rabbit. New York, NY: McGraw-Hill.

Murphey, M. (2005). C. I. Lewis: The last great pragmatist. Albany, NY: State University of New York Press.

Spear, S., & Bowen, K. (1999). Decoding the DNA of the Toyota production system (pp. 96-106). Harvard Business Review, Sept-Oct.

Nelson, R., & Winter, S. (2002). Evolutionary theorizing in economics. The Journal of Economic Perspectives, 16(Spring), 23–46. doi:10.1257/0895330027247

Stacey, R. (1996). Complexity and creativity in organizations. San Francisco, CA: Berrett-Koehler.

Ohno, T. (1988). Toyota production system: Beyond large scale production. New York, NY: Productivity Press. Peirce, C. S. (1878). How to make our ideas clear. Popular Science Monthly, 12(January), 286–302.

Sterman, J. (1989). Misperceptions of feedback in dynamic decision making. Organizational Behavior and Human Decision Processes, 43, 301–335. doi:10.1016/0749-5978(89)90041-1 Sterman, J. (1994). Learning in and about complex systems. System Dynamics Review, 10, 2–3, 291–330. doi:10.1002/sdr.4260100214

345

Toward a More Pragmatic Knowledge Management

Stewart, T. (2002). The case against knowledge management, Business 2.0, February. Thompson, J., & Cavaleri, S. (2010). Dynamic knowledge, organisational growth, and sustainability. International Studies in Management and Organization, 40(3), 50–60. doi:10.2753/ IMO0020-8825400303 Tidd, J. (2006). Enhancing innovation in Biopharma R&D through partnering between companies and universities, Discussion Paper, London, UK, Imperial College. Utterback, J. (1996). Mastering the dynamics of innovation. Cambridge, MA: Harvard Business School Press. Von Hippel. (1998). Economics of product development by users: The impact of “sticky” local information. Management Science, 44(5), 629–644. doi:10.1287/mnsc.44.5.629 Walton, M. (1986). The Deming management method. New York, NY: Perigee Books. Wiener, P. (1958). Charles S. Peirce: Selected writings. New York, NY: Dover Publications. Wiig, K. (2004). People-focused knowledge management. Amsterdam, The Netherlands: Elsevier.

346

ADDITIONAL READING Firestone, J., & McElroy, M. (2004). Organizational learning and knowledge management: The relationship. The Learning Organization, 11(2), 177–184. doi:10.1108/09696470410521628 Pedler, M. (1997). Action learning in practice (3rd ed.). Hampshire, England: Gower Publishing. Peirce, C. S. (1892). The Law of Mind. The Monist, II(4), 533–559.

KEY TERMS AND DEFINITIONS Action Learning: “In action learning, the development of a problem and a person proceeds via a continuous passing from outer actions to inner processes to outer actions and back.” (Pedler, 1997:36) Knowledge Management: “the set of processes that seeks to change the organization’s present pattern of knowledge processing to enhance both it and its knowledge outcomes.” (Firestone and McElroy, 2004) Pragmatism: to consider, “what effects, that might conceivably have practical bearings, we conceive the object of our conception to have. Then, our conception of these effects is the whole of our conception of the object.” (Peirce, 1892)

347

Chapter 19

Knowledge and the Politics of Innovation:

Insights from a R&D Company Theodora Asimakou London Metropolitan University, UK

ABSTRACT The chapter discusses the relationship between knowledge management and innovation; specifically, it examines how knowledge in organizations affects the creation of new knowledge and what the implications are for innovation management. The core argument is that in a knowledge-based company, where competition is assessed at the edge of rare expertise and the development of innovations (Boisot, 1998; Drucker, 1993; Sveiby 1997), knowledge, which is always interwoven with power, becomes a precious resource, on the grounds of which struggles are inevitably enacted over its control (Foucault, 1980; Clegg, 1989). To argue this, the chapter brings together two related fields, knowledge management and innovation, which even though in principle they examine similar phenomena, i.e. the creation and sharing of new knowledge, in practice they appear disconnected (Asimakou, 2009b). To support the arguments, two innovation mechanisms in two business groups of a major oil company are discussed. The study used a set of qualitative techniques for data collection (in-depth interview, participant observation, documentary analysis) and a sample of 41 employees, which represented the groups participating in the innovation game (manager, scientists, assistant scientists, administration staff and students). I argue that two mainstream innovation management approaches (the rational planning and the cultural approach) have shaped the understanding and actions of the Business Groups in setting up the innovation mechanisms; however, power struggles at the individual, group and organizational level impacted upon the innovation processes to the extent that the latter became passive ‘technical solutions’. DOI: 10.4018/978-1-61350-165-8.ch019

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Knowledge and the Politics of Innovation

INTRODUCTION The chapter starts by critically looking at the literature of innovation –the assumptions and the limitations of the dominant approaches. One observes that popular managerial press constructs the debate around certain core-themes, and presents innovation either as an administrative question or a technical problem, a social or a political matter (Carr, 2003; McFarlan & Nolan, 2003; Rogers, 2003; Brown, Durchslag & Hagel, 2002). Mainstream theories split innovation in various stages and attempt to control each of them with administrative or technical devices. I distinguish here two main approaches (Fonseca, 2002; Asimakou, 2009b): innovation as rational planning and innovation as culture, which, nonetheless, are grounded on the same assumptions, i.e. the controllability of ideas and innovation processes. Both approaches set out to manage innovation by controlling either directly the process or the environment/culture where innovation is supposed to grow. In order to construct a counter-argument and identify the limitations of these approaches, I suggest that the theoretical progress of the knowledge management field should be contemplated, and in particular the literature on the nature of knowledge in organizations (Collins, 1993; Blackler, 2003). Studies that encapsulate these theoretical insights, have demonstrated the complexity so much of the structure of knowledge, as much as of the processes that produce it. It becomes evident that positivistic and functionalistic methodologies cannot fully explain knowledge related phenomena at the workplace. Hence, our understanding of innovation would only be enriched if alternative approaches are also applied. Furthermore, responding to the call for giving up the ‘either structural or voluntaristic’ approaches to understanding innovation, the chapter brings evidence that both approaches may co-exist in the organization -hence which one is the ‘right’ one does not form part of the current analysis.

348

I suggest then, that these co-existing approaches form discourses and actions, of which the analysis may reveal issues of power and order. The two dominant discourses on innovation management are viewed as one language game, where various players compete to determine adequate actions. The question then becomes, how current knowledge (i.e. regime of truth) impact on the possibilities for innovation and change, and how knowledge workers embark on a power game in their effort to influence organizational transformations. The chapter does not construct one more approach to add to the analysis of innovation, but rather examines what the already existing ones actually do to the organizational life. The analysis appeals to the theoretical concepts of discourses as regimes of truth and the political dimension of knowledge (Foucault, 1971; 1980; Lyotard, 1984; Howarth & Stavrakakis, 2000). By adopting a discursive approach to the analysis of innovation, the chapter throws light into the political dimension of knowledge in a knowledge-organization, and into why organizations and individuals resist or support innovation practices. To illustrate the arguments the chapter brings evidence from a R&D dept, while in the process of changing, i.e. conferring a new order by changing the hegemonic discourse, which aspired to stimulate new ideas and support innovation. Two innovation mechanisms in two Business Groups of a major oil company are presented and the enacted politics are discussed, as manifested at the organizational, group, and individual level. As said above, the methodology adopts a discursive approach, in other words, it conceptualises innovation as a new discursive formation, which contested the existing one; it uses a set of qualitative techniques for data collection (in-depth interview, participant observation, documentary analysis) and a sample of 41 employees, which represented the groups participating in the innovation game (managers, scientists, assistant scientists, administration staff and students). I argue that two mainstream innovation management approaches

Knowledge and the Politics of Innovation

(‘innovation as rational planning’ and ‘innovation as culture’) have shaped the understanding and actions of the Business Groups in setting up the innovation mechanisms; however, the negligence of the power struggles that were enacted sentenced the innovation processes to become passive ‘technical solutions’, without achieving to spread, and to engage the experts’ population. The evidence unfolds over three main sections: first, I present ‘Hydro-Carbon Solutions’ –the context of research, main question and research methods. Then, I present the findings; on one side I present the rhetoric of the two innovation mechanisms, and the practices they suggest, and on the other side, the power games enacted at the organizational, group and individual level, the arguments which derive from various language games –depending on what is pursued each time-, and which sometimes facilitated and sometimes constrained the innovation process. Finally, I discuss the evidence in the light of the highlighted power games, arguing for the necessity to engage the work population into the governance of knowledge and innovation process.

DISCOURSES ON INNOVATION MANAGEMENT It is widely acknowledged that the literature on innovation management, formed by various disciplines (economics, finance, organizational behaviour, etc) has led the field to high inconsistency in terms of assumptions and findings. There are various suggestions for ordering the debate that shapes theory and practices (Wolfe, 1994; Slappendel, 1996; Fonseca, 2002) e.g. diffusion of innovation, organizational innovativeness and process theory, or deterministic, voluntaristic and interactive perspectives, etc. Here I suggest that dominant approaches could be conceived as powerful discourses that form organizational actions.

Broadly speaking, there are two main streams that form the debate: the first conceives innovation as a rational planning process, whereas the second as a culture management issue; these two have formed respectively two powerful discourses. The first discourse is descriptive; it developed from neoclassic economics and suggests that innovation is an entrepreneurship function, essential for the survival of small and bigger organizations (Betz, 2003; Bessant & Tidd, 2007; Trott, 2008). The rational planning of innovation suggests the splitting of the process in controllable and measurable stages, from the evaluation of ideas to the final stage of launching the product in the market. At the end of each stage, the idea is evaluated against the market, the expected profits, and the compatibility of the idea with the strategic route of the firm. All these matters should be designed in advance, and incorporated in a business plan. The second discourse is prescriptive; it developed from the human relations school and emphasizes the significance of values and culture in making innovation blossom (Kanter, 1988; Lengnick-Hall & Wolff, 1999; Rogers, 2003; Smith, 2007). The analysis of innovation from this perspective takes into account how cultural variables, biased decision-making strategies and managerial procedures mediate the processes of creating and sharing knowledge within and across institutions. This approach attributes a central role to the management of an innovative culture, and hence to charismatic leaders -the ‘innovation hero’- who design, manage or support it. Due to its emphasis on soft issues and communication, it suggests the use of communication techniques to spark, share and develop further ideas, together with the technological devices to support the processes. Interestingly, Klein (2001) argues that in principle one discourse confers its legitimacy from the other, in trying to link the organizational strategic goals with the economic growth, acting as one powerful discourse. The interest in over-

349

Knowledge and the Politics of Innovation

coming the ‘either…or’ dilemma has recently led to the formation of the concept of organizational ambidexterity, which attempts to support structurally commercial and scientific interests in a single organization (Benner & Tuschman, 2003; Gupta, Smith & Shalley, 2006; Simsek, 2009). However in practice the two discourses remain separated, and often conflict over research priorities, allocation of resources etc, for their innovation assumptions and suggested practices are not compatible; hence confusion increases and creates multiple interpretations and actions. Most importantly, such mechanistic approaches, appropriate to measure and calculate closed systems, have proved insufficient to study complex relationships, human experiences and cultural issues, which constitute the substance of knowledge. Research within these paradigms aim to control and manage the unpredictable character of innovation, whereas it is precisely the assumed rationality and power of management that should be questioned and investigated (Hassard & Pym, 1990; Alvesson & Willmott, 1992). Furthermore, both discourses assume and intentionally aim to create consensus and trust among people in organizations (Adler, 2001; Park, 2006; Usoro, Sharratt, Tsui, & Shekhar, 2007). The question of power is addressed as variable that can be manipulated, i.e. it is seen merely as means of negotiation, not as the force of creating a new order and a new set of rules (Foucault, 1980; Clegg, 1989), leaving this way many aspects of power relations outside of the analysis. On the other hand, the knowledge management field has made substantial progress in understanding the nature of knowledge and knowledge processes at the workplace, depicting the social character and the political dimension of knowledge, and most importantly its power to confer orders of truth, which allow or stop actions. Blackler (1993: 864) summarizes the output of this theoretical work: “knowledge has been described as: socially constructed (Berger

350

& Luckmann, 1966); often tacit (Polanyi, 1967); a function of the play of other meanings (Derrida, 1978); enacted (Weick, 1979); distributed (Hutchins, 1983); situated (Suchman, 1987); material, as well as mental and social (Latour, 1987); resilient, but provisional and developing (Unger, 1987); public and rhetorical (Vattimo, 1988); and acquired through participation within communities of practice (Lave & Wenger, 1991)”. The contribution of all this admittedly controversial and polyphonic work is that it triggers the expansion of the dominant rational-cognitive understanding of knowledge, by emphasizing so much the complexity of tacit skills and practice, as much as the significance of social processes, cultural categories and language in ‘creating’ knowledge (Orr, 1990; Lave & Wanger, 1991; Brown & Duguid, 1991; 2001). The narrow understanding of scientific–abstract knowledge expands and breaks the conventional distinction between people and technologies (Blackler, 2003); hence, the narrative and tacit dimension of knowledge, together with the contextual factors (structures, culture) that support knowledge processes, gain attention. The innovation literature and practice has been late to embracing the theoretical progress of the knowledge management field, even though the insights of the latter would compliment the limitations innovation studies have met (Plessis, 2007; Chatzkel, 2007). Some alternative research has indeed engaged with these theoretical advances, (Frost & Egri, 1991; Markham, 2000; Fonseca, 2002; Smith, 2007; Asimakou, 2009a) and doubted the adequacy of both the starting assumptions and the applied methodologies to study complex relationships and cultural issues. In this body of literature, I distinguish two main approaches: innovation as social construction of meanings, and innovation as a political process. The former focuses on the creation of new meanings and interpretations, which enrich organizational knowledge and understanding, and finds its roots in an interpretative epistemology. Undoubtedly the

Knowledge and the Politics of Innovation

most influential model here is the one of Nonaka (1994) has triggered a volume of research (Dierkes, Antal, Child, & Nonaka, 2003; Takeuchi, & Nonaka, 2004; Ichijo, & Nonaka, 2006) and a variety of organizational and technological practices. The model essentially conceptualizes knowledge as an on-going process, which relies on communication. Knowledge creation is a dialogue among individuals and organizations, and organizational knowledge increases as individuals span across and beyond the organizational boundaries. Despite the shift of focus towards knowing and communication, the model employed a linear interpretation of the related processes; consequently the practices that have been formed on its grounds did not achieve to break away from an instrumentalist, object-view of knowledge. The latter, i.e. innovation as a political process, deals with issues of power and conflict, while new knowledge replaces the old one, and is rooted in a critical theory or a post-structural paradigm. The chapter joins the latter approach, and challenges current models of analyzing innovation, for they neglect or downplay the force of politics and the power games enacted when setting up and managing innovation processes, in best cases reducing politics to networking. The chapter addresses the political aspects of organizational life, when a new discourse (in this case knowledge and innovation) and practices (i.e. innovation systems) emerge, and the power games that are triggered. Following Foucault (1980), discourses construct regimes of truth, which have a normalizing effect upon phenomena and practices, making some of them appear good, truthful, respectful, whereas others are considered harmful, wrong, shameful, etc. Truth is always interwoven in a circular relation with systems of power that produce it and sustain it, and with effects of power, which it induces, and which extend it (Foucault, 1980). Hence, discourses ‘embody meaning and social relationships, they constitute both subjectivity and power relations’ (Ball, 1990, p.2). From this respect, power is not simply someone’s ability

to manipulate and control others’ behaviour and actions, but it is a wider notion, which forms structures, practices and subjectivities in the organizational life. Frost and Egri (1991) claim that at the surface level, power and politics shape the everyday life, the contestations and struggles for collaborations; here, power manifests itself in the attempts of individuals and groups to exploit the rules, and take control of the current order for their own benefit, and at the expense of another group (Markham, 2000). At the deep structure level, power operates in subtle and hard to detect ways; it springs from an already contested and agreed order, which is currently accepted as natural and neutral. Hence, I suggest that innovation should be viewed as one rich language game, involving many and sometimes conflicting elements, where various stakeholders conflict over its control and articulation of rules, using arguments from dominant theories of innovation. The arguments may not always be consistent, since the actors try to achieve different things each time. The articulation of concepts that prevails, shall ultimately shape understandings and actions, and serve the interests of the group that has suggested it (this articulation may be technical or commercial etc). The political analysis of knowledge creation addresses the question of what is accepted as ‘good’ and what is rejected as ‘bad’, who decides and who benefits from these decisions (Lyotard, 1984), what supports and what stops change, and what the implications are for innovation and its management. In other words the analysis addresses the social and political dimensions of individual, group, and organizational action. Combined with a discursive approach, the analytical framework conceptualizes power relations through the lenses of discursive formations (Foucault, 1971; 1980; Fairclough, 1989; Howarth & Stavrakakis, 2000), which implies that discursive orders are shaped by and shape dominant truth-regimes and social practices.

351

Knowledge and the Politics of Innovation

THE STUDY: ‘HYDROCARBON SOLUTIONS’

Innovation Systems: Eureka and the Ideas Machine

The data gathering of the study lasted one year and was part of a broader research, which investigated knowledge discourses and innovation mechanisms in an R&D firm, ‘Hydro-Carbon Solutions’, during its commercialization turn. In this context, two newly adopted innovation mechanisms were studied, i.e. ‘Eureka’ and the ‘Ideas Machine’, while being used by two Business Groups. The methodology involved in-depth interviews (41 interviews with managers, scientists and administration staff, min. 1 hour each), examination of documentary data (newsletters, websites, e-mails, previous research projects) and participant observation (meetings, presentations, informal conversations). The interpretation of findings was conducted by means of critical discourse analysis (Fairclough, 1989; Wodak & Meyer, 2001), which supported the study of both the formal ‘innovation discourse’ as suggested by the company, and its interaction with local understandings of commercialization, research, and innovation. The analysis focused on the way the formal innovation discourse conferred the necessity for supporting research and innovation, while structures and cultures were transforming. It examined how concepts and arguments developed in this unsettled arena, allowing for multiple meanings to develop, and for conflicts between competing groups (business people, managers, scientists, etc) to emerge over defining the ‘real’ meanings and hence actions. Responding to the criticism that the approach treats meaning as fixed, the study deviated from the standard CDA by bracketing off the quest for one true meaning and other reference to cognitive elements (Potter & Wetherell, 1987), in favour of capturing multiple equally valued and co-existent realities.

The project materialized while Hydro-Carbon Solutions was experiencing structural and cultural changes. In order to make the business more profitable and commercially flexible, the parent company Oil Co gave its research laboratories a considerable degree of freedom. These laboratories started operating as independent technical consultancies with commercial objectives, for Oil Co and other customers. The new commercial environment meant that each group was thereafter responsible for its financial performance and survival. The new commercial reality affected so much the jobs and the required skills, giving the scientists a great range of administrative and managerial tasks to perform, as much as the culture of the site, which so far reminded more of a university, rather than a commercial organization. As expected, commercialization redefined the research needs. The focus and funds moved predominantly to short-term, core research, whereas longer-term and high-risk projects, which had signalized the research strategy, stopped for being financially unstable. Meanwhile, knowledge acquired a new status in the ‘knowledge-based’ society. New technological knowledge became important not only for Oil Co and its competitors, but also for their customers, i.e. it became a commercial object. The corporation embraced the innovation discourse, and this fuelled some Business Groups to design innovation systems, in order to capture and develop further the desired innovative ideas. In this unsettled arena many different groups (the Business, the market sector, the scientists, etc) saw the opportunity to enter the new knowledge game, and define what research and innovation are, in order to meet their own interests. Especially for the scientists it was an opportunity to claim back some of the benefits they used to enjoy before the commercialization turn.

352

Knowledge and the Politics of Innovation

Findings and Analysis Eureka: Rhetoric and Practice The most important innovation mechanism for the scientists was Eureka. This was an initiative of the corporation, intended to support long-term, noncore ideas that did not fit in any other innovation channel. The system provided the scientists the strategic business framework, from within they would develop viable technological innovations. “the role of Eureka is to find and nurture and support in their early stages ideas, which don’t comfortably fit into the existing Businesses; so what you could say is that there are two types of innovation: it’s in the box and out of the box, it’s core and non-core; so we are looking for those non-core ideas, which would otherwise be difficult to support, that’s essentially our role, but because it’s sometimes difficult to distinguish core from non-core, it might be almost non-core, there is actually a grey shading between the black of the core and the white of the non-core, so people come to us with ideas which are clearly core, and we might even support them at early stages, but they wouldn’t come through our mechanism for significant funding, we are likely to support them at an early stage …” [Eureka team member] In effect, the process tried to change the scientists’ understanding of ‘innovation as technology’ into ‘innovation as exploiting opportunities for change’. This intention was reflected in its vague definition and the all-inviting rhetoric, which reflected the strategic turn of Oil Co to re-invent itself from oil to energy company, and hence to expand in new markets. Eureka was a website, where scientists could log on, browse ideas, and submit their own. The Eureka team reviewed the idea, and if worth exploring, then the inventor had to present a business case in front of the innovation panel, which consisted of senior managers of Hydro-Carbon

Solutions and the Business. If the panel was convinced for the commercial value of the idea, then an initial amount of money was granted to start the scouting stage of the project. The progress would be assessed at the end of each stage and, if it could still demonstrate financial returns, then more funding was granted to the next stage. The assumptions of the ‘rational planning’ approach are evident here; the process tries to control the uncertainty of the environment by maximizing the financial control over the process of developing innovations, from the early stage of ideas generation until their launch in the market. A consequence of the all-inviting rhetoric deployed around Eureka was that many scientists read in this the opportunity to do some ‘interesting’, non-core research, of the kind that had stopped during commercialization. However, this led to the generation of ideas that were more ‘non-core and high-risk’ than what Eureka was ready to support, e.g. screen-washing devices and pieces of hardware. Not surprisingly, scientists that saw their ‘non-core and high-risk ideas’ being rejected over and over, became frustrated by the undefined and unrefined expectations of the process, which was seen as “a bit of a lottery: you put in a proposal, keep your fingers crossed, and hope you will have the OK to go ahead”.

The Ideas Machine: Rhetoric and Practice “[…] but you have to be very clear about what innovation is, to me innovation covers the whole spectrum of things, it is business processes, it is working processes and it is also ideas generation for revenues, so I think you have a really big spectrum and I think what you need to be quite careful in your project, is to make sure that that’s covered, because just because you don’t have lots of big ideas that generate lots of revenue, it doesn’t mean that you don’t have innovation, you know, if you can start off by finding ways to make the life easier you are still being innovative, to me it

353

Knowledge and the Politics of Innovation

is a big spectrum, to me that’s essential, a quite big spectrum; so yes, to ideas and big projects that work really well, but also the underground should work well as well” [Ideas Machine team member, emphasis added] The Ideas Machine was a local (i.e. technology group level) innovation system devised by Technology Group A, which first among other groups realized the importance of supporting systematically the innovation processes. Essentially, it aimed both to change the new commercial culture that made people think only of the shortterm objectives of their work, and to crack the previous elitist culture, where innovation was a scientist’s ‘prerogative’. From this respect, the question of innovation was constructed as an issue of democratizing the workplace; nobody should be excluded from the innovation game, because everybody was equally competent to come up with small ideas, which could eventually grow bigger. Beyond the rhetoric of democratization, this open and all-encompassing view of innovation had also another more practical objective: as a manager pointed out, “the more ideas you have in the beginning of the funnel the more chances you have to come up with a marketable idea at the end.” The system exhibited the assumptions of the cultural approach to innovation management. It acknowledged that innovation can only be managed by creating the right environment, and to this end it devised a combination of techniques for ideas generation together with a funnel. From there the innovation team progressed the ideas on the appropriate route, whether this involved immediate action internally by the Technology Group, or forwarding them to an external innovation funnel -mainly Eureka. The all-embracing rhetoric was successful in engaging the groups that had been excluded during the ‘university days’ of the site, in the innovation game. Lab-technicians, assistant scientists, pre-students and administrative staff saw

354

their ideas materializing, and felt that their voices were heard at the Technology Group; however, their ideas were not exactly the kind that could be technically and commercially exploited. The scientists, whose ideas were primarily sought, remained reluctant or at least indifferent to use the local innovation system: an all-embracing innovation system, where all suggestions were welcome, was not perceived as the appropriate funnel to host complex scientific ideas. Even though the rhetoric implied the democratization of the workplace, the Technology Group actually needed technical ideas, which means that the experts were still a powerful elite.

Organizational Level Conflict of Worldviews Committed to the idea of the ‘continuum’ between long and short-term ideas, a Eureka team-member discussed the problem of the gap between the edges: “yeah, and then we’ve got you know, down here [points onto a piece of paper] we’ve got next year’s new programmes or whatever; and the gap is here, it’s in the middle, because these projects that are in the long-term never ever become shortterm for some reason {laughs} because they are done by long-term researchers, the guys whose drivers are …social or scientific or whatever and haven’t really got much incentives to get the idea, and these people don’t even look off their desks, so the gap is sitting here in some sort of 3+ year horizon, and again what we are trying to do, in order to change this, is to actively manage this chunk, so that it later drags ideas from year to year, and drags experience from here” The lack of communication between the Business and scientists had always been the common excuse to justify the low number of marketable ideas; however here, the problem was constructed

Knowledge and the Politics of Innovation

as a fundamental incompatibility of drivers, interests and objectives between the two parties. Eureka, even though designed to bridge this gap, did not address this cultural and essentially political issue, but treated ideas and experiences as distinct entities that could be managed independently from the individuals who generated and would work on them. Eureka was meant to be the ‘solution’to conciliate the Business interests with the research staff capabilities and skills, in a clear business context; this combination had been impossible before the commercialization turn, when scientists were free to pursue their own research projects without tight control. However, the rise of ‘knowledge discourse gave various groups the opportunity to assert their interests via the innovation game. The scientists, who were not asked their views on designing the innovation system, seized the opportunity to challenge the rules of the new innovation game. Yet, a Eureka key-member insisted on ignoring the deep structure politics behind the failure of the process to engage the scientists, and preferred to explain the problem as an issue of different objectives and mentalities: “ehm, people don’t like… people that do long term R&D don’t like working with the Business, and people in the Business don’t like working with people who do long-term R&D, because they have other objectives; now, our role is to force them to do that, some like that, some people don’t, but those people like OUR System, our System goes down well, ehm, but the overall process is not always perceived as positively as it should, because it requires people to work with the Business and requires the Business to work with the originators” This excerpt depicts the politics of innovation, as different groups having different objectives to serve. Hydro-Carbon Solutions tried to bridge the objectives by mechanistic means. Still it did not touch the actual question, which would rather

be how to create a shared concept of innovation that would engage both Business and scientists.

Conflict over ‘Innovation’ “[…] I think the danger is that we’re being conditioned to think of innovation just as a business thing, but there are a lot of kinds; SAFE innovation that you are allowed to be creative, to think about ways where they can have a big impact on the bottom-line, and those are, if you like, good ideas that have a low risk capacity; coming up with technical ideas… I don’t know if that’s happening here… that’s where the guilty pleasure of innovation is” [emphasis added]

The excerpt demonstrates the scientists’ resistance to accept the business articulation of innovation, which essentially expects low risk and safe innovation with applied results. In the risk-averted commercial culture, blue-sky and uncertain regarding results innovation is being excluded. The approach tries to control uncertainty, which is a key-characteristic of technological innovation, by means of a business case and stage-by-stage estimation of profits. ‘Technical’ innovation is described as ‘guilty pleasure’, which emphasizes that it is a ‘forbidden’ activity in the commercial order –an activity that many scientists looked back to with nostalgia. The Technology Groups concentrated on putting proposals in the Eureka funnel, which they considered the main system to support innovative projects, since its rhetoric borrowed elements from the scientific understanding of innovation; i.e. Eureka set out to support long-term and highrisk research. However, the rhetoric did not meet the practice, and the actual process of selection of projects frustrated many scientists, who realized that what the Eureka team meant by ‘high-risk’ projects was not exactly what the scientists felt ‘real’ innovation would be:

355

Knowledge and the Politics of Innovation

“I thought Eureka would be for that, but a lot of the Eureka ideas are fairly normal, they don’t seem particularly radical at all, so I have the impression now, within this group anyway, within the company, Eureka is really a way of getting funding for the more long-term ideas, which Oil Co don’t want particularly to fund themselves, the Oil Business I mean, the sales related business, so I have to alter my impression of Eureka [laughs]” [emphasis added] Scientists attributed the perceived inconsistencies to the lack of a shared conceptual framework, and found the opportunity to assert their role in shaping the research strategic framework. “we’ve never discussed it between different teams, so I think because we have never discussed it, each one tends to bring their own, it’s never discussed as a Technology Group B ‘what is Innovation, what are we going to do about it, how much time we are going to spend on it, what is the procedure’, I mean Eureka as such has been mentioned and promoted etc. but I don’t think that within the Technology Group there is a shared vision” It is true that most of the interviewees suggested their own definitions of innovation and best ways to support it. Ultimately, what they were trying to do was to gain back some of the research structures that existed before the commercialization of the research site. Furthermore, what they pursued was to have their saying about the criteria for assessing innovation projects.

Conflict over Funds Despite the scientists’ frustration, Eureka was not abandoned, but acquired a secondary use: it was increasingly treated as a pot of funds that could sustain some jobs for a while. Eureka money was very attractive for the Technology Groups, which under the commercial identity, had to find the resources to survive and prove their value to

356

the Group. Hence, a battle between Technology Groups and Eureka over getting the funding or in some cases, as the following excerpt suggests, a battle over getting control of the money emerged. The Eureka-member introduced this concern: “[…] now, the reason why we [Eureka team] are here, is because if you allow all the R&D funding to go through the Businesses, through the Global Fuels Business or Lubes or whoever, then there is a tendency for it to get driven to the short-term, so we are here to provide an alternative to short-term time zone; now, short-term does not necessarily means, it means core, everything is driven to the core, because of the short-term objectives, so we are here to provide an alternative to that” The commercialization turn pushed the Technology Groups to constantly improve their financial performance, and consequently coreprojects became their main priority. The Business in principle liked to fund radical innovative ideas, but it is difficult to see how this individualistic, survival-directed approach to management would let innovation become the Technology Groups’ everyday life. Furthermore, this struggle addresses clearly the issue of governance of the innovative process –which is related to the question of governance of knowledge: who decides what is a good or a bad idea, and who knows what is to be decided. The Technology Groups doubted the adequacy of the innovation panel and some asserted the control of the resources.

Group Level New ‘Innovation’ vs. Old ‘Scientific Work’ The new and still vaguely construed innovation discourse has offered many career opportunities to those, who realized early that the new innovation game needed someone to set the rules –i.e. to say what is innovation, what is a good and a

Knowledge and the Politics of Innovation

bad idea, etc. As the relevant literature prescribes, innovation needs a hero, i.e. someone who is ready to fight against the tides to make things happen. Hence, ‘innovation stars’, emerge: these were individuals who saw in the new unsettled innovation game the opportunity to add some hits in their curriculum, and hence become visible to the business. Their increasing status and power frustrated some senior research colleagues, who in their turn refused to participate in these local innovation systems, and reached directly for higher innovation mechanisms. “I…perhaps had a concern with some things going into the ideas machine didn’t have any depth, and we all … we all on our jobs in some way or another innovate, but we don’t actually recognize this as innovation, and you know, some guy might be working very hard on a research project and be really doing a lot of very impressive innovation, but he doesn’t sell himself to the management team or I don’t know and says ‘this is innovation’, he just says ‘well, this is part of my job’ and he just does it, and another guy might not be working so hard, he might be coming up with a very simple, not very clever idea, and he might say ‘this is innovation’ and then just sell it” The scientist explicitly referred to the momentum innovation discourse was gaining within Oil Co, and the way people exploited it to promote themselves. The account shows how ‘innovation’ has turned into a ‘buzzword’, a vaguely defined and all-inclusive concept that allowed those who controlled it to manipulate it according to their interests.

Mistrust and Surface Politics In addition to politics enacted at the structure, the same scientist referred to politics at the surface level, by expressing his concerns regarding the (lack of) evaluation criteria in the way ideas were assessed. What is interesting is not his concerns per

se, which was actually a political way to state his objections, but how he used his scientific authority to ‘boycott’ the system which was devised by an ‘innovation star’. In other words, by refusing to review and submit further ideas, he exposed the weaknesses of the system. “I think … I have a slight worry about how those ideas are assessed, because… what’s happened with some ideas, some of the ideas… the person assessing them thought that ‘oh, they are in my…in Bob’s area’, and so he sent these 6 titles from the web and said ‘Bob, you should be looking at these’ and I said, I just sent back an e-mail saying ‘no’, so from that point of view, if all those 300 hundred ideas are just… not being pushed forward the right way, perhaps I would have a worry about it, well of course some of the ideas have been pushed forward from the Ideas Machine…., but…., I certainly, I’ve probably submitted 12 ideas into it … in the first quarter of this year, and I haven’t submitted any for the past 6 months” [emphasis added] The exposed justification for not participating in the local innovation games was common in all discursive attacks against the existing innovation systems -higher or local-, and appeared as a legitimate behaviour: where the scientists did no participate, where the conceptual framework or criteria were not clear, where the evaluation took place behind closed doors, then people would not trust the process.

Individual Level Conflict of Career Opportunities Nevertheless, not all scientists engaged in battles in the innovation arena; some were not concerned with the ‘new’ game, and chose to focus on learning the rules of commercialization, which, no doubt was the new hegemony of the site-life. Especially young recruits and scientists in managerial posi-

357

Knowledge and the Politics of Innovation

tions, even though content with the revival of innovation, preferred to see it as someone else’s job, while they were going on with their everyday work. Commercialization had certainly affected scientists’ roles, and most importantly the worklife on site: on one hand, it imposed a regime of tight resource-control, on the other hand, it prepared the new recruits for promising careers in commercial positions. Consequently, many young scientists preferred to develop the necessary managerial skills for a career away from the labs. “the big problem I think we have is time and pressures on our resources, as I say everything has changed the past 2 years and we have become more commercial, people now have less time ehm, I find myself occupied 8 hours or even 10 hours per day, therefore I guess there are things that are more critical to my learning and personal development […]” [emphasis added] The young scientist here comfortably used concepts that acquired legitimacy from the commercial discourse. I should stress here, that the question is not whether people had actually less time or they felt like that being stressed by the intense pace of changes. What matters for the present analysis is that ‘no time’ was a valid argument in the new commercial culture, and widely accepted as a shared reality; hence it provided a legitimate excuse for not engaging this extra time that innovation required. This prioritization of ‘commercial targets’ over ‘innovation time’ was supported by the Oil Co commercial culture, which was described largely as ‘conservative’ and ‘risk-averted’. In other words, especially young scientists did not want to invest their time on experimenting with uncertain ideas, because possible failures would impede their career development. Here, it becomes evident how coexisting discourses collide and create options for individual action, i.e. individuals can choose their actions from a repertoire of equally valid, but competing, discourses.

358

DISCUSSION AND FUTURE RESEARCH The study examined two innovation systems implemented in two Technology Groups of HydroCarbon Solutions. The two mechanisms were formed by two different discourses on innovation, the rational planning and the culture management, and set out to achieve different objectives. However, I showed how they both encountered similar difficulties in getting the scientists involved in the new innovation game. I argue that a clash of worldviews and interests, personal and group antagonisms, mistrust and feelings of exclusion from decisions, in other words a range of conflicts at the organizational, group and individual level, turned the innovation systems into databases where low quality or irrelevant ideas were deposed. Table 1 presents different elements of the discourses on innovation management, which were encountered during the fieldwork. These discourses provided the members of the organizations legitimate arguments, which they used in order to achieve their own objectives, while there was no hegemonic view on innovation management. Beyond the ‘rationalistic’ understanding of innovation management at the Technology Groups, which assessed how many ideas have been produced and how much money secured, the innovation move had a political aspect as well, which is evident in the transformation of power relations; while the knowledge discourse is gaining momentum, the innovation game opens up opportunities for differentiation for groups and individuals. The findings showed how some creative scientists got empowered by the revival of innovation, whereas others got marginalized. Some individuals saw their career prospects widen by endorsing the new innovation discourse, and rushed in to take on active roles. Being at the interface regarding innovation with Hydro-Carbon Solutions and the parent Oil Co, they had the legitimated authority to judge what innovation is according to the needs of their sponsors. The

Knowledge and the Politics of Innovation

Table 1. Competing discourses of innovation (adapted from Asimakou, 2009a: p.177) Innovation as Rational Planning

Long-term Commercial Innovation

Innovation as Culture

Scientific Technological Innovation

Type

Marketable ideas

Small technological ideas

Small, technological, administrative, operational, etc. ideas

Radical technological ideas

Objectives

Improved and/or new products

New products

Improved business performance

Contribution to knowledge; groundbreaking innovations

Assumptions

Innovation process as a thing to use when needed; innovation as a cost

Innovation as measurable economic element; innovation as a cost

Innovativeness as a personality trait; innovation as an asset

Innovation as a scientific community trait; innovation as an asset

Key-concepts

‘Safe’ risk

Collaboration between business and scientists

Cultural change

Uncertainty; knowledge sharing between scientists

Rhetoric

Commercial innovation as competitive advantage

Innovation strategic framework; problem solving for customers

All-embracing; big and small ideas (instead of good and bad)

Curiosity oriented; Problemsolving for knowledge

Practices and tools

Funds, Innovation Management Groups, innovation in scorecards and in Personal Performance Contract

Funds, Funnel, Panel, Business Case, Database, Networks and Alliances

Funds, Conferences, Database, Innovation Hero and Team, Innovation Chats

Funds, conferences, collaborations, publications

Responsibility

Scientists

Business, market sector and scientists

All staff

Scientists

Unanticipated consequences

Eradication of managerial responsibility; lack of strategic framework

Collision of mindsets; lack of shared understanding

A sense of democratization of workplace

A secluded culture –‘Ivory Tower’

prestigious innovation language game, especially at the local level, once established as the only right way to innovate, becomes a ‘controlled area’ from where those who did not support the related processes were excluded, i.e. called indifferent and non-innovative. At a higher level, Eureka attempted to merge the commercial ‘rationality’ of the Business with the scientists’ creativity in one discourse and one process by forcing both sides to collaborate for the sustainability of the organization. However, the findings indicated that the difficulties Eureka encountered were not merely due to different mindsets, but rather a power struggle between different groups over articulating innovation and controlling the available resources. Essentially, the scientists did not trust the Business people, who controlled the financial resources, that they could drive innovation for the interests of knowledge

production and the benefits of participant groups. The findings showed instances of Technology Groups that tried to take control over financial resources and ultimately over ‘innovation’, either directly e.g. by restructuring like Technology Group B, or indirectly by debating over what innovation is and over the value of the proposals. The scientific population, feeling marginalized or pressurized by commercialization, appealed to arguments deriving from the dominant commercial discourse or the reviving scientific to claim time, resources and career opportunities –whether this meant activities in the innovation arena or in commercial posts. The scientists who wanted to do research on their own terms used arguments from the scientific language game to justify their reluctance to collaborate, whereas the youngsters used arguments from the commercial discourse to justify their innovation ‘inertia’. Clearly, the

359

Knowledge and the Politics of Innovation

two discourses (i.e. commercialism and scientific innovation), and the orders they subsequently created, not only could they not fully support each other, since they reflected opposing rationalities and practices, but furthermore, their collision created possibilities for a variety of actions. The widely admitted problem that Business and scientists traditionally cannot work with each other is the best example of this opposition of rationalities –and this could not be resolved by forcing tighter control. This presents us with a key-question, which the two innovation mechanisms did not address, i.e. how to create an innovation concept, and hence a practice, that would achieve the consensus of the involved parties. The question that sharply arises is the political question of ‘who decides what is a good idea, who sets the criteria and who or what legitimizes this decision’; in other words, whose interests (e.g. Business, Science, Society?) innovation would ultimately serve. The account so far emphasized the significance of governance of the knowledge processes –which seems that it is not only a philosophical and sociological concern, but also Oil Co’s reality. From here on, more research is needed in the area of governance of the knowledge production process, both at macro (across organizations) and micro level (within an organization), in order to understand how the process affects various stakeholders, and the actual role of each stakeholder in this process, and ultimately the quality and social relevance of innovations. Furthermore, adopting the view that the essence of innovation is knowledge creation, and knowledge is a contested praxis, then more research is needed on how to stimulate this process given the conflicts and antagonisms that this would create. Most critically we need to understand how new knowledge replaces the already existing one at the organizational level; in other words, how a regime of truth is challenged and altered in an organization.

360

CONCLUSION The models for managing innovation attribute managers a great degree of control over the process, assuming that employees would embrace a well-designed innovation mechanism; the discussion above highlighted the limitations of such a manager-centred approach. Evidence from Hydro-Carbon Solutions suggests that the population, whose valuable ideas were sought to exploit, needed be involved in the governance of the process: the scientists, while feeling empowered by the momentum of knowledge discourse, claimed their right to have a voice over deciding the ‘what’ and ‘how’ of the research strategy. This point is crucial, since most innovation systems exclude the users from their management –whether this may be the articulation of innovation, the practices to follow, the setting of criteria or the evaluation of projects. This act that essentially means a redistribution of powers in organization would benefit so much the organization as much as society at large, since decisions for the value of technical ideas would not be taken by a singleminded decision-center. In sum, the study briefly reviewed the main approaches to innovation management, and their impact on R&D firms. It suggested that these approaches have contributed to the construction of a powerful dominant discourse, which shapes thinking and actions in organizations. However, the models of analysis neglect the power-dimension, which is critical to understand innovation management. The contribution of this chapter is that it brings together the insights and developments of knowledge management field into the innovation management literature. Contemporary managerial discourse has attributed knowledge and innovation a central role in achieving business sustainable growth, especially in R&D firms, where knowledge is the capital, the input, and the output of their operations. Approaches to innovation management tend to take a structural or a voluntaristic take in understand-

Knowledge and the Politics of Innovation

ing the related phenomena. However, the power dimension, which is said to be always interwoven with knowledge (Foucault, 1971; Howarth & Stavrakakis, 2000) has been widely neglected by adopting a very narrow view on organizational politics. The chapter conceptualizes influential innovation approaches as a powerful discourse, and adds the power dimension to the analysis of innovation processes. Given the call for refined methodologies and models for analysing innovation, the study suggests another methodological approach to conceptualize and analyze the question under investigation, and offers new empirical data. Most importantly, by bringing the insights of the knowledge management literature into the innovation field, it illustrates the importance for the readers to understand how the politics of knowledge production affect innovation in a knowledge-based firm.

REFERENCES Adler, P. (2001). Market, hierarchy, and trust: The knowledge economy and the future of capitalism. Organization Science, 12(2), 215–233. doi:10.1287/orsc.12.2.215.10117 Alvesson, M., & Willmott, H. (Eds.). (1992). Critical management studies. London, UK: Sage. Asimakou (2009a). Innovation, knowledge and power in organizations. Oxon, UK: Routledge. Asimakou (2009b). The knowledge dimension of innovation management. Knowledge Management Research and Practice, 7, 82-90. Ball, S. J. (1990). Introducing monsieur Foucault. In Ball, S. J. (Ed.), Foucault and education: disciplines and knowledge. London, UK: Routledge. Benner, M. J., & Tushman, M. L. (2003). Exploitation, exploration, and process management: The productivity dilemma revisited. Academy of Management Review, 28, 238–256.

Berger, P. L., & Luckmann, T. (1966). The social construction of reality. New York, NY: Doubleday. Bessant, J., & Tidd, J. (2007). Innovation and entrepreneurship. Chichester, UK: Wiley & Sons. Betz, F. (2003). Managing technological innovation (2nd ed.). New York, NY: John Wiley. Blackler, F. (1993). Knowledge and the theory of organizations: Organizations as activity systems and the reframing of management. Journal of Management Studies, 30(6), 863–884. doi:10.1111/j.1467-6486.1993.tb00470.x Blackler, F. (2003). Knowledge, knowledge work and organizations: An overview and interpretation (reprinted). In Tempest, S., Starkey, K., & McKinlay, A. (Eds.), How organizations learn: Managing the search for knowledge (pp. 339–362). London, UK: Thomson Learning. Boisot, M. (1998). Knowledge assets: Securing competitive advantage in the information economy. New York, NY: Oxford University Press. Brown, J. S., & Duguid, P. (1991). Organizational learning and communities of practice: Towards a unifying view of working, learning and innovation. Organization Science, 2(1), 40–57. doi:10.1287/ orsc.2.1.40 Brown, J. S., & Duguid, P. (2001). Knowledge and organization: A social-practice perspective. Organization Science, 12(2), 198–213. doi:10.1287/ orsc.12.2.198.10116 Brown, J. S., Durchslag, S., & Hagel, J. (2002). Loosening up: How process networks unlock the power of specialization. [). Retrieved from www.mckinseyquarterly.com]. The McKinsey Quarterly, 2. Carr, N. (2003). Why IT doesn’t matter. Harvard Business Review (June). Retrieved from http://hbswk.hbs.edu/ item.jhtml?id=3520&t=innovation

361

Knowledge and the Politics of Innovation

Chatzkel, J. (2007). Conference report 2006 KMWorld Conference review. Journal of Knowledge Management, 11(4), 159–166. doi:10.1108/13673270710762783

Gupta, A. K., Smith, K. G., & Shalley, C. E. (2006). The interplay between exploration and exploitation. Academy of Management Journal, 49, 693–706. doi:10.5465/AMJ.2006.22083026

Clegg, S. (1989). Frameworks of power. London, UK: Sage.

Hassard, J., & Pym, D. (Eds.). (1990). The theory and philosophy of organization. London, UK: Routledge.

Collins, H. M. (1993). The structure of knowledge. Social Research, 60(1), 95–116. Dierkes, M., Antal, A. B., Child, J., & Nonaka, I. (2003). Handbook of organizational learning and knowledge. Oxford, UK: Oxford University Press. Downs, G., & Mohr, L. (1979). Toward a theory of innovation. Administration & Society, 10, 379–408. doi:10.1177/009539977901000401 Drucker, P. F. (1993). Post-capitalist society. London, UK: Butterworth-Heineman. du Plessis, M. (2007). The role of knowledge management in innovation. Journal of Knowledge Management, 11(4), 20–29. doi:10.1108/13673270710762684 Fairclough, N. (1989). Language and power. London, UK: Longman. Fairclough, N. (1992). Discourse and social change. Cambridge, UK: Polity Press. Fonseca, J. (2002). Complexity and innovation in organizations. London, UK: Routledge. Foucault, M. (1971). Orders of discourse. Social Sciences Information. Information Sur les Sciences Sociales, 10(2), 7–33. doi:10.1177/053901847101000201 Foucault, M. (1980). Power/knowledge, selected interviews and other writings 1972-1977. Sussex, UK: The Harvester Press. Frost, P., & Egri, C. (1991). The political process of innovation. Research in Organizational Behavior, 13, 229–295.

362

Howarth, D., & Stavrakakis, Y. (Eds.). (2000). Discourse theory and political analysis: Identities, hegemonies and social change. Manchester, UK: Manchester University Press. Ichijo, K., & Nonaka, I. (2006). Knowledge creation and management: New challenges for managers. Oxford, UK: Oxford University Press. Kanter, R. M. (1988). When a thousand flowers bloom: Structural, collective and social conditions for innovation in organization. Research in Organizational Behavior, 10, 169–211. Klein, J. (2001, March). Innovation as discourse. Paper presented at 10 th IAMOT Conference, Switzerland. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge, UK: Cambridge University Press. Lengnick-Hall, C. A., & Wolff, J. A. (1999). Similarities and contradictions in the core logic of three research strategies. Strategic Management Journal, 20, 1109–1132. doi:10.1002/ (SICI)1097-0266(199912)20:12<1109::AIDSMJ65>3.0.CO;2-8 Lyotard, J.-F. (1984). The postmodern condition: A report on knowledge. Manchester, UK: Manchester University Press. Markham, S. (2000). Corporate championing and antagonism as forms of political behaviour: and R&D perspective. Organization Science, 11(4), 429–447. doi:10.1287/orsc.11.4.429.14599

Knowledge and the Politics of Innovation

McFarlan, W., & Nolan, R. (2003). Why IT does matter. Harvard Business Review (August). Retrieved from http://hbswk.hbs.edu/ pubitem. jhtml?id=3637&t=innovation Orr, J. (1990). Sharing knowledge, celebrating identity: War stories and community memory in a service culture. In Middleton, D., & Edwards, D. (Eds.), Collective Remembering (pp. 168–189). London, UK: Sage. Park, J. H. (2006). The role of trust on knowledge creation in a virtual organization: A social capital perspective. Journal of Knowledge Management Practice, 7(4). Retrieved from http://www.tlainc. com/ jkmp.htm. Polanyi, M. (1967). The tacit dimension. London, UK: Routledge & Kegan Paul. Potter, J., & Wetherell, M. (1987). Discourse and social psychology: Beyond attitudes and behavior. London, UK: Sage. Rogers, E. (2003). The diffusion of innovations (5th ed.). New York, NY: Free Press. Simsek, Z. (2009). Organizational ambidexterity: Towards a multilevel understanding. Journal of Management Studies, 46, 597–624. doi:10.1111/ j.1467-6486.2009.00828.x Slappendell, C. (1996). Perspectives of innovation in organizations. Organization Studies, 17(1), 107–129. doi:10.1177/017084069601700105 Smith, D. (2007). The politics of innovation: Why innovations need a godfather. Technovation, 27(3), 95–104. doi:10.1016/j.technovation.2006.05.001 Sveiby, K. E. (1997). The new organisational wealth: Managing and measuring knowledgebased assets. San Francisco, CA: Berret Koehler Inc. Takeuchi, H., & Nonaka, I. (2004). Hitotsubashi on knowledge management. Hoboken, NJ: John Wiley & Sons.

Trott, P. (2008). Innovation management and new products development. 4th edition. Essex, UK: FT Prentice Hall (Pearson Education Limited). Tsoukas, H. (1996). The firm as a distributed knowledge system: A constructionist approach. Strategic Management Journal, 17(Winter Special Issue), 11-25. Tsoukas, H. (2001, April). Where does new knowledge come from? Keynote addressed at the International Conference Managing Knowledge: Conversations and Critiques, Leicester University, UK. Usoro, A., Sharratt, M., Tsui, E., & Shekhar, S. (2007). Trust as an antecedent to knowledge sharing in virtual communities of practice. Knowledge Management Research and Practice, 5(3), 199–212. doi:10.1057/palgrave.kmrp.8500143 Van de Ven, A., & Rogers, E. (1988). Innovations and organizations: Critical perspectives. Communication Research, 2, 632–651. doi:10.1177/009365088015005007 Wodak, R., & Meyer, M. (Eds.). (2001). Methods of critical discourse analysis. London, UK: Sage. Wolfe, R. (1994). Organizational innovation: Review, critique and suggested directions. Journal of Management Studies, 31, 405–432. doi:10.1111/j.1467-6486.1994.tb00624.x

KEY TERMS AND DEFINITIONS Discourse: I is the articulation of a web of relations among signifiers, which produces knowledge, i.e. regimes of truth. According to Ball (1990, p.2) discourses ‘embody meaning and social relationships, they constitute both subjectivity and power relations’. Innovation: Fundamentally the process of generating new knowledge, innovation has been conceptualized as a technical or administrative

363

Knowledge and the Politics of Innovation

issue, a social or a political matter (Carr, 2003; McFarlan & Nolan, 2003; Rogers, 2003; Brown, Durchslag & Hagel, 2002); it has been defined as groundbreaking new knowledge, or as the outcome of small incremental changes. It can be either new theory or product. Here, a discursive approach is adopted, which embraces all previous definitions; it conceptualizes innovation as a discourse which re-articulates its web of relations among signifiers, depending on the politics and the context, where these signifiers acquire meaning from. Innovation Management: A set of technologies, which largely aim to manage, i.e. control the process of generating new knowledge in a knowledge-based organization. Here I distinguish two approaches: those who attempt to rationalize the process by splitting into small measurable and controllable stages (Bessant & Tidd, 2007; Trott, 2008), and those who assume that the process per se is incontrollable, and aim to influence it by controlling its context/environment (Kanter, 1988; Smith, 2007). Alternative takes to innovation management suspend the idea of controlling, and conceptualize it either as a process of creating new meanings (Fonseca, 2002), or as a political process, whereby groups constantly negotiate or collide over the articulation of the rules of the innovation language game (Frost & Egri, 1991). The latter is the working definition adopted by this chapter. Knowledge: Following Foucault (1980), knowledge is a regime of truth, which have a normalizing effect upon phenomena and practices, making some of them appear good, truthful, respectful, whereas others are considered

364

harmful, wrong, shameful, etc. Foucault talks about knowledge/power, since for him the two always co-exist in a single phenomenon. From this respect, knowledge/truth is always interwoven with systems of power, which it sustains, and with effects of power which induce it. Knowledge Production: The system of rules, process and practices that frames and supports the systematic pursuit of knowledge; within this system the dominant group each time prescribes rules, roles, directions and actions, and decides what is valued as knowledge. It is worth noting that the process is highly political and always contested by other interest groups (Lyotard, 1984). Politics of Knowledge: The subtle or direct conflict between groups, while they try to impose their articulation of a dominant discourse. The assumption here is that, since discourses generate a regime of truth, groups have an interest in influencing what this truth should be. Power: It is not simply the ability of someone to manipulate and control the behaviour and actions of others, but it is a wider notion, which forms structures, practices and subjectivities in the organizational life (Clegg, 1989). Power is always present where knowledge phenomena and effects emerge. Technological Innovation: The outcome of a long-term scientific research project, which is based on a change of the knowledge in the field. Most often it is contrasted to new product development, which is the outcome short-term projects that aim to small changes, and may not be scientifically significant.

365

Chapter 20

Innovation and Knowledge Management for Sustainability: Theoretical Perspectives

René J. Jorna Frisian Academy (KNAW), The Netherlands & University of Groningen, The Netherlands Niels R. Faber Frisian Academy (KNAW), The Netherlands & University of Groningen, The Netherlands

ABSTRACT This chapter supports the argument that innovation is a special case of knowledge management; it is about knowledge creation. With economic profit as its driving force, innovation is mostly short term and commercial, feeding the question whether innovation really can be applied to ecological and social systems. The problem concerns the goal of innovation: what does it suppose to realize? In this chapter, we combine knowledge management (KM) and innovation concepts with sustainability and we argue that as long as the emphasis in innovation is on “profit” and not on “people” and “planet” (the three P’s of sustainability) we have no guiding mechanism for innovation, namely the existence of a sustainable future. In a sustainable perspective, innovation becomes an instrument that benefits society at large. In this chapter, we explore concepts behind issues of KM and innovation through literature review and we argue along three lines of thinking. First, we demonstrate that innovation is knowledge creation at an individual and collective level. Second, we argue that innovation should be a means and not a goal. Third, we offer a perspective to operationalize the relationship between knowledge, innovation and sustainability. Sustainability as an issue requires adaptation of human and social systems to ever-changing environments. This continuous need for change demands people to constantly develop and obtain new knowledge to realize the balance between system and environment. We conclude this chapter by introducing concepts on Knowledge of Sustainability (KoS) and Sustainability of Knowledge (SoK) that form the synthesis of our discussion, and we set the outline of a framework for sustainable innovation. DOI: 10.4018/978-1-61350-165-8.ch020

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovation and Knowledge Management for Sustainability

INTRODUCTION The debate about the value of innovation is not new. Beginning in the 80s and getting stronger in the 90s, the EU has continuously stimulated innovation. One might say, metaphorically, that innovation looks like a medicine that can cure almost all social, technical and economic ailments. (Kleinknecht, 1990; Nooteboom, 2003; 2008). Of course, continuous innovation is an illusion. Improvement is often possible, but realizing something new often also brings along “destruction” as we know from Schumpeter (1934). We therefore make a distinction in innovation as improvement and innovation as an ideology. When one argues that conservatism is the general mentality, or that our economic climate is too weak or that the entrepreneurial spirit has to be stimulated and then concludes that we have to put more effort in innovation, innovation is used as an ideology. Innovation as improvement is different, but has the assumption that one has goals in mind or knows the present shortcomings. We then have to answer questions like “which goals?” or “why changes and therefore destruction?” or “is innovation a common remedy?” It should be obvious that an answer to the abovementioned questions cannot be given by one slogan. Innovation lends itself to a multitude of meanings. Often innovation is realized with the sole purpose of propelling economic growth. A broader orientation that looks at long term changes, for example with respect to ecological and social sustainability is missing if one focuses on this short term economic growth. This opens the debate to (1) mindlessness in innovation regarding its consequences, and (2) sustainability as an “answer” to address these consequences. The present basic attitude is primarily a profit orientation in which innovation leads to the development of new products, processes and services, and if they are available (supply), there will be a demand. Therefore, economic activity will increase and so will growth, which is - as

366

economists argue - favorable for us all. On the other hand, innovation is initially nearly always a continuation of the (successful) past. It does not come out of “the blue” and very often innovation destroys existing products and services and in this way seems to decrease economic strength (“creative destruction”). It seems that everyone knows what innovation is and that it simply has to be realized. We believe that this perception is at least incomplete, especially if one looks at innovation from a knowledge management and sustainability angle. In this chapter, innovation will be considered as a special phase of knowledge management, or to be more precise, innovation is about knowledge creation and knowledge acceptance. Although we need a general definition of innovation, we will not dig into the many definitions of innovation. Many adhere to an interpretation of innovation as an instrument that leads to more (economic) growth. That is not our focus. As far as innovation is concerned, we want to show that the realization of “something new” can or perhaps should be related to an increasingly important issue that is relevant for humankind in general. We are talking about sustainability, the dynamic balance of a system - of whatever kind - and its environment. This complicated dynamic balance is not beyond innovation, it is the kernel of innovation and in realizing this balance we have to create knowledge. We have to innovate in order to make our social and natural system sustainable, not to make it endlessly grow. To our knowledge, no existing physical or biological system can grow endlessly. Utterly important for any discussion about innovation are two things: the presence of knowledge (of sustainability) and the creation of (new and sustainable) knowledge. One has to know facts, rules, practice and theories on the one hand. On the other hand, one must have the conviction that risks and uncertainties, which are implicit in any innovative activity, will be such that “something better” is realized. We will argue that the issue of sustainability requires a perspec-

Innovation and Knowledge Management for Sustainability

tive on innovation that shifts the attention from “profit” and “planet” to “people” (Elkington, 1997; 1999). The only way in realizing this is by using knowledge management. The structure of this chapter is as follows. In the section “Knowledge and KM”, we will discuss various aspects of knowledge management (KM): the functions, the phases, the levels of aggregation and the various generations of KM. In the section “Innovation as Knowledge Creation”, we will especially focus on 2nd generation KM in the sense of knowledge creation (innovation). In the section “Sustainability (the Knowledge of)” and in the section “From KoS tot SoK”, we will make the step towards sustainability by introducing the notion of “knowledge of sustainability” and we will explain what we mean by this concept. Furthermore, knowledge of sustainability has to be operational and that is why we also introduce another term: “sustainability of knowledge”. The relation between the various concepts will be depicted in Figure 2 section. In the last section, we will give conclusions.

KNOWLEDGE AND KNOWLEDGE MANAGEMENT (KM) Background The first question in discussing KM is to answer “what is knowledge?” Then confusion starts. Do we still have to define what is already known in philosophy and epistemology for more than two thousand years? The answer to this question is affirmative; because how can we otherwise manage (control, coordinate or direct) this something called “knowledge”. We will not address the age-old discussions about knowledge. However, an excellent entrance can be found in The Encyclopedia of Philosophy (EoP; Edwards, 1967). According to the EoP: “knowledge is justified true belief”. In a more elaborated formulation, knowledge can

be approached as a belief on which one has very strong grounds for thinking it is true and that it has to be justified, eventually, whether it is of the propositional or inferential kind. It is interesting to see that this EoP reference to “knowledge” is missing in most present-day’s discussions in KM. One characteristic determination of knowledge, is that - whether it is inter-individual (intersubjective) or supra-individual (Plato’s World of Forms) - it is always connected to cognition of individuals. This implies that human beings are always involved as interpretation mechanisms. From a human information-processing point of view (Newell & Simon, 1972), knowledge is interpreted information. We explain this position later after we have given a short history of KM. Until recently, knowledge management was not an issue in management science. Management is supposed to be about the control, the regulation and the command of things. However, “knowledge” only became fashionable some twenty years ago. There is a lot of debate about the meaning of KM. We believe that knowledge (management) can have three meanings (Dalkir, 2005; Jorna, 2007). First, knowledge is a fashionable, somewhat more mysterious word for information, implying that knowledge management is the same as information management. Second, knowledge management is about the assessment of all kinds of competencies of staff in organizations, in which case it is almost similar to (sophisticated) Human Resource Management (HRM). Third, knowledge management is about managing the form and content of ideas, thoughts and actions of human individuals. In the remainder of this chapter we are not favoring the information equals knowledge or the HRM interpretation. Our interpretation of KM is the focus on ideas, thoughts and actions of humans, individually and collectively. We will start with discussing various aspects of knowledge and KM. First, we argue that data, information and knowledge are parts of a three-stage rocket (Jorna & Simons, 1992; Schreiber, et al., 2000; Jorna, 2007). Knowledge is based on information, and

367

Innovation and Knowledge Management for Sustainability

in turn information on data. Data are the noises, scratches, images and other unstructured elements from reality. If data are interpreted explicitly, we speak of information. If information is used in reasoning or in performing actions by people - i.e., if it is interpreted - the result is knowledge. This line of thought, namely that knowledge involves reasoning and therefore making adaptations or interpretations on data and information, also means that in the chain from data to knowledge the degrees of freedom vary. Data can be interpreted in many different ways to serve as information. In a similar way, information can be interpreted in many different ways to serve as knowledge. The crucial distinction in information and knowledge is interpretation. This activity is carried out by humans as information processing systems. Humans are the ultimate carriers of knowledge and therefore also of innovation (Jorna, 2006). Second, when knowledge management is conceived of as information management, the assumption is that knowledge more or less equals information. Information is available, accessible and can be shared and utilized. For that reason, the relationship with information and communication technology (ICT) is almost a natural one. With the help of databases, decision support systems and other ICT-tools, sharing, storing and using information is evident. The assumption with regard to knowledge is that it is a kind of information. However, problems arise when issues of innovation and creation appear. Then the equivalence between information and knowledge stops. It is quite natural to talk about knowledge creation and knowledge acquisition, but it is strange to refer to information creation or information acquisition. To formulate it stronger, ICT cannot in itself create or acquire knowledge. These processes have to be performed by humans. Therefore, the orientation towards knowledge creation and acquisition, as very important activities and processes in organizations, shifted the attention away from the ICT-orientation of KM in which knowledge management is information management. In the

368

section “Innovation as Knowledge Creation”, we will argue that most discussions about innovation neglect or ignore the essential knowledge creation process by humans (Boden, 1994a).

Functions of Knowledge Management KM started as a discipline with regard to organizational issues of knowledge. An organization or company has to deal with storage, sharing, distribution or use of knowledge. Although every researcher in KM knows, that staff is the ultimate quality or “gold” in the performance of an organization, this individual perspective remains mostly implicit in standard innovation models (Nonaka & Takeuchi, 1995; van der Ven et al., 1999). Another issue in KM is that the development, fluctuation or dynamics of knowledge, and therefore implicitly of learning, often is not accounted for. Knowledge seems to be a static, stable and defined entity, which can be manipulated and controlled as if it were something material. Nothing is less true and it seems that common sense in KM takes the volatile or dynamic character of knowledge for granted. This is unsatisfactory. The only theoretical research that at least deals with the dynamics of knowledge has been formulated by Boisot (1995). He offers a model in which change and dynamics of knowledge are accounted for. We come back to the dynamics issue in the third section. We first want to explain the functions in organizations that KM is suitable for. In spite of all the attention for innovation, it should be kept in mind that innovation in the sense of deep exploration (March, 1991) - or second order learning (Argyris & Schön, 1978) - is not the usual practice in many organizations. One could argue “it better be so”, because being only innovative all the time is non-human or at least unrealistic. Functions of knowledge management activities are use, sharing, distribution, development and integration of knowledge elements within an organizational context. These different activities

Innovation and Knowledge Management for Sustainability

operate on different levels (Dalkir, 2005). Knowledge use points to the usual business processes of staff, focusing on the actual application of a person’s knowledge during normal task executions and processes. A person’s existing set of knowledge elements enables him to make certain decisions and to perform his task. Both the activities of knowledge sharing and knowledge distribution take place at the level of a group of co-workers, expressing the transport of knowledge between them. The distinction between these two functions concerns the mode of communication. Knowledge sharing refers to peer-to-peer knowledge transfer where knowledge elements of one person are transmitted to another who integrates it into his own set of knowledge elements. In knowledge distribution, knowledge elements of one person are transported to multiple colleagues. Knowledge integration refers to the acquisition of knowledge elements from sources that are external to the individual, focusing on the input-side of employees. From external sources, a member of an organization is presented with “new” knowledge elements. Subsequently, he integrates the knowledge elements into his own set. Knowledge development concerns the generation of new knowledge elements. The generation of new knowledge elements is mainly for most an internal (mental) activity of a person. Based on an existing set of knowledge elements, a person creates new knowledge elements. Knowledge development and creation primarily are individual human-information processing activities.

Phases in Knowledge Management As indicated earlier, innovations are based on knowledge; they have knowledge as input, as throughput and as output (see section “Innovation as Knowledge Creation” for details). In KM literature (Dalkir, 2005; Jorna, 2006) various phases in dealing with knowledge are distinguished. The

phases are knowledge creation, encoding, storage, sharing, maintenance and use. Although in Figure 1 the subsequent phases are depicted linearly, they in fact take place iteratively. Knowledge creation itself already starts with something. An actual “creatio ex nihilo” (creation from nothing) does not occur, not even in radical innovations. Within this sequence, the content of knowledge can be looked at phase by phase, with regard to the people involved, the form or type of knowledge expressed and the importance of the individual or team, respectively. The phases of creation and encoding are essential in any discussion about innovation. In the remainder of this chapter, we will discuss knowledge content only when it regards the issue of sustainability. Knowledge content is too specific and domain dependent to be discussed in general. However, we will discuss details of the types of knowledge for two reasons. In the first place because in the various phases of innovation the same type can not be dominant and in the second place because the dynamics of knowledge types is as relevant as the dynamics of knowledge content and is the motor of knowledge creation.

Knowledge Processes and Knowledge Types The relation between knowledge and innovation is simple. Knowledge is both the primary source and the outcome of an innovation. It is the input, throughput and output of innovations. Apart from creating knowledge, the key activity in innovation is making and sharing knowledge. No matter how brilliant a new product or service is, if it is not transferred or exchanged, the innovation will not be successful. To complete our picture of innovation from the knowledge perspective, a distinction can be made in content of knowledge and how this knowledge content is expressed: its form or type. Content of knowledge refers to domains, e.g., the construction of houses, physics, the working of

369

Innovation and Knowledge Management for Sustainability

computers or health care. Knowledge according to type is the denomination of how this knowledge content is presented. The various aspects of knowledge make it almost impossible to define types of knowledge unambiguously. Based on the work of Boisot (1995), we developed three types of (semiotically inspired) knowledge: (a) sensory or tacit, (b) (en)coded, and (c) theoretical (or tacit) knowledge (Jorna, 2006). The first type concerns sensory (or tacit) knowledge or just behavior. It starts from a perception of difference, interpreted in terms of an analogy. The situation is well known: when you eat a fruit you never ate before, your reaction to the new taste will be something like: “Well, it reminds me of …” and you name a fruit you know. Essential is to always recognize the situation in terms of a situation you already know. It should be clear that the bigger the sensory “problem” is, the more difficult to find an analogue. We believe that sensitiveness in sensory knowledge is often underestimated but of the utmost importance, especially in the first phases of an innovation. We hypothesize that creative people also are the ones with a big talent for expressing sensory knowledge. As we will argue later, this type of knowledge requires the physical co-presence of individuals and the use of drawings or pictures. The emphasis is not on documents and formulas. The sensory - or as some would call it the tacit - perspective underlies what Michael Polanyi has coined “personal knowledge” (Polanyi, 1967, p. 11). He describes the process involved in this knowledge type as being “aware of that from which we are attending to another thing, in the Figure 1. Phases in knowledge management

370

appearance of that thing”. Sensory knowledge is bodily knowledge: “when we make a thing function as the proximal term of tacit knowing, we incorporate it in our body - or extend our body to include it - so that we come to dwell in it” (16). Boisot identifies this knowledge as the domain of the “ineffable” (Boisot, 1995, p. 62). It cannot be coded, it is about concrete experiences, and it can be shared only with those who are physically co-present. Quantification of sensory knowledge is possible through looking at details. The more detailed a sensory experience is, the richer it is. Knowledge of details is relative to domains. A professional will be able to perceive more when looking at a certain activity than an amateur will. Sensory knowledge can therefore mostly be measured through the analysis of behavior. The second type, (en)coded knowledge, materializes when signs become codes. Certain aspects of remembered situations (visual, acoustic and tactile forms) evoke these situations. For example, concrete cows are replaced (represented) by the sound “cow” and the category of “cow” emerges. With the sign, codes emerge - a code being nothing else than a convention establishing a relation of substitution. The sign enables communication and makes communication easier. The diffusion of knowledge becomes easier where signs (codes) are available (Boisot, 1995). Externalization requires coding. In terms of Boisot (1995): the diffusion of the sign now takes place along the lines of a social community. Co-workers or partners do not have to be co-present. It is therefore extremely

Innovation and Knowledge Management for Sustainability

unlikely that coded knowledge is dominant in the early phases of innovations. Codes can be quantified by taking into account the number of elements and the combination rules a code consists of. Musical notation systems are more strongly coded (allow less ambiguity) than natural languages. Therefore, in the use of images and metaphors, coded knowledge comes closest to the non-coded sensory knowledge. Further details on the weakness or strength of codes can be found in Goodman (1968), who uses five syntactic and semantic requirements to distinguish weaker from stronger sets of signs (see Jorna, 1990; 2006). A third kind of knowledge type emerges when a third aspect is added to the aspects of sensory difference and codification (substitution), that of structure or pattern. It arises when coded signs relate to the events represented, not based on a convention, but based on patterned or structural qualities. We then have theoretical knowledge. Scientific, ideological and religious knowledge are of this type. Can one be creative in this phase? Certainly one can learn. However, no longer is knowledge acquired through searching for perceptual analogies or categorizing. Knowledge is now the result of (scientific) inquiry - empirical as well as theoretical. This means that innovation, here, is much more difficult, because an enormous accumulation of past knowledge has to be re-interpreted. An attempt to quantify theoretical knowledge is to describe this type in terms of “why” or “because” chains. The longer the chain, the more abstract the theoretical knowledge. Therefore, we believe that knowledge creation and therefore innovation at the start is more sensory than theoretical. One should note that not only scientific knowledge is theoretical. Ideologies or religions also provide complex “why” chains and therefore are theoretical too. The various types of knowledge are relevant in various phases or functions of KM. Distribution and sharing are not possible without codes and neither is storage. The use of knowledge regards

all three knowledge types, of course depending on content. As we will argue later, knowledge creation requires a mixture of knowledge types.

Generations of Knowledge Management The early propagators of KM were not much interested in innovation or knowledge creation. That has changed over the last 10 years. To make this shifting position clear, McElroy (2003; 2008) made a distinction in 1st and 2nd generation KM. First generation KM focuses on capturing, encoding, storing, sharing and distributing knowledge. These knowledge processes provide knowledge workers with valuable knowledge and are called supply-side knowledge processes. This way of practicing KM emerged when researchers and practitioners assigned the success of flourishing companies to their knowledge processing capabilities. The rise of computers boosted this form of knowledge management even more. It is therefore quite understandable that ICT and KM are often named in the same breath. The purpose of 1st generation KM is to enhance the deployment of knowledge (McElroy, 2003), the exploitation of knowledge (Jorna, 2006) or the utility of knowledge (Boisot & MacMillan, 2004). KM in this form is far from processes like knowledge creation. This observation raises some interesting questions. Where can the origin of knowledge that one wants to exploit be found? How is this knowledge created? Who is responsible for validating, judging and criticizing the created knowledge? First generation KM cannot provide answers to these questions (Firestone and McElroy, 2003). Moreover, it just assumes that valuable knowledge has already been created in an organization. First generation KM neglects the fact that valuable knowledge has to be created. In line with this observation, Boisot and MacMillan (2004) argue that a practical foundation of knowledge management in the 80s and 90s, rather than a theoretical/scientific one, had the conse-

371

Innovation and Knowledge Management for Sustainability

quence that until now “practitioners of knowledge management have not been much troubled by epistemological or foundational issues” (Boisot & MacMillan, 2004, p. 22). In other words, the primary concern of organizations and knowledge management has been with the economic utility of knowledge. To make an outing to sustainability, the focus is on the P from “profit” and not on the P’s from “planet” and “people”. Second generation KM acknowledges the fact that knowledge is created, interpreted and evaluated (Firestone and McElroy, 2003). This kind of KM is little ICT oriented and requires a deeper understanding of the sources of knowledge and knowledge processing. The two generations of knowledge management differ on two major aspects: (1) assumptions about knowledge, and (2) appropriate solutions. First generation knowledge management holds a “logistics” perspective on knowledge. Knowledge exists and can be transported and stored. Knowledge needs to be delivered at the right time, at the right place, in the right form, and in the right quality (Schreiber et al., 2000). McElroy labels the logistics view, supply oriented knowledge management. When the presence of knowledge is the focus, solutions are oriented towards delivery. The strong focus of 1st generation KM on ICT is therefore not surprising. Second-generation knowledge management challenges 1st generation knowledge management on both aspects. First, knowledge is not assumed to exist already. Second-generation knowledge management starts from the notion that knowledge needs to be produced. Knowledge production is explicitly identified as an important knowledge process in addition to knowledge integration. The production orientation strongly builds on a human originating social perspective, which counteracts the strong ICT orientation of 1st generation knowledge management. Second-generation KM perceives knowledge production as a pure human oriented and social activity, which may be supported by technology. Central processes in knowledge production are individual and group

372

learning, knowledge acquisition, knowledge claim formulation, and knowledge claim evaluation (McElroy, 2003; Peters et al., 2010). The various knowledge content and the various knowledge types have a different emphasis within the innovation stages (creation versus implementation), the innovation types (from radical via incremental to imitative) and the kinds of innovation (product, process or organization). We expect sensory knowledge to be more important in radical innovation types and in creation. At the front of new knowledge (innovation or knowledge creation), the emphasis is more on showing and demonstrating and therefore on physical co-presence. The (en)coded and theoretical knowledge could be more important in incremental innovations and implementation. Knowledge management in this sense ensures that processes of knowledge production and knowledge integration are ongoing. The outcomes of knowledge production are to be evaluated knowledge claims (Peters, 2011). We therefore argue in the next section that innovation is knowledge creation and a part of KM.

INNOVATION AS KNOWLEDGE CREATION In this section, we focus on innovation as a special case of knowledge management (see also Tidd, 2006). The stages of innovation are related to the processes of knowledge creation (production) and knowledge integration (Dalkir, 2005; McElroy, 2003). In the process of knowledge production, new knowledge is “produced” by one or more individuals. During the process of knowledge integration, newly created knowledge is communicated to “others” and integrated into existing knowledge. When observing innovation processes from the perspective of knowledge management, the two (main) phases are: a phase of invention or creation or invention and a phase of implementation (Boden, 1994a; Nonaka & Tackeuchi, 1995). During the phase of invention or creation an indi-

Innovation and Knowledge Management for Sustainability

vidual - and in some cases a group of individuals - conceives something new: a new product, a new process or a new service. The actual process of creation is often considered as taking place at the individual level, but what exactly creation is, is difficult to define. Boden (1994b), for example, uses the definition of creativity as ‘bringing something into existence’ or ‘making something out of nothing’. Csikszentmihaly (1996) states that creativity is a process whereby a symbolic domain within a culture is changed. Creativity, or “invention” as it is often called in organizational environments, can be studied from the perspective of its behavioral manifestations and of its underlying mental processes and mechanisms (Michon, Jackson & Jorna, 2003). Examples of the former are a comparison of the paintings of Magritte and Rembrandt or a comparison of the Operating Systems MS-Dos (now Windows 7) developed by Bill Gates and MacOS by Steve Jobs. Results of these analyses may consist of lists of characteristics explaining that for the software case Mac-OS is more creative than MS-Dos. Very often lists of characteristics in the software case are interpreted in terms of styles of working, interfaces, functionality or even related to personality typologies suggesting that, for instance, Steve Jobs as a person is more open, innovative or inspiring than Bill Gates. Similar lists, but different in content, can be developed for the comparison of all kinds of new products, services and processes. Practice shows that the decision as to what product or service is more creative cannot be reached easily. More interesting with respect to creation from an individual, cognitive point of view are descriptions of individual cognitive processes and mechanisms. This concerns individuals in the creativity phase, but very often also the interaction of groups in the implementation phase. Concerning individual acts of creation, the most elaborate attempt to deal with creativity within an overall cognitive, human information processing, framework has been undertaken by Boden

(1994a, 1994b). Boden uses a computational view on creativity, which also implies the issue whether and how creativity can be implemented in artificial systems. Boden gives four phases of creativity, earlier proposed by Poincaré: preparation, incubation, inspiration and verification. In Boden’s cognitive perspective, this is translated into the framework of symbols, representations and the manipulations on symbols within the human mind. Because creativity implies thinking and problem solving, it means that problem spaces or conceptual spaces are the starting point for every systematic and scientific discussion about creativity. It is, however, difficult to look at and collect empirical data, because the start and ongoing of creative mental processes and creative products are unpredictable and surprising and therefore difficult to observe. One cannot just sit and wait until a creative idea materializes. With respect to creation, two kinds of novelty are discerned, the first consisting of novel combinations of familiar ideas, the second consisting of the transformation of initial conceptual spaces themselves. The former implies that combinations are found that are improbable, the latter that combinations are formed that are impossible. The last kind of novelty is often understood as “creativity”. It is a bisociation of matrices (Koestler, 1964). These matrices are in fact the mental representations in a human cognitive system. They may consist of stories, icons, texts, images or schemas, but they form the basis upon which changes take place. Bisociation means that common structures or common combinations are dissolved and that new combinations in the human mind arise by processes such as analogy, metaphor and so on. In this sense, being familiar with and bypassing constraints lie at the heart of creativity. Removing constraints then may result in new ideas and new thoughts. It should be acknowledged that Boden’s theory says nothing about the content of a creative product or idea, it is only about unraveling the mental processes and mechanisms in, especially, the creative or invention phase.

373

Innovation and Knowledge Management for Sustainability

During the implementation phase, the idea that was conceived in the invention phase is transformed into the final innovation outcome. For instance, products are developed and implemented, services are formalized and people are trained. In the implementation phase “important others” have to be convinced and be made part of the novel product or service. This is a process of one individual interacting with many others. Here, the sociological aspect will dominate the psychological perspective. In Table 1 we depict the individual and group level for the various phases of KM in combination with innovation. Depending on the characteristics and the stages of innovation and whether an innovation is product, process or organization oriented, knowledge will play a different role, individually or collectively. In the very early phases, the individual is of utmost importance, whereas the acceptance of an innovation and its use in practice can only be done by groups in companies or in society. However, if it concerns organizational innovations, the group relevance is present from the very beginning. There is a big problem in determining the relevance of innovation. Often innovation is only positioned in terms of its neo-liberal economic valuation. As a consequence of this dominance, it is not only difficult to reject this orientation, it also requires a change of mindset, for example, if one looks at sustainability that regards the whole world population. Now, the dominant view on innovation is the “profit” perspective. An innovation is successful if it has technological and commercial success. If an innovation contributes to (economic or financial) growth, it is relevant. Even if it contributes to “planet” and “people”, it is very difficult to determine or measure this valuation and therefore one often returns to the financial measure of “profit”. Even the “Millennium Development” (MD) Goals of the United Nations are difficult to incorporate in the people

374

perspective. The MD goals are about ecological, human and social issues, but they have various shortcomings. They are not about innovation and knowledge creation, they only marginally integrate private firms and organizations, they work very much top-down (from nations to people), and not as we prefer bottom-up (from people to nations), and they are very difficult to quantify, except for basic economic needs (UNMD, 2000, p. 5). Following this direction we are back at the profit issue. The before mentioned focus in innovation on profit is like a snake biting into its own tail. This is another way of formulating the innovation paradox. If an innovation is not commercial, it is not successful and if it is not successful or commercial, it is not an innovation. The question is whether there is a way out. We argue that dealing with sustainability is required, because in contrast to what many neo-liberal economists know, but do not believe: without “people” or “planet” there is no “profit”. One could argue that “social innovation” fulfils the needs of the “people” part in the sustainability discussion (Taylor, 1970; Mulgan, 2006). We have two reasons to note differences. In the first place social innovation is about the content of innovation, comparable to product or service innovation. This is not our primary concern. In the second place the sustainability issue with regard to “people” always requires or implicitly assumes a criterion or threshold. This is not in general the case with “social innovation”. In the next two sections, we will therefore focus on sustainability. Can the issue of sustainability be attacked from an innovation point of view? We believe it can, but only if one uses a knowledge management perspective and not a “profit” perspective only. Sustainability depends on knowledge, but social sustainability also requires joint knowledge actions.

Innovation and Knowledge Management for Sustainability

Table 1. The hypothesized presence or absence of group and individual in knowledge phases Knowledge creation

Knowledge encoding

Knowledge storage

Knowledge sharing

Knowledge maintenance

Knowledge use

Individual

Yes

Yes

Yes

Little

Little

Yes

Group

No

Little

Yes

Yes

Yes

Yes

SUSTAINABILITY (THE KNOWLEDGE OF) The previous sections addressed the topic of KM, and the position innovation holds within. Central to our discussion has been knowledge as basic ingredient of both KM and innovation. Various aspects of knowledge have been discussed, such as the types of knowledge that are identified. What lacked from our discussion so far however, is substance; until now, knowledge has been described without reference to a particular instance or domain. What we mean, is that knowledge was discussed without discussing its content. Knowledge always has some content that is linked to a specific domain. Schreiber et al. (2000) refer to knowledge elements as the elementary building blocks and a knowledge domain as a coherent set of such knowledge elements that together comprise a specific domain of interest. In this way, one can speak of “quantum physics” or “gardening” to refer to a specific body of knowledge. Similar to the examples provided, the topic of sustainability denotes such a knowledge domain consisting of numerous knowledge elements. Sustainability, in contrast to for instance gardening, is not an easily described knowledge domain. Various interpretations of sustainability have been provided since the term was first used in the 1960’s in the context of dealing with environmental problems. A commonly used definition of sustainability stems from the World Commission of Environment and Development (WCED), which describes a sustainable development as “a development that meets the needs of the present without compromising the ability of future genera-

tions to meet their own needs” (WCED, 1987, p. 43). Although commonly used, this definition does not provide any footholds or further elaborations of what incorporates the knowledge domain of sustainability. Aiming to provide more footholds for businesses, Elkington (1997; 1999) uses the Triple Bottom Line to capture the domain of sustainability and provide footholds for organizations to deal with it. He describes sustainability in terms of “people”, “planet”, and “profit”. In each action of an organization, all these elements should be considered; more importantly, there should be a balance between these three elements. Elkington argues that only when inclusiveness and balance are addressed, an organization will be sustainable. However, how these criteria should be met remains to be seen. In search of an answer to the question what sustainability is about, Faber et al. (2005) found about 30 definitions of sustainability and over 300 indicator lists and practical initiatives including reports, guidelines, and policies. Although commonalities exist, each definition and initiative provides a specific perspective on sustainability, either having a broad and shallow, or a small and detailed scope on issues of sustainability. In their analysis, Faber et al. (2005) use a systematic framework to position found definitions and operationalizations. Here, we discuss the framework briefly to illustrate the complexity that is involved in dealing with the domain of sustainability. The framework is constructed using a system perspective on sustainability. The argument is that sustainability is a property that is ascribed to artificial systems. We discuss the implication of applying an artificial system perspective in the

375

Innovation and Knowledge Management for Sustainability

next section; for now we use the term system. When attributing sustainability to a system, this expresses the existence of a balance between the system and its environment, such that the system can exist forever. Faber et al.’s framework for analyzing the various interpretations of sustainability consisted of three dimensions that form a so-called sustainability space. The first dimension indicates the tangibility of the system that is dealt with, stretching from concrete (e.g., a car) to abstract (e.g., an organization). The second dimension deals with the goal that is considered in ascribing the sustainability property to the system, stretching from absolute to relative. An absolute goal orientation builds on the belief that a specific configuration of the system exists that is sustainable under all conditions. The relative goal orientation rejects the absolute stance, expressing the need to constantly monitor changes in the system’s environment and adapt the system to these changes to restore the balance. The third dimension expresses the interactions between the system and its environment. This dimension relates to the question whether changes in composing parts and internal structures of the system and its environment are taken into consideration in the sustainability property. Interactions are either static or dynamic. At the static end, the environment is considered to be static. Interactions between system and environment therefore do not change over time. At the dynamic end, changes in composition and structure of environment are considered. At the static end of this dimension only the magnitude of interactions is relevant. At the dynamic end not only the magnitude of interactions, but also the quality and the dynamic changes of interactions need to be considered (Faber et al., 2005). In relation to the present discussion, Faber et al.’s (2005) framework shows that in the knowledge domain of sustainability multiple layers of complexity are detectable. When observing the extreme corners of the sustainability space we notice the following. In its simplest form, sus-

376

tainability concerns only concrete systems. For these systems clear sustainability criteria can be formulated. Finally, as these systems operate in stable environments, their sustainability will not be affected by unforeseen changes. The complex corner of the sustainability space is occupied by an entire different species of systems. There, abstract systems reside, for which no absolute measures of sustainability are available. Even stronger, each measure that exists is susceptible to change due to continuous changes in the system’s environment, constantly affecting system-environment interactions. These two sides of sustainability put entirely different demands on anyone dealing with sustainability, particularly in relation to the knowledge s/he needs in order to grasp the domain, and all the more in starting or considering innovations of whatever kind. In the simple corner of the sustainability space, problems once encountered and solved, provide the knowledge to deal with all future problems. As indicated, these systems are concrete as well as their composing parts. The environment of these systems is stable, and a finite state of sustainability is assumed to exist. Therefore, the objective is to control the system’s behavior such that this state is maintained. Once one knows what this state of sustainability is and how it can be achieved, no new knowledge is needed to realize and maintain the system’s sustainability. However, in the complex corner of the sustainability space, systems are abstract, residing in a dynamically changing environment, which constantly demands new arrangements of the system, and a finite state of sustainability is not assumed to exist. In this corner, new knowledge is constantly required in order to understand the configuration of the system and the interactions with its environment. Also, the demand for new knowledge regarding the balance between system and environment is continuous. In other words, the knowledge domain in the simple corner of the sustainability space is clearly demarcated and the internal structure is stable. In the complex corner,

Innovation and Knowledge Management for Sustainability

the knowledge domain is under constant revision regarding knowledge elements and their interrelations, and borders move continuously. It can be discussed what the discussion means with regard to the dominance of the various knowledge types in the sustainability space, but that is not the focus of the chapter at this moment. Because its underlying assumptions are more realistic (see Faber et al., 2005), we argue that any serious discussion on the sustainability knowledge domain resides in the complex corner of the sustainability space. This implies that sustainability problems and their solutions are by definition dynamic, multi-dimensional, and require in-depth knowledge about cause-effect and process relationships. Therefore, to add an economic perspective, they are beyond “profit” or “growth”. Additionally, an intrinsic demand for the continuous generation of new knowledge is embedded. Hence, appropriate KM, which is equipped to facilitate the knowledge processing demands of this domain, is needed. In the next section, we propose a configuration of KM that facilitates such knowledge processing.

FROM KNOWLEDGE OF SUSTAINABILITY TO SUSTAINABILITY OF KNOWLEDGE The previous section added content to our discussion on KM and introduced the knowledge domain of sustainability that is dealt with in this chapter. This knowledge domain is what we label “Knowledge of Sustainability” (KoS). In this section, we extend this discussion by linking sustainability to 2nd generation knowledge management. We aim to show that particularly this combination is essential in order to deal with sustainability and with innovation. Before going into depth on how 2nd generation knowledge management and sustainability are intertwined, we need to address the issue of artificial systems we mentioned before. Some further

introduction into the domain of sustainability is required. Particularly, the history of the concept is of interest here. Many publications in recent history have shaped the sustainability debate as it currently takes place. We highlight two of them. The first publication concerns the report of the Club of Rome (Meadows et al., 1972), which addresses the relationship between economic growth and the usage of non-renewable natural resources. Using computer simulations, this think tank predicted a depletion of key natural resources in the first half of the 21st century. Although the publication was strongly criticized, it affected peoples’ mindsets on economic growth around the world. The second publication is one we already mentioned in an earlier section, namely the publication “Our common future” (WCED, 1987). This report places the effects of economic activity in a larger perspective. Besides the depletion of natural resources, pollution and social impacts are presented as issues to be addressed under the umbrella of sustainability. Because of the latter publication, when currently addressing sustainability, social, natural, and economic aspects are considered simultaneously and in an interconnected way. In spite of this broader perspective, nowadays, a strict technological perspective seems to dominate the debate on sustainability. The focus is almost exclusively on environmental and technical issues. Consequently, technical solutions are thought to be the key in resolving issues of sustainability. One seems to focus on increasing the knowledge of a technically oriented sustainability. This is necessary, but only forms half of the sustainability issue. Our perspective on sustainability deviates from a sheer technological orientation, in that we position human behavior (individually and collectively) at the core of the sustainability debate. More explicitly, we argue that sustainability is strictly linked to presence (or absence) of human action. This position follows from the distinction we make in natural and artificial systems. A natural system is any system that exists by nature. For instance, a solar system and ecosystem both are considered

377

Innovation and Knowledge Management for Sustainability

natural systems. The artificial system concept originates from a system-theoretical perspective (von Bertalanffy, 1951; Simon, 1969) that is quite common within design and engineering. We define an artificial system as any kind of system that is made and operated by humans. For example, a house, a farm and its farmland are all artificial systems. Whereas the example of the house and the farm are trivial, using farmland as an example of an artificial system is not. Although land is (a) natural (resource) in origin, it also is an artificial system, because the purpose for which it is made and used is human-oriented. For instance, in the Netherlands, all land is artificial. It is conquered from the sea and cultivated. Large parts of the land are demarcated by farmers and arranged to grow a specific kind of crop or let cattle graze. Furthermore, the land is treated in such a way (e.g., fertilization, irrigation) that it provides the highest yield or the most nutritious grass. Using the definition of artificial system and the argument that human choice and action are based on individual and collective knowledge, knowledge is identified as the controlling device of this complex artificial system. In the previous section, we explained the sustainability of a system as the existence of a balance between the system and its environment. To be more precise, sustainability is an expression of the existence of a dynamic equilibrium between an artificial system and its environment (Tietenberg, 2000). Whenever an artificial system uses inputs from its environment, it depends on the capacity of the environment to produce these inputs. Commonly, the sustainability domain recognizes these inputs to be retrieved from sources in the (ecological) environment. The outputs that flow from the artificial system to its environment rely on the capacity of the environment to process these outputs. Outputs are absorbed by systems in the environment, which are commonly referred to as sinks in the domain of sustainability. The precise configuration of the interactions between artificial system and environment, through in- and

378

outputs, results from the behavior of the artificial system. By definition, the behavior of the artificial system depends on the behavior of the human(s) and their knowledge operating it, and on the way the artificial system is constructed, very often by humans. Therefore, we see the necessity to innovate and develop knowledge of ecological as well as of social sustainability. Human behavior and knowledge interact (Jorna, 2006). Knowledge that individuals hold in their minds, shape the world and their view on the world, and consequently the actions they perceive as possible and that enables them to achieve certain goals. Hence, for sustainability depends on human behavior, and behavior depends on knowledge, the knowledge people have determines the sustainability of the artificial systems they control. From the dynamics of artificial systems and a longing for innovation leading to an increased Knowledge of Sustainability (KoS), we derive another perspective on sustainability, namely Sustainability of Knowledge (SoK). Knowledge of Sustainability (KoS) refers to the content of knowledge; the latter to the knowledge processes that handle KoS. KoS consists of (1) knowledge content about causes that underlie environmental and organizational problems, and (2) the knowledge used to solve such problems. The improvement of organizational and societal behavior, i.e. improving the sustainability of organizations and societies, builds on the problem solving capabilities in which KoS is applied and on the learning processes and its content based upon which KoS is learned. SoK, on the other hand, focuses on the processes that govern the production, creation and integration of knowledge. Sustainable innovation is innovation that centers on KoS and SoK (see Jorna, Hadders, & Faber, 2009; Jorna & Hadders 2010). As we indicate in the section “Knowledge and Knowledge Management”, second generation KM aims to produce new knowledge in addition to 1st generation knowledge management, which aims to stimulate the distribution and

Innovation and Knowledge Management for Sustainability

Figure 2. Relation between generations of KM, knowledge, learning and sustainability

use of existing knowledge. From our discussion on sustainability and the concepts of KoS and SoK, we argue that sustainability is bound to a knowledge management regime that provides the functions of knowledge production, distribution, and use. SoK is realized by 2nd generation KM. Second generation KM ensures the production and integration of knowledge that is pointed out by SoK (Jorna, 2006). In order to contribute to sustainability, KoS should be the content of SoK. In Figure 2, we combine the various concepts we used in this chapter. We first make a distinction in environment and organization; an adaptive system’s view. The environment also includes the real world, science and stakeholders. From a sustainability perspective the carrying capacity of the real world is important (McElroy, 2008). Within

(the box of) an organization we discern business or operational processes and operational and strategic management. We also position routine (first order; 1st generation KM) and creative learning (second order; 2nd generation KM). We also include KoS, SoK and Knowledge Management.

CONCLUSION Unless we find another planet Earth, the issue of sustainability will stay. As much as we have exhausted our natural and social resources in the last three centuries, just as much will we need existing and new resources to solve our present ecological and social problems. This is an innovative endeavor par excellence. It implies that we

379

Innovation and Knowledge Management for Sustainability

have to face and solve poverty, starvation, aging, untimely deaths of newborns and land and water distribution problems as issues of sustainability. Whether this concerns social or ecological aspects is not relevant. In any scenario we need more knowledge of sustainability. This is part of our main message. Another part concerns the focus to shift from only “profit” to “people” and “planet”. We believe that from the perspective of mankind any issue of ecological sustainability is also an issue of social structure and vice versa. This makes sustainability a complex and multi-layered topic. This has already been the case since ages. What has changed, however, over the last three hundred years and culminating the last fifty years, is an ever-increasing exhaustion of our natural resources. What we did in the last (ten) thousands years in situations of shortage is looking for new possibilities and frontiers that can be conquered. In addition, we succeeded in sending out expeditions to new areas and in developing new instruments, technologies and science. That game can partly not be played anymore. We reached the borders of our possibilities and resources. New land, alas, is in outer space and with more than 10 billion human beings in 2050, all requiring fulfillments of their basic needs, we have to do different things, but we especially have to do things differently. We have to discover new tools, instruments and methods. Here, the human species has a great advantage compared to other species: knowledge and innovation (as knowledge creation). We can develop new knowledge and we can (re)use existing knowledge. That is what we called investing in Knowledge of Sustainability. In empirical research we showed examples of organizational projects and case studies in sustainability (Jorna et al., 2004; 2006). However, more empirical research is necessary. Also the complex issue of measuring and quantifying aspects of the “people” part is extremely important and not solved, yet. Innovation of products, services and organizational forms is essential in deepening our knowledge of sustainability. However, because

380

sustainability concerns a dynamic balance between a system and its environment, adaptation and updating is of the utmost importance. This can be done by using Sustainability of Knowledge. It concerns doing things differently, meaning emphasizing processes, dynamics and balancing of “people” in organizations. Sustainability depends on knowledge, but social sustainability also requires joint knowledge actions. This requires also a new perspective on innovation. We should not just innovate to foster continuous growth - the economic “profit” dimension -, but innovate to keep steady states going on or to return to a steady state or balance (Daly & Cobb, 1989). This is an enormous challenge to our innovative powers and our knowledge potential. However, there are signs that we can do it, but it requires as much knowledge of sustainability as we can get.

REFERENCES Argyris, C., & Schön, D. (1978). Organizational learning: A theory of action perspective. Mahwah, NJ: Erlbaum. Boden, M. A. (1994a). Précis of the creative mind: Myths and mechanisms. The Behavioral and Brain Sciences, 17, 519–570. doi:10.1017/ S0140525X0003569X Boden, M. A. (1994b). Dimensions of creativity. Cambridge, MA: MIT Press. Boisot, M. H. (1995). Information space: A framework for learning in organizations, institutions, and culture. London, UK: Routledge. Boisot, M. H., & MacMillan, I. C. (2004). Crossing epistemological boundaries: Managerial and entrepreneurial approaches to knowledge management. Long Range Planning, 37, 505–524. doi:10.1016/j.lrp.2004.09.002

Innovation and Knowledge Management for Sustainability

Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of invention. New York, NY: Harper Collins. Dalkir, K. (2005). Knowledge management in theory and practice. London, UK: Heinemann. Daly, H. E., & Cobb, J. B. Jr. (1994). For the common good. Boston, MA: Beacon Press. Edwards, P. (1967). The encyclopedia of philosophy. New York, NY: MacMillan. Elkington, J. (1997). Cannibals with forks: The triple bottom line of 21st century business. Gabriola Island, BC, Canada: Chapstone Publishing. Elkington, J. (1999). Triple bottom line revolution: Reporting for the third millennium. Australian CPA, 69(10 and 11), 75-77. Faber, N. R., Jorna, R. J., & van Engelen, J. M. L. (2005). The sustainability of ‘sustainability’: A study into the conceptual foundations of the notion of ‘sustainability’. Journal of Environmental Assessment Policy and Management, 7(1), 1–33. doi:10.1142/S1464333205001955 Firestone, J., & McElroy, M. (2003). Key issues in the new knowledge management. Burlington, MA: Elsevier Butterworth-Heinemann. Goodman, N. (1981). Languages of art. Brighton, UK: The Harvester Press. (Original work published 1968)

Jorna, R. J. (2007). Knowledge dynamics: A framework to handle types of knowledge. In Schreinemakers, J. F., & van Engers, T. M. (Eds.), Advances in Knowledge Management: 15 Years of Knowledge Management (Vol. 3, pp. 25–48). Würzburg, Germany: Ergon Verlag. Jorna, R. J., & Hadders, H. (2010). The many faces of sustainability. Leeuwarden, The Netherlands: WaddenAcademy. Jorna, R. J., Hadders, H., & Faber, N. (2009). Sustainability, learning, adaptation and knowledge processing. In King, W. R. (Ed.), Knowledge management and organizational learning, annals of information systems 4. New York, NY: Springer Verlag. doi:10.1007/978-1-4419-0011-1_20 Jorna, R. J., & Simons, J. L. (Red.) (1992). Knowledge in organizations: Theory and applications of knowledge systems. Muiderberg, The Netherlands: Coutinho. Kleinknecht, A. H. (1990). Innovation patterns in crisis and prosperity. Schumpeter’s long cycle reconsidered. London, UK: Macmillan. Koestler, A. (1964). The act of creation. London, UK: Picador. March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–98. doi:10.1287/orsc.2.1.71

Jorna, R. J. (1990). Knowledge representation and symbols in the mind. Tübingen, Germany: Stauffenburg Verlag.

McElroy, M. (2008). Social footprints: Measuring the social sustainability performance of organizations. PhD Thesis. Groningen, The Netherlands: University of Groningen.

Jorna, R. J. (2006). Sustainable innovation: The organizational, human and knowledge dimension. Sheffield, UK: Greenleaf Publishing Company.

McElroy, M. W. (2003). The new knowledge management. Complexity, learning and sustainable innovation. Boston, MA: Butterworth-Heinemann. Meadows, D. H., Meadows, D. L., Randers, J., & Behrens, W. W. (1972). The limits to growth. Report for the Club of Rome’s Project on predicament of mankind. London, UK: Earth Island Limited.

381

Innovation and Knowledge Management for Sustainability

Michon, J. A., Jackson, J. L., & Jorna, R. J. (2003). Semiotic aspects of psychology. In: R. Posner, K. Robbering & T. A. Sebeok (Eds.). Semiotics, a handbook on the sign-theoretic foundations of nature and culture. Berlin: de Gruyter.

Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., Van de Velde, W., & Wielinga, B. (2000). Knowledge engineering and management: The CommonKADS methodology. Cambridge, MA: The MIT Press.

Mulgan, G. (2006). Social innovation: What it is, why it matters, how it can be accelerated. London, UK: NESTA.

Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press.

Newell, A., & Simon, H. A. (1972). Human problem solving. Englewood Cliffs, NJ: Prentice Hall.

Simon, H. A. (1998). The sciences of the artificial. Cambridge, MA: MIT Press. (Original work published 1969)

Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 6(1), 14–37. doi:10.1287/orsc.5.1.14 Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company: How Japanese companies create the dynamics of innovation. New York, NY: Oxford University Press. Nooteboom, B. (2003). Problems and solutions in knowledge transfer. In Fornahl, D., & Brenner, T. (Eds.), Cooperation, networks and institutions in regional innovation systems. Cheltenham, UK: Edward Elgar.

Taylor, J. B. (1970). Introducing social innovation. The Journal of Applied Behavioral Science, 6, 69–77. doi:10.1177/002188637000600104 Tidd, J. (2006). From knowledge management to strategic competence – Measuring technological, market and organizational innovation (2nd ed.). London, UK: Imperial College Press. Tietenberg, T. H. (2000). Sustainable development: Defining the concept. In Tietenberg, T. H. (Ed.), Environmental and natural resource economics (pp. 86–98). Reading, MA: AddisonWesley.

Nooteboom, B. (2008). Innovation renewed. A fourfold opening. WRR Report no. 80 (in Dutch). Amsterdam, The Netherlands: Amsterdam University Press.

van de Ven, A. H. V., Polley, D. E., Garud, R., & Venkataraman, S. (1999). The innovation journey. New York, NY: Oxford University Press.

Peters, K. (2011). Knowledge claim evaluation in innovations. PhD-thesis. Groningen, The Netherlands.

von Bertalanffy, L. (1951). General systems theory: A new approach to unity of science. Human Biology, 23(4), 303–361.

Peters, K., Maruster, M., & Jorna, R. J. (2010). Knowledge claim evaluation: A fundamental issue for knowledge management. Journal of Knowledge Management, 14, 243–257. doi:10.1108/13673271011032382

WCED-commission. Brundtland, G. (1987). Our common future: The World Commission on Environment and Development. Oxford, UK: Oxford University Press.

Polanyi, M. (1967). The tacit dimension. London, UK: Routledge.

382

Innovation and Knowledge Management for Sustainability

KEY TERMS AND DEFINITIONS Ecological Sustainability: The sustainability of a system with respect to the natural and biological resources or capacities in system and/or environment. Innovation: Equals knowledge creation, ie., the intentional introduction and application within a role, group, or organization of ideas, processes, products or procedures, new to the relevant unit of adoption, designed to significantly benefit the individual, the group, organization or wider society (West & Farr, 1990). Knowledge Management: Management of the knowledge processes of creation, storage, sharing, distribution, and usage. Knowledge of Sustainability (KoS): Knowledge in terms of content or domain about ecological and/or social sustainability.

Knowledge Types: Classification of knowledge, not based on content or domain, but on structural characteristics of its representational form. Three representational forms are distinguished here: sensory (behavioural, tacit1), coded, and theoretical (tacit2) knowledge. Social Sustainability: The sustainability of a system with respect to the social, intellectual, and constructed resources or capacities in system and/or environment. Sustainability of Knowledge (SoK): The sustainable arrangement of knowledge processes, assuring the continuous creation, distribution, and usage of knowledge of sustainability (KoS). Sustainability: The dynamic relation (might be a balance) between a system and its environment that can be maintained for the long run. A system is sustainable if the dynamic relation is in balance; otherwise it is unsustainable.

383

384

Chapter 21

Dynamic Capabilities and Innovation Radicalness: Review and Analysis Jorge Cruz-González Universidad Complutense de Madrid, Spain José Emilio Navas-López Universidad Complutense de Madrid, Spain Pedro López-Sáez Universidad Complutense de Madrid, Spain Miriam Delgado-Verde Universidad Complutense de Madrid, Spain

ABSTRACT The aim of the present chapter is to theoretically analyze the determinants of firm’s innovation radicalness (the degree of novelty incorporated in an innovation) from a dynamic capabilities-based view of competitive advantage. Nevertheless, due to the fact that dynamic capabilities’ concept suffers from certain terminological inconsistence and its components are not entirely clear in current literature, we first need to carry out an in depth review and analysis of this construct. Based on this review, we argue that dynamic capabilities arise from firm’s orientation to knowledge exploration that enables the generation of new organizational capabilities, and suggest external knowledge acquisition and internal knowledge combination as its key components. Taking into account this reasoning, we propose a theoretical model on dynamic capabilities deriving some relevant propositions considering innovation radicalness as its core output and the key element to compete in dynamic environments.

DOI: 10.4018/978-1-61350-165-8.ch021

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Dynamic Capabilities and Innovation Radicalness

INTRODUCTION Since Schumpeter published The Theory of Economic Development in 1934, there has been a rising recognition of innovation as a key factor for firm’s profitability and survival. Attending to the degree of novelty of the technology, innovation comes in many different types ranging from incremental to disruptive. Incremental innovations consist of minor changes or plain adjustments to existing products or technology and are built on firm’s current technical capabilities; radical innovations imply the development of a highly novel or unique product/service or production process and are based on changes in firm’s technological trajectory and associated organizational competencies; and disruptive innovations re-write the rules of the competitive game, creating new technological systems and sometimes even new industries (Tidd, 2001; Benner & Tushman, 2003; Dahlin & Behrens, 2005). Most innovations can be characterized as incremental, whereas radical innovations, and especially disruptive innovations, are much less frequent (Schoenmakers & Duysters, 2010). As recognized in recent literature, mere improvement of products/services or production processes is not enough to ensure firm’s viability in current environments, characterized by growing technological changes and uncertainty (Rosenkopf & Nerkar, 2001; Danneels, 2002; Schreyögg & Kliesch-Eberl, 2007). To avoid the threat of obsolescence associated with this type of contexts, organizations must develop new capabilities that depart from current ones and to translate these new capabilities into new processes, products and services (Tidd, 2006). In other words, in a growing number of competitive landscapes, firm success depends on its ability to develop innovations with a higher degree of novelty (Tidd, 2001; Benner & Tushman, 2003; Jansen, Van den Bosch & Volberda, 2006).

However, in spite of many theoretical discussions on the effect of radical innovations, the origins of this kind of innovation have so far received much less attention by researchers (Schoenmakers & Duysters, 2010). Accordingly, the aim of the present chapter is to theoretically analyze the determinants of firm’s innovation radicalness (the degree of novelty incorporated in an innovation). In doing so, the theoretical framework in which we sustain our analysis is the dynamic capabilitiesbased view of competitive advantage, which has notably improved its relevance during the last decade (Teece & Pisano, 1994; Teece, Pisano & Shuen, 1997; Zahra, Sapienza & Davidson, 2006; Wang & Ahmed, 2007; O’Reilly & Tushman, 2008; Pettus, Kor & Mahoney, 2009). This new perspective in the strategic management field, with important implications for the management of innovation, considers the evolutionary nature of the resources and capabilities of the company in relation to the changes occurred in the environment in which it operates (Lavie, 2006; Pettus et al., 2009). Hence, the dynamic capabilities framework tries to link the arguments of those theories that explain the sustainable competitive advantage based on contextual factors (Porter, 1981), with those that attempt to explain the sustainability of competitive advantage from a purely internal perspective (Wernefelt, 1984; Barney, 1991). In this sense, “the competence-based approach is concerned with the identification, development and exploitation of core competencies based on prior experience. However, it fails to address how firms cope when existing competencies become obsolete, or how firms acquire new competencies” (Tidd, 2006: 14). For these reasons, we consider that dynamic capabilities framework constitutes an adequate background to analyze firm’s innovation radicalness (Galende, 2006). Nevertheless, despite its relevance and the wide and increasing number of scientific studies focused on this perspective, the concept of dynamic capabilities suffers from certain termi-

385

Dynamic Capabilities and Innovation Radicalness

nological inconsistence (Zahra et al., 2006). This fact underscores its initial phase of development (Newbert, 2007). Additionally, the lack of consensus with regard to the factors that influence the development of this kind of capabilities by firms is even more important (Wang & Ahmed, 2007). So, according to the main objective of the chapter, we first need to carry out an in depth review and analysis of this construct. Concretely, we (1) analyze the concept of dynamic capabilities in order to reconcile the different perspectives that have been developed until now, and (2) identify the key components that enable firms to develop this special kind of capabilities, or the subsets of capabilities in order to build them up. Based on a comprehensive review of the literature, we classify the main theoretical contributions regarding dynamic capabilities in three broad approaches to this construct: the innovation approach, the contingent approach, and the capability-building approach. Although the definitions provided by each of these perspectives are quite different, we try to offer an integrative definition of dynamic capabilities that brings together all these three approaches. The main conclusion of this theoretical review and analysis is that the generation of new organizational capabilities lies at the heart of the concept of dynamic capabilities. According to several authors framed within the resource-based view and knowledge-based theory of the firm, capabilities are based on collective and tacit knowledge (Collins, 1994; Pisano, 1994; Grant, 1996; Helfat & Peteraf, 2003; Nobre, Tobias & Walker, 2010). Therefore, the generation of new organizational capabilities that enables firm’s technological developments requires the acquisition of new knowledge by firms or, in other words, that explorative learning to take place (March, 1991; Van den Boch, Volberda & de Boer, 1999; Rosenkopf & Nerkar, 2001; Danneels, 2002; 2008; Tidd, 2006; Jansen et al., 2006; O’Reilly & Tushman, 2008; Uotila, Maula, Keil & Zahra, 2009).

386

Taking into account the organization as level of analysis (Tidd, 2006), we identify two basic sources of new organizational knowledge. On the one hand, firms can conduct an explorative learning from the unexplored knowledge located inside of it (internal source). On the other hand, organizations can explore new knowledge located outside the firm boundaries (external knowledge) (Bierly & Chacrabarti, 1996; Zollo & Winter, 2002; Zahra & Nielsen, 2002; Lavie, 2006). According to the previous discussion, new capability generation requires both internal and external organizational learning. In this sense, we analyze the two main facets that, according to the literature, allow firms to carry out explorative learning from internal and external sources. These are: absorptive capacity, which allows the firm to recognize the value of new external knowledge, internalizing and applying it (Cohen & Levinthal, 1990; Jansen, Van den Bosch & Volberda, 2005); and combinative capabilities, devoted to combining the existing knowledge with novelty and flexibly for generating new organizational knowledge (Kogut & Zander, 1992; Van den Bosch et al., 1999). By analyzing both factors, this chapter highlights some of the main mechanisms that allow organizations to acquire new organizational knowledge from external sources and to generate it through current knowledge combination. Our theoretical review and analysis leads us to develop a research model linking dynamic capabilities with innovation radicalness. Based on the above reasoning, and taking into account that more radical innovations require the development of new technological capabilities, we propose that both dynamic capabilities components positively influence the degree of novelty of firm’s innovation. Additionally, we justify and propose the existence a complementary effect between them on innovation radicalness. Finally, we take into account the role of radical innovations in the success of firms operating in dynamic contexts.

Dynamic Capabilities and Innovation Radicalness

DYNAMIC CAPABILITIES CONCEPT As Zahra et al. (2006) highlights, the concept of dynamic capabilities suffers from certain terminological inconsistence. In this section we offer the theoretical literature review carried out on this construct.

Main Approaches Table 1 shows the major definitions adopted by the main authors framed within the dynamic capabilities perspective. We classify these contributions in three differentiated approaches (innovation, contingent and capability-building) that are discussed in the following paragraphs. The contributions classified into innovation approach tend to define dynamic capabilities as firm’s ability to innovate in products or services, processes or business models. This approach is based on a Schumpeterian perspective, recognizing innovation as a primary means to achieve the necessary organizational renewal for firm’s adaptation and survival in the current business environment, characterized by growing changes in technology, customers and competitors (Danneels, 2002). The second approach, this is, the capabilitybuilding approach, is rooted both in the resourcebased view (Wernefelt, 1984; Barney, 1991) and evolutionary economics (Nelson & Winter, 1982). According with the resource-based view, organizational capabilities may lead the firm to achieve a competitive advantage at present. Nevertheless, under an evolutionary perspective, current attributes do not guarantee a firm’s future viability (O’Reilly & Tushman, 2008). A competitive advantage based in the same capabilities is not sustainable during a long period of time because organizational capabilities may be eroded by external changes, such as new actions carried out by competitors (Collins, 1994; Helfat & Peteraf, 2003; Sirmon, Hitt & Ireland, 2007). Hence, the capability-building approach under-

stands dynamic capabilities as those that enable the generation of new organizational capabilities (meta-capabilities or second-order capabilities), allowing the firm to sustain its competitive advantage (Collins, 1994; Danneels, 2008). “These capabilities might include the flexibility to shift between capabilities more efficiently or faster than competitors (...), or the ability to respond to or initiate radical change” (Collins, 1994: 148). Finally, the third perspective is rooted in the contingency theory (Aragón-Correa & Sharma, 2003). Under this approach, dynamic capabilities are defined in terms of fit with firm’s environmental conditions. In this sense, four scenarios can be identified: beneficial strategic change (fit), insufficient strategic change (misfit), excessive change (misfit), and beneficial inertia (fit) (Zajac et al., 2000: 433). Dynamic capabilities are classified in the first scenario, this is, when firm’s environment requires a strategic change and firm effectively change as needed, resulting in a higher performance. Hence, authors classified under this perspective consider that firm’s dynamic capabilities follow a schema such as external signals-interpretation-response. After a careful analysis of the definitions included in Table 1, we reach the same conclusion than Zahra et al. (2006): broadly, dynamic capabilities definitions are tautological. In this sense, the three mentioned approaches define dynamic capabilities based on its results: innovation, new capabilities generation, and fit with external conditions, respectively. This tautological problem can also be found in the resource-based view literature (Priem & Butler, 2001). We do not argue that dynamic capabilities do not lead to these results. Nevertheless, we argue that a concept, in this case dynamic capabilities, cannot be described based on its output. If we do this, dynamic capabilities will be conceived as a black box (Sirmon et al., 2007). In this sense, some of the cited authors have devoted considerably efforts trying to overcome this problem. For example, Helfat and Peteraf (2003) argue

387

Dynamic Capabilities and Innovation Radicalness

Table 1. Main definitions and classification of dynamic capabilities concept Main Contributions

Dynamic Capabilities Definition

Innovation Approach Schumpeter (1934)

The innovative capacity is the architect of the process of creative destruction and consists in those characteristics of entrepreneurs as key actors in the continuous change process.

Teece and Pisano (1994: 541)

Define dynamic capabilities as “the subset of the competence/capabilities which allow the firm to create new products and processes and respond to changing market circumstances”

Helfat (1997: 339)

“Dynamic capabilities enable firms to create new products and processes and respond to changing market conditions”.

Zahra (1999: 40)

“If change is the norm, companies need to develop dynamic capabilities that can be used as platforms from which to offer new products, goods, and services”.

Helfat and Raubitschek (2000: 975)

“Ability of organizations to innovate and to adapt to changes in technology and markets, including the ability to learn from mistakes”.

Teece (2007: 1319, 1320)

Dynamic capabilities “Include difficult-to-replicate enterprise capabilities required to adapt to changing customer and technological opportunities. They also embrace the enterprise’s capacity to shape the ecosystem it occupies, develop new products and processes, and design and implement viable business models (2007: 1319-1320).

Capability-building approach Nelson (1991)

Define core competences evolution based on a hierarchic pyramid of organizational routines that take place in a Schumpeterian or evolutionary context.

Collins (1994)

Argues that there are certain organizational capabilities (meta-capabilities or high-order capabilities) that drive the rate of change of ordinary capabilities.

Pisano (1994: 93)

“In turbulent environments there is strategic value in being able to develop new capabilities rapidly”

Henderson and Cockburn (1994: 66)

“The ‘architectural competence’ o fan organization allows it to make use of its component competencies: to integrate them together in new and flexible ways and to develop new architectural and component competences as they are required”

Teece, Pisano and Shuen (1997: 515, 516)

“The term ‘dynamic’ refers to the capacity to renew competences”. They define dynamic capabilities as “firm’s ability to integrate, build, and reconfigure internal end external competences to address rapidly changing environments”. Thus, they “reflect an organization’s ability to achieve new and innovative forms of competitive advantage”.

Winter (2000: 983)

“A dynamic capability for innovation in steel making” is a “capability whose ‘output’ is not steel but new capabilities for making steel”.

Makadok (2001: 388)

The “Schumpeterian dynamic capability view highlights the importance of an alternative rent-creation mechanism – namely, capability-building – which is rather different from resource-picking”.

Griffith and Harvey (2001: 598)

“Global dynamic capabilities is the creation of difficult-to-imitate combinations of resources, including effective coordination of inter-organizational relationships, on a global basis that can provide a firm a competitive advantage”.

Zollo and Winter (2002: 340)

“A dynamic capability is a learned and stable pattern of collective activity through which the organization systematically generates and modifies its operating routines in pursuit of improved effectiveness”.

Zahra and George (2002: 185)

“Dynamic capabilities (…) enable the firm to reconfigure its resource base and adapt to changing market conditions in order to achieve a competitive advantage”. Absorptive capacity is presented “as a dynamic capability that influences the creation of other organizational competences”

Verona and Ravasi (2003: 579)

Dynamic capabilities nature is fundamentally based on knowledge and “requires the simultaneous presence of three processes at the organizational level: knowledge creation and absorption, knowledge integration and knowledge reconfiguration”.

continued on following page

388

Dynamic Capabilities and Innovation Radicalness

Table 1. Continued Main Contributions

Dynamic Capabilities Definition

Innovation Approach Winter (2003: 991)

“One can define dynamic capabilities as those that operate to extend, modify or create ordinary capabilities”.

Helfat and Peteraf (2003: 997)

“By definition, dynamic capabilities involve adaptation and change, because they build, integrate, or reconfigure other resources and capabilities”.

Zahra et al. (2006: 918; 921)

“The abilities to reconfigure a firm’s resources and routines in the manner envisioned and deemed appropriate by its principal decision-maker(s)”… “Presence of rapidly changing problems (an environmental characteristic)” for which the firm has “the ability to change the way the firm solves its problems (a higher-order capability to alter capabilities)”.

Schreyögg and Kliesch-Eberl (2007: 914)

“The notion of dynamic is devoted to addressing the continuous renewal of organizational capabilities, thereby matching the demands of (rapidly) changing environments”

Augier and Teece (2007: 179)

“Dynamic capabilities refer to the (inimitable) capacity firms have to shape, reshape, configure and reconfigure the firm’s asset base so as to respond to changing technologies and markets”.

Wang and Ahmed (2007: 35)

“Firm’s behavioural orientation constantly to integrate, reconfigure, renew and recreate its resources and capabilities and, most importantly, upgrade and reconstruct its core capabilities in response to the changing environment to attain and sustain competitive advantage”.

Ng (2007: 1486)

“An organization’s ‘dynamic capabilities’ refer to its capability to develop and seek new resources and configurations that match the changing conditions of the market”.

Danneels (2008: 519, 520)

“The first form of dynamic capability” is “the competence to build new competences”, defined as “ability of the firm to engage in exploration”.

Oliver and Holzinger (2008: 496-497)

“Dynamic capabilities refer to the ability of firms to maintain or create firm value by developing and deploying internal competences that maximize congruence with the requirements of a changing environment”.

Pettus et al. (2009: 188-189)

“Dynamic capabilities involve the organisational processes by which resources are utilised to create growth and adaptation within changing environments. (…) these capabilities are the fundamental drivers of the creation, evolution and recombination of other resources to provide new sources of growth”.

Contingent approach Eisenhardt and Martin (2000: 1106)

“Dynamic capabilities consist of specific strategic and organizational processes like product development, alliance, and strategic decision making that creates value for firms within dynamic markets by manipulating resources into new value-creating strategies”.

Cockburn, Henderson and Stern (2000: 1129)

“Competitive advantage results from a firm’s ‘strategic’ response to changes in its environment or to new information about profit opportunities”.

Zajac, Kraatz and Bresser (2000: 433)

“Dynamic fit (…) represents the situation where an organization faces the necessity to change (i.e., as defined by environmental an organizational contingencies) and does change as needed, resulting in a performance benefit”.

Rindova and Kotha (2001: 1264)

Use the term “continuous morphing” to describe “profound transformations” occurring inside the firm “to achieve dynamic fit with these environments” (“hypercompetitive, high-velocity or rapidly changing”).

Lee, Lee and Rho (2002: 734)

“In particular, dynamic capabilities are conceived as a source of sustainable competitive advantage in Schumpeterian regimes of rapid change where the window of profit-making opportunities by selling existing products is limited”.

Aragón-Correa and Sharma (2003: 73)

“Dynamic capabilities, by definition, vary with the level of market dynamism and enable an organization to adapt to changes in the general business environment”.

389

Dynamic Capabilities and Innovation Radicalness

that dynamic capabilities are oriented to the generation, integration, or reconfiguration of firm’s resources and capabilities. Verona and Ravasi (2003) propose that dynamic capabilities nature is fundamentally based on knowledge and require knowledge creation and absorption, knowledge integration and knowledge reconfiguration. Similarly, Zahra et al. (2006) consider that dynamic capabilities consist in new reconfiguration of firm’s resources and routines. In the same way, Augier and Teece (2007) include in their dynamic capabilities definition the processes of shape, reshape, configure and reconfigure of the firm’s assets base. Another valuable example is provided by Wang and Ahmed (2007) when athors argue that dynamic capabilities consist in firm’s behavioural orientation constantly to integrate, reconfigure, renew and recreate its resources and capabilities. Note that all these definitions have been classified into the capability-building approach. Once this rider has been added, it can be seen that the capability-building approach is the perspective in which more authors have been classified. One explanation provided by the literature is that new capabilities generation is required both for innovation as well as for adaptation to environmental turbulence (Henderson & Cockburn, 1994; Zahra & George, 2002; Dannels, 2002, 2008; Jansen et al., 2006; Lavie, 2006; O’Reilly & Tushman, 2008). Accordingly, we argue that, although different, the three approaches identified are not incompatible. Hence, new capabilities generation (capability-building approach) may allow the firm to innovate in products, processes or business models (innovation approach), enabling it to be adapted to a turbulent environment (contingent approach). Therefore, new organizational capabilities have to be considered as the direct output of dynamic capabilities. If a firm develops new technological capabilities, it may improve its ability to produce better products, new products, or the same products at a lower cost. Similarly, if a firm develops new market capabilities, it may better serve its current customers, or to serve a

390

new market segment (Danneels, 2008). These new technological and market capabilities are essential for firm survival in the face of changes affecting technology or customers’ demand patterns (Lavie, 2006; Sirmon et al., 2007). So, at this point, it is necessary to consider the capability-building approach as the central perspective in the academic literature focused on a dynamic capabilities-based view of competitive advantage.

The Role of Environmental Dynamism Another question emerging from the analysis of the definitions included in Table 1 is the consideration of external factors as key element in the dynamic capabilities perspective. It can be seen how most authors include environmental conditions as a fundamental factor of their dynamic capabilities definition. Furthermore, the tendency to consider environmental dynamism increases in the most recent works. This can be explained because a growing body of literature argues that the value of firm resources and capabilities is context-dependent (Collins, 1994; Brown & Eisenhardt, 1997; Teece et al., 1997; Eisenhardt & Martin, 2000; Rindova & Kotha, 2001; Priem & Butler, 2001; Barney, 2001; Helfat & Peteraf, 2003; Benner & Tushman, 2003; Jansen et al., 2006; Lavie, 2006; Sirmon et al., 2007). Under this reasoning, firm’s current capabilities, while valuable if they can provide competitive advantage at present, do not ensure that the firm would be able to change in the face of a new threat (Tidd, 2006; O’Reilly & Tushman, 2008). In this sense, rapid technological progress is considered as the most important source environmental dynamism (Benner & Tushman, 2003; Uotila et al., 2009), being a serious threat of obsolescence in firm’s current technological and market capabilities, since new technology developed or assimilated earlier by competitors will enable them to invent new products, improve the existing ones, or to produce at a lower cost

Dynamic Capabilities and Innovation Radicalness

(Danneels, 2008; Uotila et al., 2009). Hence, under the dynamics of Schumpeterian external regimes, competitive advantage sustainability lies in firm’s ability to continually reconfigure its technological capabilities base (Danneels, 2002, 2008; Benner & Tushman, 2003). “Core competencies can represent a set of tacit and collective knowledge which is developed through learning processes” (Nobre et al. 2010: 392). In this sense, firm’s survival in the face of external turbulence lies in its ability to accomplish an explorative learning that expands its current knowledge base, allowing organizational capabilities regeneration (March, 1991; Levinthal & March, 1993; Danneels, 2002, 2008; Sirmon et al., 2007; 0’Reilly & Tushman, 2008; Uotila et al. 2009). However, it would be wrong to fully assimilate dynamic capabilities to environmental dynamism. This tendency to equate the presence of dynamic capabilities to environmental conditions is one of the main sources of confusion in the literature (Zahra et al., 2006). Although it seems clear that the usefulness of dynamic capabilities is higher in turbulent environments, it is necessary to avoid confusions between external conditions and firm’s internal capabilities (Zahra et al., 2006). In a similar fashion to the arguments given in the previous section when stating that dynamic capabilities should not be confused with their outputs, we must highlight here that neither should they be confused with the optimal conditions for their implementation. Based on the previous discussion, we define dynamic capabilities as firm’s ability to constantly explore new market and technological knowledge in order to build new organizational capabilities. This ability is especially valuable in the face of rapid changes in markets and/or technologies. Thus, the greater the environmental dynamism, the greater should be the ability of the firm to engage in explorative learning that enables capability reconfiguration.

DYNAMIC CAPABILITIES AND INNOVATION RADICALNESS Until now, we have argued that firms need to continuously seek new technological and market knowledge to develop their dynamic capabilities and to be adapted to a dynamic environment. As Tidd points out, a central task in corporate strategy is “(and perhaps more important), to identify and explore the new competencies that must be added if the functional capability is not to become obsolete” (2006: 8). But, where can firms find new knowledge that enables firm’s capability reconfiguration? And how leads this capability renewal to firm’s adaptation to fastchanging competitive contexts? In this section we try to identify the basic sources of new knowledge for organizations and argue that firm’s success (adaptation) in dynamic contexts is achieved through translating new capabilities generation into more than just incremental innovations (Tidd, 2006). Again, following Tidd, “the fit with existing competencies is an important consideration when determining new product development strategy. This is particularly so for more novel or complex products (2006: 14)”. Alternatively, this author also suggest that there is an opposing motive, consisting in learn or acquire new capabilities. According to the exposed reasoning, firms should focus on this second motive more than on leveraging current capabilities in their innovation process when facing environmental dynamism. Additionally, Tidd also addresses an interesting problem in organizational learning research when he stays that “much of the research on technology management and organisational change has failed to address the issue of organisational learning. Instead, it has focussed on learning by individuals within organisations” (2006: 16). So, to overcome this problem, we must depart from individual learning and to focus on explorative learning at organizational level.

391

Dynamic Capabilities and Innovation Radicalness

In doing so, literature argues that, at organizational level, there are two basic sources of new knowledge: internal and external sources. According to Bierly and Chakrabarti, “internal learning occurs when members of the organization generate and distribute new knowledge within the boundaries of the firm”, while “external learning occurs when boundary spanners bring in knowledge from an outside source via either acquisition or imitation and the knowledge is then transferred through the organization” (1996: 124). These and other authors sustain that internal learning allows the firm just to improve its current capabilities (knowledge exploitation), whereas external learning is required to develop a broader knowledge base (knowledge exploration), becoming critical in dynamic environments. In this sense, Lavie (2006) carries out an interesting review of the method for capability reconfiguration through three main mechanisms: capability evolution, substitution and transformation. Based on evolutionary economics, capability evolution involves incremental learning through experimentation from internal sources of knowledge. Capability substitution is rooted in the competence-enhancing/destroying framework and involves radical learning from external sources, such as industry associations, alliance partners, newly acquired subsidiaries, and newly hired employees. Finally, capability transformation is an intermediate mechanism for firm capabilities reconfiguration that combines internal and external learning. By contrast, many other authors argue that not only external knowledge, but also internal knowledge sources are important for developing a successful explorative learning process (Henderson & Cockburn, 1994; Zahra, 1999; Zollo & Winter, 2000; Rosenkopf & Nekar, 2001; Tidd, 2006; Jansen et al., 2006; Morrow, Sirmon, Hitt & Holcomb, 2007; Sirmon et al., 2007; Danneels, 2008). Attending to its definition, “exploration is search for new knowledge, use of unfamiliar technologies, and creation of products with unknown

392

demand” (Greve, 2007: 945), so “the essence of exploration is experimentation with new alternatives” (March, 1991: 85). This process should not be based only on external sources, but also on the firm’s uncharted internal knowledge. As Grant argues, “the essence of organizational capabilities is the integration of individuals’ specialized knowledge” (1996: 375). Thus, according to Kogut and Zander (1992), new capabilities creation relies on firm’s ability to generate new applications for existing knowledge and to discover the unexplored knowledge located inside the firm, so, internal learning may be also explorative when it promotes new combinations of current knowledge (Van den Bosch et al., 1999; Rosenkopf & Nekar, 2001; Jansen et al., 2006; Danneels, 2008). A firm’s ability to novelty recombine and utilize its current knowledge base is what Kogut and Zander (1992) define as combinative capabilities. This internal knowledge combination enhances knowledge exchange between individuals and disciplinary boundaries and generates new organizational knowledge (Henderson & Cockburn, 1994; Jansen et al., 2006; Tidd, 2006). In other words, “boundaries matter; here it is not only the boundary that separates the organization from its environment, but it is also internal boundaries that have arisen to organize various technological subunits” (Rosenkopf & Nekar, 2001: 289) within the organization. This reasoning leads Rosenkopf and Nekar (2001) to propose two types of organizational knowledge exploration: external boundary-spanning and internal boundary-spanning. Therefore, it seems that firms can develop its ability to build new capabilities through explorative learning by investing in a special kind of internal learning based on its current knowledge combination, and by creating linkages to external knowledge sources. As Nobre et al. (2010) stays, organizational capabilities are key sources for innovation, and the higher the degree of novelty incorporated in an innovation, the higher must be the required firm’s technological capabilities renewal for its development (Tidd, 2001; Benner

Dynamic Capabilities and Innovation Radicalness

& Tushman, 2003; Dahlin & Behrens, 2005). So, in the following subsections we present the role of the two identified learning mechanism on innovation radicalness.

External Knowledge Acquisition and Innovation Radicalness External knowledge acquisition by firms is the way in which organizations carry out an external boundary-spanning exploration that integrates knowledge from other organizations (Rosenkopf & Nerkar, 2001). We consider this element as one

of the key components of dynamic capabilities. Table 2 presents the identified mechanisms that, according to literature review, enable external knowledge acquisition by organizations. Henderson and Cockburn (1994) argue that one key form of ‘integrative’ or ‘architectural competences’ especially relevant as source of sustainable competitive advantage in a dynamic context, as pharmaceutical research, is “the ability to access new knowledge from outside the boundaries of the organization” (1994: 66). As Rosenkopf and Nerkar (2001) highlights, greater levels of reliance on the firm’s own prior knowl-

Table 2. Mechanisms for external knowledge acquisition Mechanism

Author

Mergers and acquisitions

Kogut and Zander (1992); Karim and Mitchell (2000); Zahra and George (2002); Lavie (2006)Morrow, et al. (2007)

Alliances and cooperation agreements

Kogut and Zander (1992); Mowery, Oxley and Silverman (1996); Dyer and Singh (1998); Lane and Lubatkin (1998); Zahra (1999); Beinhocker (1999); Tidd (2001); Zahra and Nielsen (2002); Zahra and George (2002); Blyer and Coff (2003); Lavie (2006); Tidd (2006); Morrow, et al. (2007); Danneels (2008)

Information exchanges with customers and suppliers

Tidd (2001); Jansen et al. (2005); Galende (2006); Teece (2007); Arbussà and Coenders (2007); Grimpe and Sofka (2009); Escribano et al. (2009); Murovec and Prodan (2009); Pettus et al. (2009)

Information exchanges with competitors and complementary

Galende (2006); Teece (2007); Grimpe and Sofka (2009); Escribano et al. (2009); Murovec and Prodan (2009)

Benchmarking activities

Leonard-Barton (1992); Helfat and Raubitschek (2000); Teece (2007)

Reverse engineering

Kogut and Zander (1992); Galende (2006)

People, teams or organizational units specifically devoted to capture external knowledge (gatekeepers)

Cohen and Levinthal (1990); Helfat and Raubitschek (2000); Schoenmakers and Duysters (2010)

Relations with universities and research centres

Henderson and Cockburn (1994); Lenox and King (2004); Galende (2006); Arbussà and Coenders (2007); Danneels (2008); Bierly et al (2009); Grimpe and Sofka (2009); Escribano et al. (2009); Fabrizio (2009); Murovec and Prodan (2009)

Outsourcing and licensing

Zahra (1999); Zahra and Nielsen (2002); Zahra and George (2002)

External personnel recruitment

Kogut and Zander (1992); Zahra and Nielsen (2002); Figueiredo (2003); Lavie (2006)

Active use of technical assistance and consultants

Zahra and Nielsen (2002); Figueiredo (2003); Jansen et al. (2005); Murovec and Prodan (2009)

Participation in professional associations’ activities

Lavie (2006); Arbussà and Coenders (2007); Danneels (2008); Escribano et al. (2009)

Attendance and/or participation in congresses, conferences, exhibitions and fairs

Arbussà and Coenders (2007); Danneels (2008); Murovec and Prodan (2009)

Scientific and professional journals

Arbussà and Coenders (2007); Danneels (2008); Escribano et al. (2009)

External R&D

Cohen and Levinthal (1990); Murovec and Prodan (2009)

393

Dynamic Capabilities and Innovation Radicalness

edge is associated with more innovation, but this innovation has a lower level of novelty, because not all technological knowledge can be effectively generated or embodied solely within the firm (Bierly et al., 2009). This occurs because inwardly focused learning is one of the hallmarks of core competence. But such myopic behaviour leads to the development of core rigidities (Leonard-Barton, 1993) and competency traps (Levinthal & March, 1993). In other words, it is not possible to carry out an explorative learning only based on firm’s current knowledge combination (Sirmon, et al., 2007). Therefore, firms need continually acquire diverse and new knowledge that serve as the seed for future technological developments (Miller, Fern & Cardinal, 2007; Escribano et al., 2009). External knowledge acquisition has been extensively studied in the field of absorptive capacity literature (Cohen & Levinthal, 1990; Van den Bosch et al., 1999; Zahra & George, 2002; Jansen et al., 2005; Lane, Koka & Pathak, 2006; Todorova & Durisin, 2007). In their seminal paper, Cohen and Levinthal define absorptive capacity as “the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends” (1990: 128). This ability to scan and acquire new external knowledge is critical for firm innovation (Zahra & George, 2002). Recent empirical results in the field of radical inventions suggest that emergent technologies are key to achieve radical innovations (Schoenmakers & Duysters, 2010), highlighting the importance of speed in understanding emergent technologies. Learning from external sources expands the firm’s knowledge base, enhances the recognition of opportunities and threats, and provides access to new ideas that promote the generation of new technological capabilities (Miller et al., 2007; Danneels, 2008). As more radical innovations are based on distant knowledge and capability reconfiguration, it is expected that external knowledge acquisition by organizations contributes to develop innovations incorporating a higher degree of novelty. This

394

is especially evident in the concept and selection stages of innovation development (Tidd, 2006). For example, scientific journals may be a source of great deal of publicly available knowledge for R&D teams (Escribano et al., 2009). Similarly, collaborations with universities and research centres may enable the firm to access more rapidly and at a lower cost to new technological knowledge necessary for new product development (Fabrizio, 2009). Likewise, participation in professional association’s activities may lead the firm to have access to new trends in the market and technology, providing some clues about the future evolution of the industry (Danneels, 2008). In addition, if organization uses gatekeepers, managers will be able to take new initiatives to react faster to changing market and technological conditions (Andersen, 2004). These arguments lead us to derive our first proposition. Proposition 1. External knowledge acquisition by a firm positively influences the degree of novelty of its innovations.

Internal Knowledge Combination and Innovation Radicalness According to the reasoning followed in this chapter, we consider internal knowledge combination by firms as the second key component of dynamic capabilities. It can be defined as the way in which organizations carry out an internal boundaryspanning exploration that integrates technologically distant knowledge residing within the firm (Rosenkopf & Nerkar, 2001). As in the previous case, we have carried out a literature review to identify the mechanisms for internal knowledge combination by organizations (Table 3). In addition to scanning the environment, “the ability to integrate knowledge flexibly across disciplinary (…) boundaries within the organization” (1994: 66) is also considered by Henderson and Cockburn as a key form of ‘architectural competences’. This internal organizational knowl-

Dynamic Capabilities and Innovation Radicalness

Table 3. Mechanisms for internal knowledge combination Mechanism

Author

Internal R&D

Lenox and King (2004); Morrow, et al. (2007); Arbussà and Coenders (2007); Murovec and Prodan (2009)

R&D Intensity

Cohen and Levinthal (1990); Bierly and Chakrabarti (1996); _Arbussà and Coenders (2007)

Cross-functional and inter-disciplinary teams

Cohen and Levinthal (1990); Henderson and Cockburn (1994); Zahra and Nielsen (2002); Jansen et al. (2005); Tidd (2006); Leskovar-Spacapan and Bastic (2007); Schoenmakers and Duysters (2010)

Shared spaces

Figueiredo (2003)

Shared-problem solving

Rosenbloom (2000); Zahra and Nielsen (2002); Figueiredo (2003); Leskovar-Spacapan and Bastic (2007); Danneels, (2008)

Regular meetings to discuss new market and technology trends

Zahra and Nielsen (2002); Figueiredo (2003); Jansen et al. (2006)

Participation in decision-making

Van den Bosch et al. (1999); Rosenbloom (2000); Andersen (2004); Jansen et al. (2005)

Tolerance to failure

Leskovar-Spacapan and Bastic (2007); Danneels (2008)

Organizational structure that promotes flexible information flow

Van den Bosch et al. (1999); Rosenbloom (2000); Zahra and Nielsen (2002); Jansen et al., (2006); Leskovar-Spacapan and Bastic (2007)

Promotion of informal relationships

Van den Bosch et al. (1999); Zahra and Nielsen (2002); Jansen et al. (2006)

Job rotation

Cohen and Levinthal (1990); Van den Bosch et al. (1999); Jansen et al. (2005)Figueiredo (2003)

Flexible job descriptions

Van den Bosch et al. (1999); Leskovar-Spacapan and Bastic (2007)

Firm’s investments in training

Van den Bosch et al. (1999); Zahra (1999); Murovec and Prodan (2009)

edge combination is what Kogut and Zander (1992) defined in their seminal paper as combinative capabilities. In contrast to the conventional wisdom that radical innovations are based less on current knowledge (Bierly & Chakrabarti, 1996; Lavie, 2006), Schoenmakers and Duysters (2010) find that they are to a higher degree based on existing knowledge than non-radical innovations. These results have important implications for the management of firm’s internal knowledge, showing the need for more coordination of the knowledge within the organization, and more internal openness because different divisions might possess knowledge that, when put together, could potentially deliver a radical innovation. Again, it can be seen how, as Rosenkopf and Nekar (2001) maintain boundaries matter. But not just external boundaries, but also internal ones are

important for knowledge creation and application, and hence for innovation. As Tidd points out, “the development of new products may demand new technology-product-market linkages and, therefore, require close collaboration between different divisions” (2006: 18). This author considers information distribution a key process for organizational learning and innovation, defining it as the process by which information from different sources within an organization is shared, leading to new knowledge or understanding. This reasoning leads Tidd to stay that “firms with fewer divisional boundaries are associated with a strategy based on capabilities-broadening, whereas firms with many divisional boundaries are associated with a strategy based on capabilities-deepening” (2006: 19). So, attending to the characteristics of both incremental and radical innovations, firms with many (or strong) divisional boundaries tend

395

Dynamic Capabilities and Innovation Radicalness

to develop more incremental innovations, whereas organizations with less (or weak) divisional boundaries tend to develop more radical innovations. Van den Bosch et al. (1999) refer to lateral ways of coordination that enhance the scope and flexibility of organizational learning through relations between its members and groups. This kind of capabilities can be developed as a result of training and job rotation, cross-functional interfaces and participation of subordinates in the decision-making process (Van den Bosch et al., 1999; Jansen et al., 2005). This internal knowledge combination enhances knowledge exchange between different individuals and groups within the firm, so encouraging the development of new knowledge and promoting radical innovation. As Zollo and Winter highlights, “important collective learning happens when individuals express their opinions and beliefs, engage in constructive confrontations and challenge each other’s viewpoints” (2002: 341). This constructive conflict refers to the vigorous debate of ideas, beliefs, and assumptions by organizational members that enable the discussion of opposite views, leading to make better decisions and to develop new organizational capabilities required for incorporate major changes in technological trajectory (Danneels, 2008). R&D intensity of a firm has been traditionally used as a primary input variable to internal learning (Bierly & Chakravarty, 1996). In this sense, internal R&D is a way to put together the knowledge possessed by the firm’s scientific staff. Although Cohen and Levinthal (1990) used this variable as a proxy of firm’s absorptive capacity, they were based on their argument that firms need some previous related knowledge to assimilate new external information. Another example of internal knowledge combination is the use of cross-functional interfaces. This practice support organizational members in rethinking the nature of existing products and services and revisit the ways in which components are integrated (Henderson & Cockburn, 1994; Jansen et al., 2005). Similarly, participation in decision-making promotes more

396

market views and technological perspectives to be considered in innovative decisions, which should lead to more marketable radical inventions (Schoenmakers & Duysters, 2010). Job rotation of employees who each possesses diverse and varied knowledge enhances the diversity of background, increases the problem-solving skills and develops organizational contacts that may increases employees’ ability to identify technological opportunities (Jansen et al., 2005). In the same way, because radical innovation requires non-routine problem solving and deviation from existing knowledge, organizational forms promoting formalization and centralization of decision making are likely to reduce the degree of novelty of firm’s innovation (Jansen et al., 2006). Accordingly, our second proposition stays as follows: Proposition 2. Internal knowledge combination by a firm positively influences the degree of novelty of its innovations.

Complementarities between External Knowledge Acquisition and Internal Knowledge Combination In previous paragraphs we have exposed our reasoning about the effect that, ceteris paribus, external knowledge acquisition or internal knowledge combination has on innovation radicalness. However, nothing was mentioned about the possible existence of a joint effect between both elements. In other words, what could be the effect on innovation radicalness if a firm develops its ability in external knowledge acquisition and internal knowledge combination simultaneously? Indirectly, we have already answered this question in previous discussion when proposing both elements as the key components of firm’s dynamic capabilities that enable a major renewal of firm’s technological competences and subsequently introduce a higher degree of novelty on innovations. As noted, Schoenmakers and Duysters’ (2010) results highlight the importance of speed in un-

Dynamic Capabilities and Innovation Radicalness

derstanding emergent technologies for innovation radicalness. But this speed is higher when a firm is able not only to gets an early access to new technology as consequence of great efforts devoted to environmental scanning, but also when it is able to carry out a fast dissemination of this new external knowledge within the organization throw internal knowledge combination. In this sense, authors conclude that “firms that are quick in understanding the possibilities that emergent technologies posses, and that therefore are able to combine this knowledge with mature and well understood knowledge, might be better at delivering radical inventions” (Schoenmakers & Duysters, 2010: 1057). Following our reasoning, it seems clear that external knowledge acquisition is imperative to introduce new knowledge within the organization necessary to develop more radical innovations. Nevertheless, although necessary, external knowledge acquisition per se may be not enough to carry out a complete explorative organizational learning required to incorporate more novelty on innovations. If not only external, but also internal boundaries matter (Rosenkopf & Nekar, 2001), new external knowledge acquired by the firm may be trapped by internal boundaries and therefore that knowledge will not reach the knowledge place where it would be relevant within the organization, or not at time (and speed also matters - Schoenmakers & Duysters, 2010). This may explain why firms exposed to the same amount of external knowledge flows might not derive equal innovation results (Escribano et al., 2009). In addition to external knowledge scanning, firms need to develop its ability in internal knowledge combination in order to rapidly understand, distribute and apply current and newly acquired external knowledge to develop radical innovations. Following this, we reach our third proposition. Proposition 3. There is a complementary effect between firm’s external knowledge acquisition and internal knowledge combination (that

is, firm’s dynamic capabilities) on the degree of novelty of its innovations. So, if a firm acquires new external knowledge and combines current and new acquired knowledge its innovations will be more radical than if it only develops one of these abilities.

Innovation Radicalness and Adaptation to Environmental Dynamism Benner and Tushman stays that “the ability to develop new technological capabilities rapidly is especially critical in environments characterized by rapid innovation and change” (2003: 249). We have argued that this occurs because the value of firm’s resources and capabilities, that is, its potential to generate economic rents, is contextdependent (Priem & Butler, 2001; Barney, 2001; Benner & Tushman, 2003; Jansen et al., 2006; Sirmon et al., 2007), and dynamic environments are value-destroying (Teece et al., 1997; Uotila et al., 2007). In other words, firm’s current technological and market capabilities, while valuable in that they can provide competitive advantage at present, do not ensure that the firm would be able to maintain its competitive advantage in the face of rapid external changes (O’Reilly & Tushman, 2008). But the market does not value firm’s capabilities directly. It values organizational capabilities indirectly through valuating their outputs. And in this chapter we have followed the argument that innovation is an output of an organization’s technological capabilities (Tidd, 2006; Nobre et al., 2010). Concretely, we have argued that innovation radicalness is an output of firm’s dynamic capabilities that enable organizational capabilities reconfiguration. Attending to its definition, incremental innovations are based on firm’s current technological capabilities, whereas more radical innovations are based on the development of new technological capabilities (Tidd, 2001; Benner & Tushman, 2003; Dahlin & Behrens, 2005). In

397

Dynamic Capabilities and Innovation Radicalness

this sense, as Jansen et al. points out, “dynamic environments make current products and services obsolete and require that new ones be developed” (2006: 1664). Accordingly, if competitors (current or potential) introduce new products based on a new technology that clearly outperforms a firm’s products and technology, and the firm just tries to improve its current products, the results will be highly unsatisfactory. This occurred to IBM’s slow response to personal computers (Benner & Tushman, 2003) or in Kodak’s inertia at introducing in digital photography (Kaplan & Henderson, 2005). In both cases, radical innovations developed by other firms fundamentally changed the nature of the industry and IBM and Kodak had to spend billions to survive. Many other firms without those financial resources directly died. So, to reduce this threat of obsolescence, organizations must introduce more radical innovations that depart from existing products, services and markets. Organizations that pursue such innovations can capitalize on changing circumstances by creating opportunities for above-normal return by targeting premium market segments and creating new niches (Levinthal & March, 1993). Accordingly, we expect that firms operating in dynamic

contexts that develop more radical innovations will increase their long-term performance. Proposition 4. Environmental dynamism positively moderates the relationship between the degree of novelty of firm’s innovations and its long-term performance. The reasoning and derived propositions developed in this chapter can be graphically represented as it appears in our theoretical research model (Figure 1). Note that propositions 1, 2 and 3 combine the arguments offered by capability-building and innovation approaches identified when analyzing dynamic capabilities concept. That is, the development of new organizational capabilities leads to innovations with a higher degree of novelty. On the other hand, proposition 4 combine innovation and contingency approaches. In this case, radical innovation is not an output, but an input to firm’s adaptation to its context. In this way, our model highlights the central role played by innovation radicalness in what Tidd (2006) denominate the “competence cycle”.

Figure 1. Dynamic capabilities’ effect on innovation radicalness and adaptation

398

Dynamic Capabilities and Innovation Radicalness

CONCLUSION Inadequate responses given by organizations to growing environmental dynamism (especially to rapid technological progress) found in a greater number of competitive landscapes may be the explanation of the reduction in average life expectancy of firms in recent times (O’Reilly & Tushman, 2008). In this sense, as people do, organizations tend to fail in a “success trap”, that is, firms are inclined to repeat the same actions that have been previously rewarded (Levinthal & March, 1993). This reasoning is supported by recent empirical results suggesting that stabilised companies tend to systematically overemphasize exploitation (Uotila et al., 2009). Such behaviour leads firms to specialize in exploiting their current knowledge domain, thus being more efficient. However, if the decision-maker adopts this behaviour in a rapid change context, its decisions will be generally unsatisfactory, since in this type of environments new challenges do not usually coincide with the already passed. As O’Reilly & Tushman highlight, “being large and successful at one point in time is no guarantee of continued survival” (2008: 186). So, understanding why some organizations sustain their competitive advantage when facing environmental dynamism while others can not has emerged as one of the essential questions for recent strategic management literature (Teece et al., 1997; Jansen et al., 2006; Uotila et al., 2009). The efforts directed in answering this question have supplanted traditional and more static theories of strategy, such as industrial economy (Porter, 1981) or the resource-based view (Wernefelt, 1984; Barney, 1991), with dynamic approaches exploring how some firms acquire, recombine and integrate their resources to adapt to market and technological changes (Tidd, 2006; O’Reilly & Tushman, 2008). Dynamic capabilities framework is one of the most promising approaches in this arena (Teece et al., 1997; Zahra et al., 2006).

Considering the argument given by Benner and Tushman that because “organizational outcomes are affected by delayed or inadequate responses to environmental turbulence, (...) adaptation to environmental uncertainty and variation requires similar variety within the firm” (2003: 250), this chapter has tried to theoretically identify the organizational antecedents of innovation radicalness, since radical innovations are based on changes in firm’s technological trajectory and associated organizational competencies. In other words, we have tried to answer the question of what attributes lead firms to achieve variety. In doing so, we have drawn on the dynamic capabilities-based view of competitive advantage. Our theoretical review and analysis of the concept has leaded us to define dynamic capabilities as firm’s ability to constantly explore new market and technological knowledge in order to build new organizational capabilities and to consider this ability especially valuable in the face of rapid changes in markets and/or technologies. This definition constitutes an attempt to integrate the three identified approaches on dynamic capabilities in a sequential way: new capabilities generation (capability-building approach) is necessary to develop more radical innovations (innovation approach), enabling firm’s adaptation to environmental dynamism (contingent approach). The next step was to identify the mechanisms that allow firms to carry out an explorative learning at organizational level (that is, to develop their dynamic capabilities). By reviewing organizational learning literature, we have identified several mechanisms that can be classified into two factors: external knowledge acquisition, which allows the firm to have access to externally generated information; and internal knowledge combination, which leads the firm to newly recombine current and acquired knowledge and to distribute it along internal boundaries. Taking into account both organizational learning mechanisms, we have derived a theoretical model linking dynamic capabilities and firm’s

399

Dynamic Capabilities and Innovation Radicalness

adaptation to environmental dynamism proposing that innovation radicalness plays a central role on this process, that is, radical innovations are considered an output of dynamic capabilities and, at the same time, an input of firm’s adaptation to environmental dynamism. So, managers of firms operating in rapid change contexts should promote some of the identified mechanisms for explorative organizational learning in order to develop more than just incremental innovations that may be rapidly obsolete in their competitive arenas.

FUTURE RESEARCH DIRECTIONS The first research challenge emerging from our theoretical analysis consists in to carry out empirical tests. Most of the empirical studies in the field of dynamic capabilities are qualitative (Wang & Ahmed, 2007). This fact, again, underscores the initial state of the perspective. Our work has highlighted some measures and possible scales for operationalizing dynamic capabilities based on internal organizational process which may be very useful for researchers interested in this field. In addition to innovation, it may be interesting to empirically address the link between the two explorative learning mechanisms proposed and other elements of firm’s strategy, such as diversification, changes in competitive strategy or higher levels of internationalization, among others. All of these strategic decisions should require new knowledge on markets and technology to be successful and dynamic capabilities may lead to changes not only in the resource and capabilities base, but also in the way that they are managed and in where they are employed. One relevant research issue consists in to determinate what external knowledge sources may have a higher impact on the degree of novelty of innovations. This is related to the debate on “market pull” vs. “technology push” knowledge strategies. In this sense, Tidd (2006) argues that “market pull” is better for incremental adaptations

400

or product line extensions, whereas “technology push” is necessary for more radical innovations. In the same line, it would be also interesting to investigate if some mechanisms for external knowledge acquisition may be more adequate than others for developing radical innovations depending on the industry in which firms operate. For example, it seems that collaborations with universities and research centres is highly important in experimental sciences sectors, such us pharmaceutical industry (Henderson & Cockburn, 1994), whereas in the automobile industry it could be more important to develop collaborations with suppliers. Similarly, different competitive sectors may demand different mechanisms for internal knowledge combination. Just few recent studies have tried to fill this gap, and have focused exclusively in some mechanism for external knowledge acquisitions, such us collaboration with universities (Bierly et al., 2009). In this sense, the results obtained by Grimpe & Softka (2009) support this reasoning. These authors find that a search pattern that targets market knowledge (customers and competitors) provide superior innovation success in low-technology sectors, whereas technological knowledge leads to higher innovation success in high-technology sectors. It can be explained because, as Tidd (2006) argues, market knowledge contributes to more incremental innovations which lead to better results in relatively static environments, whereas technological knowledge contributes to develop more radical innovations leading to higher performance in turbulent environments. But more evidence is needed. In addition, the moderating role of environmental dynamism also needs to be tested. If our proposition that predicts a greater effect of radical innovations on firm performance is supported, important managerial implications will be derived. In this sense, managers should overcome their risktaking aversion and try to increase their emphasis on exploration when the environment requires it. Our review has highlighted some mechanism

Dynamic Capabilities and Innovation Radicalness

that managers may use in order to promote knowledge exploration, and as a result innovation radicalness, in their organizations (Tables 2 and 3). Again, empirical research about exploration of new knowledge, innovation radicalness and environmental dynamism is very scarce (Jansen et al., 2006; Danneels, 2008, Uotila et al., 2009), so the gap is just beginning to be filled.

REFERENCES Andersen, T. B. (2004). Integrating decentralized strategy making and strategic planning processes in dynamic environments. Journal of Management Studies, 28(8), 1271–1299. doi:10.1111/j.14676486.2004.00475.x Aragón-Correa, J. A., & Sharma, S. (2003). A contingent resource-based view of proactive corporate environmental strategy. Academy of Management Review, 28(1), 71–88. Arbussá, A., & Coenders, G. (2007). Innovation activities, use of appropriation instruments and absorptive capacity: Evidence from Spanish firms. Research Policy, 36(10), 1545–1558. doi:10.1016/j.respol.2007.04.013 Augier, M., & Teece, D. J. (2007). Dynamic capabilities and multinational enterprise: Penrosean insights and omissions. Management International Review, 47(2), 175–192. doi:10.1007/s11575007-0010-8

Benner, M. J., & Tushman, M. L. (2003). Exploitation, exploration, and process management: The productivity dilemma revisited. Academy of Management Review, 28(2), 238–256. Bierly, P. & Chakrabarti, A. (1996). Generic knowledge strategies in the U.S. pharmaceutical industry. Strategic Management Journal, 17(Winter Special Issue), 123-135. Bierly, P. E., Damanpour, F., & Santoro, M. D. (2009). The application of external knowledge: Organizational conditions for exploration and exploitation. Journal of Management Studies, 46(3), 481–509. doi:10.1111/j.1467-6486.2009.00829.x Blyler, M., & Coff, W. (2003). Dynamic capabilities, social capital, and rent appropriation: Ties that split pies (Research Notes and Commentaries). Strategic Management Journal, 24(7), 677–686. doi:10.1002/smj.327 Brown, S. L., & Eisenhardt, K. M. (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42(1), 1–34. doi:10.2307/2393807 Cockburn, I. M., Henderson, R. M., & Stern, S. (2000). Untangling the origins of competitive advantage. Strategic Management Journal, 21(10/11), 1123–1145. doi:10.1002/10970266(200010/11)21:10/11<1123::AIDSMJ130>3.0.CO;2-R

Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. doi:10.1177/014920639101700108

Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective of learning and innovation. Administrative Science Quarterly, 35(1), 128–152. doi:10.2307/2393553

Barney, J. B. (2001). Is the resource-based “view” a useful perspective for strategic management research? Yes. Academy of Management Review, 26(1), 41–56.

Collins, D. J. (1994). How valuable are organizational capabilities (Research Note)? Strategic Management Journal, 15(Winter Special Issue), 143-152.

Beinhocker, E. D. (1999). Robust adaptive strategies. Sloan Management Review, 40(3), 95–106.

401

Dynamic Capabilities and Innovation Radicalness

Dahlin, K. B., & Behrens, D. (2005). When is an invention really radical? Research Policy, 34(5), 717–737. doi:10.1016/j.respol.2005.03.009 Danneels, E. (2002). The dynamics of product innovation and firm competences. Strategic Management Journal, 23(12), 1095–1121. doi:10.1002/smj.275

Grant, R. M. (1996). Prospering in dynamicallycompetitive environments: Organizational capability as knowledge integration. Organization Science, 7(4), 375–387. doi:10.1287/orsc.7.4.375 Greve, H. R. (2007). Exploration and exploitation in product innovation. Industrial and Corporate Change, 16(5), 945–975. doi:10.1093/icc/dtm013

Danneels, E. (2008). Organizational antecedents of second-order competences. Strategic Management Journal, 29(5), 519–543. doi:10.1002/ smj.684

Griffith, D. A., & Harvey, M. G. (2001). A resource perspective of global dynamic capabilities. Journal of International Business Studies, 32(3), 597–606. doi:10.1057/palgrave.jibs.8490987

Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660–679.

Grimpe, C., & Sofka, W. (2009). Search patterns and absorptive capacity: Low- and high-technology sectors in European countries. Research Policy, 38(3), 495–503. doi:10.1016/j.respol.2008.10.006

Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities. What are they? Strategic Management Journal, 21(10/11), 1105–1121. doi:10.1002/10970266(200010/11)21:10/11<1105::AIDSMJ133>3.0.CO;2-E

Helfat, C. E. (1997). Know-how and asset complementarity and dynamic capability accumulation: The case of R&D. Strategic Management Journal, 18(5), 339–360. doi:10.1002/ (SICI)1097-0266(199705)18:5<339::AIDSMJ883>3.0.CO;2-7

Escribano, A., Fosfuri, A., & Tribó, J. A. (2009). Managing external knowledge flows: The moderating role of absorptive capacity. Research Policy, 38(1), 96–105. doi:10.1016/j.respol.2008.10.022 Fabrizio, K. R. (2009). Absorptive capacity and the search for innovation. Research Policy, 38(2), 255–267. doi:10.1016/j.respol.2008.10.023 Figueiredo, P. N. (2003). Learning, capability accumulation and firm differences: Evidence from Latecomer Steel. Industrial and Corporate Change, 12(3), 607–643. doi:10.1093/ icc/12.3.607 Galende, J. (2006). Analysis of technological innovation from business economics and management. Technovation, 26(3), 300–311. doi:10.1016/j. technovation.2005.04.006

402

Helfat, C. E., & Peteraf, M. A. (2003). The dynamic resource-based view: Capability lifecycles. Strategic Management Journal, 24(10), 997–1010. doi:10.1002/smj.332 Helfat, C. E., & Raubitschek, R. S. (2000). Product sequencing: Co-evolution of knowledge, capabilities and products. Strategic Management Journal, 21(10/11), 961–979. doi:10.1002/10970266(200010/11)21:10/11<961::AIDSMJ132>3.0.CO;2-E Henderson, R. & Cockburn, I. (1994). Measuring competence? Exploring firm effects in pharmaceutical research. Strategic Management Journal, 15(Winter Special Issue), 63-84.

Dynamic Capabilities and Innovation Radicalness

Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2005). Managing potential and realized absorptive capacity: How do organizational antecedents matter? Academy of Management Journal, 48(6), 999–1015. doi:10.5465/ AMJ.2005.19573106 Jansen, J. J. P., Van den Bosch, F. A. J., & Volberda, H. W. (2006). Exploratory innovation, exploitative innovation, and performance: Effects of organizational antecedents and environmental moderators. Management Science, 52(11), 1661–1674. doi:10.1287/mnsc.1060.0576 Kaplan, S., & Henderson, R. (2005). Inertia and incentives: Bridging organizational economics and organizational theory. Organization Science, 16(5), 509–521. doi:10.1287/orsc.1050.0154 Karim, S., & Michell, W. (2000). Path-dependent and path-breaking change: Reconfiguring business resources following acquisitions in the U.S. medical sector. Strategic Management Journal, 21(10/11), 1061–1081. doi:10.1002/10970266(200010/11)21:10/11<1061::AIDSMJ116>3.0.CO;2-G Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397. doi:10.1287/orsc.3.3.383 Lane, P. J., Koka, B. R., & Pathak, S. (2006). The reification of absorptive capacity: A critical review and rejuvenation of the construct. Academy of Management Review, 31(4), 833–863. doi:10.5465/AMR.2006.22527456 Lane, P. J., & Lubatkin, M. (1998). Relative absorptive capacity and interorganizational learning. Strategic Management Journal, 19(5), 461–477. doi:10.1002/ (SICI)1097-0266(199805)19:5<461::AIDSMJ953>3.0.CO;2-L

Lavie, D. (2006). Capability reconfiguration: An analysis of incumbent responses to technological change. Academy of Management Review, 31(1), 153–174. doi:10.5465/AMR.2006.19379629 Lee, J., Lee, K., & Rho, S. (2002). An evolutionary perspective on strategic group emergence: A generic algorithm-based model. Strategic Management Journal, 23(8), 727–747. doi:10.1002/ smj.250 Lenox, M., & King, A. (2004). Prospects for developing absorptive capacity through internal information provision. Strategic Management Journal, 25(4), 331–345. doi:10.1002/smj.379 Leonard-Barton, D. (1992). Core capabilities and core rigidities: A paradox in managing new product development. Strategic Management Journal, 13(Summer Special Issue), 111-125. Leskovar-Spacapan, G., & Bastic, M. (2007). Differences in innovation capability in transition economy: Internal aspect of the organization’s strategic orientation. Technovation, 27(9), 533–546. doi:10.1016/j.technovation.2007.05.012 Levinthal, D. A. & March, J. G. (1993). The myopia of learning. Strategic Management Journal, 14(Winter Special Issue), 95-112. Makadok, R. (2001). Toward a synthesis of resource-based and dynamic-capability views of rent creation. Strategic Management Journal, 22(5), 387–401. doi:10.1002/smj.158 March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. doi:10.1287/orsc.2.1.71 Miller, D. J., Fern, M. J., & Cardinal, R. B. (2007). The use of knowledge for technological innovation within diversified firms. Academy of Management Journal, 50(2), 308–326. doi:10.5465/ AMJ.2007.24634437

403

Dynamic Capabilities and Innovation Radicalness

Morrow, J. L., Sirmon, D. G., Hitt, M. A., & Holcomb, T. R. (2007). Creating value in the facing of declining performance: Firm strategies and organizational recovery. Strategic Management Journal, 28(3), 271–283. doi:10.1002/smj.579

Oliver, C., & Holzinger, I. (2008). The effectiveness of strategic political management: A dynamic capabilities framework. Academy of Management Journal, 33(2), 496–520. doi:10.5465/ AMR.2008.31193538

Mowery, D. C., Oxley, J. E. & Silverman, B. S. (1996). Strategic alliances and interfirm knowledge transfer. Strategic Management Journal, 17(Winter Special Issue), 77-91.

Pettus, M. L., Kor, Y. Y., & Mahoney, J. T. (2009). A theory of change in turbulent environments: The sequencing of dynamic capabilities following industry deregulation. International Journal of Strategic Change Management, 1(3), 186–211. doi:10.1504/IJSCM.2009.024509

Murovec, N., & Prodan, I. (2009). (in press). Absorptive capacity, its determinants and influence on innovation output: Cross-cultural validation of the structural model. Technovation. doi:10.1016/j. technovation.2009.05.010 Nelson, R. R. (1991). Why do firms differ, and how does it matter? Strategic Management Journal, 12(Winter Special Issue) 61-74. Nelson, R. R., & Winter, S. G. (1982). An evolutionary theory of economic change. Cambridge, USA: Belknap Press of Harvard University Press. Newbert, S. L. (2007). Empirical research on the resource-based view of the firm: an assessment and suggestions for future research. Strategic Management Journal, 28(2), 121–146. doi:10.1002/ smj.573 Ng, D. N. (2007). A modern resource based approach to unrelated diversification. Journal of Management Studies, 44(8), 1481–1502. Nobre, F. S., Tobias, A. M., & Walker, D. S. (2010). A new contingency view of the organization: Managing complexity and uncertainty through cognition. Brazilian Administration Review, 7(4), 379–396. doi:10.1590/S180776922010000400005 O’Reilly, C. A. III, & Tushman, M. L. (2008). Ambidexterity as a dynamic capability: Resolving the innovator’s dilemma. Research in Organizational Behavior, 28, 185–206. doi:10.1016/j. riob.2008.06.002

404

Pisano, G. P. (1994). Knowledge, integration, and the locus of learning: An empirical analysis of process development. Strategic Management Journal, 15(Winter Special Issue), 85-100. Porter, M. E. (1981). The contribution of industrial organization to strategic management. Academy of Management Review, 6(4), 609–620. Priem, R. L., & Butler, J. E. (2001). Is the resourcebased ‘view’ a useful perspective for strategic management research? Academy of Management Review, 26(1), 22–40. Rindova, V. P., & Kotha, S. (2001). Continuous ‘morphing’: Competing through dynamic capabilities, form and function. Academy of Management Journal, 44(6), 1263–1280. doi:10.2307/3069400 Rosenbloom, R. S. (2000). Leadership, capabilities, and technological change: The transformation of NCR in the electronic era. Strategic Management Journal, 21(10/11), 1083–1103. doi:10.1002/10970266(200010/11)21:10/11<1083::AIDSMJ127>3.0.CO;2-4 Rosenkopf, L., & Nerkar, A. (2001). Beyond local search: Boundary spanning, exploration, and impact in the optical disk industry. Strategic Management Journal, 22(4), 287–306. doi:10.1002/ smj.160

Dynamic Capabilities and Innovation Radicalness

Schoenmakers, W., & Duysters, G. (2010). The Technological Origins of Radical Inventions. Research Policy, 39(8), 1051–1059. doi:10.1016/j. respol.2010.05.013 Schreyögg, G., & Kliech-Eberl, M. (2007). How dynamic can organizational capabilities be? Towards a dual-process model of capability dynamization. Strategic Management Journal, 28(9), 913–933. doi:10.1002/smj.613 Schumpeter, J. (1934). The theory of economic development. Cambridge, USA: Harvard University Press. Sirmon, D. G., Hitt, M. A., & Irelland, R. D. (2007). Managing firm resources in dynamic environments to create value: Looking inside the black box. Academy of Management Review, 32(1), 273–292. doi:10.5465/AMR.2007.23466005 Teece, D. J. (2007). Explicating dynamic capabilities. The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. doi:10.1002/smj.640 Teece, D. J., & Pisano, G. (1994). The dynamic capabilities of firms: An introduction. Industrial and Corporate Change, 3(3), 537–556. doi:10.1093/ icc/3.3.537-a Teece, D. J., Pisano, G., & Shuen,A. (1997). Dynamic capabilities and strategic management. Strategic ManagementJournal,18(7),509–533.doi:10.1002/ (SICI)1097-0266(199708)18:7<509::AIDSMJ882>3.0.CO;2-Z Tidd, J. (2001). Innovation management in context: environment, organization and performance. International Journal of Management Reviews, 3(3), 169–183. doi:10.1111/1468-2370.00062

Tidd, J. (2006). The competence cycle: Translating knowledge into new processes, products and services. In Tidd, J. (Ed.), From knowledge management to strategic competence: Measuring technological, market and organizational innovation (2nd ed., pp. 5–25). London, UK: Imperial College Press. doi:10.1142/9781860948138_0001 Todorova, G., & Durisin, B. (2007). Absorptive capacity: Valuing a reconceptualization. Academy of Management Review, 32(3), 774–786. doi:10.5465/AMR.2007.25275513 Uotila, J., Maula, M., Keil, T., & Zahra, S. A. (2009). Exploration, exploitation, and financial performance: Analysis of S&P 500 corporations. Strategic Management Journal, 30(2), 221–231. doi:10.1002/smj.738 Van den Bosch, F. A. J., Volberda, H. W., & De Boer, M. (1999). Coevolution of firm absorptive capacity and knowledge environment: Organizational forms and combinative capabilities. Organization Science, 10(5), 551–568. doi:10.1287/ orsc.10.5.551 Verona, G., & Ravasi, D. (2003). Unbundling dynamic capabilities: An exploratory study of continuous product innovation. Industrial and Corporate Change, 12(3), 577–606. doi:10.1093/ icc/12.3.577 Wang, C. L., & Ahmed, P. K. (2007). Dynamic capabilities: A review and research agenda. International Journal of Management Reviews, 9(1), 31–51. doi:10.1111/j.1468-2370.2007.00201.x Wernefelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171–180. doi:10.1002/smj.4250050207 Winter, S. G. (2000). The satisficing principle in capability learning. Strategic Management Journal, 21(10-11), 981–996. doi:10.1002/10970266(200010/11)21:10/11<981::AIDSMJ125>3.0.CO;2-4

405

Dynamic Capabilities and Innovation Radicalness

Winter, S. G. (2003). Understanding dynamic capabilities. Strategic Management Journal, 24(10), 991–995. doi:10.1002/smj.318 Zahra, S. A. (1999). The changing rules of global competitiveness in the 21st century. The Academy of Management Executive, 13(1), 36–42. doi:10.5465/AME.1999.1567300 Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185–203. Zahra, S. A., & Nielsen, A. P. (2002). Sources of capabilities, integration and technology commercialization. Strategic Management Journal, 23(5), 377–398. doi:10.1002/smj.229 Zahra, S. A., Sapienza, H. J., & Davidsson, P. (2006). Entrepreneurship and dynamic capabilities: A review, model and research agenda. Journal of Management Studies, 43(4), 917–955. doi:10.1111/j.1467-6486.2006.00616.x Zajac, E. J., Kraats, M. S., & Bresser, R. F. K. (2000). Modeling the dynamics of strategic fit: A normative approach to strategic change. Strategic ManagementJournal,21(4),429–453.doi:10.1002/ (SICI)1097-0266(200004)21:4<429::AIDSMJ81>3.0.CO;2-# Zollo, M., & Winter, S. G. (2002). Deliberate learning and the evolution of dynamic capabilities. Organization Science, 13(3), 339–351. doi:10.1287/orsc.13.3.339.2780

406

KEY TERMS AND DEFINITIONS Absorptive Capacity: The ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends (Cohen & Levinthal, 1990). Combinative Capabilities: A firm’s ability to flexibly recombine and utilize its current and acquired knowledge (Kogut & Zander, 1992). Dynamic Capabilities: A firm’s ability to constantly explore new market and technological knowledge in order to build new organizational capabilities. This ability is especially valuable in the face of rapid changes in markets and/or technologies. Thus, the greater the environmental dynamism, the greater should be the ability of the firm to engage in explorative learning that enables capability reconfiguration. Dynamic Environment: Competitive context characterized by rapid, continuous and unpredictable changes in product and/or factor markets. External Organizational Learning: Occurs when boundary spanners bring in knowledge from an outside source via either acquisition or imitation and the knowledge is then transferred through the organization (Bierly & Chakrabarti, 1996). Internal Organizational Learning: Occurs when members of the organization generate and distribute new knowledge within the boundaries of the firm (Bierly & Chakrabarti, 1996). Radical Innovations: Imply the development of a highly novel or unique product/service or production process and are based on changes in firm’s technological trajectory and associated organizational competencies (Benner & Tushman, 2003).

Section 5

R&D&T Management and Innovation

408

Chapter 22

Research Profiles:

Prolegomena to a New Perspective on Innovation Management Gretchen Jordan Sandia National Laboratories, USA Jonathon Mote Southern Illinois University, USA Jerald Hage University of Maryland, USA

ABSTRACT Despite the increasing importance of the management of research for innovation, the range of differences among types of research, as well as projects and programs, is not adequately captured in current theories of either project or organizational innovation. This chapter offers preliminary discussions for a new perspective about alternative styles of management for different types of research, whether basic, applied, product development, manufacturing, quality control or marketing. Based on these discussions, the chapter proposes a framework for a new perspective of innovation management, called Research Profiles, which is derived from a literature review and extensive field research. This new perspective delineates four research profiles on the basis of two dimensions of research objectives and two dimensions of research tasks. In matching the research objectives and tasks, we identify inherent dilemmas that managers must address and this developing perspective suggests some appropriate research management approaches.

DOI: 10.4018/978-1-61350-165-8.ch022

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Research Profiles

INTRODUCTION Despite the central importance of scientific and technological research, including product development, for national competitiveness and security, at present there is not an adequate theory about the appropriate managerial styles needed to address alternative kinds of research objectives at the research project, program or inter-organizational level. Organizational innovation theory stemming from Burns and Stalker (1961) typically focuses on the entire organization and, we would suggest, one organizational model (the organic organization), rather than recognizing the existence of different kinds of research work. More critically, the organic model does not include either the concept of complexity (Brown & Eisenhardt, 1995; Hage, 1999) or external networks of expertise, which are precisely the ones that are increasingly important in the growth of knowledge network communities (Mohrman, Galbraith, & Monge, 2004; Shinn, 2002), and the spread of inter-organizational relationships (Alter & Hage, 1993; Hagedoorn & Duysters, 2002; Powell, 1998; Powell, Koput, & Smith-Doerr, 1996; Van De Ven & Polley, 1992). Indeed, in the organizational innovation literature there is only one study that examines the structure and performance of research laboratories and it does not include external relationships of any kind (Hull, 1988). Although we are beginning to see an increasing number of studies of research labs (Brown, 1997; Joly & Mangematin, 1996; Jordan, Streit, & Matiasek, 2003; Menke, 1997), inter-organizational alliances (Gomes-Casseres, 1996) and a few studies of research consortia (Browing, Beyer, and Shelter, 1995), the fact remains that none of these studies have connected the measurement of scientific and technological research objectives, to the nature of the research tasks and their appropriate managerial styles. The research literatures cited above stand largely in isolation, often ignoring other kinds of research work. Specifically, the level of the project is overlooked, which is a smaller unit

than the organization, the whole organization, and inter-organizational networks of various kinds. Indeed, what makes a proposed theory of management styles necessary is the considerable range in the ways scientific and technology research is organized. While many small research projects funded by the National Science Foundation (NSF) and the National Institutes of Health (NIH), such as those found in academia, tend to be the standard structure, a considerable amount of research is conducted in large-scale organizations and programs, such as mission agencies like the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA), as well as large scale inter-organizational research programs such as the Human Genome Project. For the same reason, the new and growing literature on projects (Brown and Eisenstadt, 1995) overlooks what might be called “Big Science” as represented in the research conducted at the large national and international laboratories such as Argonne in the US and CERN in Switzerland. Further, as Clarke (2002) has discussed in comprehensive detail, the management of a large number of researchers is very different from the typical management issues involved in contemporary firms or public bureaucracies. Among other differences are the oft-cited assertions that researchers are more motivated by intellectual curiosity than monetary compensation, the longer and more uncertain time horizons for successful objectives, and, perhaps most importantly, work that is seldom standardized and difficult to evaluate. While a theory about the diversity of research management styles would necessarily differ from more general theories of organizations, the logic in the construction of our perspective is basically the same. First, one must specify particular kinds of research objectives and identify the potential trade-offs. Then one must also distinguish different kinds of research work and tasks. Finally, the management styles appropriate for the linking of

409

Research Profiles

the typology of research tasks with a typology of research objectives at the levels of project, program and inter-organization networks have to be determined. In this chapter, we present our argument for a diversity of research management styles in three sections. First, we provide a more detailed justification of the need for our perspective on of management styles. Second, we specify a typology of research work and a typology of research objectives and provide a theoretical linkage between the two. Finally, we offer our proposed view of Research Profiles and discuss the managerial styles necessitated by the kinds of management challenges that are presented in each profile’s combination of research tasks and research objectives.

BACKGROUND: THE NEED FOR A NEW PERSPECTIVE OF RESEARCH MANAGEMENT STYLES Essentially, we identify two lines of argument for justifying a new perspective of management styles. We take as a given that the central importance of scientific and technological research, not only for competitiveness but many other national goals, speaks to the need for greater attention. First, the closest appropriate specialty, namely organizational innovation research, needs to be altered in the light of new theoretical and conceptual developments (see Hage, 1999). Second, the literature on scientific and technological research is missing a conceptual apparatus that would allow for the accumulation of findings across a myriad of studies. The first argument is based on the fact that most current and past innovation research continues to be dominated by Burns and Stalker’s (1961) seminal work on the organic model. In many ways, this model has become outdated. For example, the model is largely focused on new product development by engineers, rather than scientific and technological research. This model also largely

410

ignores the concept of complexity, which has proven to be fundamental when combined with the organic model and the strategy of risk-taking in explaining differences in innovation rates (Hage, 1999). Finally, as argued previously, the organic model is not designed to handle the varying sizes of units in which research is conducted, from the very small project within an organization to the very large mission agencies such as NOAA and NASA or a research consortium such as SEMATECH (Browning, 1995) or various strategic alliances (Gomes-Casseres, 1996). More recently, the importance of both the organizational learning perspective (Grant, 1996; Kim & Wilemon, 2007) and the theory of idea innovation networks (Hage & Hollingsworth, 2000; Kline & Rosenberg, 1986) are implicitly calling attention to the importance of research as a mechanism for learning. Further, these perspectives suggest the importance of inter-organizational networks that connect two or more of the six arenas of research: basic, applied research, product development, manufacturing research, quality research, and commercialization research. In fact, the latter literature necessitates a considerable revision of the organic model, specifically to allow for external relationships. In short, the organic model, and organizational innovation research in general, needs to be linked in various ways to the research project literature (Brown & Eisenhardt, 1995; Hobday, 1998; Shenhar, 2001) and the abundant literature on inter-organizational relationships cited above. One of the reasons for this is the dramatic changes that have occurred because of the explosive growth and globalization of R&D and the way in which science and technology are evolving (Hage & Hollingsworth, 2000). Furthermore, the linkages between arenas (for example basic and applied) of research are usually at the project/program level and therefore research projects and the problems of how to manage them should be the analytical focus.

Research Profiles

The second line of reasoning that justifies the need for a theory of research management styles is that much of the social studies of science literature have emphasized concrete categories rather than general dimensions that would allow one to accumulate evidence about how best to manage research. For example, the outcomes of research are typically measured in concrete categories, such as papers, patents, peer review assessments, and citations. As we discuss below, we propose a reconceptualization of these ideas so that they can be used as general dimensions, such as the degree of radicalness of the outcome of the research or the scope of the research outcome, that can be applied to basic or applied research, product development research, manufacturing research, and so on. Similarly, research work is often described by such terms as scientific and technological research or the specific content, i.e. physics, chemistry, or biology. Again, there is a need for general dimensions of research tasks that can be applied across these various situations such as the degree of complexity or diversity in the research team and the size of the research program or inter-organizational network. Until these general dimensions are developed and linked, it is not possible to identify the correct managerial practices for linking the nature of the research task with the kind of desired outcome. In summary, the increasing importance of research and these two lines of reasoning provide a compelling case for the importance of our perspective of Research Profiles based on tasks, objectives, as well managerial styles and managerial challenges.

THE BASIC DIMENSIONS FOR RESEARCH MANAGEMENT STYLES What characteristics might one desire in a categorization of research management styles? Ideally, one should encompass dimensions that tap into

the fundamental dilemmas, tensions and problems of conducting research. Since our interest is in making meaningful distinctions, we want to isolate multiple dimensions of research objectives and tasks. Another concern is to connect choices about objectives as much as possible to the existing literature and, in particular, to the literature on innovation. To provide new insights about research management styles across a wide range of different kinds of research projects, programs and inter-organizational networks, we conducted an inductively-based exploratory study, funded by the U.S. Department of Energy (DOE), to help identify the critical factors facing the research workers and managers. Utilizing the Competing Values Framework as an organizing framework for understanding the pursuit of research (Cameron & Quinn, 1998; Quinn & Rohrbaugh, 1983), a number of focus groups were conducted with scientific researchers to more specifically identify attributes of a research environment. The focus group discussions uncovered a number of unique tensions in managing research, which demonstrated not only that competing values exist in the research environment, but that these values differ depending on the research objectives and tasks. For example, a tension mentioned often in these discussions was between researchers’ desire and need for autonomy and management’s desire and need to focus research and meet deadlines. In their study of productive climates for scientists, Pelz and Andrews (1976), found similar tensions such as these prevalent and important to consider in managing scientists because of their significant impact on performance. The findings of the exploratory study and subsequent surveys suggest that the diversity of research projects, programs and organizations can be sorted according to two primary dimensions for research objectives and two primary dimensions for describing the nature of the research work or task.

411

Research Profiles

The Research Objectives Dimension We define the research objectives dimension as Degree of Radicalness in the Scientific or Technological Advance on a continuum from incremental to radical. In slight contrast to the Schumpeterian notion of the degree of radicalness, which focuses primarily on the competitive impact of an invention (Dahlin & Behrens, 2005), we would argue that the degree of radicalness in research includes the degree of change in the state of the art, the centrality of the research problem, and the discovery of a pattern that upsets existing theory or a technology that creates a market niche. For scientific research, the task environment is the knowledge world or “the state of the art,” that is, how much is known, and what is considered to be an important scientific concern or requirement. Radical advances in science sometimes occur when a central problem is solved, such as the identification of the structure of DNA (Judson, 1979). Sometimes this also happens when a major discovery is made, such as the observation of the first candidate black hole in 1971 (Cygnus X-1), or when a research finding challenges an existing theory, such as the discovery of skeletal remains in the Americas estimated to over 1,000 years older than it was theorized that the Americas were colonized or the discovery in China of fossils of dinosaurs with feathers. The second dimension of research objectives is the Scope of Focus, a continuum from narrow to broad, defined by the number of variables or processes or components or the number of levels or systems involved, or the extremeness of the environments of the work. In product development, this includes the number of performances affected as well as the need to change supply chains and distribution chains and create idea innovation networks or strategic alliances, as discussed in great detail by Shenhar (2001) and Hobday (1998). The challenge is adapting these concepts of scope from the product development

412

and industrial innovation literature for scientific and technological research. As we have already observed, the question of the amount of the scientific advance can involve multiple outcomes, that is, the number of variables or processes that are being researched at the same time. Some disciplines have a systemic quality, that is, a large number of variables have to be considered at the same time. Further, not all scientific problems can be approached with small research teams; some of them require a large scale focus. While progress in mapping and sequencing the human genome could have proceeded with small research teams, it took a large-scale interorganizational program to coordinate a range of efforts so that the time needed to complete the entire genome was appreciably lessened. Indeed, the systemic quality of some types of research is frequently overlooked as a critical dimension to the scientific problem. One example of what might be called a systemic problem is research on the weather, which encompasses both oceanic and atmospheric systems. NOAA was created in 1970 to unify and coordinate the government’s research efforts on various aspects of the global environmental system, including the National Weather Service (NWS). Altogether, the scope of NOAA’s mandate necessitates quite expensive and specialized equipment and teams to collect the relevant data, including satellites, ships, buoys, and planes. Indeed, one could argue that the choice to conduct large scale data collection represents one form of a broad scope focus. Just as science has a systemic quality in some areas that cannot be easily divided into small projects, there are technical systems that necessitate a large program of product development that may last many years. Leifer and colleagues (2000) observe in a series of case studies that this is a common characteristic of radical product innovation. Further, the research involves not simply the program, but also supporting technologies as well. For example, research on high speed trains, hydrogen-fueled cars, or fusion research

Research Profiles

also necessitates accompanying research on infrastructure, distribution and delivery systems. Taken together, these two dimensions of research objectives, or intended outcomes, can be cross-classified to generate a typology of research objectives (see Table 1). In this manner, the choice of the relative emphasis on the radicalness of the scientific discovery or technological advance and focus scope generates four distinctive kinds of strategic choices. In general, the research of Shenhar (1993; 2001) on engineering projects is suggestive of how these two dimensions of research objectives can be operationalized in scientific research, where both the idea of scientific or technological uncertainty and systemic scope are in effect. In science and technology, it is the combination of objectives such as superconducting at room temperatures that reflects a radical advance.

The Research Tasks Dimensions Research tasks can also be characterized by two dimensions. The first, and most obvious, dimension is the relative size of the research project, measured by the number of researchers, the number of different instruments, the number of technicians that are involved, and the number of teams and organizations involved. Furthermore, as is obvious, as the costs increase--the movement from 10 million to 100 million to one billon—there is a need for significant changes in the organization and management of the research. These changes in organization roughly parallel the movement from research project to research program or research

organization, such as a national laboratory, to mission agency or inter-organizational network, as in a research consortium. At the extreme is the cost of a space shuttle, with a price tag of over 20 billion dollars expended over ten to twenty years (Gelès, 1999). Significant work can be accomplished in small projects, such as the theoretical advances involving DNA (the double helix structure) and RNA (the messenger), which were radical advances in scientific knowledge, involved relatively small and complex research teams working within a circumscribed knowledge community (see Judson, 1979). In contrast, the mapping of the human genome necessitated a large research program that required the coordination of multiple research teams and inter-organizational relationships since there were over 3,000 genes. In systemic research, it is the large number of variables or properties of the system that require large scale programs to test and develop theories. In large organizations, programs of research are frequently housed in separate divisions because they focus on a specific area of research. This dimension of size is similar to the fundamental distinction in the Competing Values Framework between flexibility and controlled structures, with the idea that larger projects are those that are more likely to be controlled. But the dimension of size also encompasses a number of consequences that create tensions about coordination and control mechanisms that inevitably impact on project autonomy that are discussed at greater length below. Some would classify the cost

Table 1. A typology of research objectives Degree of Radicalness in Scientific or Technological Advance Scope of Focus

Incremental

Radical

Narrow

Minor advances in a limited area, a few performances or components

Major advances in a limited area, a few performances or components

Broad

Minor advances in a system or on multiple performances of a system; Changes outside of system.

Major advances in a system or on multiple performances of a system; Changes outside of system.

413

Research Profiles

of a project as an indicator of radicalness of the innovation (McDermott & O’Connor, 2002), but we would argue this should be kept quite separate from measures of revolutionary breakthroughs in science or in technology because the cost of these projects is variable. Beyond this, the issue of the cost leads naturally into the more critical question of the size of the research project. The other dimension of research projects is the complexity or diversity of research on a continuum from specialized to very diverse, as represented by the variety of scientific and engineering disciplines involved. This dimension is equally well established in the literatures on organizational innovation (Hage, 1999) and contingency theory more generally (Lawrence & Lorsch, 1967), as well as in science more generally (Mote, 2005). In our research at Sandia National Laboratories, we have found that many research projects had only six to ten people but in some cases, this represented six or more departments; in other instances, it reflected only one or two departments (Jordan, Hage, Mote, & Hepler, 2005). Thus, even in relatively small research projects, there can be a considerable variation in the degree of diversity in the composition of the researchers and technicians. Above, we have stressed the importance of the technicians and the equipment as one aspect of the size of the project. These factors also represent an element of complexity that is frequently ignored. For example, one of the more interesting aspects of complex research projects is the variety of research equipment that is utilized. In Latour and Woolgar’s (1979) well-known study of the research laboratory, they found ten different instruments used for the purposes of measurement. Diversity or complexity in the number of researchers and technicians can change across time. Furthermore, as research findings develop, one begins to recognize the need for still other kinds of equipment or of other kinds of expertise, that is, knowledge areas. The changes in the knowledge composition of the research project or fluidity over time are yet another measure of complexity. Again,

414

as our research on Sandia National Laboratories research projects and programs demonstrates, typically each year, new scientific and engineering specialties were added and in some cases, others were dropped. In other words, complexity has not only a static dimension but a temporal one as well. This dimension of structure typically measures whether expertise exists within an organization or within external organizations. Since complexity is essentially a measure of the knowledge pool of the research effort, it is to be expected that not all of the necessary skills and attributes needed are to be found in the same research unit or even within the same research organization, even in large organizations such as the national laboratories or mission agencies. The literature has consistently demonstrated that as the complexity of the research effort increases, there is frequently the need for expertise outside the research organization (Alter & Hage, 1993). In this manner, the search for additional expertise or knowledge fosters a greater external focus within the research project or program. The two dimensions of size and complexity (see Table 2) yield four distinctive types of research projects: (1) small complex research projects; (2) large complex research programs or research organizations; (3) large specialized research programs or research organizations; and (4) small specialized research projects. Earlier, we emphasized the importance of adding the external, inter-organizational dimension to the variations on the organic model. Small complex research projects are usually connected to knowledge or practice communities, but typically in a more informal manner, and perhaps one inter-organizational relationship. In contrast, large complex research programs are more likely to be connected to set of inter-organizational relationships and maybe even a consortium, as in global alliances (Gomes-Casseres, 1996) or research consortia such as SEMATECH (Browning, 1995). Again, these are general dimensions with a considerable range of variability.

Research Profiles

Table 2. A typology of research tasks Degree of Complexity or Diversity Size of Research Effort

Some

A Lot

Small

Specialized research projects

Complex research projects; knowledge communities

Large

Specialized research programs or research organizations

Complex research program or research organization; inter-organizational relationships

The Amount of Choice Involved in the Selection of Research Objectives and Tasks Although we have employed the word “choice”, there still remains a question of the latitude that managers have in selecting particular research tasks. For instance, the choices may be dictated to them by the environment, whether because of the agendas of funding agencies, control exerted by the state, or certain socialization practices that create a distinctive world view (DiMaggio & Powell, 1983). An example is that the culture surrounding the peer panel review process in general creates a bias toward what is often termed “normal science,” that is, toward incremental advances in knowledge (Braun, 1998). Crises can also affect the choice of research objectives and tasks. For example, the cyclical nature of environmental concerns has been manifested in rising and falling pressures on public research laboratories and private companies and shifting choices of research objectives and tasks from incremental ones, such as minor improvements in gas mileage, to more radical ones, such as the hydrogen fuel car. As this illustrates, not all pressures are necessarily directed towards radical advances in knowledge. For instance, the pressing need for immediate improvements in national security after the events of September 11, 2001 in the United States might necessitate the need to place greater emphasis on incremental advances, that is, to quickly transfer current technology into security applications (Trajtenberg, 2006).

But the most interesting constraints on choice emerge from the nature of the research problem. Natural systems that are at the extremes of scale, from the very small (subatomic) to the very large (outer space), require quite expensive equipment, numerous technical personnel and many researchers to study them. It is the case that the research problem might be capable of compartmentalization so that it can be pursued as smaller research projects. Obviously, when this is possible, the pursuit of a smaller research project presents itself as a viable research choice. But if one wants to study the system in its entirety, then either a large research organization, mission agency or a research consortium becomes necessary.

Dilemmas in the Choice of Research Objectives and Research Tasks The influence of the external world is not the only pressure that affects the choice of the research objectives and tasks. Other, perhaps more critical, pressures are the different kinds of management dilemmas that accompany each choice. These need to be discussed in some detail because they reflect important management challenges and provide examples of how management style could make a difference. Two very common terms in the management literature, especially in discussions of innovation, are the terms “risk” and “uncertainty”. Both of these apply to the choice of the research objectives and reflect dilemmas, particularly in the notion of how much risk one should absorb and how much uncertainty. While the terms are frequently

415

Research Profiles

used interchangeably in the literature, we would propose making the following distinctions: risk is a measure of the degree of radicalness in the research objective, while uncertainty is a measure of the scope of the focus on possible outcomes. A review of the literature on the management of innovation indicates that when one shifts to the language of uncertainty, the issue becomes simply a matter of counting the number of uncertainties. In other words, there are not only technological uncertainties but market uncertainties and others, although the role of the market in many areas of basic and applied research are not readily clear (Clarke, 2002). And while it follows that a large number of uncertainties, almost by definition, translates to high risk, the converse is not necessarily true. Indeed, there might only be a few technological uncertainties but still the choice to pursue a radical outcome would entail high risk. For example, Shenhar (1993) and Hobday (1998) suggest that technological uncertainty is related to the degree in which new devices, knowledge or techniques are embodied in a product. But it could be the case that one seeks a radical research outcome, yet still utilize existing technology to do so. In short, we propose the idea of using risk and uncertainty in somewhat different ways, while still recognizing that the combination of many uncertainties with high radicalness presents the most difficult management tasks. In this manner, we are suggesting that each dilemma flows from a different set of issues than that found in new product development and industrial organization. Attempting to make a significant advance in science or technology development obviously carries a large risk of failure. Uncertainty, however, flows more from the scope of the focus that one is desiring to achieve because as the implicit number of unknowns increases, it becomes more and more uncertain as to which set is the most critical. Stated another way, when the focus is on understanding an entire system, either large

416

or small, especially at multiple levels, there are a large number of potential unknowns or avenues of research. One might assume that the simple solution to reducing risk is by pursuing a greater number of smaller, incremental research projects. In one sense, this is a familiar dilemma faced by managers of research in risk-averse, budget-conscious organizational environments. But there are times when progress can only be made by taking a radical approach, and “failures” can still result in a scientific advance in the sense that learning took place. In this regard, one is reminded of Thomas Edison’s remark the he did not fail, he simply found ways that did not work. Similarly, one might assume that the simple solution for reducing uncertainty is to pursue a small-scale project that is highly focused on a smaller range of unknown factors, but this can result in losing what many might call the “big picture”, a problem in any systemic science or multiple component technology. Managerial dilemmas are not restricted simply to the choice of research objectives but also exist in the selection of research tasks. Research projects of a large size require a significant investment in management control and coordination. Such projects also typically need a substantial support staff and support systems for required services, such as accounting, human resources, and library resources. Further, larger teams also need effective leaders who can allocate resources and maintain communication and focus among team members. Finally, management also must define and communicate clear goals and strategies in order to align large groups with strategies. Indeed, the success of a large research project often depends on management correctly positioning the research to fulfill a need or fill a niche. Overall, a unifying system-wide scope makes it possible to set specific goals and track progress. The dilemma is that in increasing size and, correspondingly,

Research Profiles

internal coordination and control, there is less and less research autonomy and more bureaucracy. Clearly, the distinction between autonomy and internal control is one of the basic structural dilemmas. Therefore, given the tight connection between size and managerial control, we have included the degree of coordination of the research project or program on the vertical dimension of the typology of structure. The desired independence and autonomy of academics are well known, as is the fact that researchers are motivated as much by the recognition of their work and the intrinsic pleasure of doing their research as by extrinsic rewards. The tension between autonomy and control also manifests itself in another way, which is the need to search for expertise as complexity increases. In so far as one locates this expertise outside the organization, another structural dilemma emerges because it conflicts with organizational autonomy given that some external control comes with the external expertise. In this regard, coordination difficulties across organizational boundaries are a dominant theme in the inter-organizational literature. We note that there is a certain irony in this dilemma. Those projects that are already more complex because of their revolutionary strategy are precisely the ones that are most likely to recognize the need for other pools of knowledge. This flows from their aspirations and thus makes the strategic choice so critical, as Zammuto and O’Connor (1992) argued in explaining the adoption of the radical process technology of flexible manufacturing. Meeus and Faber (2006) also observe this is true on the inter-organizational side of the structure as well. In summary, we have identified a number of dilemmas attached to both the choice of research outcome and the choice of research task within the constraints of how the context—economic, political and scientific—constrain the choices that are made. And as we combine the choice of outcome with the choice of task, these dilemmas multiply, a subject we turn to in the next section.

Constructing the Research Profiles and Management Styles A central idea in contingency theory is that structure must follow from strategy, thus the two basic dimensions of research objectives discussed above must dictate how the research tasks should be structured. The creation of general variables that is accomplished with the typologies describing both the research objectives and the research tasks allows one to develop several hypotheses about the match between task and objective or intended outcome, the equivalent at the project or program level to the match between structure and strategy. The heart of our perspective is connecting the typology of research objectives with the typology of research tasks, which results in four kinds of research profiles. And since each choice of outcome and of task also has a set of related dilemmas, it is also the case that there are four general areas of managerial problems.

Connecting Research Tasks to Research Objectives As we stated above, the matching of research task with research outcome is the heart of the theory of management styles. The construction of the new perspective is based on a series of hypotheses that emphasize the range of each of the dimensions used to identify research objectives and research tasks. Of these hypotheses, we present two, both of which draw heavily on contingency theory. 1. The greater the emphasis on the radicalness of the outcome in science or technology, the greater the need to emphasize the complexity or diversity of expertise in the research project, program or inter-organization network. The more that managers choose to pursue a radical breakthrough in science, then the research project itself must become complex, particularly in terms of different types of knowledge. As

417

Research Profiles

discussed before, this flows from the need to synthesize different perspectives as a way of achieving the radical breakthrough. In this vein, Shenhar’s (2001) study of engineering projects provides at least some evidence for the fit between the choice of a revolutionary strategy and the need for expertise; projects coded as most uncertain had the highest proportion of academic degrees. Research findings on the positive relationship between complexity and industrial innovation defined as new products or services have been accumulated over a forty-year time period. Damanpour (1991) summarized the first thirty years of work in a meta-analysis that explored the relative importance of complexity vis-à-vis other variables while controlling for a number of alternative possibilities. Hage (1999) updated this study and noticed the absence of research on complexity and radical innovation in science. For instance, in discussions about the importance of the discovery of the double helix structure of DNA, it is often overlooked that Watson had been trained as a biologist and Crick as a physicist (Watson, 2001). In a study of the Institut Pasteur, the relationship between complexity and radical innovation holds quite strongly at the level of project (Hage & Mote, 2008). 2. The greater the emphasis on a broad scope of focus, the greater the need to increase the size of the research project, program or inter-organizational network. As the scope of research broadens, the specific expertise that is needed may not reside within the research organization and must be sought outside the organization, either informally, as in knowledge or practice communities, or formally, as in inter-organizational alliances or consortia. The search for expertise suggests that the research unit increases in size as a consequence, moving along the continuum from project to program to inter-organizational network. The movement along this continuum is driven by the notion that scope is a measure of the number of variables 418

involved in the research and the choice to study multiple levels, components of systems or entire systems. Many of the national public laboratories in the U.S. were created to work on difficult and intractable problems. For example, the origins of both Los Alamos and Sandia National Laboratories reside in the Manhattan Project and the drive to construct the first atomic weapon. In response, the Europeans created CERN in 1954 to reverse the brain drain of physicists to the United States and to restore and rebuild European research in high-energy physics. In general, these types of large national laboratories and mission agencies are quite different from the smaller academic research projects funded by the National Science Foundation (NSF) or National Institutes of Health (NIH). Furthermore, within these national laboratories and mission agencies, additional distinctions can be made between problems that can be approached with small projects and those that require a more extensive program of research. If the project focuses on a system, then almost by definition, one needs a large-scale research program to handle all the aspects of the system, if not a mission agency or national laboratory. Oceanographic ships, space shuttles, and radio astronomy observatories are all examples of quite expensive equipment needed to study particular natural systems, which in turn means quite large support staff and a large number of technicians for their operation. Another aspect of scientific research is what might be called the difficulty of the research problem, that is, studying phenomena under extreme conditions. For example, consider the case of conducting research on flora and fauna at the bottom of the ocean or the difficulty of studying black holes at the other end of the universe. Again, the presence of extreme conditions often necessitates a large scale program of research. With these two hypotheses, we can delineate four distinctive kinds of Research Profiles, each with their own distinctive management challenges and dilemmas. We now turn to a discussion of these four Research Profiles.

Research Profiles

FUTURE RESEARCH DIRECTIONS: RESEARCH PROFILES AND MANAGEMENT STYLES Combining the two dimensions generates four ideal-type Research Profiles, each of which can be used to define a particular management style. In addition, because we have suggested that there were a series of dilemmas associated with the choices of the degree of radicalness and the degree of scope and similarly with the degree of complexity and the size of the project, we want to explore ways in which these dilemmas can be managed. In Table 3, we have combined the dilemmas associated with the strategic structural choices on the assumption that structure follows strategy as we have hypothesized above. Within each quadrant are potential solutions to the dilemmas associated with each Research Profile. It is critical that one interpret this figure as suggesting dilemmas in all four quadrants. While it is easy to argue that high risk or many uncertainties pose managerial problems that necessitate solutions, it is much harder to recognize that too little risk or too few uncertainties also pose managerial problems that require solutions. In particular, the combination of little risk and few uncertainties, which is part of the Small Incremental Research Profile, raises issues about the loss of competitiveness of the research organization in which the project of this nature are located, as well as lack of understanding

even by research sponsors, of the importance of some of this work. Two important general qualifications need to be made about the four Research Profiles. First, the dimensions on which the Research Profiles are based have considerable range. In other words, one must remember that the underlying dimensions are the degree of radicalness, the broadness of the focus, the degree of complexity, and the size of the project, program, or inter-organizational network. Of course, this means that the specific managerial problem discussed occurs in varying quantities accordingly. Second, we recognize that each of these dilemmas exists to a certain degree in each quadrant. For example, if we focus on the Small Radical Research Profile, the two primary managerial problems are to encourage risk-taking and integration of diverse perspectives. But these same issues exist in the Large Radical Research Profile, only now they are overshadowed by the larger number of uncertainties and the greater amount of coordination needed to conduct research. In contrast, in the Small Incremental Research Profile, the motivational problems are more centered on the issue of keeping abreast of the discipline or the competition. As a consequence, a very different set of managerial solutions are needed because of the greater research autonomy. In the Large Incremental Research Profile, the same motivational problems exist but now they emerge at the level of research teams within the program and thus necessitate a different set of managerial solutions.

Table 3. Research profiles: Strategic and structural dilemmas and associated management challenges Strategy Structure Lower Uncertainty

Higher Uncertainty

Lower Risk/Payoff

Higher Risk/Payoff

Less Integration

More Integration

Less Coordination

Small specialized projects; Value the individual; Provide professional development.

Small complex projects Encourage exploration and risk taking; Integrate ideas externally and internally.

More Coordination

Large specialized programs; Good internal allocation of resources; Good technical management.

Large complex programs; Clearly defined vision, project goals; Build strategic relationships.

419

Research Profiles

In this respect, we associate dilemmas and Research Profiles where the problems tend to be accentuated. To help set the stage for future research on this perspective, we identify one managerial problem associated with the choice of the research outcome and one problem associated with the choice of the research task. Many of these examples arose from the discussions in the focus groups that were conducted in the development of the research environment survey instrument discussed earlier (Jordan & Streit, 2003; Jordan, Streit, & Binkley, 2003; Jordan, Streit, & Matiasek, 2003)

Small Radical Research Profile It goes without saying that most, if not all, researchers would like to have a radical breakthrough in their scientific or technological research, and many often tend to think that their research is geared toward that end. However, as we have suggested, it is important to view this along a dimension with considerable range. In our work at Sandia National Laboratories, we identified several examples of small projects (under 10 million funding over five years) with complex research teams that achieved radical breakthroughs, such as the project that developed a particulate trap for diesel engines that reduced particulates by 400 percent as well a project focused on the development of semiautonomous, modular robotic control technology that greatly decreases the necessity of human control. Within NOAA, we identified a project focused on new compression methods for satellite data which achieved compression rates of almost a factor of 3 over a current compression standard (Mote, Jordan, & Hage, 2007). Two managerial problems associated with this Research Profile are encouraging researchers to take intellectual risks and to integrate them as a team. In other words, the motivation issue is how to encourage a team of researchers to think and act boldly. The managerial solution associated with the choice of pursuing radical objectives

420

is to create enough time to think and to explore, encourage the willingness to take risks and also have an atmosphere of challenge. A potential solution is to provide sufficient flexibility, with the resources and freedom to pursue new ideas. This suggests that it is necessary to give researchers in this profile enough time while resisting the pressure of deadlines that may be coming from those higher in the hierarchy. As we have discussed, increasing the radicalness of the outcome requires that one increase the complexity of the research team, adding multiple disciplines, specialties within them, and technicians and their specialized equipment. But here we face a critical managerial problem associated with this Research Profile: How does one integrate across the various disciplines and equipment so that there is access to tacit knowledge? Furthermore, as Nooteboom (1999, 2000) has observed, although one creates radical innovation by increasing cognitive distance, the tendency is for people to communicate less as the cognitive distance increases. Clearly, the managerial solution is to develop a number of mechanisms to encourage the sharing of tacit knowledge (Judson, 1979), that is to encourage integration across diverse perspectives. Furthermore within the context of science and smaller research projects that address only a component of a larger system or area, we would suggest that this requires more than the classical mechanisms suggested by Lawrence and Lorsch (1967), because this involves ensuring the cross-fertilization of ideas and managing the external collaborations with various knowledge communities.

Large Radical Research Style As one moves from a project that costs less than ten million dollars over a five year period to a program that costs more ten million dollars, and even upwards of a billion as in the example of NASA’s space program, a new set of problems emerge that necessitate a different managerial

Research Profiles

style. Indeed, the increase in scale magnifies the problems described above, but alters them in interesting ways. One of the earliest examples of a large-scale program of research is the famous Manhattan Project that produced the first atomic weapon. Since that time, large-scale research programs have been initiated to pursue a number of high-profile topics, with recent examples being the Human Genome Project and the National Nanotechnology Initiative (NNI). On a somewhat smaller scale, Sandia National Laboratories has initiated a handful of relatively large projects under the category of Grand Challenges, which are designed to be first to solve a major technical challenge. One recent example has been a research project on the feasibility of wide-scale, mainstream use of light emitting diodes (LED), which requires advances in both semiconductor design and manufacturing. In this Research Profile, not only does one want to encourage taking risks and to integrate diverse perspectives, but one also has to be concerned about handling the number of uncertainties and the multiple research teams, including teams that cross organizational boundaries. What are the solutions? To maintain an emphasis on a radical breakthrough in a larger scale program of research, one must put forth a clear and consistent vision that provides much of the motivation for the research teams. Part of this vision is the investing in future opportunities that may provide the breakthrough in either the knowledge or technology needed to advance. The problem of handling the many uncertainties is dealt with by developing a clear set of project goals and strategies so that the many different research teams and organizations that are cooperating together in this effort can understand their responsibilities. The clarity of the vision, such as Project Apollo’s explicit goal to land a man on the moon and return him safely to Earth, is critical for the success of these large scale and complex efforts. Initially, the process of determining the right research strategy and achieving a consensus on that strategy can be both time and resource

intensive. Hence, continued funding over long time periods is essential. Therefore, projects and programs in this profile often endure well beyond the shorter time horizon of smaller projects, as Leifer et al (2000) have observed. But an increase in scope of focus also creates new difficulties with managing the complexity of multiple research teams in networks of organizations, all of which have to be integrated. And in large programs and research organizations, it is important to maintain coordination and control over the research efforts. As research autonomy is reduced in this manner, so too are the opportunities to create a radical breakthrough. One of the ways in which this reduction in autonomy impacts on the creativity of the research is the inherent conflict between creativity and maintaining progress and schedules—an important issue in large complex programs. While measuring and tracking progress is an essential part of the solution to this managerial problem, it must be done in a way that does not force researchers to focus on shorter term, incremental, measurable products, benchmarks, or milestones, or take too much time away from research.

Small Incremental Research Profile The managerial problems shift dramatically in small scale research projects designed for incremental improvements in science and technology, which, of course, are the most common ones in academia, government and in industry. Interesting examples from our work with NOAA include the ongoing, incremental improvements in the calibration of satellite data, as well as the identification of a new type of hurricane that maintains its intensity for a longer time period. A project from our work at Sandia National Laboratories also helps to illustrate this profile. This research project seeks to understand the nature of soot formation from unsteady, “dirty” flames; previous research primarily focused on the properties of steady flames generated by simple, pure hydrocarbon

421

Research Profiles

fuels. As these examples demonstrate, as well as many of the research projects funded by the NIH or the NSF, the research is not necessarily aimed at radical advances but at incrementally pushing the knowledge boundaries. Since the projects in this profile are relatively smaller, the effectiveness depends much more upon the individual researcher and, at most, a small team. Therefore, one of the managerial problems in this profile is to ensure continued professional development, particularly with regard to maintaining and improving skills. Left to their own devices, researchers often tend to focus on the same set of problems across much of their professional life. In this regard, a kind of human capital decay sets in because not enough new issues are being considered to really continue to master a particular specialty. Professional development, such as continued education, seminars, and conferences, becomes a key mechanism for increasing their human capital. Individual growth is also encouraged when there is an atmosphere of cooperation rather than competition among diverse research projects in an organization. Under these circumstances, individuals are more willing to interact and talk with others about their research, particularly scientific challenges they might be facing and need help in overcoming. Unlike the Small Radical profile, the problem here is potentially too low a level of aspiration rather than one that is too high. Again, the managerial solution to this problem is in various ways to indicate to the individual that they are valued and their work is valued even if it does not need to take intellectual risks or a broad focus. This can be accomplished by providing respect for the individual and valuing their ideas and opinions which can be achieved by allowing autonomy in decision-making, as well as more latitude in choosing areas of research. While this may appear to be quite simple, it is, in fact, often more difficult because typically the rewards are given to those scientists and research teams that make the big breakthroughs. Therefore, part of the

422

solution includes providing greater recognition to the contributions of researchers who have not experienced similar achievements.

Large Incremental Research Profile The combination of less radical and broad scope of focus research is frequently found in the various national laboratories and mission agencies funded by federal governments. This profile is characterized by large-scale and functionally specialized teams. For example, NOAA maintains separate research programs on both the atmosphere and the oceans, each of which encompasses a number of integrated research projects. Further, the development and implementation of a new weather satellite typically entails a substantial program that includes teams from a number of mission agencies, such as NOAA and NASA, the military and private contractors. This type of research is focused largely on incremental advances and poses different managerial challenges than research efforts focused on radical advances, such as hydrogen fuel-based cars or unmanned aerial vehicles. Paradoxically, the large scale of research in this profile poses two managerial problems that are also observed in small, specialized projects discussed above, that is, professional development and individual respect. Given the larger scale of research, however, the existence of these two problems in this profile reflects the need to overcome the impersonality of layers of bureaucracy and, hence, suggests different management strategies. A major difference in which the handling of motivation in this profile differs from that above is that rather than value the individual or the few individuals in the team, here the problem is proper recognition of each team. Unlike the Large Radical Profile, which also emphasizes teams and teamwork, this profile emphasizes the pursuit of incremental advances, primarily on components of an overall system and use of functionally specialized teams. It goes without saying that coordination among

Research Profiles

these teams relies not only on management that is well informed about the research and rewarding and recognizing individual merit, but also on good internal allocation of funding. Cultivating well-informed, technically adept management within the research project is always difficult, for it requires skill in administration and management of people as well as knowledge and skills in the research area. This is particularly important given that the research expertise may lie in separate departments not under the immediate control of the program manager. Indeed, it is this kind of profile that led to the creation of matrix authority structures and, as is well known, this particular structure has not always functioned well because employees find it difficult to serve two masters, discipline (or department) and project (Tushman & O’Reilly, 1999; Tushman & O’Reilly, 1996). For all of these reasons, the need for clear cut measures of technical progress for each team is essential so that progress can be measured carefully and appropriately. As indicated in the Large Radical profile, one of the major issues for large projects is the lack of research autonomy. Shenhar (2001) provides a vivid description of how managers in this profile attempt to bureaucratize the coordination of the disparate parts of the research program or teams. But, in fact, this solution is what creates many of the problems within this research profile. In addition to the impersonal effects, bureaucratic control also has negative impacts on technical management in requiring time for administrative tasks that can detract from time spent on research. Indeed, in this situation, team leadership becomes very desirable as a solution (Hage & Mote, 2008).

CONCLUSION In summary, our argument is that the management of different types of research, including basic, applied, product development, and quality control, necessitates an adaption of existing theories of

innovation and R&D management in the current literature. The Research Profiles should help with portfolio level decisions because it proposes general categories of research objectives and tasks that can be applied across various arenas of research from basic to manufacturing research to inform strategy decisions and to judge progress and effectiveness. Thus, our perspective about the diversity of research projects, contained in the Research Profiles, has an incredible spread of potential impact. Of course, a test of this assertion is the number of insights that one obtains from the perspective and below we identify and discuss three such insights. One of the insights is the revision of the organizational learning perspective. In this respect, we would argue that the Research Profiles represent four different kinds of learning. The strategic choice of pursuing a radical breakthrough is probably going to lead to more learning than the pursuit of an incremental strategy. This corresponds to the notion of competency destroying innovation and competency enhancing innovation, which largely looks at the impact on other organizations. The Research Profiles perspective suggests that the organization that has the radical breakthrough is learning a great deal and building its capabilities in the process. As has been indicated in our discussion of each of the four profiles, whether the organizational structure and management style match the research strategy will determine if the desired scientific and organizational learning actually takes place. In each instance, different obstacles to learning present themselves. A second insight is the revision of organizational innovation theory, particularly the emphasis on the organic model, and the integration with the inter-organizational literature. The diversity of research projects shifts the attention in organizational innovation to the study of where the research is largely accomplished, while recognizing that there is not just the organic model but four profiles of research activity.

423

Research Profiles

The third insight is the discussion of inherent dilemmas and problems. Rather than perceive low risk and low uncertainty as presenting no managerial dilemmas, we have suggested that they do. And unlike traditional contingency arguments that assert that the correct fit ameliorates any managerial problems, we are suggesting quite the opposite. Even with a good fit, there are still managerial problems associated with each of the four types of Research Profiles. These problems flow from the dilemmas that have been delineated. We have suggested what some of the solutions to these dilemmas are and then indicated that these define specific management styles. This is clearly not the usual perspective in either contingency theory, or management theory in general, but we would argue it is critically important given the central importance of research for both economic competitiveness and national security.

REFERENCES Alter, C., & Hage, J. (1993). Organizations working together. Newbury Park, CA: Sage. Braun, D. (1998). The role of funding agencies in the cognitive development of science. Research Policy, 27, 807–821. doi:10.1016/S00487333(98)00092-4

Burns, T. R., & Stalker, G. M. (1961). The management of innovation. London, UK: Tavistock. Cameron, K. S., & Quinn, R. E. (1998). Diagnosing and changing organizational culture: Based on the competing values framework. Reading, MA: Addison-Wesley. Clarke, T. E. (2002). Unique features of an R&D Work environment and research scientists and engineers. Knowledge in society, 15(3), 58. Dahlin, K. B., & Behrens, D. M. (2005). When is an invention really radical? Defining and measuring technological radicalness. Research Policy, 34(5), 717–737. doi:10.1016/j.respol.2005.03.009 Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34(3), 555–590. doi:10.2307/256406 DiMaggio, P., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147–160. doi:10.2307/2095101 Gelès, C. (1999). Managing science: Management for R and D laboratories. Gomes-Casseres, B. (1996). The alliance revolution: The new shape of business rivalry. Cambridge, MA: Harvard University Press.

Brown, E. A. (1997). Measuring performance at the army research laboratory: The performance evaluation construct. The Journal of Technology Transfer, 22(2), 21. doi:10.1007/BF02509641

Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17, 109–122.

Brown, S. L., & Eisenhardt, K. M. (1995). Product development: Past research, present findings and future directions. Academy of Management Review, 20(2), 343–378.

Hage, J. (1999). Organizational innovation and organizational change. Annual Review of Sociology, 25(1), 597–622. doi:10.1146/annurev. soc.25.1.597

Browning, L. D. (1995). Building cooperation in a competitive industry: SEMATECH and the semiconductor industry. Academy of Management Journal, 38(1), 113–151. doi:10.2307/256730

Hage, J., & Hollingsworth, J. R. (2000). A strategy for the analysis of idea innovation networks and institutions. Organization Studies, 21(5), 971–1004. doi:10.1177/0170840600215006

424

Research Profiles

Hage, J., & Mote, J. (2008). Transformational organizations and institutional change: The case of the Institut Pasteur and French science. Socioecon Rev, 6(2), 313–336. Hagedoorn, J., & Duysters, G. (2002). Learning in dynamic inter-firm networks: The efficacy of multiple contacts. Organization Studies, 23(4), 525–548. doi:10.1177/0170840602234002 Hobday, M. (1998). Product complexity, innovation and industrial organization. Research Policy, 26(6), 689–710. doi:10.1016/S00487333(97)00044-9 Joly, P. B., & Mangematin, V. (1996). Profile of public laboratories, industrial partnerships and organisation of R & D: The dynamics of industrial relationships in a large research organisation. Research Policy, 25, 901–922. doi:10.1016/00487333(96)00882-7 Jordan, G. B., Hage, J., Mote, J., & Hepler, B. (2005). Investigating differences among research projects and implications for managers. R & D Management, 35(5), 501–511. doi:10.1111/j.14679310.2005.00407.x Jordan, G. B., & Streit, L. D. (2003). Recognizing the competing values in science and technology organizations: implications for evaluation. In Shapira, P., & Kuhlmann, S. (Eds.), Learning from science and technology policy evaluations. Northhampton, MA: Edward Elgar. Jordan, G. B., Streit, L. D., & Binkley, J. S. (2003). Assessing and improving the effectiveness of national research laboratories. IEEE Transactions on Engineering Management, 50(2), 228–235. doi:10.1109/TEM.2003.810820 Jordan, G. B., Streit, L. D., & Matiasek, J. (2003). Attributes in the research environment that foster excellent research: An annotated bibliography. Albuquerque, NM: Sandia National Laboratories.

Judson, H. F. (1979). The 8th day of creation: Makers of the revolution in biology. New York, NY: Simon & Schuster. Kim, J., & Wilemon, D. (2007). The learning organization as facilitator of complex NPD projects. Creativity and Innovation Management, 16(2), 176–191. doi:10.1111/j.1467-8691.2007.00427.x Kline, S. J., & Rosenberg, N. (1986). An overview of innovation. In Landau, R., & Rosenberg, N. (Eds.), The positive sum strategy: Harnessing technology for economic growth (pp. 275–306). Washington, DC: National Academy Press. Latour, B., & Woolgar, S. (1979). Laboratory life: The social construction of scientific facts. Beverly Hills, CA: Sage Publications. Lawrence, P., & Lorsch, J. (1967). Organizations and environment. Boston, MA: Harvard Business School. Leifer, R., McDermott, C. M., O’Connor, G. C., Peters, L. S., Rice, M., & Veryzer, R. W. (2000). Radical innovation: How mature companies can outsmart upstarts. Boston, MA: Harvard Business School Press. McDermott, C. M., & O’Connor, G. C. (2002). Managing radical innovation: An overview of emergent strategy issues. Journal of Product Innovation Management, 19(6), 424–438. doi:10.1016/ S0737-6782(02)00174-1 Meeus, M. T. H., & Faber, J. (2006). Interorganizational relations and innovation: A review and theoretical extension. In Hage, J., & Meeus, M. T. H. (Eds.), Innovation, science and institutional change: A research handbook (pp. 67–87). London, UK: Oxford Press. Menke, M. M. (1997). Managing R&D for competitive advantage. Research Technology Management, 40(6), 40–42.

425

Research Profiles

Mohrman, S. A., Galbraith, J. R., & Monge, P. (2004). Network attributes impacting the generation and flow of knowledge within and from the basic science community (Tech. Rep.). Technical Report Submitted to the Department of Energy. Mote, J. E. (2005). R&D ecology: Using 2-mode network analysis to explore complexity in R&D environments. Journal of Engineering and Technology Management, 22(1/2), 93–111. doi:10.1016/j.jengtecman.2004.11.004 Mote, J. E., Jordan, G. B., & Hage, J. (2007). Measuring radical innovation in real time. International Journal of Technology. Policy and Management, 7(4), 355–277. Nooteboom, B. (1999). Inter-firm alliances: Analysis & design. London, UK: Routledge. doi:10.4324/9780203265277 Nooteboom, B. (2000). Institutions and forms of co-ordination in innovation systems. Organization Studies, 21(5), 915–939. doi:10.1177/0170840600215004 Pelz, D. C., & Andrews, F. M. (1976). Scientists in organizations: Productive climates for research and development. New York, NY: Wiley. Powell, W. W. (1998). Learning from collaboration: Knowledge and networks in the biotechnology and pharmaceutical industries. California Management Review, 40(3), 228–240. Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41(1), 116–145. doi:10.2307/2393988 Quinn, R. E., & Rohrbaugh, J. (1983). A spatial model of effectiveness criteria: Towards a competing values approach to organizational analysis. Management Science, 29(3), 363. doi:10.1287/ mnsc.29.3.363

426

Shenhar, A. J. (1993). From low- to high-technology project management. R & D Management, 23(3), 199–214. doi:10.1111/j.1467-9310.1993. tb00823.x Shenhar, A. J. (2001). One size does not fit all projects: Exploring classical contingency domains. Management Science, 47(3), 394–414. doi:10.1287/mnsc.47.3.394.9772 Shinn, T. (2002). The triple helix and new production of knowledge: Prepackaged thinking on science and technology. Social Studies of Science, 32(4), 599–614. Trajtenberg, M. (2006). Defense R&D in the antiterrorist era. Defence and Peace Economics, 17(3), 177–199. doi:10.1080/10242690600645076 Tushman, M. L., & O’Reilly, C. A. (1999). Building ambidextrous organizations. Health Forum Journal, 42(2), 20. Tushman, M. L., & O’Reilly Iii, C. A. (1996). Ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38(4), 8. Van De Ven, A. H., & Polley, D. (1992). Learning while innovation. Organization Science, 3(1), 32. doi:10.1287/orsc.3.1.92 Watson, J. (2001). The double helix: A personal account of the discovery of the structure of DNA. New York, NY: Touchstone. Zammuto, R. F., & O’Connor, E. J. (1992). Gaining advanced manufacturing technologies’ benefits: The roles of organization design and culture. Academy of Management Review, 17(4), 701.

Research Profiles

KEY TERMS AND DEFINITIONS Competing Values Framework: The Competing Value Framework is a theoretical framework for assessing an organization’s culture. The framework consists of two dimensions, organizational focus and decision making control, from which one can derive four distinct organizational cultural archetypes: Clan, Adhocracy, Hierarchy, and Market. (Cameron & Quinn, 1998; Quinn & Rohrbaugh, 1983) Idea Innovation Network: The idea innovation network theory is a conceptual framework for understanding the generation of innovations across organizations. The theory posits that research is differentiated among six arenas reflecting basic, applied, product development, production, quality control and commercialization/marketing (Hage & Hollingsworth, 2000). Innovation: Involves the creation of a new idea, method, process or device. One of the earliest contributions on organizational innovation was

the concept of the organic organization (Burns & Stalker, 1961). In recent years, a great deal of attention has focused on radical innovation (Leifer et al, 2000, McDermott & O’Connor, 2002). Networks: A network is a pattern of relationship among actors, from individuals to organizations. Within the innovation literature, the types of networks studied have included intraorganizational networks (Mote, 2005), knowledge communities (Mohrman, Galbraith & Monge, 2004; Shinn, 2002), interorganizational networks (Alter & Hage, 1993; Powell, Koput & SmithDoerr, 1996), and strategic alliances (Hobday, 1998; Shenhar, 2001). R&D Organizations: Research and development (R&D) organizations are public or private organizations, or subunits of these organizations, focused on the development of scientific or product innovations (Trajtenberg, 2006). Many have argued that such organizations have unique work environments (Clarke, 2002), which require different approaches to management (Geles, 1999).

427

428

Chapter 23

Determinants and Consequences of R&D Strategy Selection Diana A. Filipescu Autonomous University of Barcelona, Spain Claudio Cruz Cázares Autonomous University of Barcelona, Spain

ABSTRACT Nowadays firms are not able to achieve all innovation in-house due to the specific set of technologies required by most products and processes, obliging firms to access external knowledge. In this context, the aim of this chapter is two-fold with the final goal of increasing our knowledge on firm innovating behavior. First, this chapter analyzes the determinants of the R&D strategy (RDS) selection posting the make, buy and make-buy as the three RDSs. Second, this chapter analyzes the consequences that each of the RDSs has on firm innovativeness. Results show that commercial and organizational resources, jointly with the information sources, influence the selection of the strategy. As for the second part of the analysis, we see that all RDSs have positive effects on firm innovative performance but these effects are not straightforward and simple since they vary depending on firm´s type and on the radicalness of the innovation achieved.

INTRODUCTION In order to survive in the competitive scene that companies have faced in recent years and which is characterized by a high level of dynamism (Teece, 1998; López & García, 2005; Diaz et al., 2008), DOI: 10.4018/978-1-61350-165-8.ch023

the continual renewal of competitive advantages through innovation (Cho and Pucik, 2005) and the development of new capabilities (Grant, 1996) has become necessary (Danneels, 2002; Branzei & Vertinsky, 2006). In this context, technology represents one of the most important factors in increasing the national and international competi-

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Determinants and Consequences of R&D Strategy Selection

tiveness of firms, while successful technological innovation in new products and processes is gradually more regarded as being the central issue in economic development (Porter, 1998). Moreover, as highlighted by Shrivastava and Souder (1987) and Bone and Saxon (2000), a key element in the competitive business strategy is the combination of technological innovation and R&D activities. Since the objective of R&D strategies (RDSs) is to guide the firm in acquiring, developing and applying technology in order to generate sustainable competitive advantages (Swan & Allred, 2003), it is extremely important for the firm to select the best way of achieving the technology needed (Clarke et al., 1995). It is emphasized in the literature that firms establish their boundaries based on the decision regarding the type of R&D activities – whether they should be integrated within the company or not. In fact, Williamson (1975) identified a dichotonomous decision between make (internal) and buy (external) RDS; later on, Veugelers and Cassiman (2006) added a third, complementary one, make-buy RDS1. The effect of these RDSs over firms’ innovative results has been thoroughly studied; however, there is no general conclusion except that all of them are, in a way, highly significant in a firm’s innovative impetus. Explicitly, Diaz et al. (2008) find that the three RDSs have a positive impact, while Veugelers and Cassiman (2006) suggest that only make-buy yields the best results, whereas buy has the lowest ones. Even more, most of the research studies carried out in this field of investigation focus on the choice between make and buy strategies, the attention towards a makebuy one or to the reasons behind the selection of one strategy as opposed to another being almost inexistent (e.g., Veugelers & Cassiman, 1999). When referring to the make RDS, firms understand a sole source of knowledge and, thus, important sources of competitive advantages achieved with high costs whose results cannot be clearly foreseen. The buy strategy, on the other hand, is a relatively low-cost one with more

predictable results, offering solutions to some problems related to a lack of capacity. However, it does not stand for competitive advantages since there is a high probability that competitors attain it as well. As for the combination between them, the make-buy strategy, it enhances both the advantages and disadvantages of make and buy RDSs, being extremely complex to manage it. Taking this into consideration, this study has a two-fold focus. Firstly, it aims at finding the determinants of the innovation strategy selection and, secondly, it has the objective of understanding which of the RDSs produce the best results in term of firm’s innovative performance. In order to reach this objective, data from the Technological Innovation Panel (PITEC) provided by the National Statistics Institute from Spain are analyzed, precisely the period 2004-2007. As for the main contributions of this study, they are as follows: Firstly, we look at RDSs as a whole process, considering the determinants of selecting one strategy over another, and next their consequences over a firm’s innovative performance. Secondly, we consider the R&D Capital Stock Model developed by Grilliches (1979), which emphasizes the relation between RDSs and a firm’s innovative performance, employing lagged values of RDSs in order to improve prospects of valid causal inference (Baum, 2006) and to reduce possible endogeneity problems (Bernard and Jensen, 1999; Salomon and Shaver, 2005). Thirdly, we will look at both manufacturing and service industries, aiming at offering a better understanding of the latter, which has not been analyzed in the sense that our investigation does. The study is organized as follows. First, the advantages and disadvantages of each of the RDSs are presented. Next, the determinants and consequences of RDSs are described, with their respective hypotheses, based on the absorptive capacity and open innovation approaches as well as the resource-based view (RBV) theory. The conceptual model is then presented, followed by the description of the methodology employed in

429

Determinants and Consequences of R&D Strategy Selection

this analysis. Results and discussions are offered in a late section, finalizing the study with the conclusions, contributions, limitations and future research lines of investigation.

R&D STRATEGIES: ADVANTAGES AND DISADVANTAGES The make strategy is defined as the internal development of R&D activities, being such a complex one that it requires the creation of internal departments in order to develop it (Dosi, 1988). The information flow between the R&D department of the firm and those which will use the resultant technology could considerably increase as a result of the integration of R&D activities (Fernandez, 2005). At the same time, in-house R&D constitutes a unique source of knowledge and allows for an objective assessment of real innovation needs (West, 2002), with economies of scale being enhanced, transaction costs avoided and barriers against imitation constructed (Contractor & Lorange, 1988). However, choosing to achieve R&D internally has some disadvantages: It is less cost-effective, riskier and less predictable, it takes longer to commercialize the new product (West, 2002), and the firm might remain isolated in only one technology if the R&D department is not flexible (Perrons & Platts, 2004). The speed of development in new technologies is increasing, and due to this some firms prefer to externalize R&D activities since it is not feasible for them to develop such specific technologies internally (Quinn, 2000). Moreover, as stated in the RBV, it is not necessary for firms to own all the resources and capacities when they could access them externally (Barney, 1999). The buy strategy is valuable because it is more reliable and firms’ results are more predictable, since the technology has been already developed and tested (Kessler & Bierly, 2002). In addition, it allows risk calculation a priori, offers solutions to some problems related

430

to a lack of capacity, increases the speed of access to new technology, and reduces risk (West, 2002). When firms decide to externalize the R&D, they acquire access to new knowledge areas (Haour, 1992) through the productive networks that are created (Nishiguchi, 1994). Value creation, agility, quality of technology commercialization, and transfer cost of technology are some factors which condition the buy RDS (Tsai & Hsieh, 2006). Nevertheless, acquiring external technology is not a competitive advantage per se, since it is available for competitors as well (Barney, 1991), providing a short-term strategy to the firm (Kurokawa, 1997). External dependence, functional inequalities, and coordination problems are other disadvantages of the buy strategy (Kotabe & Helsen, 1999). In addition, if a firm has a learning gap it will be unable to take advantage of the technology acquired (Steensma, 1996). As for the complementarity between make and buy RDSs, it is based on the assumption that existing products are more complex, as they must be technologically feasible and economically viable, this complexity requiring multidisciplinary knowledge that may sometimes be exclusively found beyond the firms’ boundaries, involving the combination of internal and external R&D (Chesbrough & Crowther, 2006). Two different theoretical approaches hold that the make and buy strategies may be regarded as complements rather than as alternatives. In this way, the make-buy strategy would be characterized by the advantages and disadvantages for the make and buy strategies but with the additionality that it is more complex to manage and more expensive to achieve. The first approach highlighting the complementarity of the make and buy strategies is the absorptive capacity (Cohen & Levinthal, 1990), being defined as the firm’s ability to recognize the value of external knowledge and to assimilate and apply it for commercial ends (AbecassisMoedas & Mahmoud-Jouini, 2008). Acquisition, assimilation, transformation and exploitation are the four organizational capabilities constituting

Determinants and Consequences of R&D Strategy Selection

the firm’s absorptive capacity (Zahra & George, 2002). Complementarity between make and buy should be emphasized since firms must develop in-house R&D in order to generate or increase their capabilities to scan (acquisition-assimilation) and to integrate (transformation-exploitation) the external knowledge acquired through the buy strategy (Arora & Gambardella, 1990). In other words, a firm will not make the most of the buy strategy efficiently if it does not develop R&D activities internally (Colombo & Garrone, 1996). Furthermore, greater knowledge gained through in-house R&D may serve to modify or improve external technological acquisitions (Veugelers & Cassiman, 1999). The second theoretical background underlying such complementarity is the open innovation approach (Chesbrough, 2003). It argues that firms have changed from the closed-innovation process to a more open process of innovation, where knowledge and technology flow are two-fold: inside-out and outside-in. The former implies that the internal inventions not used by the firm should be commercialized in order to profit from them. The latter, more important in this research, refers to the fact that not even large firms can afford to solely rely on their internal research and might acquire external knowledge though buying patents, licenses, or establishing cooperation agreements, or licensing processes or R&D activities. That is, open innovation is the combination of internal and external ideas and technologies in order to achieve new products, processes and technologies and to reduce time to market (Enkel et al., 2009). As a consequence, those firms acting within a closed innovation perspective will reduce their knowledge-base over the long term (Koschatzky, 2001).

DETERMINANTS OF R&D STRATEGIES Based on the RBV, we consider that the main determinants of RDS selection are the firm’s resources. Amit and Schoemaker (1993) characterized firm resources as the stock of available factors owned and controlled by the firm. Tangible factors, like financial and physical assets, and intangible factors, such as human capital and technological know-how, are the components of firm resources (Grant, 1991). Firm capability is the ability to use and transform the owned resources into a desired end. Without these capabilities, the mere possession of a large amount of resources does not guarantee the creation of a competitive advantage (Song et al., 2007). Thus, according to Penrose (1959), Barney (1991) and Grant (1991), a firm should possess certain intangible assets that competitors cannot copy easily, in this way gaining a sustainable competitive advantage in the market. A firm’s organizational resources are viewed as determinants of RDS selection since they reflect the efficiency and synergy between the departments involved in the R&D process (e.g., R&D, production, and marketing). These resources also embody management and organizational excellence and enable the integration of internal and external knowledge (Bughin & Jacques, 1994; Dyerson & Mueller, 1999), enhancing the absorptive capacity. However, these internal resources have been analyzed as a fostering factor in innovation processes (Bughin & Jacques, 1994; Galende & De la Fuente, 2003), but not as a determinant of RDS selection, a gap in the research literature that this contribution aims at filling. Theory considers a firm’s experience as an intangible asset which represents the basis for obtaining a sustainable competitive advantage (Nonaka et al., 2000; Barney et al., 2001). A firm’s experience is also understood as attainment

431

Determinants and Consequences of R&D Strategy Selection

of knowledge. It is worth underline that a firm’s experience is related to a better management of communication and of necessary creativity to innovate, and to a more effective capacity for absorption (Rothwell, 1986; Cohen & Levinthal, 1990). Hence, it is more likely that experienced firms develop the make RDS since it requires organizational capabilities to control the complex process of R&D, and due to the fact that it is usually more risky and expensive (West, 2002). On the contrary, firms which lack experience are more prone to select the buy strategy so as to externalize risk and overcome environmental uncertainties (Poon & McPherson, 2005). These arguments lead us to pose the following hypothesis:

tions which are usually needed for entry into new international markets (Etflie et al., 1984; Galende and De la Fuente, 2003). When a firm becomes international, it creates new networks and, at the same time, gains access to foreign information and communication technologies, as well as production methods, transportation, and international logistics, which could reduce business transaction costs with potential suppliers, facilitating the buy strategy. Considering this, we state the second hypothesis of this study:

H1: The greater the firm’s organizational resources, the lower the probability of selecting the buy strategy and the higher the probability of selecting the make-buy strategy.

We consider that the technological/knowledge intensity might also affect the RDSs selection. Industries experiencing a large number of technological changes estimate R&D externalization to be the best option because it does not seem right to rely on internal R&D when the market is changing substantially (Noori, 1990). Similarly, when there is great technological diversity in the market, firms are likely to externalize R&D (Cesaroni, 2004). On the other hand, it is suggested that when technological changes are unpredictable, R&D integration becomes necessary (Shrivastava & Souder, 1987) so as to prevent technological innovations that dramatically threaten market stability (Cooper and Schendel, 1976). In the end, a balance between these two poles might be found in the absorptive capacity and the open innovation approaches; that is, firms need to be aware of shifts in technology and gain greater flexibility through the buy strategy. At the same time, however, they might also develop in-house R&D in order to integrate the acquired technology efficiently and gain a competitive advantage. Finally, information sources are also important in the selection of a specific type of RDS. Explicitly, firms which positively assess internal information tend to look for the complementar-

A firm’s relations with foreign clients (Galende & Suárez, 1999), regularly measured by its international achievements, are important intangible assets as well. International achievements are often considered useful for properly exploiting technological innovations (Teece, 1986). As argued by Prashantham (2005), internationalization often leads to crucial growth and useful learning outcomes; it also increases a firm’s market size, thus favoring innovation activity (Galende & Suárez, 1999). Some studies have analyzed the firm’s internationalization as a determinant of R&D activities and found a positive relationship (Kumar & Saqib, 1996; Salomon & Shaver, 2005; Vila & Kuster, 2007; Filipescu et al., 2009). In the study carried out by Veugelers and Cassiman (1999), it was observed that export intensity reduces external R&D selection. One of our arguments is that international firms are more likely to combine make and buy strategies since technological advances are achieved through the development of internal R&D, increasing competitiveness and enacting disruptive innova-

432

H2: The greater a firm’s commercial resources, the greater the probability of selecting the makebuy strategy.

Determinants and Consequences of R&D Strategy Selection

ity between the two RDSs (Veugelers & Cassiman, 1999). Thus, in order to take advantage of external knowledge, firms develop their internal capabilities. When the external knowledge is highly valued, firms will avoid solely developing the make or buy strategies, as they will prefer to combine them in order to make the most of external knowledge through internal R&D development.

CONSEQUENCES OF R&D STRATEGIES The R&D Capital Stock Model developed by Grilliches (1979) emphasizes the positive relation between RDSs and the firm’s innovative performance. This model stresses that R&D activities enhance innovations and these foster firm performance. Furthermore, Grilliches (1979) also argues that the R&D’s effects on innovations are lagged since R&D projects take a minimum of one year to be completed. However, there is no evidence which accounts for lagged effects of make, buy and make-buy RDSs, and this is one of the contributions of this study. The empirical evidence of the effects of the make and buy strategies on firm innovativeness is insufficient and somehow controversial. Interestingly, the buy strategy has always been associated with negative effects when it was the only RDS evaluated. Kessler et al. (2000) analyzed how RDSs affect new product development and found that the buy strategy during the generation of the idea was negatively related to product competitiveness and that externalization during the technological development decreased innovation speed. Lanctot and Swan (2000) developed a scale for measuring a firm’s tendency to externalize technology development and discovered a negative effect of externalization of product and process technology on the firm’s success. Finally, Fey and Birkinshaw (2005) found a negative relationship between contracting R&D and the creation of new products and technologies. These results are

understandable if we consider that those firms solely externalizing R&D activities will not take advantage of it since they have not previously generated the absorptive capacity. There is empirical evidence showing that internal R&D produces better results than on external one. For example, Beneito (2006) found that the buy strategy had positive effects on incremental innovations, while the make strategy had positive effects on both incremental and radical innovations. Haro-Dominguez et al. (2007) and Chen and Yuan (2007) observed positive effects of external and internal R&D on new product development, although the effects were greater for internal R&D. Results of studies where both the make and buy strategies were analyzed are also quite diverse. Jones et al. (2001) observed that external R&D significantly detracted from firm performance in terms of product, market and financial measures, while the make strategy had a positive effect on new product development. Diaz et al. (2008) concluded that both internal and external R&D increased the probability to achieve innovations. Santamaría et al. (2009) considered low-, mediumand high-technology industries and found that the make strategy was significant for both groups, while buy was positive for process innovations in the former and product ones in the latter. Scarce is also the empirical evidence of the complementarity between make and buy strategies on firm innovativeness. Beneito (2006) observed that external R&D had no effect on innovation output per se; however, when it was combined with internal R&D, positive effects arose. Adopting the supermodularity and productivity approaches, Veugelers and Cassiman (2006) found support for this complementarity. They observed that the make-buy strategy had the highest impact on sales due to new products. Nevertheless, following the same methodology, Schmiedeberg (2008) did not observe any trace of complementarity for a sample of German firms. Tsai and Wang (2007) concluded that external R&D had no effect on firm performance when used in isolation; rather, its ef-

433

Determinants and Consequences of R&D Strategy Selection

fect depended on internal R&D efforts. Hence, the level of knowledge positively influenced inward technology for improving firm performance. In 2009, the authors analyzed inward technology for low- and medium-technology firms and found contradictory results. Internal R&D negatively moderated the role of external R&D on sales due to new products. Drawing on the discussion above, the following hypotheses are formulated: H3: All RDSs will have a positive effect on the firm’s innovative performance. However, we do not expect all RDSs to have the same impact on firm innovativeness. Based on the open innovation (Chesbrough, 2003), innovation network (Pyka & Küppers, 2003) and absorptive capacity (Cohen & Levinthal, 1990) approaches and on previous empirical research (i.e.,Veugelers & Cassiman, 2006; Cruz-Cázares et al., 2010), we believe that the make-buy strategy will produce the greatest effect on the firm’s innovation performance because innovations occur mainly through the combination of ideas, resources and technologies (Fey & Birkinshaw, 2005). H3a: The make-buy strategy will have the highest impact on the firm’s innovative performance. Finally, despite the flexibility gained through the externalization of the R&D activities, coordination problems, transactional costs and functional inequalities emerge when externalizing R&D (Kotable & Helsen, 1999), and researchers have found empirical evidence of these limitations (i.e.,Kessler et al., 2000; Fey & Birkinshaw, 2005). Thus, based on theoretical and empirical evidence, we would argue that the buy strategy will have the lowest impact on the firm’s innovative performance. H3b: The buy strategy will have the lowest impact on the firm’s innovative performance.

434

MODEL The conceptual framework developed in this study is presented in Figure 1. As mentioned, this study is composed of a two-step analysis. In the first part, aiming to explain the determinants of the RDS, we set Hypotheses One and Two, arguing that the organizational resources and commercial resources will condition the firm’s selection of a certain RDS. Furthermore, we consider that the firm’s information sources will also influence firm’s selection. Additionally, at this first stage we control for the technological/ knowledge intensity, the fact that a firm belongs to a holding group and the firm’s size. In the second stage of the analysis, following the R&D Capital Approach, we assume that these strategies will have a positive and lagged effect on firm’s innovative performance. The firm’s size and the technological/ knowledge intensity are also used as control variables in the model estimation. We do not consider that the fact that a firm belongs to a group might affect the firm’s innovative performance. In the Methodology section, the variables operationalization and the modes estimates to test the model presented in Figure 1 are described.

METHODOLOGY Data The empirical analysis carried out in this paper draws on the Technological Innovation Panel (PITEC) dataset (2003-2007). The PITEC dataset is conducted by the Spanish National Institute of Statistics (INE) in collaboration with the Spanish Science and Technology Foundation (FECYT) and the Foundation for Technological Innovation (COTEC). Particularly, PITEC compiles the information provided by the Spanish Community Innovation Survey (CIS), which follows the guidelines of the Oslo Manual (OECD, 1997). It includes data on the technological innovation

Determinants and Consequences of R&D Strategy Selection

Figure 1. Conceptual framework

activities like the main obstacles for achieving innovations, the main technological information sources, innovation and R&D expenditures, qualifications of the R&D personnel, outsourcing R&D activities classified by origin and type of partners, and the effects the innovation achievements. This dataset is available in a set of files for each year (i.e., a file for each year 2003, 2004 … 2007). However, due to sampling procedure limitations for the year 2003, we specifically used data for the period 2004-2007, with a sectoral coverage of manufacturing and service firms2. In order to have a consistent longitudinal dataset, we excluded those firms that have experienced any important contingency during the period 2004-2007 from the sample (i.e., mergers and acquisitions, fusions, changes in the industrial activity and missing values in some of the year’s corresponding to the period under analysis). In addition, we excluded those firms belonging to the primary sector (agriculture and mining) and those involved in construction and energy production and/or distribution activities. In order to observe the differences between manufacturing

and service firms, the panel dataset was divided into two samples, the first one containing 6,776 observations of 1,694 service firms, and the second one 14,188 observations of 3,547 manufacturing firms. As observed, both samples are balanced panels. Following Miotti and Sachwald (2003), innovative and non-innovative firms are included in the panel in order to prevent bias in the sample. The main advantage of estimating the model in a panel dataset is that it allows for solving the endogeneity problem by including the independent variables lagged, thus improving the inference of causal effects (Baum, 2006).

Variables Definitions Dependent Variables As commented, this study is composed of a two-stage analysis. In the first stage we evaluate the determinants of RDS selection, leading us to consider the different strategies as dependent variables. This variable was constructed by the two original variables of internal and external

435

Determinants and Consequences of R&D Strategy Selection

R&D expenditures. Firms were asked to report the percentage of R&D expenditures for each of the internal and external activities over the total innovation expenditures. Thus, if a firm reported zero expenses on both activities, the resultant variable has the value of 1 (no R&D), if the firm reported positive internal expenditures and zero external, the dependent variable has the value of 2 (make), for firms with zero internal expenditures and positive external expenditures, the variable has the value of 3 (buy), finally, if the firm reported positive expenditures for internal and external R&D, the composed variable has the value of 4 (make-buy). As observed, the resultant variable has four levels, each for one strategy, and these levels are mutually exclusive. For the second stage of this study, when evaluating the consequences of the RDSs on firm innovative performance, we consider the percentage of sales due to new products - new to the firm-, as the first dependent variable. Additionally, we also attempt to measure the novelty of the innovations achieved, thus, a second dependent variable is considered which measures the percentage of sales due to new products that are new to the market. Measuring the effect of the innovation activities as the percentage of sales due to new products is accepted in the literature (Veugelers & Cassiman, 2006). The main advantage of considering this indicator of innovative performance is that it does not merely measure the innovations achieved but also the successful innovations that reached the market (Cano & Cano, 2006).

Independent Variables As argued in the theoretical background, for the first stage of the analysis, we consider that organizational and commercial resources will influence the selection of the RDSs. The age of a firm is considered a proxy for measuring the organization resources since it represents experience and learning capacity (Galende & De la Fuente, 2003). This variable has the value of 1 if the firm is of

436

recent creation and 0 otherwise. The degree of firm internationalization is considered as a proxy for measuring the organizational resources (Filipescu et al., 2009). This variable has the value of 1 if the firm commercializes its products in a local and national market, 2 if the firm commercializes in other EU countries and 3 if the firm sells its products in any other country. The last independent variables for the determinants of the RDS selection are the firm’s information sources. With the PITEC sample, there are eleven different items that capture the importance of each of the information sources. Firms are asked to mark, from 1 to 5, with the latter being the highest degree, the importance given to that specific information source. Using a factorial analysis those eleven items were reduced into three different factors. The first one captures the information coming from the firm’s market, the second one gathers the information from public organisms and the latter represents the information from conferences and publications3. As observed, all of these information sources are beyond firm boundaries and, following the open innovation approach, we expect that the higher their assessment, the more prone firms will be to externalize R&D activities. The dichotomous variable of belonging to a group is included as a control variable since firms with access to group technology will have incentives to achieve the buy strategy due to a reduction in the transaction costs. For controlling the industry effect, a dummy variable was included which has the value of 1 if the service firm belongs to one of the industries considered with a high knowledge intensity according to Felix’s (2000) classification. The Oslo Manual (OECD, 1997) classification was used to categorize manufacturing firms depending on their technology intensity being low, medium or high. The logarithm of the number of employees is included to account for firm size. The main explanatory variables of firm innovative performance are the RDSs which, contrary to the first stage of the analysis, are separately introduced into the model as dichotomous variables,

Determinants and Consequences of R&D Strategy Selection

with four resulting variables: no R&D, make, buy and make-buy. To assert the lagged effect of the RDSs, we included these variables at t-1 and t-2. The commercial resources, measured as the degree of firm internationalization, are considered independent variables so as to explain firm’s innovative performance. The firm’s technological resources are also considered to be an explanatory variable of the firm’s innovative performance, and they are measured as the percentage of R&D expenditures over total innovation expenses. In order to solve the endogeneity problem, both technological/ knowledge and commercial resources at t-1 were introduced into the model. Finally, the knowledge and technological intensity levels and firm size are included in the model as control variables.

RESULTS Descriptive Analysis Next, Table 1 shows the distribution of RDS selection among service and manufacturing firms. As observed, 38.90% of those service firms in lowknowledge sectors do not achieve any RDS. This percentage is reduced by more than half for those firms in high-knowledge sectors. We can observe the same behavior for manufacturing firms, since the percentage of firms with no R&D decreases as the technological intensity increases. There is a clear tendency for all sectors: the make strategy is the most selected, followed by the make-buy and finally the buy strategies. Interesting is the fact that the highest percentage of firms developing the buy strategy is represented by the low-knowledgeintensity service firms. Table 2 shows the relationship between the RDSs achieved and firm innovative performance. As commented, we consider the percentage of sales due to new products for the firm and for the market as two variables accounting for the firm’s innovative performance. For service and manufacturing firms, these descriptive results highlight

the importance of achieving R&D activities in order to obtain radical innovations. Observe that for those firms without R&D activities the percentage of sales for products new to the firm is quite similar to those firms achieving any RDSs; however, for the percentage of sales for products new to the market, the difference between those firms achieving the make or make-buy strategies is considerably higher than in those firms without R&D activities. Additionally, we could assume that the buy strategy does not influence the products new to the market since its percentage is very low.

Determinants of RDS Selection Since the dependent variable of the first stage of the analysis is a categorical one, we estimate a multinomial logit model with random intercepts that accounts for the individual, unobservable heterogeneity4. In Table 3, the model estimates for the determinants of RDSs selection for service and manufacturing firms are seen. Two models were estimated for each sample; in the first one, the make strategy is the reference variable which is compared with buy and make-buy strategies. In the second model, the buy strategy is the reference and it is compared against the make-buy strategy. By doing so, we are able to compare the preference for selecting one strategy against the others5, something that the previous literature failed to do (e.g., Veugelers & Cassiman, 1999). As observed in Table 3, organizational resources determine RDS selection. For service and manufacturing firms, the negative and significant effects of buy and make-buy strategies in Models A and C indicate that when organizational resources are high firms tend to select the make strategy. From Models B and D we see that there is no significant difference between buy and makebuy. These results lead us to reject Hypothesis 1 and contradict previous studies that highlight that young firms lacking organizational resources avoid the make strategy since they are likely to

437

Determinants and Consequences of R&D Strategy Selection

Table 1. Percentage of RDSs by knowledge/technology intensity Innovation Strategies no R&D

€€€€€€€€€€a. Service firms Low-knowledge intensity 38.92

b. Manufacturing firms

High-knowledge intensity 14.64

Low-Tech. intensity

Medium-Tech. intensity

20.12

High-Tech. intensity

19.09

9.49

make

28.77

44.59

42.95

39.81

47.82

buy

11.03

5.72

6.41

8.33

4.07

make-buy

21.27

35.05

30.53

32.78

38.62

Table 2. Percentage of RDSs by sector Innovation Strategies

€€€€€€€€€€a. Service firms New to the firm

b. Manufacturing firms

New to the market

New to the firm

New to the market

no R&D

15.53

5.88

15.06

6.57

make

16.14

16.13

17.00

10.81

buy

14.86

7.07

15.51

6.44

make-buy

16.11

18.63

16.44

12.65

select the buy strategy in order to externalize risk and overcome uncertainties (Poon & McPherson, 2005). Hypothesis 2 states that the higher commercial resources, the higher the probability for selecting the make-buy strategy; however, this hypothesis cannot be supported. Again, for Models A and C we can observe that the make strategy is preferred over the other two, while make-buy is preferred over the buy strategy for Models B and D. These results are in line with those of Veugelers and Cassiman (1999), who stated that the higher the commercial resources, the lower the probability to select the buy strategy. The information sources for innovations also determine RDSs selection although not in the expected direction. For both service and manufacturing firms, the information for innovation coming from the firm’s market reduces the possibility to solely externalize the R&D activities (Models A and C); however, -due to the positive sign of make-buy in all models-, it does influence the selection of the make-buy strategy. This fact highlights the open innovation approach since

438

those firms aware of changes, tendencies and facilities of competitors, clients and equipment suppliers look forward to gaining the flexibility and speed through externalizing while, simultaneously, developing internal R&D to create knowledge and barriers to imitations. Against what was expected, the negative and significant sings of the buy and make-buy strategies in Models A and C show that when firms highly value the importance of information coming from public institutes, they tend to select the make strategy. As for the information coming from conferences and publications, it does not seem not so clear to determine RDS selection since it is not significant for any case in the service sample, and for the manufacturing firms results merely show that the make strategy is preferred over buy. As for the belonging to a group variable, observe in Model A that buy and make-buy strategies have a positive and significant coefficient showing that the make strategy is the less preferred. These results indicate that belonging to a group, due to a reduction in the transaction cost, stimulates the externalization of R&D, being in isolation or in

Determinants and Consequences of R&D Strategy Selection

Table 3. Determinants of RDS selection Service firms Variables

A. make as ref.

Organizational Resources

-1.9380* (1.0599)

-0.7352** (0.3627)

Commercial Resources

-0.8915*** (0.1158)

Info. firm’s market

buy

Manufacturing firms B. buy as ref.

make-buy

make-buy

C. make as ref. buy

make-buy

D. buy as ref. make-buy

0. 9709 (1.5614)

-2.2619** (1.1165)

-0.9865** (0.4960)

1.0978 (1.5691)

-0.2472*** (0.0745)

0.3944* (0.2147)

-0.3342*** (0.0805)

-0.1728*** (0.0619)

0.2366* (0.1266)

-0.3773*** (0.1107)

0.0255 (0.0706)

0.4344** (0.1782)

-0.1848** (0.0774)

0.2224*** (0.0542)

0.4022*** (0.1095)

Info. public organism

-0.4706*** (0.1119)

-0.1638** (0.0730)

0.3678** (0.1853)

-0.5679*** (0.0788)

-0.1399** (0.0540)

0.4780*** (0. 1220)

Info. conf. & publications

-0.0620 (0.1220)

0.0241 (0.0814)

0.2451 (0.2248)

-0.3914*** (0.0843)

-0.0230 (0.0606)

0.1879 (0.1281)

Group

0.6768*** (0.2135)

0.4419*** (0.1610)

0.0451 (0.4025)

0.1243 (0.1478)

-0.0540 (0.1114)

-0.1557 (0.2312)

High knowledge Int.

-2.8135*** (0.2796)

-1.3856*** (0.2499)

1.9523*** (0.4235)

Medium Tech.

0.3122* (0.1834)

0.1581 (0.2499)

0.1278 (0.2767)

High Tech.

-1.0814*** (0.1576)

-0.5303*** (0.1203)

0.6147** (0.2463)

Size

0.3581*** (0.0548)

0.2147*** (0.0422)

-0.1901** (0.0944)

-0. 1469*** (0.0506)

-0.0162 (0.0418)

0.1736* (0.0915)

Constant

-0.7542* (0.3949)

-0.3465 (0.3112)

5.0410*** (0.7447)

-1.4963*** (0.2978)

-0.6798*** (0.2347)

4.3382*** (0.5221)

log-likelihood: -5022.4754 N. observations: 5082 N. firms: 1694

log-likelihood: -10316.92 N. observations: 10641 N. firms: 3547

* p <.1; ** p <.05; *** p <.01; standard errors in brackets

combination with internal R&D. Nevertheless, these results are not extendable for manufacturing firms. Service firms in high-knowledge industries will be likely to select the make strategy, while the buy one is the least preferred. Regarding manufacturing firms, we can see that the technological intensity sector to which the firm belongs also conditions RDS selection. For medium-technology firms, the buy strategy seems to be preferred over make, while for high-technology firms, the buy strategy is the least selected. Contrary to the regular effects on service and manufacturing firms of the determinants described above, firm size presents almost an inverse effect for the two samples. On one hand, for the service

sample, the bigger the firm is, the higher the probability to select the buy strategy, while the lowest probability accounts for the make strategy. On the other hand, bigger manufacturing firms will prefer the make or make-buy strategies over exclusively buying.

Consequences of RDSs The second-stage analysis aims at evaluating the effect of RDSs on firm innovative performance. To do so, the effects of the RDSs are evaluated on the percentage of sales due to new products for the firm and for the market. Due to the truncated nature of the dependent variables, we estimated a

439

Determinants and Consequences of R&D Strategy Selection

Tobit model with random effects for service and manufacturing firms. As commented, in order to empirically demonstrate the lagged effect of R&D activities on firm innovativeness (Griliches, 1979), and looking to solve any endogeneity problem, we include the RDSs in the model lagged at t-1 and t-2. Additionally, this double-lagging allows us to capture the short- and long-term effects of the RDSs on firm innovativeness. First of all, the results of the new-to-the-firm model corresponding to service firms presented in Table 4 are surprising. As observed, none of the RDSs has any short-term (t-1) or long-term (t-2) effect on firm innovativeness. This might indicate that service firms do not need to attain R&D activities in order to obtain non-radical innovations. Continuing with service firms, we can see that all RDSs have positive and significant effects over the percentage of sales due to new products for the market, confirming Hypothesis 3. However, as predicted in Hypotheses 3a and 3b, not all strategies have the same impact. Due to the complementarity stressed in the open in-

novation (Chesbrough, 2003) and absorptive capacity (Cohen and Levinthal, 1990) approaches, the make-buy strategy produces a greater impact for achieving successful radical innovations, confirming Hypothesis 3a. Despite the difficulties that arise when R&D activities are externalized (Narula, 2001), the buy strategy positively impacts the achievement and commercialization of radical innovations for service firms. When increasing the spectrum, we can clearly detect the so-called short-term effect of the buy strategy (Kurokawa, 1997) since it is no longer significant at t-2. As for the make and make-buy strategies, they still impact on firm innovativeness two years after they were achieved; nevertheless, their effect is reduced by half. Interestingly, the greatest effect of the make-buy strategy loses strength at t-2, and its effect is practically the same as the make strategy. Important results emerge when paying attention to manufacturing firms. First, considering the positive and significant effects of RDSs on sales due to new products for the firm, it could be assumed that R&D activities are needed to achieve

Table 4. Consequences of RDS selection Service firms New to firm

New to market

Manufacturing firms New to firm

New to market

Make t-1

5.3661 (5.6233)

30.2971*** (6.4906)

11.9663*** (2.8946)

20.5586*** (3.1499)

Buy t-1

2.4156 (6.5951)

24.2054*** (7.8600)

9.3077** (3.5386)

3.9463 (4.0303)

Make-buy t-1

3.6505 (5.8399)

36.1143*** (6.7580)

10.7482*** (3.0190)

26.0626*** (3.2936)

Make t-2

4.5290 (3.2322)

17.7258*** (3.9480)

4.1783** (2.1354)

9.4276*** (2.4053)

Buy t-2

-3.2977 (4.7804)

-0. 2255 (6.2348)

2.4960 (2.8437)

5.6346* (3.2673)

Make-buy t-2

5.7134 (3.5605)

17.9095*** (4.2867)

4.4934** (2.2567)

12.3009*** (2.5100)

Commercial Resources t-1

0.3342 (1.3543)

6.9480*** (1.4511)

0.9060 (0.9486)

1.0844 (0.9949)

Technological Resources t-1

-0. 0458 (0. 0554)

-0.1091* (0.0624)

-0.0747** (0. 0258)

-0.0778** (0.0277)

High -knowledge Int.

-4.5117 (3.8399)

13.9377*** (4.2633)

Medium-Tech.

-4.2021* (2.2428)

-1.1146 (2.3086)

High-Tech.

1.9892 (1.9301)

5.3593** (1.9791)

Size

-0.7496 (0.7361)

-1.5860** (0.7895)

0. 2306 (0.6254)

-0.7416 (0.6366)

Constant

-6.9791 (6.1713)

-64.6966 *** (6.9983)

-9.5435** (4.0823)

-38.4766*** (4.3749)

* p <.1; ** p <.05; *** p <.01; standard errors in brackets

440

Determinants and Consequences of R&D Strategy Selection

non-radical innovations. Here, Hypothesis 3 is again verified. However, due to the coefficient magnitude, we are not able to support Hypothesis 3a since the make-buy strategy does not produce the greatest impact. It seems that for achieving non-radical innovation, the make strategy is the best option for manufacturing firms. In line with Chen and Yuan (2007), the estimates show that the buy strategy is the one with the least significant effect, confirming Hypothesis 3b. When focusing on the long-term effect, the make and make-buy strategies still positively influence the innovative performance but, as service firms, its effect is reduced by more than half of that of the year before. The buy strategy is no longer significant at t-2. We are not able to support Hypothesis 3 for the last model since the buy strategy does not seem to influence the sales due to new products for the market. Based on the coefficient magnitude, Hypothesis 3a is supported, in which we indicated that the make-buy strategy would produce the greater impact (Veugelers & Cassiman, 2006). The same pattern of the long-term effect-reduction is also detected in this model. Nevertheless, the buy strategy increased when referring to the coefficient size and significance, indicating that this strategy influences radical innovations, but exclusively in a long-term. The absorptive capacity approach is useful to clarify this behavior. Those firms that achieve the make and buy strategies simultaneously can profit from the complementarity in a short-term since they can easily integrate the external knowledge into the firm’s routines. On the contrary, those firms which exclusively buy technology and knowledge can profit from it after two years, since the integration of knowledge takes longer. Concerning the commercial resources, we can observe in Table 4 that they slightly affect firm innovativeness. The only effect registered in the estimates is positive for the sales due to new products for the market for the service firms, meaning that firm internationalization requires highly innovative products and allows access to

knowledge that stimulates these innovations (Filipescu et al., 2009). Contrary to what was expected, the firm’s technological resources, measured as R&D expenditures, negatively influence firm innovativeness for service and manufacturing firms. A possible explanation would be that the innovation process is inefficient for most of the firms in the sample since those R&D expenditures that are not successfully transformed into innovations are sunken costs that negatively affect firm performance (Koellinger, 2008). Finally, knowledge/ technological intensity and firm size little affect firm innovativeness. This might indicate that the knowledge and technology required for achieving this type of innovation is less complex, and a single firm can manage it successfully.

CONCLUSION Why do firms select one RDS over another? What are the effects of the RDSs on firm innovative performance? Are these effects similar for all RDSs? Responding to these questions marked the aim of this research. We selected a sample of service and one of manufacturing firms in order to empirically answer these questions, thus far inconclusive. Initially, two hypotheses were stated for the first part of the analysis - determinants of RDS selection. In the first hypothesis it was argued that firms with higher commercial resources would tend to select the make-buy strategy since it could give the firm the capacity for going beyond the local market and, at the same time, a firm with activities abroad could access new information and networks, thus facilitating the externalization of R&D activities. However, neither for the service nor for the manufacturing sample were we able to support our hypotheses. Our second hypothesis stated that the higher the organizational resources, the higher the probability for selecting the make-buy strategy and the lower the probability for selecting the buy

441

Determinants and Consequences of R&D Strategy Selection

strategy. The results obtained did not give support for this statement either. For high commercial resources, the make strategy is preferred over the others for service and manufacturing firms. This might indicate that when firms are aware of their available resources, they feel confident to achieve R&D activities on their own without taking into account the technologies and knowledge available in the market. Nevertheless, as mentioned next, this excess of self-confidence might be negative. As for the second part of the analysis, three hypotheses were proposed. In the first one, opposing some previous studies (Fey & Birkinshaw, 2005), we stated that the make, buy and make-buy strategies will produce positive effects on firm innovative performance and results gave support for it, for both service and manufacturing firms. Based on the absorptive capacity and open innovation approaches, we hypothesized that the make-buy strategy would produce the better results and the buy strategy the worse results. These hypotheses were confirmed but with some nuances. We observed that the effects of all of the strategies are not straightforward and simple since they vary depending on firm type and on the radicalness of innovation achieved. For manufacturing firms, the make-buy strategy produces the higher results in firm innovativeness as long as the innovation achieved is radical. Nevertheless, when the innovation achievement is non-radical, the make strategy is the best option. For service firms there is not a significant difference between choosing one strategy or another if the firm aims to achieve non-radical innovations, that is, innovations new to the firm, but when the innovation is radical, the make-buy strategy is the one producing the better results. Contrary to some studies which stated that the buy strategy did not affect the innovation output (Schmiendeberg, 2008), or affected it negatively (Fey & Birkinshaw, 2005), we found that this strategy positively affects firm innovation performance for service firms when achieving radical innovations and for manufacturing firms achiev-

442

ing non-radical innovations. Additionally, this strategy has a slight effect on radical innovations for manufacturing firms, but only two years later. Drawing on the absorptive capacity, we could assume that those firms which exclusively buy technology and knowledge can profit from it after two years, since the integration of knowledge takes longer in the absence of an efficient absorptive capacity. On the contrary, those firms that achieve the make and buy strategies simultaneously can profit from the complementarity in a short-term since they can easily integrate external knowledge into firm routines. This study has academic and managerial implications. Firstly, as far as the authors’ knowledge goes, this is the first study that empirically looks at RDSs as a whole process, considering the determinants of selecting one strategy over another and next their consequences over firms’ innovative performances. Second, contrary to previous research, we consider and use the R&D Capital Stock Model (Grilliches, 1979) and observe the lagged effect of the RDSs on firm performance, improving the prospects of valid causal inference (Baum, 2006) and reducing possible simultaneity problems (Bernard and Jensen, 1999; Salomon and Shaver, 2005). Thirdly, we look at both manufacturing and service industries, aiming at offering a better understanding of the latter which has not been analyzed in the sense that our investigation has. Finally, for managers this study can be useful to understand the characteristics of the RDSs and their potential impact on innovative performance to a greater extent. This study is not free of limitations, which come especially from the fact that we dealt with a longitudinal sample which, according to Baltagi (2007), includes problems in the design, data collection, and data management of panel surveys. It is also possible that panel data show bias due to sample selection problems and attrition (Wooldridge, 1995). Other limitations are related to the introduction and measurement of some other variables in the analyses, thus conferring a more

Determinants and Consequences of R&D Strategy Selection

complete image of R&D activities. Moreover, the approach used to measure some of the factors may be less precise than desired. As for future research lines, it would be interesting to be able to realize comparisons between similar studies. By replicating this investigation in distinct geographical contexts, results could be generalized to larger populations. In this way, it would reveal if institutional factors play a role in influencing the relation (Kogut et al., 2002; Peng et al., 2005; Kumar, 2009). Moreover, comparisons among firms with different types of ownership could be also acknowledged, as well as the employment of other criteria to separate the database (e.g. size, sector).

REFERENCES Abecassis-Moedas, C., & Mahmoud-Jouini, S. B. (2008). Absorptive capacity and source-recipient complementarity in designing new products: An empirically derived framework. Journal of Product Innovation Management, 25(5), 473–490. doi:10.1111/j.1540-5885.2008.00315.x Amit, R., & Schoemaker, P. J. (1993). Strategical assets and organizational rent. Strategic Management Journal, 14(1), 33–46. doi:10.1002/ smj.4250140105 Arora, A., & Gambardella, A. (1990). Complementarity and external linkages: The strategies of the large firms in biotechnology. The Journal of Industrial Economics, 38(4), 361–379. doi:10.2307/2098345 Baltagi, B. (2007). Comments on: Panel data analysis - Advantages and challenges. Test, 16(1), 28–30. doi:10.1007/s11749-007-0048-8 Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. doi:10.1177/014920639101700108

Barney, J. B. (1999). How a firm’s capabilities affect boundary decisions. Sloan Management Review, 40(3), 137–145. Barney, J. B., Wright, M., & Ketchen, D. J. Jr. (2001). The resource-based view of the firm: 10 years after 1991. Journal of Management, 27(6), 625–641. doi:10.1177/014920630102700601 Baum, C. F. (2006). An introduction to modern econometrics using Stata. Texas, USA: Stata Press. Bayona, C., Garcia, T., & Huerta, E. (2001). Firms’ motivations for cooperative R&D: An empirical analysis of Spanish firms. Research Policy, 30(8), 1289–1307. doi:10.1016/S00487333(00)00151-7 Beneito, P. (2006). The innovative performance of in-house and contracted R&D in terms of patents and utility models. Research Policy, 35(4), 502–537. doi:10.1016/j.respol.2006.01.007 Bernard, A., & Jensen, J. (1999). Exceptional exporter performance: Cause, effect or both? Journal of International Economics, 47(1), 1–25. doi:10.1016/S0022-1996(98)00027-0 Bone, S., & Saxon, T. (2000). Developing effective technology strategies. Research Technology Management, 43(4), 50–58. Branzei, O., & Vertinsky, I. (2006). Strategic pathways to product innovation capabilities in SMEs. Journal of Business Venturing, 21(1), 75–105. doi:10.1016/j.jbusvent.2004.10.002 Bughin, J., & Jacques, J. M. (1994). Managerial efficiency and the Schumpeterian link between size, market structure and innovation revisited. Research Policy, 23(4), 653–659. doi:10.1016/00487333(94)90015-9 Cano, C. P., & Cano, P. Q. (2006). Human resources management and its impact on innovation performance in companies. International Journal of Technology Management, 35(1-4), 11–28. doi:10.1504/IJTM.2006.009227

443

Determinants and Consequences of R&D Strategy Selection

Cesaroni, F. (2004). Technological outsourcing and product diversification: Do markets for technology affect firms’ strategies? Research Policy, 33(10), 1547–1564. doi:10.1016/j.respol.2004.08.003 Chen, Y., & Yuan, Y. (2007). The innovation strategy of firms: empirical evidence from the Chinese high-tech industry. Journal of Technology Management in China, 2(2), 145–153. doi:10.1108/17468770710756095 Chesbrough, H. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press. Chesbrough, H., & Crowther, A. K. (2006). Beyond high tech: Early adopters of open innovation in other industries. R & D Management, 36(3), 229–236. doi:10.1111/j.1467-9310.2006.00428.x Cho, H. J., & Pucik, V. (2005). Relationship between innovativeness, quality, growth, profitability, and market value. Strategic Management Journal, 26(6), 555–575. doi:10.1002/smj.461 Clarke, K., Ford, D., & Saren, M. (1995). Technology strategy in UK firms. Technology Analysis and Strategic Management, 7(2), 169–190. doi:10.1080/09537329508524203 Cohen, W. M., & Levinthal, D. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–142. doi:10.2307/2393553 Colombo, M. G., & Garrone, P. (1996). Technological cooperative agreements and firm’s R&D intensity. A note on causality relations. Research Policy, 25(6), 923–932. doi:10.1016/00487333(96)00883-9

Contractor, F. J., & Lorange, P. (1988). Why should firms cooperate? The strategy and economics basis for cooperative ventures. In Contractor, F. J., & Lorange, P. (Eds.), Cooperative strategies in international business (pp. 3–30). Lexington, MA: Lexington Books. Cooper, A., & Schendel, D. (1976). Strategic responses to technological threats. Business Horizons, (February): 1–12. Cruz-Cázares, C., Bayona-Sáez, C., & GarcíaMarco, T. (2010). R&D strategies and firm innovative performance: A panel data analysis. International Journal of Innovation Management, 14(6), 1–33. doi:10.1142/S1363919610002982 Danneels, E. (2002). The dynamics of product innovation and firm competences. Strategic Management Journal, 23(12), 1095–1121. doi:10.1002/smj.275 Díaz, N. L., Aguiar, I., & Saá, P. D. (2008). The effect of technological knowledge assets on performance: The innovative choice in Spanish firms. Research Policy, 37(9), 1515–1529. doi:10.1016/j. respol.2008.06.002 Dosi, G. (1988). Sources, procedures and microeconomics effects of innovation. Journal of Economic Literature, 26(3), 1120–1171. Dyerson, R., & Mueller, F. U. (1999). Learning, teamwork and appropriability: Managing technological change in the Department of Social Security. Journal of Management Studies, 36(5), 629–652. doi:10.1111/1467-6486.00152 Enkel, E., Gassman, O., & Chesbrough, H. (2009). Open R&D and open innovation: Exploring the phenomenon. R & D Management, 39(4), 311–316. doi:10.1111/j.1467-9310.2009.00570.x Etflie, I. E., Bridges, W. P., & O’Keeie, R. D. (1984). Organization strategy and structural differences ior radical versus incremental innovation. Management Science, 30(June), 682–695.

444

Determinants and Consequences of R&D Strategy Selection

Felix, B. (2006). High tech industries and knowledge based services. Statistics in Focus, Science and Technology, 13. EUROSTAT. Fernández, E. (2005). Estrategias de innovación. España: Thomson Editores. Fey, C. F., & Birkinshaw, J. (2005). External sources of knowledge, governance mode, and R&D performance. Journal of Management, 31(4), 597–621. doi:10.1177/0149206304272346 Filipescu, D. A., Rialp, A., & Rialp, J. (2009). Internationalisation and technological innovation: Empirical evidence on their mutual relationship. In Sinkovics, R. R., & Ghauri, P. N. (Eds.), New Challenges To International Marketing: Advances in International Marketing (Vol. 20, pp. 125–154). Bradford, UK: Emerald Group Publishing Limited. Galende, J., & De la Fuente, J. (2003). Internal factors determining a firm’s innovative behaviour. Research Policy, 32(5), 715–736. doi:10.1016/ S0048-7333(02)00082-3 Galende, J., & Suárez, I. (1999). A resource-based analysis of the factors determining a firm’s R&D activities. Research Policy, 28(8), 891–905. doi:10.1016/S0048-7333(99)00029-3 Grant, R. M. (1991). The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, 33(3), 114–135. Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(Winter), 109–122. Grilliches, Z. (1979). Issues in assessing the contribution of research and development to productivity growth. The Bell Journal of Economics, 10(1), 92–116. doi:10.2307/3003321

Haour, G. (1992). Stretching the knowledge base of the enterprise through contract research. R & D Management, 22(2), 177–182. doi:10.1111/j.1467-9310.1992.tb00805.x Haro-Dominguez, M. C., Arias, D., Lloréns, F. J., & Ruiz, A. (2007). The impact of absorptive capacity on technological acquisitions engineering consulting companies. Technovation, 27(8), 417–425. doi:10.1016/j.technovation.2007.04.003 Iansiti, M. (1997). From technological potential to product performance: An empirical analysis. Research Policy, 26(3), 345–365. doi:10.1016/ S0048-7333(97)00021-8 Jones, G. K., Lanctot, A., & Teegen, H. J. (2001). Determinants and performance impacts of external technology acquisition. Journal of Business Venturing, 16(3), 255–283. doi:10.1016/S08839026(99)00048-8 Kessler, E. H., & Bierly, P. E. (2002). Is faster really better? An empirical test of the implications of innovation speed. IEEE Transactions on Engineering Management, 49(1), 2–12. doi:10.1109/17.985742 Kessler, E. H., Bierly, P. E., & Gopalakrishnan, S. (2000). Internal vs. External learning in new product development: Effects on speed, cost and competitive advantage. R & D Management, 30(3), 213–223. doi:10.1111/1467-9310.00172 Koellinger, P. (2008). The relationship between technology, innovation, and firm performance -Empirical evidence from e-business in Europe. Research Policy, 37(__), 1317-1328. Kogut, B., Walker, G., & Anand, J. (2002). Agency and institutions: National divergences in agency behaviour. Organization Science, 13(2), 162–178. doi:10.1287/orsc.13.2.162.533

445

Determinants and Consequences of R&D Strategy Selection

Koschatzky, K. (2001). Networks in innovation research and innovation policy – An introduction. In Koschatzky, K., Kulicke, M., & Zenker, A. (Eds.), Innovation networks: Concepts and challenges in the European perspective. Heidelberg, Germany: Physica Verlag. Kotabe, M., & Helsen, K. (1999). Global marketing management. New York, NY: John Wiley & Sons, Inc. Kumar, M. V. (2009). The relationship between product and international diversification: The effects of short-run constraints and endogeneity. Strategic Management Journal, 30(1), 99–116. doi:10.1002/smj.724 Kumar, N., & Saqib, M. (1996). Firm size, opportunities for adaptation and in-house R&D activity in developing countries: The case of Indian manufacturing. Research Policy, 25(5), 713–722. doi:10.1016/0048-7333(95)00854-3 Kurokawa, S. (1997). Make-or-Buy decisions in R&D: Small technology based firms in the United States and Japan. IEEE Transactions on Engineering Management, 44(2), 124–134. doi:10.1109/17.584921 Lanctot, A., & Swan, S. K. (2000). Technology acquisition strategy in an internationally competitive environment. Journal of International Management, 6(3), 187–215. doi:10.1016/S10754253(00)00024-7 López, J., & García, R. M. (2005). Technology and export behaviour: A resource-based view approach. International Business Review, 14(5), 539–557. doi:10.1016/j.ibusrev.2005.07.002 Miotti, L., & Sachwald, F. (2003). Co-operative R&D: Why and with whom? An integrated framework of analysis. Research Policy, 32(8), 1481– 1499. doi:10.1016/S0048-7333(02)00159-2

446

Narula, R. (2001). Choosing between internal and non-internal R&D activities: Some technological and economic factors. Technology Analysis and Strategic Management, 13(3), 365–387. doi:10.1080/09537320120088183 Nishiguchi, T. (1994). Strategic industrial sourcing: The Japanese advantage. Oxford, UK: Oxford University Press. Nonaka, I., Toyama, R., & Nagata, A. (2000). A firm as a knowledge-creating entity: A new perspective on the theory of the firm. Industrial and Corporate Change, 9(1), 1–20. doi:10.1093/ icc/9.1.1 Noori, H. (1990). Managing the dynamics of new technology. Englewood Cliffs, NJ: Prentice Hall. OECD. (1997). Proposed guidelines for collecting and interpreting technological innovation data: Oslo manual. OECD Publishing, 2nd (revised). Edition. Peng, M. W., Lee, S. H., & Wang, D. (2005). What determines the scope of the firm over time? A focus on institutional relatedness. Academy of Management Review, 30(3), 622–633. doi:10.5465/ AMR.2005.17293731 Penrose, E. T. (1959). The theory of the growth of the firm. Oxford, UK: Blackwell. Perrons, R. K., & Platts, K. (2004). The role of clockspeed in outsourcing decision for new technologies insights from the prisoner’s dilemma. Industrial Management & Data Systems, 104(7), 624–632. doi:10.1108/02635570410550287 Poon, J., & McPherson, A. (2005). Innovation strategies of Asian firms in then United States. Journal of Engineering and Technology Management, 22(4), 255–273. doi:10.1016/j.jengtecman.2005.09.001 Porter, M. E. (1998). On competition. Boston, MA: Harvard Business School.

Determinants and Consequences of R&D Strategy Selection

Prashantham, S. (2005). Toward a knowledgebased conceptualization of internationalization. Journal of International Entrepreneurship, 3(1), 37–52. doi:10.1007/s10843-005-0304-5 Pyka, A., & Küppers, G. (2003). Innovation networks: Theory and practice. Northampton, MA: Edward Elgar Publishing. Quinn, J. B. (2000). Outsourcing innovation: The new engine of growth. Sloan Management Review, 41(4), 13–28. Rothwell, R. (1986). The role of small firms in technological innovation. In Curran, J., Stanworth, J., & Watkins, D. (Eds.), The survival of the small firm (Vol. 2, pp. 114–139). London, UK: Gower. Salomon, R., & Shaver, J. (2005). Learning-byexporting: New insights from examining firm innovation. Journal of Economics & Management Strategy, 14(2), 431–461. doi:10.1111/j.15309134.2005.00047.x Santamaría, L., Nieto, M. J., & Barge-Gil, A. (2009). Beyond formal R&D: Taking advantage of other sources of innovation in low- and mediumtechnology industries. Research Policy, 38(4), 507–517. doi:10.1016/j.respol.2008.10.004 Schmiedeberg, C. (2008). Complementarities of innovation activities: An empirical analysis of the German manufacturing sector. Research Policy, 37(9), 1492–1503. doi:10.1016/j.respol.2008.07.008 Shrivastava, P., & Souder, W. E. (1987). The strategic management of technological innovation: A review and a model. Journal of Management Studies, 24(1), 25–41. doi:10.1111/j.1467-6486.1987. tb00445.x Song, M., Benedetto, A. D., & Nason, R. W. (2007). Capabilities and financial performance: The moderating effect of strategic type. Journal of the Academy of Marketing Science, 35, 18–34. doi:10.1007/s11747-006-0005-1

Steensma, K. (1996). Acquiring technological competencies through inter-organizational collaboration: An organizational learning perspective. Journal of Engineering and Technology Management, 12(4), 267–286. doi:10.1016/09234748(95)00013-5 Swan, K. S., & Allred, B. B. (2003). A product and process model of the technology-sourcing decision. Journal of Product Innovation Management, 20(6), 485–496. doi:10.1111/1540-5885.00044 Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15(6), 285–305. doi:10.1016/00487333(86)90027-2 Teece, D. J. (1998). Capturing value from knowledge assets: The new economy, markets for know-how, and intangible assets. California Management Review, 40(3), 55–79. Tsai, K., & Wang, J. (2007). Inward technology licensing and firm performance: A longitudinal study. R & D Management, 37(2), 151–160. doi:10.1111/j.1467-9310.2007.00464.x Tsai, K., & Wang, J. (2009). External technology sourcing and innovation performance in LMT sectors: An analysis based on the Taiwanese Technological Innovation Survey. Research Policy, 38(3), 518–526. doi:10.1016/j.respol.2008.10.007 Tsai, Y., & Hsieh, L. (2006). An innovation knowledge game piloted by merger and acquisition of technological assets: A case study. Journal of Engineering and Technology Management, 23(3), 248–261. doi:10.1016/j.jengtecman.2006.06.004 Veugelers, R., & Cassiman, B. (1999). Make and buy in innovation strategies: Evidence from Belgian manufacturing firms. Research Policy, 28(2), 63–79. doi:10.1016/S0048-7333(98)00106-1

447

Determinants and Consequences of R&D Strategy Selection

Veugelers, R., & Cassiman, B. (2006). In search of complementarity in innovation strategy: Internal R&D and external knowledge acquisition. Management Science, 52(1), 68–82. doi:10.1287/ mnsc.1050.0470 Vila, N., & Kuster, I. (2007). The importance of innovation in international textile firms. European Journal of Marketing, 41-1(2), 17-36. West, A. (2002). Estrategia de Innovación. Clásicos COTEC. Williamson, O. (1975). Markets and hierarchies: Analysis and antitrust implications. New York, NY: Free Press. Wooldridge, J. M. (1995). Selection corrections for panel data models under conditional mean independence assumptions. Journal of Econometrics, 68(1), 115–132. doi:10.1016/03044076(94)01645-G Zahra, S., & George, G. (2002). Absorptive capacity: A review, reconceptualization and extensions. Academy of Management Review, 27(2), 185–203.

ADDITIONAL READING Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. doi:10.1177/014920639101700108 Drucker, P. (1958). Innovation and entrepreneurship. New York, NY: Harper & Row. OECD. (2005). Guidelines for collecting and interpreting innovation data: Oslo Manual (3rd ed.). OECD Publishing.

KEY TERMS AND DEFINITIONS Absorptive Capacity: Is the firm’s ability to recognize the value of external knowledge and

448

to assimilate and apply it for commercial ends (Abecassis-Moedas & Mahmoud-Jouini, 2008). Competitive Advantage: A firm is said to have competitive advantage when it is implementing a value creation strategy not simultaneously being implemented by any current or potential competitor (Barney, 1991). Firm Resources: Firm resources include all assets, capabilities, organizational processes, firm attributes, information, knowledge, etc; controlled by a firm that enable the firm to conceive of and implement strategies that improve its efficiency and effectiveness. They are strengths that firm can use to conceive and implement their strategies (Barney, 1991). Innovation: Is the specific tool of entrepreneurs –and firms-, the means by which they exploit change as an opportunity for a different business or service. It is capable of being presented as a discipline, capable of being learned, capable of being practiced (Drucker 1985). Open Innovation: An approach highlighting that technology and knowledge flows of the firm is tow-fold; inside-out and outside-in. That is, firms must profit for the technology and knowledge generated that are not core to the firm and, firm may actively search new technologies and ideas beyond the firm’s boundaries and combine them with internal knowledge and technologies in order to achieve new products, processes and technologies and reduce time to market (Chesbrough, 2003). R&D Activities: It comprises creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications (OECD, 2005). R&D Strategy: Strategic activity of the firm which objective is to guide the firm in acquiring, developing and applying technology in order to generate sustainable competitive advantages (Swan and Allred, 2003).

Determinants and Consequences of R&D Strategy Selection

ENDNOTES 1

2

3







There is also a fourth RDS, called cooperation in R&D activities (Colombo and Garrone, 1996), but this has usually been studied independently due to its specificity and complexity (Bayona et al., 2001). In 2003 PITEC gathered two samples, one containing firms with more than 200 employees and the other with firms reporting intramural R&D expenditures. This limitation was corrected in 2004 to include a representative sample of firms with less than 200 employees and/or external R&D expenditures, as well as firms with no R&D activities. A detailed description of the database can be found at http://sise.fecyt.es/ Estudios/PITEC.asp (in English). The factorial analysis was carried out following a principal factor with varimax rotation. The original items of the information sources are: inside the firm or group; equipment suppliers; clients; laboratories

4



5



or private institutes; universities; public research institutes; technological centers; conferences and expositions; scientific journals or technical articles; professional or industrial associations. For a detailed description for the model formulation and the analytical solution of the integral, see Rabe-Hesketh et al. (2002). When estimating each model, we can see in the output the probability for selecting each level of the dependent variable against the reference variable; for the first model, the probability for buy, make-buy and no R&D. However, we do not show the probability for no R&D since it represents the probability of enrolling in R&D activities, which is not the aim of this research. For the second model the estimates would show the probability of make, make-buy and no R&D. Here, due to redundancy with the first model, we omitted the make strategy and the no R&D for the same reasons mentioned above.

449

450

Chapter 24

Institutional Innovation Practices in Technopoles: An Example in France Anne Berthinier-Poncet Université de Savoie, France Rachel Bocquet Université de Savoie, France Sébastien Brion Université de Savoie, France Caroline Mothe Université de Savoie, France

ABSTRACT This chapter aims at filling a void in the literature on the question as to whether organizational proximity can be fostered within clusters. We address a dimension that has received little attention until recently, namely the local governance structures of technopoles. The objective was to gain an insight into such institutional practices and to evaluate their effects on firms’ innovation performance. By identifying how geographical and organizational (cognitive and relational) proximity interrelate in the analysis of cluster forms we sought to contribute to the burgeoning literature on the different types of proximity. The empirical research relies on a representative sample of 88 firms implanted within the Savoie Technolac technopole, in the French Rhône-Alpes region. Our results suggest that, even though local governance contributes to territorial anchoring, only the local labor market had a direct significant impact on the firms’ innovation performance. In addition, territorial anchoring combined with the roles played by governance in terms of ‘matchmaking’ and support for technology transfer significantly increased the number of innovation projects. These results suggest that governance has a decisive role in the creation of communication and interaction structures between firms, which are essential for firm innovation. This research may have important implications for governance modes, in not only technopoles but also more generally in clusters.

DOI: 10.4018/978-1-61350-165-8.ch024

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Institutional Innovation Practices in Technopoles

INTRODUCTION The established typology of territorial innovation makes it possible to identify the characteristics of specific clusters such as technopoles and technology parks (Longhi & Quéré, 1993; Levesque, Fontan & Klein, 1998; Moulaert & Sekia, 2003; Carluer, 2006). Despite the importance of their research activities, innovation technopoles are often characterized as having weak inter-firm relationships (Cooke, 2001; Asheim, 2007), thereby limiting their innovation potential on a collective level. Among the factors that contribute to this process, the development of non-spatial forms of proximity represents a key explanatory factor (Markusen, 1996; Angel, 2002; Rallet & Torre, 2007). The various forms of non-spatial proximity can be assimilated to organizational proximity with respect to the interactions between actors, regardless of their nature (Bouba-Olga & Grossetti, 2009). Pecqueur and Zimmermann (2004) proposed a more nuanced characterization that distinguishes between coordination processes based on direct interaction among actors (organizational proximity) and those with no direct interaction (institutional proximity). This distinction seemed particularly relevant to introduce the role that governance may play in order to help develop a local and stable environment, conducive to collective innovation (Longhi & Quéré, 1993; Levesque et al., 1998). Focusing on the dynamics of innovation, two types of technopoles can be distinguished (Cooke, 2001). A “linear” type, which is typical of science parks “à la française” and related to a simple localized agglomeration of productive activities that have no real relationship with each other, and by contrast, an ‘interactive’ type, which is based on organizational and institutional networking between firms, promoting their ability to innovate. Research has long focused on the impact of the structural properties of clusters on their performance and evolution (Brezis et al. 1993; Suire et al. 2006). More recently, Bocquet and Mothe

(2009) have shown that cluster characteristics also affect the type of governance mode. This is in line with many studies that underline the central role of institutions in the creation of non spatial forms of proximity in interactive agglomeration forms (Grossetti, 2004; Pecqueur & Zimmermann, 2004; Leloup et al. 2005; Asheim, 2007; Rallet & Torre, 2007; Carrincazeaux, Grosseti & Talbot, 2008). The French School of Proximity (Torre & Gilly, 2000; Torre, 2006) explicitly introduces the notion of “territorial governance” to designate “the institutional and organizational process of bringing together different modes of coordination between geographically close actors” (Colletis et al., 1999: 34). Territorial (or local) governance (Leloup et al. 2005;Ehlinger et al. 2007;Bocquet & Mothe, 2009) has been shown to play a role in the creation of favourable conditions for collaborative innovation. In interactive technopoles, where firms already share material and cognitive resources, one could think that the coordination challenge associated with governance would be lower. However, this is far from being the case when the cognitive distance between firms is weak, leading to higher appropriation defaults (Nooteboom, 2009). The governance structure can thus play an active role in maintaining and developing these resources within linear types of technopoles as well as in certain types of interactive forms. Empirical research dedicated to the institutional innovation practices implemented by local governance is scarce. The original approach adopted in this chapter consists in identifying such practices within a technopole and in assessing their impact on its members’ innovation performance. We seek here to fill a void in the literature on the question as to whether organizational proximity can be fostered by taking into account a dimension that has been given low consideration, namely the local governance structures of technopoles. The empirical research concerned a representative sample of 88 companies affiliated to the French technopole Savoie Technolac in the Rhone-Alpes

451

Institutional Innovation Practices in Technopoles

region and yielded two types of results. Firstly, although the governance was involved in the territorial anchoring of firms, we showed that calling upon a local labor market had a direct impact on the firms’ innovation performance. Secondly, together with the inter-firm matchmaking role of governance and its facilitating role in technology transfer between research and industry, this territorial anchoring also contributed significantly to the implementation of innovation projects within the technopole. As these innovation projects were ongoing at the time of the study, their effects on innovation performance were difficult to observe. This chapter is organized as follows: We first characterize the concept of “technopole” by focusing on the specificities of French technopoles. Then, following the proximity approach, we consider the possible influence of institutional practices on the innovation performance of member firms, and analyze the impact of the institutional practices implemented by the local governance on innovation through the study of Savoie Technolac.

TECHNOPOLES AND DYNAMICS OF INNOVATION The technopolitan phenomenon and its associated technology parks or technopoles have experienced strong growth in many developed countries since the late seventies (Longhi & Quéré, 1991, 1993; Doloreux, 1999). Technopoles are a tool for the strategic development of regional innovation systems (Doloreux 1999; Longhi & Quéré, 1993). Technopoles are public initiatives designed to promote technological innovation. They are also viewed as local zones created in order to coordinate existing resources and create new ones. Far from presenting a homogeneous model of territorial innovation, recent research has identified two types of technopoles with distinct properties and performances (Cooke, 2001). We interpret this distinction following the proxim-

452

ity view and identify the role of the institutional practices adopted by a technopole’s governance on its members’ innovation performance. Within technopoles, “natural” geographical proximity has been shown to influence innovation performance (Amin & Cohendet, 2005). However, geographical proximity alone cannot account for knowledge flows, learning and innovation (for a review, see Ozman, 2009): other forms of proximity may be essential in order to foster interactive learning and innovation capabilities (Boschma, 2005; Rallet & Torre, 2005). Since the founding distinction between geographical proximity and organizational proximity, different types of proximity were added to refine the concept of organizational proximity (BoubaOlga & Grossetti, 2008). For Rallet and Torre (2005), “organized proximity” designates two types of logics: similarity and belonging. Similarity includes actors who are alike, who share the same reference space and knowledge, whereas belonging refers to actors who interact. Other authors, such as Suire et al. (2006), adopt a similar view by proposing the concepts of cognitive proximity and relational proximity. Cognitive proximity suggests that agents are cognitively close, i.e. share conventions, values and representations. Relational proximity refers to actors sharing a same interaction structure to make transactions or to exchange. As mentioned above, Pecqueur and Zimmermann (2004) differentiate the nature of interactions between actors depending on whether they are direct (organizational proximity) or indirect (institutional proximity). This distinction enables us to introduce the idea that actors can rely on coordination arrangements without having to rely on personal channels such as norms, standards, directories, human intermediaries. As suggested by Bouba-Olga and Grossetti (2008), these devices or mediation resources are no longer considered at the individual level (cognitive or relational proximity) but rather as collective coordination resources. Such a perspective seems

Institutional Innovation Practices in Technopoles

particularly relevant when establishing the role that governance may play when it has to face a lack of cognitive and relational proximities. More precisely, we propose that cluster local governance may contribute to foster organizational proximity in linear technopoles. Governance may enhance cognitive proximity when it is low due to high inter-firm heterogeneity (in terms of size, activity, markets, status, etc.) and/or create incentives for relational proximity. Cognitive and relational proximities become possible without physical proximity (Amin & Cohendet, 2005) and “the social architecture of learning in firms cannot be reduced to territorial ties” (ibid: 469) as knowledge is not linked to particular geographical sites. The extent to which organizational proximity can be fostered remains an open question. We contribute to fill this void in the literature by analyzing whether governance structures might help to develop innovative networks.

Technopoles: “Cathedrals in the Desert” or Networks for Innovation? The concept of technopole refers to various forms of industrial organization. In the United States, the Silicon Valley is often cited as a typical example of a technopole, viewed as a new techno-industrial complex of high-tech firms in which government and universities play a crucial role for its development (Castells & Hall, 1994). In Great Britain, “science parks” have helped to “reinforce the power of universities in the face of an important disengagement of the State” (Longhi & Quéré, 1991). An economic logic of innovation diffusion and technology transfer to small local firms is predominant in German “Technologieparks”. In France, technopoles such as Sophia Antipolis and ZIRST Meylan have emerged as the result of public policies for economic development oriented towards high technology activities (Longhi & Quéré, 1993). These are organized around three main functions (Faberon, 1990): (1) company

enrolment and anchoring; (2) cross-fertilization and the development of local synergies between scientific, industrial and financial representatives; and (3) technology transfer, as the scientific component is inseparable from the concept of technopole (Doloreux, 2002). Although this model of technopolitan development has been very successful in developed countries, empirical studies show a strong heterogeneity in terms of their innovative performance. Despite significant investments in innovation services and infrastructure, French technopoles seem to be the locus of weak relationships between co-localized firms (Carluer, 2006) and of a lack of synergy between research and industry (Cooke, 2001; Rallet & Torre, 1998). French technopoles tend to correspond to the linear innovation policy (Cooke, 2001). They result from large-scale political investment in public infrastructure. Agglomeration is induced and no institutional effort is made to create links between co-localized actors. This lack of interaction is mainly due to the explicit motivation to provide hosting facilities for high-tech companies instead of facilitating links between scientific, academic and industrial potentials (Quéré, 1996; Doloreux 1999; Longhi & Quéré, 1991). French technopoles share a set of specific properties extensively identified in the literature on local development. Levesque et al. (1998) observed that technopoles are characterized by a high number of innovative firms from high-tech sectors, mainly SMEs. However, they are seldom involved in innovation networks, particularly with local private or public partners. In their longitudinal study of Sophia Antipolis, Longhi and Quéré (1993) showed that when inter-firm relationships existed, these remained essentially vertical in nature. Often isolated from their parent company or due to their small size, firms are not encouraged to collaborate with research laboratories and/or neighbouring partners. The main reason is the fear of losing specific expertise. Levesque et al. (1998) confirmed the weakness of contractual relations

453

Institutional Innovation Practices in Technopoles

within linear technopoles: only the largest SMEs were successful in finding their place within a permanent network of business relations. The lack of trust within the technopole also hinders the establishment of informal relationships and of a local labor market, both key dimensions for territorial anchoring. De Bernardy (1999) showed that when these dimensions exist, they remain highly vulnerable to competitive pressure. Fierce competition between firms acts against the creation of informal relationships. Carluer (2006) explained the absence of genuine local anchoring of firms by the fact that geographical proximity does not lead to relational embeddedness. Indeed, companies have access to generic, readily available and transferable resources without having to engage in non-market relationships. Altogether, these findings echo recent studies that question the premise that geographical proximity would be sufficient for the creation and dissemination of innovation at a collective level. Conversely, “interactive” technopoles (Cooke, 2001) reject the linear view of innovation and focus on the dynamic learning process taking place in a local “milieu” (Camagni, 1991; Maskell & Malmberg, 1999; Antonelli, 2000) where institutions are expected to play a central role (Amin, 1999; Cooke & Morgan, 1998). The success of this second type of technopole no longer relies on the existence of infrastructures, generic resources and skilled workforce. It depends on strong territorial anchoring and on active networking between firms, as well as on closer ties between research and industry. For Longhi and Quéré (1991), the “innovative network” depends on both the complementarity of activities/skills available on site and on the dynamics of the local labor market. These two central dimensions, which form the basis for local learning, require a strong synergy between firms and local institutions (Boekholt & Van der Weele, 1998, Levesque et al., 1998). Although geographic proximity plays a significant role, approaching innovation from an interactive perspective is insufficient to explain

454

innovation; organizational proximity must also be considered. Doloreux and Parto (2005) showed the importance of “social relations” that support the activities of production, consumption and trade: “[they] are made up of symbolic elements, social activities, and material resources that define the structure of the interaction among humans based on rules, norms, and values” (ibid: 146). This dimension is inherent to the concept of organizational proximity between actors that are geographically close (Gilly et al., 2004). It guarantees the viability and stability of the technopole in the long run (Dupuy & Gilly, 1999). When geographical proximity is observed without any form of organizational proximity, the economic actors have little chance of maintaining direct relations (Torre, 2006). This is especially true when the technopole brings together a high proportion of small businesses (Leloup et al. 2005;Ehlinger et al. 2007;Bocquet & Mothe, 2009). Studying clusters with a strong concentration of SMEs, Bocquet and Mothe (2010) showed the difficulties that arise when trying to establish synergies between SMEs due to their highly individualistic behaviour and difficulties to perceive innovation opportunities. Although cooperation and the use of external sources are key dimensions to their innovation activity (De Jong & Marsili, 2006; Freel & Harrison, 2006; Huet & Lazaric, 2008), not all SMEs have the ability to absorb external resources and/or are reluctant to establish such relationships. As cross-fertilization is one of the main functions of the technopole, it is clearly challenging the governance to create mediation resources (institutional proximity) when dealing with weak organizational proximity (both, cognitive and relational proximities). “Anchoring appears when the territorial organization (geographic proximity) is capable of generating organizational and institutional proximity effects based on the interaction and cooperation between units operating in the same geographical proximity” (Zimmerman, 2008: 115).

Institutional Innovation Practices in Technopoles

Institutional Practices for Innovation in Technopoles The emergence of a technopole as an innovative network can stem from the establishment of a local governance structure aimed at developing a cognitive proximity so as to create a sense of common belonging that will bind actors together, as well as a relational proximity designed to favour the emergence of innovative collaborations. Gilly and Wallet (2001) identified four modes of territorial governance: (1) private governance structured around a broker; (2) collective private governance, where the broker is a formal institution that brings together private operators; (3) public governance, where the public actors that manage the network and the private actors who benefit from these resources are distinct; and (4) joint governance where dominant players are from both public and private sectors. Following this approach, the governance of technopoles should play a significant role in stimulating innovation through the quality of the local anchoring, and via networks and cooperation between research and industry.

Territorial Anchoring Beyond the services and infrastructure developed to host firms (generic resources), the governance of the technopole should adopt a strategic approach (Simmie et al., 2004) to generate diversity and complementarity of activities. The combination of a common strategy, of the actors’ involvement in social, personal or professional networks and of geographic proximity makes it possible to generate specific resources (Grossetti, 2000). The governance should therefore develop incentive schemes designed to encourage opportunities for formal or informal meetings between actors. This can be achieved through thematic meetings or seminars and the exchange of information between members. The governance must also

ensure consistency and continuity of the local labor market in order to enable firms to exchange expertise and to benefit from localized learning spillovers (Longhi & Quéré, 1991).

Networking The governance plays a major role in stakeholder networking in order to develop synergies. This networking dimension has a formal nature here, as opposed to informal relationships that characterize territorial anchoring. Technological incubators also contribute to the promotion of innovation (Doloreux, 1999). Hosting knowledge-intensive business services (KIBS) has a strategic impact in this cross-fertilization to the extent that KIBS play a “key interface role between a bunch of generic knowledge and a variety of unique and specific applications” (Antonelli & Quéré, 2002: 1060). The governance can also sustain the development of a common “knowledge architecture” among members (Tallman et al., 2004), seen as a translator or a knowledge hub between different communities (Bocquet & Mothe, 2010). Lazaric et al. (2008) highlighted the need for specific coordination mechanisms (as a knowledge platform) to create places where to exchange and confront ideas.

Cooperation between Research and Industry Access to new skills and resources is a key motive in research partnerships (Mowery et al., 1998). University-industry relations are considered to be a determinant of innovation performance, particularly in high-technology sectors (Arvanitis et al., 2008). Although personal contacts and social ties between actors are necessary for innovation, they are not sufficient to gain access to knowledge often embodied in joint scientific and industrial research teams (Breschi & Lissoni, 2001; Balconi & Laboranti, 2006). The technopole governance can play an active role in supporting innovation

455

Institutional Innovation Practices in Technopoles

by facilitating spin-offs and patents or license registrations, which are essential channels of technology transfer (Arvanitis et al., 2008). Overall, the ambition of governance should focus on building an “innovative network” through appropriate mediation resources (material and cognitive) in order to create and sustain the actors’ interest and motivation to collaborate. The following empirical section is based on a recent study of the French technopole Savoie Technolac. It presents a first quantitative analysis of the effects of the governance institutional practices on firms’ innovation performance.

CASE STUDY OF SAVOIE TECHNOLAC The study of Savoie Technolac, conducted in June 2009, is based on a survey of 125 companies located in the technopole. Internet questionnaires were sent to all CEOs. After two follow-up mails, we received 88 valid questionnaires, thus leading to a final response rate of 70.5%. The final sample is representative of the business population in terms of sector affiliation and size.

Background and History Savoie Technolac was created in 1987 after the closure of the military air base at the Bourget-duLac and is the result of a territorial restructuring. Following the Silicon Valley model, the technopole emerged from a joint local political and economic motivation to develop a new territory combining university, research and high technology services. Savoie Technolac is currently made up of around 180 companies, 19 research laboratories and 69 scientific and technical higher education programmes covering four main activity sectors: (1) Solar energy and environmentally sound technologies; (2) Information, electronic and communication technologies; (3) Design, development and prototyping of industrial equipment;

456

and (4) Plastics and composite materials. Savoie Technolac has centered its development around environmental concerns by offering a pleasant natural environment. In 2005, this environmental dimension was explicitly reinforced with the establishment of the National Institute for Solar Energy (INES). Savoie Technolac also hosts firms that belong to the Tenerrdis cluster focused on renewable energies. The resulting economic conversion has turned the “Solar Valley” into a reference for solar industry in France.

Descriptive Data (see Appendix 1.1) A large proportion of mostly independent very small firms with less than 10 employees characterizes Savoie Technolac. Most firms (87.5%) operate in service activities, especially in knowledge-intensive business services (KIBS): consulting, engineering or R & D. Most firms are engaged in technological innovation: 55.7% in product innovation, 52.3% in service innovation and 39.8% in process innovation. Their main markets in 2008 were local or regional (69.4%). 47.8% export their goods or services. 28.8% are engaged in other innovative clusters at the regional or national level. Descriptive data show that 45.5% of firms were engaged in innovation projects with co-located partners - but only 15.9% with the local university and less than 5% with nearby customers and suppliers.

Savoie Technolac: A “Linear” or “Interactive” Model of Technopole? Savoie Technolac has a public governance mode made up of a joint syndicate of local authorities including the department of Savoie, Chambery Métropole and the Community of Municipalities of the Bourget Lake. This public governance expresses the motivation for local public institutions to remain independent from regional or national public policies. From its creation, the local institutions decided to set up a permanent team that

Institutional Innovation Practices in Technopoles

would be in charge of managing and developing the technopole. The executive team of Savoie Technolac has twelve members. Alongside a CEO in charge of the overall strategy and an administrative and financial director, the team fulfils the three above-mentioned governance missions:

Territorial Anchoring Building on three major resources – large available space in a highly attractive environment, proximity of university and academic facilities, and funding sources - Savoie Technolac succeeded in attracting SMEs as well as scientific departments of the University of Savoie. It assists firms seeking to relocate in the technopole and helps innovative start-ups through an incubator. Among the 70% of firms that were created on the site, 47% were incubated, attesting to the dynamism of the incubator, also to the spin-off role played by the technopole. A vast majority of firms (68.2%) rely on the local labor market. In order to anchor firms on the territory, Savoie Technolac offers a wide range of generic services and infrastructure, which are widely used (by 90.9% of firms). 40% of firms use more specific business services such as events (theme breakfasts, conferences, open days...) to disseminate information, facilitate meetings between firms and create a dynamic territorial anchoring.

Networking Savoie Technolac has taken a number of strategic initiatives to build innovation networks. It is a member of an innovation network dedicated to French technopoles and incubators. It is also involved in two “competitiveness clusters” in the Rhône-Alpes region: Tenerrdis, dedicated to renewable energies, and Plastipolis, specialized in plastics and composites. It has also developed links with other science parks at the international level - such as the Metropolitan Technopark (Quebec) and Techno Park (Montreal). However, as shown

above in the descriptive statistics on innovation collaborations, innovation networking remains to be developed. The low involvement of firms within on-site innovation networks, either horizontal or vertical, is typical of a ‘linear’ type of technopole. However, the firms do acknowledge that the governance structure of Savoie Technolac plays a significant role in developing relationships with on-site and/or off-site partners for innovation.

Cooperation between Research and Industry Developing industry-research cooperation through enhanced networking incentives in order to develop the technology transfer opportunities is a priority for the governance of Savoie Technolac. It endeavors to reinforce the circulation of information through specific newsletters or thematic meetings that will encourage researchers to “come out of their laboratories”. The creation of spinoffs is also sustained.

METHOD AND RESULTS PLS Modelling We used the PLS (Partial Least Square) structural equation modeling to process the data1. PLS is relevant when it comes to evaluating predictive relationships among variables and for analyses aimed at building theory (Wold, 1985). PLS is well suited to the exploratory nature of our approach, bearing in mind the limited research on governance and determinants of innovation in technopoles. Analysis using PLS follows two steps. The first aims at validating the relevance of the latent construct from theoretical literature (see table 1), the second seeks to evaluate the explanatory and predictive dimensions of the structural model. To highlight the impact of the technopole governance on innovation, we built two successive models corresponding to the interactive model of

457

Institutional Innovation Practices in Technopoles

the technopoles (Cooke, 2001). The first (PLS1) shows the direct effects of governance on business innovation. The second (PLS2) highlights the effects of governance on collaborative projects for innovation within the technopole.

Variables Dependent Variables Following the Oslo Manual and the approach adopted in the CIS surveys, we focused on the subjective approach to innovation (Archibugi & Pianta, 1996; Mairesse & Mohnen, 2010). Data were collected at company level. Respondents were asked to declare whether they had introduced an innovation in the three years preceding the survey (2006-2008), and, if so, what type of innovation. In the first model (PLS1), the following three binary variables corresponded to our three dependent variables: product innovation, process

innovation and service innovation. In the second model (PLS2), a fourth binary dependent variable was introduced to clarify whether companies had used innovation projects in collaboration with other partners. In this second model (PLS2), this variable was interposed between governance variables and the dependent variables of the first model (PLS1).

Independent Variables Two latent variables were constructed to illustrate the institutional practices serving innovation in the technopole. The first latent variable illustrated the collective services used by firms on site. A second variable indicated whether the firms used local labor. Together, these two variables captured the quality of local anchoring. A third variable measured the networking activity within the technopole. This variable consists of three items describing collaborations with customers and

Table 1. Composition of latent variables Independent Variables

Items

Measures

Networking activity performed by the technopole (NetworkingST) (De Jong et Marsili, 2006;Favoreu et al.2008)

Did the Savoie Technolac team put you in relation with another organization, located on or off-site, that became: €€€€€1. An innovation partner (RelaPART) €€€€€2. A customer (RelaCLST) €€€€€3. A supplier (RelaFOST)

Binary Binary Binary

Quality of Territorial Anchoring (ServiceEnt) (Cooke et al., 1997; Grossetti, 2000;Carluer, 2006)

Does your firm use the business services offered by Savoie Technolac? €€€€€1. Specific business services (themed business breakfasts, conferences, symposium, E-entrepreneur Club, open-day visits…) (Servent) €€€€€2. Services dedicated to business creation (incubators, personalized counselling, providing help to request funds…) (Servcrea)

Binary Binary

Innovation Expenses (ExpenseInno) (Freel, 2006;De Jong & Marsili, 2006)

€€€€€1. What percentage of your firm’s turnover was dedicated to R&D in 2008? (DepRD) €€€€€2. How much working time (in %) did your firm dedicate to innovation in 2008? (LaborIn)

Continuous (Value Ln) Binary

Clusters’ affiliation (Cluster) CIS 2006

Is your firm member of another cluster: €€€€€1. In the Rhône-Alpes region ?(CluRegR) €€€€€2. Outside the region? (ClusHreg)

Binary Binary

Innovation sources within branch of activity (Source) (Tether, 2003;De Jong et Marsili, 2006;CIS 2006)

Over the last three years, did your firm use the following sources to innovate? €€€€€1. Collaboration with customers (SourcCLSrv) €€€€€2. Collaboration with suppliers (SourcForSrv)

Binary Binary

Control Variables

458

Institutional Innovation Practices in Technopoles

suppliers. A fourth and final explanatory variable assessed the level of technology transfer between universities and companies within the technopole.

Control Variables Among the five control variables, three were latent. The first (innovation expenditure) is composed of two items: the percentage of turnover devoted to R&D and the working time dedicated to innovation. This latent construct sought to capture the internal effort made by the company to innovate in a broader manner than the traditional measures of input exclusively focused on R & D expenses and number of patents. This construct was particularly suited to capture the innovative efforts of smaller companies, especially services, which are largely dominant within Savoie Technolac. The second latent variable stated whether the company also belonged to another regional, national or international cluster. The third latent variable measured the level of the company’s vertical cooperation for innovation by combining upstream (supplier) and downstream (customer) collaboration. The two other control variables were the independent status of the company and its size (less than 10 employees, 10-20 employees, more than 20 employees).

Validation of the Latent Constructs Before retaining latent constructs in structural equation modeling, it is necessary to examine the convergent and divergent validity of the confirmatory factor analysis (Gefen & Straub, 2005). Convergent validity is demonstrated when items measuring a latent variable reach a significant value on the axis of this variable (t-value). It also requires that all latent constructs reach a minimum average variance extracted (AVE) score of 0.5 (Fornell, 1987). This criterion can be consolidated by checking the values of composite reliability for each construct (see Table 2). To investigate the discriminating validity of latent constructs, we used the matrix of factor loadings of the full model. All items exceed the value of 0.7 and each item obtained a higher score on its corresponding factorial axis – comparatively to values obtained in other areas (see Appendix 2.1 and 2.2). Discriminating validity is demonstrated when the square root of the AVE for each construct is greater than any correlation between that construct and each of the other constructs (see Appendix 3.1 and 3.2).

Results Results for both models, PLS1 and PLS2, are presented in Table 3. They indicate that, beyond the traditional determinants for firm innovation performance, governance also plays a significant role. Given the relatively high R-square values

Table 2. Indicators of convergent validity Model 1 (PLS1) AVE

Model 2 (PLS2)

Composite Reliability

AVE

Composite Reliability

Cluster

0,688

0,813

0,699

0,823

ExpenseInno

0,910

0,953

0,910

0,953

NetworkingST

0,630

0,835

0,638

0,840

Source

0,661

0,796

0,662

0,797

ServiceEnt

0,683

0,812

0,683

0,812

459

Institutional Innovation Practices in Technopoles

in each model, we can first conclude that the variables capturing the institutional practices of innovation implemented by the governance have a significant impact on business innovation performance in PLS1 and / or on innovative collaborative projects in PLS2.

Model PLS1: The Effect of Governance on Innovation Performance According to the three institutional practices previously identified, three key results show the impact of the technopole’s governance on the innovation performance of co-located firms: The first result concerns the quality of the local anchoring, which does not have a full impact on business innovation. The results show that although the local labor market has a significant impact on product innovation (β=0169, t=2,027, p <0.05), this is not the case for the specific services offered by the governance, regardless of the type of innovation concerned. The second result shows the significant effect of technology transfer between universities and firms within the technopole on product innovation (β=0174, t= 2,071, p <0.05). The effect of this covariate (CollUniST) is positive and indicates that governance plays a role in supporting scientific collaboration. The third result concerns the networking practices implemented by the governance. No direct effect of these institutional practices has been measured on the different types of innovation. Moreover, we noted that the traditional determinants of innovation also had a significant influence on the innovation performance of firms within the technopole. This was particularly pronounced for product innovative firms. These were rather small (β=- 0348, t = 3.683, p <0.001) and belonged to a group (Indepr: β = - 0455, t= 4.819, p <0.001). Thus, the internal resources at their disposal for innovation (ExpenseInno: β=0,447, t = 5.282, p <0.001) positively affected

460

their firm’s innovation performance. In addition to these internal resources, these firms also collaborated upstream and downstream as part of their innovation process, probably through the group to which they belonged (Source: β= 0.226, t =2.246, p <0.05). However, given the risk of potential leakage of specific expertise, belonging to another cluster represents a barrier to product innovation (cluster: β=- 0.229 t = 2.536, p <0.01). Firms engaged in process or services innovation presented a distinct innovation profile. The results show that only internal expenses (ExpenseInno: β= 0.282, t= 2.581, p <0.01) represent a key determinant with respect to process innovation. By contrast, firms that innovated in services benefited only from external sources related to their affiliation with another cluster (cluster: β = 0.276, t = 3.538, p <0.01).

Model PLS2: The Role of Governance for Collaborative Innovation Projects The second structural model aimed to highlight the explanatory power of the cluster governance on the firms’ collaborative innovation projects. Unlike the previous model (PLS1), specific business services offered by the governance contributed positively to collaborative innovation projects (β =0.231, t = 2.204, p <0.05) whereas the local labor market had no influence. The results of this second model are particularly interesting for the institutional practices of networking. They confirm an impact of these practices on collaborative innovation projects (β=0.314, t=3.631, p <0.001). Finally, collaboration with the university remains significant (β=0.243, t=2.841, p<0.01), attesting to the persistent nature of technology transfers between universities and companies as part of innovative projects. Thus, we note that the institutional practices implemented by the governance have an impact on the innovation projects rather than on innovation itself. This result is not surprising since the projects are still

-0,046

0,154

€€€€NetworkingST

ServiceEnt

5,282*** 4,819*** 2,246* 3,683***

0,447

-0,455

0,226

-0,348

0,423

€€€€Indep

€€€€Source

€€€€Size

R²

Product Innovation

0,206

-0,074

0,098

0,038

0,282

-0,013

0,165

0,012

0,112

0,133

0,675

0,916

0,344

2,581**

0,103

1,407

0,104

1,114

1,337

0,230

-0,027

0,150

-0,048

0,079

0,188

0,127

0,176

0,152

-0,039

0,233

0,916

0,423

0,670

1,767*

1,035

1,291

1,440

0,407

t

InnoSRV

0,362

-0,307

0,234

-0,410

0,416

-0,134

3,613***

2,465**

4,358***

4,914***

1,409

t

InnoPDT

* p <.05 (One tailed test: 1.645, df = 499) ; ** p <.01; (2.326, df = 499) ; *** p <.001 (3.090, df = 499).

2,536**

-0,229

€€€€ExpenseInno

1,581

€€€€Cluster

Control Variables

2,027*

0,169

€€€€WorkST 0,354

2,071*

t

T

0,174

InnoPROC

InnoPDT

€€€€CollUniST

Independent Variables

Service Innovation

0,161

-0,059

0,132

0,097

0,298

-0,013

0,641

1,321

0,943

2,826**

0,865

t

InnoPROC

Process Innovation

0,148

-0,066

0,231

-0,048

0,079

0,276

0,689

2,284*

0,425

0,635

3,538***

t

InnoSRV

Service Innovation

Dependent Variables

Dependent Variables Process Innovation

PLS2

PLS1

Product Innovation

Table 3. Results of PLS Model

3,631*** 2,204*

0,231

0,264

0,187 0,314

2,841** 0,017

0,243

t

ProjetInnoCollabST

Innovative Collaborative Projects ST

Institutional Innovation Practices in Technopoles

461

Institutional Innovation Practices in Technopoles

ongoing. The traditional determinants of innovation represented by the control variables showed a close proximity with the results of PLS1. Rare differences remained, particularly in terms of sources of innovation for vertical firms engaged in innovation in the services sector (β=0.231, t = 2.284, p <0.01).

DISCUSSION AND CONCLUSION This first quantitative analysis of the role of governance in a French technopole not only confirms the fact that “traditional” variables effectively foster innovation performance for co-localized firms, but it also emphasizes the role played by the technopole governance. Of the three identified dimensions - technology transfer, local anchoring and networking - only technology transfer between research and industry had an impact on both product innovation and collaborative innovation projects. Territorial anchoring had a more ambiguous effect: recourse to local labor market had a positive effect on product innovation, whereas providing business services only promoted inter-firm collaboration for innovation. A similar result was found with the networking practices implemented by the governance: the latter affected collaboration for innovation but no direct effect was evidenced on innovation. Following Longhi and Quéré (1991), we confirmed the importance of territorial anchoring on product innovation through the existence of a local labor market. This suggests that the governance of Savoie Technolac has succeeded in creating mediation resources and incentive schemes for collaboration, which, in fine, enhance the firms’ innovation performance. By contrast, the other dimensions (territorial anchoring through business services, networking and technology transfer) had no direct effect on firm innovation. This can be explained by the fact that:

462

Specific business services (start-up support, themed breakfasts, conferences, I-entrepreneur club, seminars, etc.) are transverse enough to enable the different actors to meet, to get to know each other and to create a common language. These services appear to be a prerequisite for the creation of organizational proximity. However, proposing such services does not compensate for inter-firm heterogeneity. The focus on the solar industry should improve this aspect soon, leading to the emergence of a dominant activity and a critical threshold (Levesque et al., 1998), essential for local anchoring and its effectiveness in terms of innovation. Networking practices for innovation are effective with partners within Savoie Technolac. However, the technopole is “linear” in its form, as these relationships are limited to local partners on one hand, and have no direct effect on product innovation on the other hand. This result can also be explained by the specific nature of our sample. Indeed, firms engaged in product innovation are mainly subsidiaries. They largely depend on resources held by their parent company in order to innovate. Their business opportunities are governed and often enhanced by the group to which they belong, thus limiting the use of calling upon co-located actors. After 20 years of existence, Savoie Technolac relies on a dynamic local labor market and has partly succeeded in implementing networking incentives. Although industry-research collaboration boosts firms’ product innovation thanks to the presence of university laboratories on site, inter-firm networking is still not very satisfactory due to its restricted perimeter and its low direct effect on the firms’ innovation performance. This fact is not singular as most studies show that a certain lapse of time is required in order to establish a network of relationships between industry, research and education (Levesque et al., 1998). Time is indeed a key variable for the construction

Institutional Innovation Practices in Technopoles

of a common history (Torre, 2006). Examples of successful technopoles suggest a maturation period of 15 to 20 years and a long initial starting process that enables the development of a sufficiently stable context of inter-organizational relationships (Levesque et al., 1998). In parallel to the development observed with Sophia Antipolis (Lazaric et al., 2008), which evolved from a satellite platform toward a hightechnology cluster thanks to the emergence of specific local skills rooted in global innovation networks, the question remains as to whether Savoie Technolac will be able to evolve gradually from a “linear” form to an “interactive” technopole (Cooke, 2001). In order to accelerate the current evolution of the technopole towards an interactive model, the public institutions in charge of the governance of Savoie Technolac need to reinforce their commitment toward the solar industry and to adopt an implementation strategy designed to increase the impact of synergies and territorial anchoring. However, this should not be assimilated to a “quantitative” approach, i.e. an increase in the number of member companies, which could play against the development of cognitive proximity. In the Laval (Canada) technopole, firms were selected only on the basis of the nature of their activities, which did not leave room for complementaries and synergies nor for the identification to a collective project (Doloreux, 1999). As noted by Nooteboom (2009), the “right degree of cognitive proximity” in accordance with geographic proximity should thus be neither too high nor too low. As the primary objective for Savoie Technolac is to reach a critical threshold, firms will need to be recruited with careful attention. Generic, transversal activities and services for businesses could be developed to the detriment of more specific forms of support for innovative enterprises (Longhi & Quéré, 1993). The strategic approach adopted by the technopole governance with the development of excellence hubs in the solar energy industry (with the Tenerrdis cluster and the INES) therefore seems justified.

This research is not without limitations, in particular due to the specificities of our sample. Although representative of Savoie Technolac firms, it mainly focuses on SMEs in the service industry. The measures used to assess the role and action of the governance could also be enriched. Future research could be undertaken in order to enrich empirical knowledge pertaining to organizational proximity and to the role of institutional practices aimed at boosting firms’ innovation performance. It could be of particular interest to compare the actions taken by the governances of several technopoles or, more broadly, of clusters such as the recent French competitiveness clusters. Such a comparative approach could provide a more nuanced characterization of the role played by governances by controlling the distinct structural dimensions of the clusters involved.

REFERENCES Amin, A. (1999). The Emilian model: Institutional challenges. European Planning Studies, 7(4), 389–405. Amin, A., & Cohendet, P. (2005). Geographics of knowledge formation in firms. Industry and Innovation, 12(4), 465–486. doi:10.1080/13662710500381658 Angel, D. P. (2002). Inter-firm collaboration and technology development partnerships within U.S. manufacturing industries. Regional Studies, 36(4), 333–344. doi:10.1080/00343400220131115 Antonelli, C. (2000). Collective knowledge communication and innovation: The evidence of technological districts. Regional Studies, 34(6), 535–547. doi:10.1080/00343400050085657 Antonelli, C., & Quéré, M. (2002). The governance of interactive learning within innovation systems. Urban Studies (Edinburgh, Scotland), 39(5/6), 1051–1063. doi:10.1080/00420980220128453

463

Institutional Innovation Practices in Technopoles

Archibughi, D., & Pianta, M. (1996). Measuring technological change through patents and innovation surveys. Technovation, 16(9), 451–468. doi:10.1016/0166-4972(96)00031-4 Asheim, B. (2007). Differentiated knowledge bases and varieties of regional innovation systems, Innovation. European Journal of Soil Science, 20(3), 223–241. Balconi, M., & Laboranti, A. (2006). Universityindustry interactions in applied research: The case of microelectronics. Research Policy, 35(10), 1616–1630. doi:10.1016/j.respol.2006.09.018 Bocquet, R., & Mothe, C. (2009). Gouvernance et performance des pôles de PME. Revue Française de Gestion, 35(190), 101–122. doi:10.3166/ rfg.190.101-122 Bocquet, R., & Mothe, C. (2010). Le rôle des institutions publiques dans la gouvernance des pôles de compétitivité de PME. Revue Canadienne de Sciences Régionales, 32(3). Boekholt, P., & Van der Weele, E. (1998). Southeast Brabant: A regional system in transition. In Braczyk, H.-J., Cooke, P., & Heidenreich, M. (Eds.), Regional innovation systems: The role of governances in a globalized world (pp. 48–71). London, UK: Routledge. Boschma, R. (2005). Proximity and innovation: A critical assessment. Regional Studies, 39(1), 61–74. doi:10.1080/0034340052000320887 Bouba-Olga, O., & Grossetti, M. (2008). Socioéconomie de proximité. Revue d’Economie Regionale et Urbaine, 3, 311–328. doi:10.3917/ reru.083.0311 Breschi, S., & Lissoni, F. (2001). Knowledge spillovers and local innovation systems: A critical survey. Industrial and Corporate Change, 10(4), 975–1005. doi:10.1093/icc/10.4.975

464

Brezis, E. S., Krugman, P., & Tsiddon, D. (1993). Leapfrogging in international competition: A theory of cycles in national technological leadership. The American Economic Review, 83(5), 1211–1219. Camagni, R. (1991). Innovation networks: Spatial perspective. London, UK: Belhaven Press. Carluer, F. (2006). Réseaux d’entreprises et dynamiques territoriales: Une analyse stratégique, Géographie, Economie. Société, 8(2), 193–214. Carrincazeaux, C., Grossetti, M., & Talbot, D. (2008). Clusters, proximities and networks. European Planning Studies, 16(5), 613–616. doi:10.1080/09654310802049091 Castells, M., & Hall, P. (1994). Technopoles of the world: The making of 21st century industrial complexes. Abingdon. Oxon: Routledge. CIS. (2006). Enquête communautaire sur l’innovation. In INSEE (Ed.). Paris, France. Retrieved from http://www.insee.fr/fr/methodes/ default.asp?page=definitions/ enquete-ue-innovation.htm. Colletis, G., & Gilly, J.-P. (1999). Construction territoriale et dynamiques économiques. In Gilly, J.-P., & Menville, J. (Eds.), Entreprises et Territoire (Vol. 48, pp. 26–46). Toulouse, France: PUM. Cooke, P. (2001). From technopoles to regional innovation systems: The evolution of localised technology development policy. The Canadian Journal of Regional Science, 24(1), 21–40. Cooke, P., Gomez Uranga, M., & Etxebarria, G. (1997). Regional innovation systems: Institutional and organisational dimensions. Research Policy, 26(4-5), 475–491. doi:10.1016/S00487333(97)00025-5 Cooke, P., & Morgan, K. (1998). The associational economy: Firms, regions and innovation. Oxford, UK: University Press.

Institutional Innovation Practices in Technopoles

De Bernardy, M. (1999). Reactive and proactive local territory: Co-operation and community in Grenoble. Regional Studies, 33(4), 343–352. doi:10.1080/713693561 De Jong, J. P. J., & Marsili, O. (2006). The fruit flies of innovations: A taxonomy of innovative small firms. Research Policy, 35(2), 213–229. doi:10.1016/j.respol.2005.09.007 Doloreux, D. (1999). Technopoles et trajectoires stratégiques: Le cas de la ville de Laval (Québec). Cahiers de Geographie de Quebec, 43(119), 211–235. Doloreux, D. (2002). What we should know about regional systems of innovation. Technology in Society, 24(3), 243–263. doi:10.1016/S0160791X(02)00007-6 Doloreux, D., & Mattson, H. (2008). To what extent do sectors “socialize” innovation differently? Mapping cooperative linkages in knowledge intensive industries in the Ottawa region. Industry and Innovation, 15(4), 351–370. doi:10.1080/13662710802239463 Doloreux, D., & Parto, S. (2005). Regional innovation systems: Current discourse and unresolved issues. Technology in Society, 27(2), 133–153. doi:10.1016/j.techsoc.2005.01.002 Ehlinger, S., Perret, V., & Chabaud, D. (2007). Quelle gouvernance pour les réseaux territorialisés d’organisation? Revue Française de Gestion, 170, 155–171. doi:10.3166/rfg.170.155-171 Faberon, J.-Y. (1990). Technopoles et développement. Revue Francaise de Science Politique, 40(1), 46–63. doi:10.3406/rfsp.1990.394458 Favoreu, C., Lechner, C., & Leyronas, C. (2008). Légitimité des politiques publiques en faveur des clusters, Revue française de gestion, 183(3), 157-178.

Fornell, C. (1987). A second generation of multivariate analysis: Classification of methods and implications for marketing research. In Houston, M. (Ed.), Review of marketing. Chicago, IL: American Marketing Association. Freel, M. (2006). Patterns of technological innovation in knowledge-intensive business services. Industry and Innovation, 13(3), 335–358. doi:10.1080/13662710600859157 Freel, M. S., & Harrison, R. T. (2006). Innovation and cooperation in the small firm sector: Evidence from Northern Britain. Regional Studies, 40(4), 289–305. doi:10.1080/00343400600725095 Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Communications of AIS, 16, 91–109. Gilly, J.-P., Leroux, I., & Wallet, F. (2004). Gouvernance et proximité. In Pecqueur, B., & Zimmermann, J. (Eds.), Economies de proximité (pp. 185–206). Paris, France: Editions Lavoisier. Gilly, J.-P., & Wallet, F. (2001). Forms of proximity, local governance and the dynamics of local economic spaces: The case of industrial conversion processes. International Journal of Urban and Regional Research, 25(3), 553–570. doi:10.1111/1468-2427.00329 Grossetti, M. (2004). Concentration d’entreprises et innovation: Esquisse d’une typologie des systèmes productifs locaux, Géographie, Economie. Société, 6(2), 163–177. Huet, F., & Lazaric, N. (2008). Capacités d’absorption et d’interaction: Une étude de la coopération dans les PME françaises. Revue d’Economie Industrielle, 121, 65–84.

465

Institutional Innovation Practices in Technopoles

Lazaric, N., Longhi, C., & Thomas, C. (2008). Gatekeepers of knowledge versus platforms of knowledge: From potential to realized absorptive capacity. Regional Studies, 42(6), 837–852. doi:10.1080/00343400701827386

Miles, I., Kastrinos, N., Flanagan, K., Bilderbeek, R., Den Hertog, P., & Huntink, W. (1995). Knowledge-Intensive Business Services: Users, Carriers and Sources of Innovation. Manchester, UK: University of Manchester.

Leloup, F., Moyart, L., & Pecqueur, B. (2005). La gouvernance territoriale comme nouveau mode de coordination territoriale? Géographie, Economie. Société, 7(4), 321–332.

Moulaert, F., & Sekia, F. (2003). Territorial innovation models: A critical survey. Regional Studies, 37(3), 289–302. doi:10.1080/0034340032000065442

Lévesque, B., Klein, J.-L., & Fontan, J.-M. (1998). Les systèmes industriels localisés: Etat de la recherche. Montréal, Canada: UQAM.

Mowery, D. C., Oxley, J. E., & Silverman, B. S. (1996). Strategic alliances and interfirm knowledge transfer. Strategic Management Journal, 17, 77–91.

Longhi, C., & Quéré, M. (1991). La technopole comme système industriel localisé: Eléments d’analyse et enseignements empiriques. Economies et Sociétés, 32, 21–41. Longhi, C., & Quéré, M. (1993). Innovative networks and the technopolis phenomenon: The case of Sophia-Antipolis. Environment and Planning. C, Government & Policy, 11, 317–330. doi:10.1068/c110317 Mairesse, J., & Mohnen, P. (2010). Using innovations survey for econometric analysis (NBER Working Paper n°15857). Cambridge, MA: National Bureau of Economic Research. Markusen, A. (1996). Sticky places in slippery space: A typology of industrial districts. Economic Geography, 72(3), 293–313. doi:10.2307/144402 Maskell, P., & Malmberg, A. (1999). Localized learning and industrial competitiveness. Cambridge Journal of Economics, 23(2), 167–185. doi:10.1093/cje/23.2.167 Mendez, A., & Bardet, M. (2009). Quelle gouvernance pour les pôles de compétitivité constitués de PME? Revue française de gestion, 35(190), 123-142.

466

Nooteboom, B. (2009). A cognitive theory of the firm: Learning, governance and dynamic capabilities (p. 280). Cheltenham, UK: Edward Elgar. Ozman, M. (2009). Inter-firm networks and innovation: A survey of literature. Economics of Innovation and New Technology, 18(1), 39–67. doi:10.1080/10438590701660095 Pecqueur, B. (2008). Pôles de compétitivité et spécificité de la ressource technologique: Une illustration grenobloise. Géographie, Economie. Société, 10(3), 311–326. Pecqueur, B., & Zimmerman, J. B. (2004). Economies de Proximités. Paris, France: Hermès. Rallet, A., & Torre, A. (2007). Faut-il être proches pour innover ensemble? In A. Rallet & A. Torre (Eds.), Quelles proximités pour innover? Paris, France: L’Harmattan. Simmie, J., Siino, C., Zuliani, J.-M., & Jalabert, G. (2004). Local innovation system governance and performance: A comparative analysis of Oxfordshire, Stuttgart and Toulouse, International Journal of Technology Management, 28(3/4/5/6), 534-559.

Institutional Innovation Practices in Technopoles

Suire, R., Vicente, J., & Dala Pria, Y. (2006). Why some clusters succeed whereas others decline? Modelling the ambivalent stability properties of clusters. Economics Working Paper Archive (University of Rennes 1 and University of Caen), Center for Research in Economics and Management (CREM), France. Tallman, S., Jenkins, M., Henry, N., & Pinch, S. (2004). Knowledge, clusters and competitive advantage. Academy of Management Review, 29(2), 258–271. Tether, B. S. (2003). The sources and aims of innovation in services: Variety between and within sectors. Economics of Innovation and New Technology, 12(6), 481–505. doi:10.1080/1043859022000029221 Torre, A. (2006). Clusters et systèmes locaux d’innovation: Retour critique sur les hypothèses naturalistes de transmission des connaissances à l’aide des catégories de l’économie de la proximité. Région et Développement, 24, 15–43. Torre, A., & Gilly, J.-P. (2000). On the analytical dimension of proximity dynamics. Regional Studies, 34(2), 169–180. doi:10.1080/00343400050006087 Torre, A., & Rallet, A. (2005). Proximity and localization. Regional Studies, 39(1), 47–59. doi:10.1080/0034340052000320842 Wold, H. (1985). Partial least squares. In Kots, S., & Johnson, N. L. (Eds.), Encyclopedia of statistical sciences (pp. 581–591). New York, NY: John Wiley.

Zimmermann, J.-B. (2008). Le territoire dans l’analyse économique - Proximité géographique et proximité organisée. Revue Française de Gestion, 184(4), 105–118. doi:10.3166/rfg.184.105-118

KEY TERMS AND DEFINITIONS Governance: Governance is defined here as the intended, collective actions of cluster players in view of upgrading a cluster. Innovation: Here intended as technological innovation, it refers to the process that leads to the introduction of an enhanced or new product or process. Institutional Practices: The term is here intended to mean the practical actions set up by the institutional governance in order to enhance the quality of the local anchoring, networking between cluster members, and cooperation between research and industry. Technopole: A technopole is a specific type of cluster implemented by local institutions whose economic development strategies are based on maximizing their academic and research potential, hoping that it will lead to new initiative industrialization of high-technology, created or attracted on the site. Territorial Anchoring: All the resources provided to technopole members (such as an attractive environment, the proximity of university and academic facilities, funding sources, a help for start-ups, for firms who want to relocate on the technopole, etc.) and the actions set up to attracting new organizations, firms or university scientific departments and research labs.

467

Institutional Innovation Practices in Technopoles

APPENDIX 1.1 Descriptive Statistics (n=88) Table 4. Economic Characteristics of firms implanted within Savoie Technolac Economic Characteristics of firms implanted within Savoie Technolac Variables

n (%)

Definition

0

1

KIBS

=1 if the firm belongs to the sector of knowledge intensive business services (0 if not)

35 (39,8)

53 (60,2)

INCUB

=1 if the firm was incubated in the technopole (0 if not)

46 (52,3)

42 (47,7)

INDEP

=1 if the firm belongs to a group (0 if not)

60 (68,2)

28 (31,8)

1

2

71 (80,7)

17 (19,3)

1

2

3

NAF

=1 if the firm belongs to the service sector ; =2 if the firm belongs to the manufacturing sector

SIZE

=1 if less than 10 employees ; = 2 if 10 to 20 employees ; =3 if more than 20 employees.

58 (65,9)

15 (17)

15 (17)

COMPET

During the last three years (2006-2008), how would you describe the competitive environment of your company? (=1 if weak to medium competitive intensity ; =2 if intense competition ; =3 if very intense competition

39 (44,3)

28 (31,3)

21 (23,9)

How much of your turnover (in %) did your export sales represent in 2008? (1= if export % < 2% of total turnover; =2 if export % between 2 and 10%; =3 if export % > 10%)

54 (61,4)

6 (6,8)

28 (31,8)

MARKET

On which geographic market did your firm sell its goods or services between 2006 and 2008? (1=Regional; 2=France; 3=International)*

61 (69,4)

40 (45,5)

42 (47,8)

AGE

Since how many years does your company exist? (1= if firm age < 5 years ; =2 if age between 5 and 10 years ; =3 if firm older than 10 years)

21 (23,9)

24 (27,3)

43 (48,8)

ANCIEN

Since how many years is your company established in Savoie Technolac? (1= if establishment < 2 years; =2 if establishment between 2 to 10 years ; =3 if more than 10 years)

14 (15,9)

45 (51,1)

29 (33)

EXPORT

* Note that the total percentage is superior to 100% as multiple responses were permitted

468

Institutional Innovation Practices in Technopoles

Table 5. Innovation Profile of firms located in SAvoie Technolac Innovation Profile of firms located in SAvoie Technolac

0

1

InnoPDT

=1 if the firm introduced goods innovation during the last 3 years (0 if no product innovation)

39 (44,3)

49 (55,7)

InnoSRV

=1 if the firm introduced service innovation during the last 3 years (0 if no service innovation)

42 (47,7)

46 (52,3)

InnoPROC

=1 if the firm introduced new manufacturing process during the last 3 years (0 if no process innovation)

53 (60,2)

35 (39,8)

SourcCLSrv

=1 if the firm did collaborate with co-located customers in order to innovate (0 if not)

85 (96,6)

3 (3,4)

SourcForSrv

=1 if the firm did collaborate with co-located suppliers in order to innovate (0 if not)

84 (95,5)

4 (4,5)

SourcConSrv

=1 if the firm did collaborate with co-located competitors in order to innovate (0 if not)

87 (98,9)

1 (1,1)

CollUniST

=1 if the firm did collaborate with co-located university or other higher education institutes to innovate (0 if not)

74 (84,1)

14 (15,9)

InnoCollabST

=1 if the firm did have innovation projects together with co-located partners (0 if not)

47 (53,4)

40 (45,5)

0

1

Table 6. Territorial Anchoring and Networking on Savoie Technolac Territorial Anchoring and Networking on Savoie Technolac SERVICES

=1 if the firm uses offered services to employees and companies / 0 if not

8 (9,1)

80 (90,9)

EmploiST

=1 if the firm uses local labor (0 if not)

28 (31,8)

60 (68,2)

RelaPart

=1 if the governance team did put the firm in relation with a potential innovation partner / 0 if not

68 (77,3)

20 (22,7)

RelaCLST

= 1 if the governance team did put the firm in relation with an organization that became a customer afterwards / 0 if not

72 (81,8)

16 (18,2)

RelaFOST

= 1 if the governance team did put the firm in relation with an organization that became a supplier afterwards / 0 if not

76 (86,4)

12 (13,6)

APPENDIX 1.2 Table 7. Sector-based distribution of firms (n=88) Manufacturing HTECH (a) NAF. Rev.2, ISIC Rev. 4

26

n

7

%

8

Services

LMTECH (b)

KIBS (c)

Non KIBS

Total

28, 18, 33

58, 62, 70, 71, 73, 74, 85

35, 41, 43, 46, 47, 78, 79, 82, 90, 94

4

53

24

88

4,5

60,3

27,2

100

(a) High-Tech = R&D intensity> 7% ; (b) Low-Medium Tech = R&D intensity ≤ 7% (cf. OECD, 2005) (c) and (d) KIBS: Knowledge Intensive Business Services (cf. Miles et al., 1995; Freel, 2006)

469

470

0,729

0,919

0,068

0,331

0,436

0,262

-0,033

0,034

0,174

0,309

-0,167

0,060

0,114

0,184

0,152

0,135

0,212

0,148

CLUSHREG

CLUSREGR

COLLUNI

LABORINN

DepRDLN

EMPLST

INDEPR

INNOPDT

INNOPROC

INNOSERV

RELACLST

RELAFOST

RELAPART

SIZE08R

Servcrea

Servent

SourcCLSrv

SourcForSrv

Cluster

0,072

-0,030

-0,100

0,004

0,034

0,061

0,008

-0,124

-0,020

0,154

0,075

0,230

0,164

-0,065

0,092

1,000

0,152

-0,107

CollUniST

0,219

0,344

0,154

0,174

0,123

0,237

0,302

-0,015

0,274

0,348

0,396

0,057

0,059

0,952

0,955

0,016

0,408

0,225

Depense Inno

-0,064

-0,002

0,057

-0,211

0,232

-0,037

-0,013

0,069

0,178

0,106

0,078

-0,048

1,000

0,011

0,100

0,164

0,254

0,168

EmploiST

Table 8. Items loading on each factor – PLS1

0,033

-0,051

0,156

0,248

-0,434

0,196

0,271

0,259

0,031

0,156

-0,217

1,000

-0,048

0,059

0,051

0,230

-0,020

-0,043

Indépendants

0,231

0,313

0,117

0,179

-0,091

0,156

0,155

-0,054

0,109

0,117

1,000

-0,217

0,078

0,380

0,375

0,075

0,033

0,021

InnoPDT

0,181

0,200

0,194

0,227

-0,057

0,113

0,218

0,099

0,358

1,000

0,117

0,156

0,106

0,304

0,358

0,154

0,232

0,001

InnoPROC

0,297

0,157

0,219

0,228

0,014

0,084

0,247

0,273

1,000

0,358

0,109

0,031

0,178

0,270

0,254

-0,020

0,279

0,235

InnoSRV

0,224

0,068

0,272

0,420

-0,260

0,752

0,889

0,731

0,271

0,194

0,110

0,310

0,009

0,269

0,174

-0,027

-0,004

0,009

NetworkingST

0,119

0,058

-0,118

-0,243

1,000

-0,149

-0,221

-0,237

0,014

-0,057

-0,091

-0,434

0,232

0,085

0,149

0,034

0,157

0,156

Taille

0,224

0,248

0,780

0,845

-0,227

0,313

0,342

0,384

0,275

0,260

0,185

0,253

-0,108

0,236

0,152

-0,053

0,227

0,017

Service Ent

0,834

0,819

0,258

0,210

0,108

0,116

0,192

0,095

0,276

0,231

0,329

-0,010

-0,041

0,343

0,304

0,027

0,260

0,053

Sourcefilière

Institutional Innovation Practices in Technopoles

APPENDIX 2.1

0,284

0,0291

0,1174

0,1896

0,1381

Servent

SourcCLSrv

SourcForSrv

-0,1323

0,1121

0,2823

0,1867

0,1362

0,3218

SIZE08R

0,1161

RELAPART

0,3688

0,2797

0,0042

0,1441

0,0356

0,1539

Servcrea

-0,1644

0,0598

RELACLST

RELAFOST

0,3084

INNOSERV

0,0794

0,0328

0,1512

INNOPDT

0,256

-0,0364

EMPLST

INDEPR

INNOPROC

0,3296

0,3157

LABORINN

0,2269

0,0909

0,0406

0,424

1

COLLUNI

0,0216

COLLABST

0,0559

-0,0269

ProjetInno CollabST

DepRDLN

0,8043

0,8668

CLUSHREG

CLUSREGR

Cluster

0,072

-0,0297

-0,0995

0,0044

0,034

0,0607

0,0082

-0,1245

-0,0198

0,1544

0,0753

0,2304

0,1637

0,092

-0,0648

1

0,2269

0,1522

-0,1068

CollUniST

0,2187

0,3435

0,1534

0,1737

0,1239

0,2362

0,3009

-0,0152

0,2742

0,348

0,3957

0,0574

0,0599

0,9566

0,9507

0,0168

0,1294

0,4072

0,2238

Depense Inno

Table 9. Items loading on each factor – PLS2

-0,0643

-0,0022

0,0566

-0,2113

0,2323

-0,037

-0,0129

0,069

0,1776

0,1065

0,0781

-0,0476

1

0,1

0,0115

0,1637

0,0356

0,254

0,1677

EmploiST

0,0333

-0,0511

0,1563

0,2484

-0,4343

0,1958

0,2714

0,2588

0,0311

0,1563

-0,2165

1

-0,0476

0,0511

0,0585

0,2304

0,3296

-0,0199

-0,0431

Indépendants

0,2314

0,3132

0,1174

0,179

-0,091

0,1563

0,1545

-0,0539

0,1093

0,1174

1

-0,2165

0,0781

0,3747

0,3803

0,0753

0,0794

0,0327

0,0213

InnoPDT

0,181

0,2005

0,1935

0,227

-0,0573

0,1133

0,2183

0,0985

0,3581

1

0,1174

0,1563

0,1065

0,3581

0,3041

0,1544

0,1441

0,2322

0,0011

InnoPROC

0,2969

0,1565

0,2187

0,2284

0,0141

0,0839

0,2471

0,2735

1

0,3581

0,1093

0,0311

0,1776

0,254

0,2695

-0,0198

0,0042

0,2786

0,2345

InnoSRV

0,2033

0,0802

0,2744

0,4136

-0,2513

0,8202

0,8589

0,7103

0,2497

0,1855

0,1183

0,3022

0,0034

0,1801

0,27

-0,0157

0,4078

0,0083

0,0218

NetworkingST

0,1186

0,0583

-0,1177

-0,243

1

-0,1491

-0,2213

-0,237

0,0141

-0,0573

-0,091

-0,4343

0,2323

0,1492

0,0851

0,034

-0,1323

0,1569

0,156

Taille

0,2239

0,2528

0,8149

0,8125

-0,2215

0,3104

0,3373

0,3754

0,2747

0,2584

0,182

0,2485

-0,0945

0,152

0,234

-0,0586

0,348

0,227

0,0157

Service Ent

0,8336

0,8192

0,2582

0,2105

0,1077

0,1158

0,1922

0,0952

0,2759

0,2306

0,3285

-0,0098

-0,041

0,3039

0,3434

0,0268

0,0863

0,2603

0,0529

Sourcefilière

Institutional Innovation Practices in Technopoles

APPENDIX 2.2

471

472

0,184

Taille

(1) AVE square root

0,177

0,217

Sourcefilière

0,000

NetworkingST

ServiceEnt

0,174

0,309

InnoPROC

0,034

InnoPDT

InnoSRV

0,262

-0,033

EmploiST

Indépendants

0,034

0,027

-0,053

-0,027

-0,020

0,154

0,075

0,230

0,164

1,000 0,016

0,068

0,401

CollUniST

0,830 (1)

CollUniST

DepenseInno

Cluster

Cluster

0,123

0,339

0,202

0,231

0,274

0,348

0,396

0,057

0,059

0,954

DepenseInno

0,232

-0,041

-0,108

0,009

0,178

0,106

0,078

-0,048

1,000

EmploiST

Table 10. Correlations and AVE square roots – PLS1

-0,434

-0,010

0,253

0,310

0,031

0,156

-0,217

1,000

Indépendants

-0,091

0,329

0,185

0,110

0,109

0,117

1,000

InnoPDT

-0,057

0,231

0,260

0,194

0,358

1,000

InnoPROC

0,014

0,276

0,275

0,271

1,000

InnoSRV

-0,260

0,179

0,432

0,794

NetworkingST

-0,227

0,285

0,813

ServiceEnt

0,108

0,826

Sourcefilière

1,000

Taille

Institutional Innovation Practices in Technopoles

APPENDIX 3.1

0,017

0,022

0,156

0,198

0,187

NetworkingST

ProjetInnoCollabST

ServiceEnt

Sourcefilière

Taille

0,034

0,027

-0,059

0,227

-0,016

-0,020

0,154

0,075

0,124

0,339

0,201

0,129

0,234

0,274

0,348

0,396

0,057

0,060

0,954

DepenseInno

0,232

-0,041

-0,095

0,036

0,003

0,178

0,106

0,078

-0,048

1,000

EmploiST

-0,434

-0,010

0,249

0,330

0,302

0,031

0,156

-0,217

1,000

Indépendants

-0,091

0,329

0,182

0,079

0,118

0,109

0,117

1,000

InnoPDT

(1) AVE square root 1 We used the SmartPLS 2.0 version (Ringle, Wende & Will, 2005, cf. http://www.smartpls)

0,151

0,308

InnoPROC

InnoSRV

0,033

InnoPDT

0,230

0,164

0,256

-0,036

EmploiST

Indépendants

0,017

0,041

0,386

1,000

CollUniST

CollUniST

0,836

Cluster

DepenseInno

Cluster

Table 11. Correlations and AVE square roots – PLS2

-0,057

0,231

0,258

0,144

0,185

0,358

1,000

InnoPROC

0,014

0,276

0,275

0,004

0,250

1,000

InnoSRV

-0,251

0,173

0,422

0,408

0,799

NetworkingST

-0,132

0,086

0,348

1,000

ProjetInnoCollabST

-0,221

0,288

0,814

ServiceEnt

0,108

0,826

Sourcefilière

1,000

Taille

Institutional Innovation Practices in Technopoles

APPENDIX 3.2

473

474

Chapter 25

Choosing Locations for Technology and Innovation Support Centers: Methodological Proposal and Brazilian Studies Mário Otávio Batalha Federal University of São Carlos, Brazil Daniela Tatiane dos Santos Federal University of São Carlos, Brazil Nelson Guedes de Alcântara Federal University of São Carlos, Brazil Sérgio Ronaldo Granemann University of Brasília, Brazil

ABSTRACT This chapter discusses the structuring of problems of location of Technology and Innovation Support Centers (TISC) through multicriteria analyses to identify factors of demand and supply of these services. The methodology uses quantitative and qualitative elements, establishing a sequence of steps that include a variety of aspects ranging from criteria preferences to global valuation of the model. Multicriteria analysis was applied to the choice of geographic locations for Brazilian Technology Centers, allowing for the identification of the most suitable regions for the creation of technology centers and revealing particular characteristics of the dynamics of such services in the regions in question.

DOI: 10.4018/978-1-61350-165-8.ch025

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Choosing Locations for Technology and Innovation Support Centers

INTRODUCTION Many developing countries have made considerable efforts to reduce technological disadvantages that prevent them from implementing innovations to establish high quality standards and internalize core activities of technical progress (World Bank, 2008). These efforts have received government incentives for innovation, and involved numerous companies that have come to recognize the well-nigh inseparable link between innovation and competitiveness. These companies require a series of technological services (assays, calibration, standardization, inspection, new product development, etc.) of a strongly horizontal nature and with multiplying effects on the economy. Moreover, the supply of such services can contribute to consolidate more prosperous and industrially advanced regions, reinforcing the dynamic effects of technological demand (Feller, Ailes & Roessner, 2002; Kakuta & Luz, 2001). The supply of technology support services plays a dynamizing role in an economy, favoring the innovation process by overcoming technical obstacles than hinder market action. Many Technology and Innovation Support Centers (TISCs) provide a technical basis for specialized knowledge that reinforces innovation generated in companies. The Danish TISCs are a well known example – a set of nine large networking laboratories whose activities are broadly cross-sectional and whose research and development efforts extend far beyond the mere supply of technical services (Andersen et al., 2009). The proximity of a TISC which can provide technological resources to a large number of companies can be considered an element that contributes to cost reductions through transaction economies (Williamson, 1989), and whose main characteristic is that of facilitating the acquisition of services. The presence of a TISC can also compensate for competencies companies lack, enabling them to concentrate on their core business, such as the production process itself.

Above and beyond business interests, a TISC is also important for other economic and government agents (Zucker, Darby & Armstrong, 1998, 2002). Professors and researchers could use TISC laboratory facilities for research, and a TISC could be an important tool for politicians to support and boost regional development. However, it should be noted that politics will not, per se, ensure the success of a TISC. Brazilian experience indicates that purely bureaucratic government initiatives to establish Technology and Innovation Support Centers (TISCs) in regions that lack a preexisting industrial structure have failed. Among the factors that have most contributed to the many faulty choices for TISC locations is the lack of qualified human resources. Thus, when evaluating a location for a TISC, it is necessary to consider regions that have a relatively consolidated education, productive and technological structure, and will therefore benefit more from it. This chapter starts from the above premises, using elements of demand and supply of technology services to structure problems relating to the location of TISCs. Multicriteria analysis has not been widely used in the literature on innovation management. However, methods of multicriteria analysis can contribute considerably to decision making about technology choices by public institutions. The use of methods such as the one proposed here is aimed at finding solutions for the location of TISCs that are less subject to the inevitable political pressures that such decisions engender. The starting point for this work is the need to identify cities in the Central West (CW), North (N), and Northeast (NE) regions of Brazil with the best conditions to establish a TISC in the area of materials, limited to one center per region. This project was funded by FINEP (Study and Project Financing Agency), which is linked to the Brazilian Ministry of Science and Technology. Materials Technology Centers (MTC) contribute to the core competencies and innovations of lo-

475

Choosing Locations for Technology and Innovation Support Centers

cal industries, regions, states, and to the country, offering technological support in science and engineering areas. In countries such as Brazil, MTCs favor innovation-related activities through the development of new materials, e.g., biomedical and smart materials, advanced materials for practical applications such as civil infrastructures, compressor engineering and manufacturing, or the fabrication of materials and structures. The strategic management of these Centers would be a fundamental instrument for achieving cumulatively sustainable competencies that could reduce the technological gaps existing among nations with different levels of development. The multicriteria method used here was the Analytic Hierarchy Process – AHP (Saaty, 1990), which allowed for the development of a decision process based on quantitative and qualitative criteria. The results obtained with this method were consistent and did not pose any problems of comparison between the criteria and possible alternative solutions. The AHP was used as a method for location choice, and the results obtained indicate the suitability of this approach. The application of AHP to location decisions has been tested in different types of problems and in different areas. One of the drawbacks of this method, however, is the number of location criteria that can be considered in the analysis of the problem. The AHP allows for the consideration of a maximum of 9 criteria or a group of criteria, although the ideal situation would be the use of a minimum of 5 to 7 criteria and a maximum of 7 to 9 criteria. There is no doubt that the determinants involved in the choice of technology centers are much greater than those considered in this work. Therefore, to use the AHP rationally required grouping the criteria with similar characteristics around aspects of supply and demand for technological services. This chapter is divided into five main sections, besides this introduction. The second section focuses on a review of the literature on the process of choosing the location of technology centers,

476

as well as some factors concerning the demand and supply of technology services. The third and fourth sections focus on applying the multicriteria analysis for decision making about the location of centers, as well as the main results and discussion. The last section presents the conclusions of this study.

TECHNOLOGY SUPPORT CENTERS AND CHOICE OF LOCATION Technology support centers can be defined as institutes engaged not only in providing goods and basic laboratory services but also research activities and the development of products and processes (COTEC, 2003). Their most routine activities involve the short-term demands of companies, mainly those relating to projects aimed at generating economies of scale and meeting immediate market needs. However, more advanced studies that favor long-term industrial competitiveness can and should also be conducted by these centers. Numerous countries have focused efforts towards establishing and consolidating TISCs. There are several different models for creating institutes with reduced technological intensity (technology transfer centers, support centers to increase competitiveness, technology acquisition consortiums) or even more daring ventures involving institutes of high density technology (public research and development centers, private R&D centers, mixed R&D centers, and NGOs). A large part of such institutes have achieved results that are highly relevant for the economy of the countries and regions where they are established. Nevertheless, a study by Beise and Stahl (1999) that analyzed the effects of public research on industrial innovations in Germany between 1993 and 1995 found that many public technology centers failed to transfer knowledge to companies. Even so, many companies would not be able to implement innovations in the absence of these technology centers. The authors also point out that

Choosing Locations for Technology and Innovation Support Centers

the role of stimulating innovation is, in most cases, attributed to the universities that contain technology centers rather than to the centers themselves. A set of preconditions related to the characteristics of the area where the center is to be located seems to be crucial for the successful establishment and development of technology centers. Some studies on center location, such as that of Krugman, Fujita and Vernables (1999), have been based, to a certain extent, on concepts established by the classic theory of industrial location (Von Thünen, 1826; Teruya, 1999; Predöhl, 1928). In general, the aim is to analyze the location of economic activities by identifying factors such as raw materials transportation cost and labor cost. According to Predöhl (1928), economic location is a function of the compared costs of transportation of the different production factors (capital, work, and land) and the relative prices. Having defined the costs involved and the possible revenue to be obtained, it would be possible to determine the best combination of factors that would allow for choice optimization. This is a systematic approach to understanding the geographic advantages offered by each location where investments are to be made. The classical theory about location choice offers important contributions towards an understanding of the elements that foster the attraction of enterprises. However, such an approach would reduce decision making to strictly quantitative elements that may not always be relevant to a TISC, and that are only partially applicable in explaining the pattern of location of technology enterprises. For example, the availability of labor and parts for equipment maintenance is more relevant to the success of a TISC than the availability of raw material. In this context, the contribution of industrial clusters has been highlighted by Gordon and McCann (2000) and by Morosini (2004). Research and development institutes, like the TISCs situated in industrial centers, would obtain economies of scale and scope by cooperating with companies

and other institutes. It should be noted that the mere presence of such institutes does not ensure the success of a cluster’s technology and innovation activities. Its success depends on a set of other factors such as interaction and cooperation among local agents, the presence of qualified labor in the region, relationships with suppliers, and, in some cases, the existence of government incentives. Jaffe, Trajtenberg and Henderson (1993) investigated the effects of the geographic proximity of spillovers. An understanding of the location choice of many Technology Centers may point to the characteristics of technology diffusion in a given region. On the other hand, Beise and Stahl (1999) discard the hypothesis that the proximity of public research centers would be a determining factor for the implementation of technology innovation by companies. Moreover, many authors have attempted to adapt some of the classical elements of industrial location to the specificities and needs for the establishment of regional technology development policies, including the creation of TISCs. Public sector policies and the innovation potential of a region are issues that have been addressed by authors such as Breschi and Malerba (2001) and Salerno and Kubota (2008). It is worth highlighting the importance contemporary theory has attributed to the State’s role as a promoter of regional development policies. This role leads to the recognition that natural resources and other production factors do not suffice to justify industrial location in those areas based on classical competitive advantages. The location of technology centers is only partially determined by government incentive policies. The dynamics of technological innovation has also provided decisive interpretations in analyzing the success of TISCs. It has been found that the location concentration of technology centers has been determined by complex and specialized factors, particularly by scientifically and technically qualified labor, communication infrastructure, and sophisticated consumer markets.

477

Choosing Locations for Technology and Innovation Support Centers

These factors have made it possible to take advantage of synergies that result from acting in networks. Many technology centers have the ability to combine the needs of industry and the capabilities of local universities in the construction of new standards of quality in products and processes. Thus, the various factors set forth in the classical and contemporary literature concerning the reasons for locating technology centers in a given region should be specified based on elements of the demand and supply of technology services, which is the subject of this study.

DEMAND AND SUPPLY OF TECHNOLOGY SERVICES The services of technology centers can be classified according to different criteria (COTEC, 2003). One of them classifies technological services according to their functionality, which may involve knowledge sharing activities (courses, lectures, and training), activities that promote interaction between different economic agents, or even functions that favor the supply of specialized services to a company. This functionality may lead toward an approach that specifies the services of technology centers according to different stages of the production process, encompassing the generation and acquisition of knowledge and technology and

the preparation for production and commercialization, as illustrated in Table 1. Some elements of the demand for technology center services are related to the specificities of a region’s industrial structure. First of all, it can be stated that the supply of regional technological services appears to derive from the characteristics of the size of companies situated in the region. Wren and Storey (2002) found that the probability of using these services is positively correlated to the number of employees in a company with a workforce of up to 150, and negatively correlated to companies with a larger workforce. A possible explanation for this finding is the internalization of research and development by companies whose larger size enables them to carry out activities in-house which were previously outsourced. Smaller companies, but with a solid technology basis, are strongly dependent on a variety of technological services. The technological level achieved by a company is undoubtedly a determining condition for the demand of services from a technology center (Quevedo & Mas-Verdú, 2008). It can be stated that companies lacking in technological dynamism do not make permanent use of services such as patent-related activities, quality control, or product certification. However, such needs are common in companies that have already reached higher qualitative standards. Smallbone (1993) found evidence that consolidated or mature companies, regardless of their size, are more likely

Table 1. Services generally supplied by technology centers Generation and acquisition of knowledge

Preparation for production

Preparation for commercialization

Generation of new products and processes (R&D projects)

Standardization and quality

Market studies and business plans

Support for the acquisition of technology

Pilot facilities

Support for investments in new markets

Education and access to new ideas

Process modernization and automation

Support for the creation of new companies (spin offs)

Access to qualified resources

Assays, tests and certifications

Support for the launch of new products

Support for the acquisition of imported equipment

Support for the creation of new production lines

Support for intellectual property

Source: Adapted from COTEC (2003).

478

Choosing Locations for Technology and Innovation Support Centers

to require outsourced technological services. This indicates the need for the adoption of measures, besides those traditionally implemented in technology centers, aimed at stimulating younger companies to develop innovative ideas. The export dynamics of companies seems to be related directly to the technological content of the production exported by given regions. Exposure to competition from foreign companies leads to the search for competitive advantages in terms of product and service differentiation, and expands the areas to be covered by technology support centers (Quevedo & Mas-Verdú, 2008). In this context, the need for higher levels of competitiveness may explain the greater use of TISCs. In developing countries, companies seeking to expand their share in international trade should adapt to international standards and norms through technological services aimed directly at overcoming technical and commercial barriers. These barriers can be obstacles to growth if a region is unable to overcome the challenges of technological evolution and the requirements of more developed markets (Kakuta & Luz, 2001). On the other hand, the availability of technological services favors directly the achievement of systemic competitiveness, helping in the definition of more industrially advanced areas. Qualified human resources such as specialized researchers, whose expertise can be used by these institutes, and the availability of laboratory infrastructure, machinery and equipment, as well as training courses related to the activities of the TISC, are elements consistent with the aforementioned theories. The institutional conditions in which the supply of these services takes place are highly varied. In this context, one must keep in mind that the environment of technological research in developing countries has always been linked, one way or another, to government institutions. One of the consequences of this institutional design, which is particularly true in the case of Brazil, is that few centers and institutes have achieved

the economic autonomy that would render them independent of public sources. This situation is due to the fact that the technological solutions of these centers have often failed to be market-oriented, or even because company demands showed little technological dynamism, focusing mainly on the acquisition of foreign technology (Kakuta & Luz, 2001). Nevertheless, according to these authors, knowledge about the forces that drive the demand and supply for technological services in Brazil is still limited, indicating the need for more in-depth studies on this issue.

METHODOLOGICAL PROCEDURES General Methodological Aspects of this Research Multicriteria analysis was used in two distinct phases of this study. The first phase consisted of an extensive review of the literature and searches on specialized websites to find the quantitative variables most commonly used for the identification of demand and supply of technological services. The variables thus identified were then collected and compiled in tables for an initial multicriteria analysis. The purpose of this analysis was to select, among the 19 states in the Central West, North, and Northeast regions of Brazil, the ones that would be the object of a detailed field research. This initial analysis was necessary due to the limited time and resources to carry out the study. Several states therefore were discarded in this initial stage of the study. The quantitative information was garnered from various sources, such as the Brazilian Institute of Geography and Statistics (IBGE), Ministry of Labor and Employment (MTE), Secretariat of Foreign Trade (SECEX), Council for Scientific and Technological Development (CNPq), and Brazilian Technology Network of the Ministry of Science and Technology (MCT).

479

Choosing Locations for Technology and Innovation Support Centers

The second multicriteria analysis, which provided the final guidance for the best locations for TISCs, required gathering qualitative information in the cities and states selected in the initial analysis. In each city, interviews were held with industrial federations, research foundations, universities, and research centers. The characteristics of the method used here and the procedure for selecting the most suitable states for the creation of Materials Technology Centers (MTC) are explained below.

The Method of Multicriteria Analysis The use of methods of multicriteria analysis allows for the inclusion of criteria of individual values designated by specialists in order to solve a number of problems simultaneously. These methods include the Analytic Hierarchy Process (AHP), which aims to associate the list of preferences (subjective) with the various criteria in the decision-making process, considering both quantitative and qualitative variables (Saaty, 1990; Granemann, Tedesco & Candal, 2008). The determining factor for the choice of the AHP method was the possibility of treating qualitative variables based on intangible criteria, which are therefore more difficult to evaluate. The method is structured on a sequence of steps that encompass the delimitation of the objective and the relevant criteria for problem-solving and decision-making, the determination of alternatives, evaluation of the relative importance of each criterion and of the alternatives in relation to the criteria, and determination of the global valuation of each alternative. After considering the relative importance of the criteria, an entirely analogous process is used to establish the level of preference of the alternatives. Lastly, the global valuation is considered according to the weighted sum method, using the following equation:

480

n

V (q) = ∑ px ⋅ ax (q) , x =i

n

∑p x =i

x

= 1 and 0≤px≤1 (1)

where: V(q): global valuation of the alternative px: weight of criterion x ax: level of preference of the alternatives analyzed in the criterion Thus, the aforementioned model was applied to identify the optimal location of technology centers, considering that the criteria would be the factors most closely related to the demand and supply for technological services and that would determine the attractiveness of the various regions.

The Process of Location Choice First Multicriteria Analysis The purpose of this section is the selection, among the 19 states in the Central West, North, and Northeast regions of Brazil, of the ones with the best conditions for the creation of Materials Technology Centers. The project’s goal was to reduce technological disparities between Brazilian states. In general, Brazil’s Central West, North, and Northeast regions have less advanced technology centers than the South and Southeast regions. Table 2 identifies the criteria selected for the first multicriteria analysis and described their characteristics and importance for this type of decision making. Eight critical variables were used here to explain the demand and supply of innovation-related technological services, three of them related to supply and five to demand. Note that the human resources indicator (HRI) and the publication indicator (PI) are composite indicators obtained by combining two or more variables. Table 3 lists the values of these indicators for all the states considered in the analysis.

Choosing Locations for Technology and Innovation Support Centers

Table 2. Variables used in the first multicriteria analysis Analysis

Supply

Demand

Criteria (variables)

Indicator source and creation

Importance

HRI (Human resources indicator)

Assignment of weights to the sum of researchers with a master’s degree (weight 1), with a doctoral degree in the field of materials or related area (weight 2). Indicator created based on the Tabular Plan of the Council for Scientific and Technological Development (CNPq) (2004).

Indicator of the level of training of human resources qualified to work for a technology center

PI (Publication indicator)

Assignment of weights to the sum of the number of national (weight 4) and international (weight 8) publications, published book chapters (weight 4), and complete works published in the proceedings of events in materials or correlated areas (weight 2). Indicator created based on the Tabular Plan of CNPq (2004).

Indicator of the presence of knowledge and intellectual qualifications that can favor the sustainability of the TISC

Research institutes and universities

Research Institutes and universities acting in materials or correlated areas* registered with CNPq (2004) and in the Brazilian Network of Technology - MCT (2007)

Indicator of the number of institutes (supply). The creation of technology centers in states that already have research institutes and universities may favor joint collaborations.

Exports

Secretariat of Foreign Trade (2006)

In addition to indicating the potential demand for a technology center resulting from stimuli from foreign markets, it demonstrates the technological content of the exports of the states.

Number of employees

Annual Record of Social Information - Ministry of Labor and Employment of Brazil (2004).

Quantifies the workforce formally employed

Number of employees with higher education

Annual Record of Social Information - Ministry of Labor and Employment of Brazil (2004).

Quantifies the workforce with higher education. The demand of technologically dynamic companies represents potential clients to be served

Number of local units

Annual Industrial Survey - Brazilian Institute of Geography and Statistics (2005)

Industrial companies with 5 or more employees. Allows for quantification of the potential market to be served by the TISC

Industrial transformation value

Annual Industrial Survey - Brazilian Institute of Geography and Statistics (2005).

Difference between the gross value of industrial production and industrial operating costs. Indicator of productivity that shows the added value of each segment to the state’s production.

Source: Developed by the authors. * The fields refer to materials-related activities such as chemistry, chemical engineering, mechanics and physics.

The research team prioritized the criteria in decreasing order of importance, which resulted in the following hierarchy: research institutes and universities, Human Resources Indicator (HRI), Publication Indicator (PI), number of employees, exports, number of local units, and industrial transformation value. Greater importance was given to the presence of research institutes and universities acting in materials and/or related fields, since their presence indicates initiatives and efforts already made in this area. The second most important factor was

the Human Resources Indicator (HRI), since it is understood that TISCs need researchers with expertise in the areas of materials. A relatively lower degree of importance was given to the publication indicator (PI), which refers to studies published in the area of materials and/or related fields and indicates the presence of knowledge and intellectual capability that can favor the operations of a TISC. The lesser importance of HRI and PI compared to the presence of research institutes and universities is due to the fact that human resources and knowledge 481

Choosing Locations for Technology and Innovation Support Centers

Table 3. Brazilian states selected for the first multicriteria analysis

Exports US$ (2006)

Number of employees (2004)

Number of employees with higher education (2004)

Number of local units (2005)

Industrial transformation value in R$ (2005)

9

65,749,524

18,588

1,352

919

1,140,079

8

2,092,027,930

135,717

4,119

4,513

8,501,887

6,094

3

4,333,376,419

72,248

1,385

2,403

6,295,994

15,716

5

1,004,204,248

48,391

1,408

1,314

2,766,885

77

1,266

3

17,795,969

3,644

50

184

95,688

20

82

2

127,980,007

2,779

67

107

259,972

Amazonas

1,033

18,740

11

1,522,851,015

86,236

5,093

918

19,769,522

Pará

1,088

24,046

10

6,707,603,218

90,479

2,323

2,019

8,165,561

Rondônia

40

638

1

308,018,812

25,945

217

1,073

1,126,990

Roraima

161

2,608

2

15,358,447

1,523

21

96

30,665

Tocantins

243

4,888

4

203,886,580

8,702

119

392

276,118

Alagoas

419

8,422

3

692,543,376

94,916

1,435

667

2,075,454

Bahia

1,973

43,474

13

6,771,981,469

148,102

6,576

4,160

24,184,645

Ceará

1,559

43,512

12

957,045,076

176,854

3,826

3,805

5,392,342

Maranhão

354

10,636

3

1,712,701,103

23,190

560

764

2,235,720

Paraíba

1,510

48,312

8

208,589,087

51,153

1,447

1,302

1,852,656

Pernambuco

2,237

62,774

11

780,340,072

147,209

5,573

3,786

5,675,220

Piauí

249

3,416

3

47,127,095

20,777

555

819

702,169

Rio Grande Norte

880

24,110

7

371,503,239

55,095

1,753

1,349

2,904,517

Sergipe

435

9,002

3

78,939,173

29,116

1,121

825

2,638,893

Total

16,268

401,864

121

28,019,621,859

1,240,664

39,000

31,415

96,090,977

Human resources indicator (2004)

Publication Indicator (2004)

Research institutes and universities (2004)

Federal District

1,723

47,984

Goiás

1,031

26,144

Mato Grosso

493

Mato Grosso Sul

743

Acre Amapá

Alternatives (States)

Central West

North

Northeast

Source: Brazilian Institute of Geography and Statistics (IBGE), Ministry of Labor and Employment (MTE), Secretariat of Foreign Trade (SECEX), National Council for Scientific and Technological Development (CNPq), and Brazilian Network of Technology of the Ministry of Science and Technology (MCT)

can be transferred to nearby regions to meet the requirements of the TISC. Ranking fourth and fifth in terms of priority are, respectively, the number of people with a higher education working in the state’s industrial companies and the overall number of employees. The number of employees with a higher educa-

482

tion indicates the qualifications of the companies’ human resources. For a TISC, the demand of technologically dynamic companies represents potential clients to be served. Precisely because the technological dynamism of these companies is relevant to a center, a lower priority was given to the overall number of employees.

Choosing Locations for Technology and Innovation Support Centers

The two lowest priority levels were assigned to exports and to the number of local units. An export analysis can indicate the degree of insertion of companies in the export market. However, this insertion may occur mainly through goods with low added value, as is typically the case of commodity exporter states. Hence, even if the export rate may serve to indicate the size of the market to be served by a TISC, the technologically dynamic export markets in the Central West, North, and Northeast regions to be served by this TISC would be relatively small, since these Brazilian regions are known historically as exporters of low added value goods. Similarly, although the number of local companies allows for quantification of the potential market to be served by a TISC, it does not guarantee that these industrial companies actually require technological services. Therefore, less importance was given to these criteria than to the previous ones. Lastly, an even lower priority was assigned to the industrial transformation value, which is defined as the difference between gross industrial production and industrial operating costs (intermediate consumption). This is a productivity indicator that indicates each sector’s added value to the production of the state under analysis. The lower priority given to the industrial transformation value compared to exports is due to the fact that the intermediate consumption of the sectors that require technology in these states depends, to a large extent, on imports, which contributed to diminish the role to be played by the TISC. Therefore, the parity comparisons resulted in the following weights for the criteria: research institutes and universities (34.3%), human resources indicator (HRI) (24.4%), publication indicator (PI) (17.3%), number of employees with higher education (8.9%), overall number of employees (6.1%), exports (4.1%), number of local units (2.9%), and industrial transformation value (2.1%). Table 4 presents the global valuation of the alternatives, which was obtained from their com-

parison to each other based on each criterion. The global value indicates the attractiveness of the 19 states of the CW, N, and NE regions, considering that 7 states would be strong candidates to receive a technology support center. Note that the in CW region, the Federal District (Brasília) and Goiás are competitors, since they present attractiveness indices of 0.537 and 0.282, respectively. On the other hand, the highest scoring states in the North are Pará (0.362) and Amazonas (0.352), In the Northeast, Pernambuco, Bahia, Ceará and Paraíba presented the highest scores, i.e., 0.246, 0.241, 0.146 and 0.141, respectively.

Second Multicriteria Analysis The objective of this analysis is the choice, among the seven states and the Federal District selected in the first analysis, of the three states that would receive technology centers, one in each region of the country. In this stage, qualitative information garnered in the field research was combined with previously available quantitative data. Thus, seven variables were selected for a second multicriteria analysis, three of them related to supply and four to demand for technological services. The variables of exports and industrial transformation value had already served as the basis for the first analysis. Five new variables that had been the objects of the field research were now included, namely, institutional environment, existing infrastructure, technology service demanding sectors, private projects in the area of action of the TISC, and expanded human resources indicator. The following priorities were assigned to the criteria in decreasing order: demanding sectors, private projects, institutional environment, expanded HRI, industrial transformation value, existing infrastructure, and exports. The first level of priority or importance was assigned to the existence of sectors that demand the TISCs’ services, which would indicate the current demand for materials-related technological services in the regions under analysis. The second

483

Choosing Locations for Technology and Innovation Support Centers

Table 4. Attractiveness of the alternatives Alternatives (States)

Level of attractiveness

Central West Federal District

0.537

Goiás

0.282

Mato Grosso

0.081

Mato Grosso Sul

0.100

North Pará

0.362

Amazonas

0.352

Tocantins

0.109

Rondônia

0.054

Acre

0.051

Amapá

0.037

Roraima

0.035

Northeast Pernambuco

0.246

Bahia

0.241

Ceará

0.146

Paraíba

0.141

Rio Grande Norte

0.084

Sergipe

0.050

Maranhão

0.036

Alagoas

0.030

Piauí

0.026

Source: Developed by the authors.

level of priority was assigned to the existence of large investment projects. This variable, which would indicate the existence of current and future demand for technological services on the part of large industrial projects, was assigned a lower priority than the existence of demanding sectors due to the uncertain nature of many projects, which could render them unviable. The third and fourth levels of priority were assigned to the presence of an institutional environment and the expanded human resources indicator. The presence of a favorable institutional environment indicates the commitment of institutional support agencies to the creation of the TISC. The expanded human resources indicator denotes the level of materials-related qualifications of the hu484

man resources, as well as the research efforts that have been published in materials-related areas. The latter is a combination (average) of the HRI and PI indicators used in the first multicriteria analysis. The presence of a favorable institutional environment was considered a more important requisite for the creation of a TISC than the presence of human resources, since people can be transferred to and from the regions near the TISC. The fifth level of priority was assigned to the industrial transformation value of the states. In the first multicriteria analysis, a higher priority was assigned to exports than to the industrial transformation value, due to the characteristics of intermediate goods consumption in the CW, N, and NE regions, based, to a large extent, on imported technology. However, the interviews were conducted with the main representatives of the states investigated, such as presidents and directors of industry associations and unions, presidents of universities and professors of university departments. The interviews revealed that this priority could be inverted because the intermediate consumption of the sectors that require technological services depends little on imports and the demand can be supplied partially by local technology centers. The sixth level of priority was assigned to the existence of infrastructure in the states, such as laboratories and equipment that could support the TISC structure. The lowest level of priority was assigned to exports, since exports in the regions under analysis consist of low added value goods, limiting the action of the TISC. Thus, the resulting weights for the different criteria were: demanding sectors (36.8%), private projects (22.7%), institutional environment (17.1%), human resources indicator (9.9%), industrial transformation value (6.4%), infrastructure (4.5%), and exports (2.6%). Table 5 describes the evaluation of the alternatives according to different criteria. In the Central West region, the state of Goiás presented the highest scores in all the criteria with the exception of human resources, for which the

Choosing Locations for Technology and Innovation Support Centers

Table 5. Attractiveness of the alternatives according to different criteria Alternatives (States)

Criteria (variables)

Total

DEMSEC

PRIPROJ

INSTENV

HRI EXP

ITV

INFRA

EXP

Goiás

0.315

0.114

0.086

0.017

0.057

0.038

0.023

0.650

Federal District

0.053

0.113

0.085

0.082

0.007

0.007

0.003

0.350

Amazonas

0.307

0.057

0.137

0.025

0.053

0.034

0.006

0.619

Pará

0.061

0.170

0.034

0.075

0.011

0.011

0.020

0.382

Pernambuco

0.099

0.145

0.095

0.057

0.010

0.018

0.003

0.427

Bahia

0.215

0.023

0.022

0.012

0.042

0.018

0.017

0.349

Ceará

0.038

0.048

0.046

0.012

0.009

0.003

0.005

0.161

Paraíba

0.016

0.011

0.008

0.018

0.003

0.006

0.001

0.063

Central West

North

Northeast

Legend: DEMSEC: Demanding sectors; PRIPROJ: Private projects; INSTENV: Institutional environment; HRI EXP: Expanded human resources indicator; ITV: Industrial transformation value; INFRA: Available infrastructure; EXP: Exports

Federal District showed a better classification. In 2004, the number of publications by researchers with master’s and doctoral degrees, as well as the number of theses and dissertations concluded in the Federal District, was relatively higher than in the state of Goiás. Nevertheless, the total sum of the variables (0.650 for Goiás and 0.350 for the Federal District) indicated that Goiás would be the most suitable location for a materials technology center in the Central Western region. In the North, the state of Amazonas reached higher scores than the state of Pará for the following criteria: demanding sectors (0.307), institutional environment (0.137), industrial transformation value (0.053), and infrastructure (0.034), while Pará showed a better performance in human resources, exports, and private projects. The sum of all the variables was 0.619 for the state of Amazonas and 0.382 for Pará, which would justify the choice of the former state over the latter. The state of Pernambuco showed the best performance in the Northeast region, with higher scores than the other states in three criteria: private projects, institutional environment, and human resources, Ceará scored higher than Pernambuco

only in the exports criterion, and received the second highest score in the institutional environment criterion (0.046). The state of Paraíba presented the second best performance in human resources (0.018), Bahia scored higher than the other states in the following criteria: demanding sectors, industrial transformation value, and exports. However, the final sum of the variables favored the choice of Pernambuco as the most suitable state for a technology center in the Northeast. The global valuation of the multicriteria analysis for the state of Pernambuco was 0.427, while the other states showed the following scores: Bahia 0.349, Ceará 0.161, and Paraíba 0.063.

RESULTS AND DISCUSSION The evaluation of the process of location based on multicriteria analysis using the AHP method demonstrated that Pernambuco (NE), Amazonas (N), and Goiás (CW) are the states with the best conditions for the creation of Materials Technology Centers (MTC). The two multicriteria analyses showed an inconsistency index of 0.07, indicating

485

Choosing Locations for Technology and Innovation Support Centers

that the results fall within standards acceptable to the AHP (maximum inconsistency of 0.1). The use of the AHP model allowed for a better understanding of the different factors that affect the location of technology support centers. Analyses of the relative importance of all the factors used in the two multicriteria approaches led to the conclusion that there is a good proportionality in terms of the impact of demand and supply on the location of technology centers. Considering jointly the weights obtained for the criteria in the first and second analyses, and determining an average value for the criteria that are common to both of them, it was possible to obtain the respective sums for demand and supply. Figure 1 illustrates the different attributes used in the first and second multicriteria analyses. The total sum of supply-related factors was 0.83, while that of demand was 0.85, indicating that factors of technology demand and supply exerted the same influence on decision-making about the most suitable choice for the implementation of TISCs.

The analysis corroborated the relevance of many aspects of contemporary location theory. On the one hand, the presence of demand sectors, private projects, research institutes, institutional environments, and qualified labor constitute a set of complex and specialized factors that are poorly explained by the market rationality which theoreticians use as the basis for this approach. On the other hand, it should be kept in mind that some factors considered important in classical theory, such as the industrial transformation value and the number of local units in a region, also appear to justify and influence the standards of technology center location. An in-depth analysis of Figure 1 leads to the conclusion that the high weight of research institutes and universities denotes not only the presence of institutes that favor joint collaborations with technology centers but also reflects the historical connection of these centers to local public universities. Most technology centers in Brazil are located on universities campuses proper, and cases of academic spin-offs that are technically

Figure 1. Relative importance of the factors that influence the choice of locations for technology support centers. (Source: Developed by the authors)

486

Choosing Locations for Technology and Innovation Support Centers

and financially self-sustainable are rare. The high risks of acting in the market and the relatively low demand for technology services appear to be some of the obstacles that technology centers in Brazil face. Notwithstanding the high correlation that Wren and Storey (2002) identified between technology services and the number of employees in a company, demand appears to depend less on company size and more on the innovative characteristics and competitive conditions to which the sectors requiring these services are exposed. This fact would also support the high weight of this criterion in the TISC location process.

CONCLUSION The existence of technology centers is an important source of motivation for regions and countries to overcome technology and innovation disadvantages. The location of these centers is a relevant theme within the sphere of Strategic Innovation Management. This field of research contributes to the innovation of companies and countries through technology management and decision-making support. The mobilization of technological knowledge and competencies in order to favor the best location choice is not a simple task and should be managed and planned strategically so as to encourage the creation of innovative environments. In this context, the design of robust methodologies that augment the chances of success of enterprises is entirely justifiable. The analysis presented here attempted to advance in this direction by allowing for the identification and combined weighting of the elements pertinent to the location choice of such centers. In countries where the choice of a site for the implementation of enterprises of this type is strongly influenced by political criteria alien to technical and scientific logic, the application of research multicriteria methods of this nature offers unquestionable advantages. Government incentives can be vital when it comes to establishing a TISC. Moreover, the role

of the State in innovation stimulates the creation of environments that are more favorable for the development of innovations, inducing the elaboration of innovation-related business strategies and decisions (Salerno & Kubota, 2008). However, although the public sector can act as an articulator of the outcomes of technological innovation, the technical inconsistency of its decisions may sometimes conceal particular orientations not aligned with the productive characteristics of a given region. Reality shows a plethora of situations in which regions and technology projects were the recipients of ventures that were justified more by political will than by an adequate technical basis. To a large extent, this fact is also the result of importing models that are firmly established in well industrialized countries but that contribute little to the development of the local industrial structure, since the competitive conditions of this structure differ from those of the regions from which these development models were imported. Therefore, this location model can be very useful for decision makers seeking to dissociate the allocation of technological services from any less technical classification criterion. This model could undoubtedly represent an advance in reducing the technological imbalances to which industrialized regions are subject. Many imbalances in these regions have long been known; however, despite the mechanisms that have been applied to reverse them, further efforts to mitigate them are still required. Studies involving the location of technology centers are strongly dependent on the identification of the determining factors of supply and demand for technology. Future research should focus on the identification of cause and effect relationships between the various factors that affect the supply and demand for technological services. This type of research would undoubtedly contribute to improve analyses concerning the location of technology centers.

487

Choosing Locations for Technology and Innovation Support Centers

REFERENCES Andersen, B., Honoré, J., Jorno, P., Leppävuori, E., & Storvik, K. (2009). A step beyond: International evaluation of the GTS institute system in Denmark. Stockholm, Sweden: Ministry of Science, Technology and Innovation. Audretsch, D. B. (1998). Agglomeration and the location of innovative activity. Oxford Review of Economic Policy, 14, 18–29. doi:10.1093/ oxrep/14.2.18

Gordon, I. R., & McCann, P. (2000). Industrial clusters: Complexes, agglomeration and/or social networks? Urban Studies (Edinburgh, Scotland), 37, 513–532. doi:10.1080/0042098002096 Granemann, S. R., Tedesco, G. M. I., & Candal, P. C. (2008). Seleção de modais para o transporte de derivados de petróleo utilizando o método AHP. Anais do Congresso Panamericano de Engenharia de Trânsito e Transporte PANAM, Cartagena das Índias, Colômbia, 15 (in Portuguese).

Beise, M., & Stahl, H. (1999). Public research and industrial innovations in German. Research Policy, 28, 397–422. doi:10.1016/S00487333(98)00126-7

Jaffe, A. B., Trajtenberg, M., & Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. The Quarterly Journal of Economics, 108, 577–598. doi:10.2307/2118401

Brazilian Institute of Geography and Statistics (IBGE). (n.d.). Annual industrial survey. Retrieved March 10, 2007, from http://www.ibge. gov.br/ home/ estatistica/economia/ industria/ pia/ empresas/2008/ defaultempresa.shtm.

Kakuta, S. M., & Luz, G. M. S. (2001). Estudo da oferta e demanda por serviços tecnológicos. Instituto de Tecnologia do Paraná e Confederação Nacional da Indústria. (in Portuguese)

Brazilian Network of Technology (MCT). (2007). Innovation portal. Retrieved February 20, 2007, from www.portalinovacao.mct.gov.br. Breschi, S., & Malerba, F. (2001). The geography of innovation and economic clustering: Some introductory notes. Industrial and Corporate Change, 10, 817–833. doi:10.1093/icc/10.4.817 COTEC. (2003). Las infraestructuras de provisión de tecnología a las empresas. Madrid, Spain: Fundación COTEC. Council for Scientific and Technological Development (CNPq). (2004). Tabular plan. Retrieved February 13, 2007, from http://dgp.cnpq.br/ planotabular Feller, I., Ailes, C. P., & Roessner, J. D. (2002). Impacts of research universities on technological innovation in industry: Evidence from engineering research centers. Research Policy, 31, 457–474. doi:10.1016/S0048-7333(01)00119-6

488

Krugman, P., Fujita, M., & Vernables, A. J. (1999). The spatial economy: Cities, regions and international trade. London, UK: The MIT Press. Ministry of Labor and Employment of Brazil. (2004). Annual record of social information. Retrieved March 10, 2007, from www.mte.gov.br Morosini, P. (2004). Industrial clusters, knowledge integration and performance. World Development, 32, 305–326. doi:10.1016/j.worlddev.2002.12.001 Predohl, A. (1928). The theory of location in its relation to general economics. The Journal of Political Economy, 36, 371–390. doi:10.1086/253950 Quevedo, J. G., & Mas-Verdú, F. (2008). Does only size matter in the use of knowledge intensive services. Small Business Economics, 31, 137–146. doi:10.1007/s11187-007-9090-x Ramos, R. A. R., & Mendes, J. F. G. (2001). Introdução às teorias de localização industrial. Portugal: Universidade do Minho. (in Portuguese)

Choosing Locations for Technology and Innovation Support Centers

Robinson, D. K. R., Rip, A., & Mangematin, V. (2007). Technological agglomeration and the emergence of clusters and networks in nanotechnology. Research Policy, 36, 871–879. doi:10.1016/j.respol.2007.02.003 Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48, 9–26. doi:10.1016/0377-2217(90)90057-I Salerno, M. S., & Kubota, L. C. (2008). Estado e inovação. In Negri, J. A., & Kubota, L. C. (Eds.), Políticas de Incentivo à Inovação no Brasil (pp. 16–66). Brasilía: IPEA. (in Portuguese) Samuelson, P. A. (1937). A note on measurement of utility. The Review of Economic Studies, 4, 155–161. doi:10.2307/2967612 Secretariat of Foreign Trade (SECEX). (n.d.). Alice Web. Retrieved March 05, 2007, aliceweb. desenvolvimento.gov.br/ Smallbone, D., North, D., & Leigh, R. (1993). The use of external assistance by mature SMEs in the UK: Some policy implications. Entrepreneurship and Regional Development, 5, 279–295. doi:10.1080/08985629300000017 Teruya, D. Y. (1999). Os fatores de concentração industrial de empresas de alta tecnologia. Mexico: V Seminario Internacional de la RII. (in Portuguese) Theter, B. (2003). The sources and aims of innovation in services: Variety between and within sectors. Economics of Innovation and New Technology, 16, 481–506. doi:10.1080/1043859022000029221 World Bank. (2008). Technology diffusion in the developing world. Global Economic Prospects. Wren, C., & Storey, D. (2002). Evaluating the effect of soft business support upon small firm performance. Oxford Economic Papers, 54, 334–365. doi:10.1093/oep/54.2.334

Zucker, L. G., Darby, M. R., & Armstrong, J. (1998). Geographically localized knowledge: Spillovers or markets? Economic Inquiry, 36, 65–86. doi:10.1111/j.1465-7295.1998.tb01696.x Zucker, L. G., Darby, M. R., & Armstrong, J. (2002). Commercializing knowledge: University science, knowledge capture, and firm performance in biotechnology. Management Science, 48, 138–153. doi:10.1287/mnsc.48.1.138.14274

KEY TERMS AND DEFINITIONS Analytic Hierarchy Process (AHP): A type of multicriteria analysis that arranges the important elements of a problem within a hierarchical structure similar to a genealogical tree. Location Theory: Approach that is concerned with the geographic location of economic activity. It has become an integral part of economic geography, regional science, and spatial economics. Multicriteria Analysis: A technique to aid or support people and organizations in making decisions using multiple criteria. Technological Demand: It involves activities related to exports, number of employees, number of employees with high education, number of local units and industrial transformation value. Technological Services: Activities that involve investigation, monitoring and technological evaluation, including conformity assessment (calibration, testing, analysis, certification). The objective is to aid institutes in overcoming technological obstacles to market access. Technological Supply: It involves activities related to human resources indicator, publication indicator and research institutes and universities Technology and Innovation Support Centers (TISCs): Institutes that supply technical and specialized knowledge in support of innovation processes.

489

Section 6

Marketing and Innovation

491

Chapter 26

Taxonomy of Marketing Core Competencies for Innovation Eric Viardot EADA Business School, Spain

ABSTRACT This chapter argues there is a lack of taxonomy of the various marketing capabilities that are necessary to achieve the market success of innovation. It tries to fill this gap by proposing a model that subsumes two classes of Marketing Core Competencies (MCC) for successful innovative companies. The first category of core competencies is related to a superior ability of the firm to identify and to connect the actual market needs with the innovation during the preparation of the new product launching phase. Once the innovation is on the market, a second group of core competencies is associated with the capacity of the firm to ease the customers’ tensions in order to facilitate the acceptance of the innovation and turn it into a market success through adoption and diffusion. In conclusion, the chapter underlines the importance of the place of these two categories of Marketing Core Competencies (MCC) in innovative firms.

INTRODUCTION Large is the number of firms that have introduced an innovation with an original concept or a superior technology but failed to establish it on the markets. This is because innovation is more than invention. It is taking a new idea and developing it into a solution which satisfies a specific human DOI: 10.4018/978-1-61350-165-8.ch026

need in a new and cost-effective way so that it generates customer value and a positive business impact (Viardot, 2004). Innovations can be incremental or disruptive (Bower & Christensen, 1995). Incremental innovations improve the performance of established goods and services along the dimension that mainstream customers in major markets have already valued. Examples include continual development of faster microprocessors, flatter

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Taxonomy of Marketing Core Competencies for Innovation

screen for computers or higher -resolution medical scanning devices or Short Message Service (SMS) for cellular phones. Disruptive innovations offer a different, original and often untested solution to a larger category of needs (Christensen & Raynor, 2003).They are diffused throughout the economy like electricity, transistors, or machine tools in the past and computers, networks, and robots nowadays. They often provide the basis for the emergence of new industries that create major new markets. For instance, once computers were introduced and accepted, it made sense to expand their power, offer new application software, and connect them. Once they were connected, online services and electronic commerce naturally made their way into the economy and consumers’ behavior. Similarly, today some very promising technologies could open new markets such as 3D mobile phones, engineered stem cells, solar fuel, green concrete, cloud programming… as identified by MIT in its 2009 special report on emergent technology (www.technologyreview. com/specialreports). Many studies have been carried out on the new product adoption process, following the leading research by Rogers (1983) which defines the diffusion of innovation as a process that communicates innovation through certain channels over time among the members of a social system. These studies show that not all customers, individuals or organizations, react to innovations in identical ways, mostly because of their degree of involvement with technology (Latour & Alii, 2002). Some consumers will buy new products immediately, while others will buy them much later as they are uncomfortable with innovations, especially radical ones because they are difficult to understand, untested, or perceived as one-off which will pass quickly. The consumers are going to wait for the next generation that may provide them with a solid benefit. But the next generation of products will never happen if the current generation is discontinued. It comes down to marketing to explain this innovation, so that the people can make an educated choice. What is true for consumers is also 492

true for organizations. Many managers fret about innovative solutions and use various strategies to reduce risks in purchasing an innovative product. They try to assess the balance on the risk/return relationship of such investment much more than considering the novelty of a technology (Meldrum & Millman, 1991). In line with the resource-based theory, marketing can be defined as a continuous set of skills and competencies of a firm that constitutes a better value than its competitors (Vargo & Lusch, 2004). Consequently, the specificities of product innovation are driving the building of new capabilities for innovative companies. Although some papers are discussing the role of some specific Marketing Core Competencies (MCC) for innovations (Story & alii, 2009, Reid & de Brentani, 2010), there is not a taxonomy of the various marketing skills that are necessary to achieve the market success of innovation. This chapter tries to fill this gap with a descriptive research based on literature review. As illustrated in Figure 1, the chapter proposes a model for successful innovative companies by subsuming two sets of specific MCC that are taking place at two different phases in the innovation process; this one is considered as a complex set of communication paths over which knowledge is transferred internally and externally between the organization, the science base and the marketplace (Trott, 2008). The first category of core competencies is related to a superior ability of the firm to connect the actual markets needs with the innovation during the preparation of the launching phase of the new product. This group is composed of three different Marketing Core Competencies (MCC). Once the innovation is on the market, a second group of three other MCC is associated with the capacity of the marketing organization to ease customers’ tensions in order to facilitate the innovation´s acceptance and to turn it into a market success. In that chapter we define a marketing organization as one organization which is specialized in marketing, and/or as a unit of an organization/firm, and/or as an Organization Creative Area.

Taxonomy of Marketing Core Competencies for Innovation

Figure 1. Marketing core competencies (MCC) in the innovation process

THE MARKETING CORE COMPETENCIES BEFORE THE INTRODUCTION PHASE OF AN INNOVATION In the groundwork of the introduction phase of an innovation, three specific competencies are developed by the marketing organization. The first one is the capacity to help the firm’s top management to assess the market potential of an innovation. The second one is the particular skill to segment the potential markets for the innovation, either with a comprehensive study of the potential customers or with a proactive vision of the future market. The third core competence is the ability to define the innovation´s positioning for its introduction on the market.

Marketing Core Competence 1: Assessing the Market Potential of an Innovation Before considering the introduction of an innovation to the market, the primary step is to evaluate its business potential (Easingwood & Koustelos, 2000). This requires a situation analysis in order to

identify the opportunities and threats in the market as well as to evaluate the possible market demand. The situation analysis starts with an evaluation of the various elements of the firm´s environment (Technological, Economic, Sociological, Ecological, Ethical, Political and Legal forces) which may represent some threats or opportunities vis-à-vis the innovation considered. Regarding innovations the technological forces are obviously always important as many innovations are technology-driven. This is even more important in the case of radical innovation and radical new products where companies can be blindsided when they tend to underestimate the potential of a breakthrough innovation or when they listen too loosely to their best customers and invest only in incremental innovation to lose ground ultimately (Christensen, 1997). However, it would be an error not to take into consideration the other forces (Talke & Salom, 2009). Most specifically, many firms tend to misjudge the sociological constraints which may slow the adoption process of an innovation. The political and legal dimensions are also extremely important as some innovations may not be accepted by a local government, such as in China when

493

Taxonomy of Marketing Core Competencies for Innovation

Google had to agree that all search results with contents viewed as objectionable by the government should be censored (O´Rourke & Alii, 2007) In the case of innovations, government often acts as a market raiser, through governmental research programs such as Eureka in Europe or HPCCI (High Performance Computing and Communications Initiative) in the United States. Those programs are funded and managed by various governmental agencies which can introduce much competitive bias by championing national suppliers. Through IP and patents regulations, local government can also impede or reduce the adoption of an innovation. For example, in China the government is willing to promote more eco-friendly cars and energies in order to reduce the massive air pollution in large cities. This has provided a boost for BYD one of China’s biggest producers of batteries for cell phones which is now a fast-growing maker of green cars and solar panels. (Arndt & Einhorn, 2010). Governmental constraints can especially be felt by the importance of standards in international contracts. For example, the European Union’s taxation on the broadcasting of television programs by the D2 Mac satellite killed the market of D-Mac decoders. On the other side, when the French, Italian and German governments signed an agreement for the development of GSM (Global System for Mobile communication) as a common standard for the development of an effective pan-European solution to mobile communications, they paved the way for the meteoric growth of the mobile telecommunication industry in the 90’s in Europe (Seo & Hashem Sherif, 2009). If the government has an influence on the competitive environment, one should note that its force varies according to the size and the characteristics of the firms. The power of any governmental organization can also be affected by the political lobbying of large firms or the alliance of small ones. Marketers must also provide an analysis of the potential competition for an innovation in

494

order to assess its market potential. For example, disruptive innovations tend to create new markets and usually take root on the weakest segments of large companies which are already in the markets. While incumbents tend to stick with sustaining innovations for their traditional customers, challenging companies will take on competitors with disruptive innovations. For instance, the Chinese HTC has long been the manufacturer of unbranded devices bearing the logos of wireless giants such as Verizon, T-Mobile, Sprint Nextel, or NTT DoCoMo. But HTC was the first to adopt the open-platform of Google´s Android operating system for smartphones. Android lowers the entry barrier for newcomers because it takes a lot of the innovation burden off of the hardware companies. HTC built the first phone powered by Google’s Android operating system, for T-Mobile, in 2008 and has launched its own line of smartphones with great success. Regarding the competitive analysis for an incoming innovation, the traditional five forces framework created at Harvard University and popularized by Michael E. Porter (1985), need to be adapted slightly. Indeed, besides the rivalry among existing competitors, the threat of both substitute products and new entrants, the bargaining power of suppliers and of buyers, it is important to consider the relative influence of the “complementors”. They can be defined as the firms that provide complementary product or services which are adding value to the product innovation (Adner & Kapoor, 2010) For example, the functioning of ERP or CRM software—a radical innovation for many organizations trying to implement and to adapt it—requires the help of specialized consulting firms such as Accenture, Cap Gemini Ernst &Young and hundreds of smaller ones. Similarly the value of an innovative operating system depends on the number of application software available on it. Similarly software developers are “complementors” of Windows, Linux, Symbian or Android. Comple-

Taxonomy of Marketing Core Competencies for Innovation

mentors can have some significant influence in expanding the market. For instance, a recent work has shown that offering greater levels of access to independent hardware developer firms produces up to a fivefold acceleration in the rate of new handheld device development (Boudreau, 2010). Finally to complete the environmental and competitive analysis, Marketers have to provide an estimate level of market demand. Demands are desires that can materialize thanks to money and some purchasing power. For instance, many consumers want broadband with unlimited Internet access connected to a sophisticated home cinema system. Only a few are able and willing to buy that. In the case of incremental innovations, marketers can always go and interview customers who are already using this category of product. They can rely on several tools such as, ethnographic surveys, concept tests and prototype tests, expert opinions, sample groups, test markets, etc. For instance, Nokia combined some fundamental ethnographic with long-term user research in China, India, and Nepal to analyze how illiterate people live in a world full of numbers and letters (Katz, 2003). As a consequence, Nokia created an innovative “iconic” menu that can be navigated only by images. Furthermore, the growing percentage of the population having online access in western and emergent countries, coupled with the unlimited capacity of the Internet to influence lifestyles, has turned the Web into a tool for understanding and anticipating consumer needs and to gauge consumer thinking and behavior (Hardey, 2009). But a precise evaluation of demand is not easy to accomplish when the innovation is radical and markets are exploding. Thus, estimating the overall demand of an innovation is never straightforward because markets are in a constant state of flux and because the goal is to create markets rather than battle for market share on existing markets.

Marketing Core Competence 2: Segmenting the Potential Markets for the Innovation If the conclusion of the situation analysis indicates a potential demand for an innovation, the next step is to segment the market because, in today´s environment, an innovation cannot reach everyone everywhere at every time. The time when one product sufficed to satisfy demand is over. Customers have become more demanding and more informed, and competition drives companies to differentiate themselves. Groups (segments) of customers with similar wants desires, buying behavior, or some other significant characteristic needs must be identified. Consequently, successful innovative firms are very much aware that they have to determine the most important customers and what they value (Thomke & Von Hippel, 2002) in a given innovation. Those are the necessary conditions to ensure that the innovation corresponds well to customer wants and expectations. To successfully market an innovation, there exist two approaches: demand-driven marketing for incremental innovations that customers are awaiting and vision-driven marketing for radical innovations. The former approach is based upon market knowledge, whereas the latter is based upon the views of the innovator and requires some kind of market pro-activeness (Sandberg, 2002). The dichotomy between market-driven marketing and vision-driven marketing leads to two different segmentation methods. The market-demand approach breaks down the market into different segments, the needs of which are analyzed before defining a product. The market-vision (or marketsupply) approach identifies a certain number of future customers who will then serve to construct the segments by extrapolation. A large number of incremental innovations happened because of customer demand in response to an expressed or latent need. Many of these

495

Taxonomy of Marketing Core Competencies for Innovation

innovations only show variations of an original product with simply some improvements that were requested by the customers. For instance, microcomputers are becoming more and more compact, portable, and powerful; but they have not really changed since 1981. For these demanddriven innovations, segmentation methods that are developed and frequently used in marketing can generally be used. They are based on the selection of segmentation criteria to break down the total market according to the characteristics and the behavior of consumers or industrial customers, in order to regroup them in different segments that are as heterogeneous as possible in terms of needs and expectations. Nevertheless many innovations are not pulled by the market but they are pushed by the ideas of companies or individuals, as more than 80% of all researchers of all time are still alive and working today. The market for a new radical innovation is more difficult to understand as it is coming from a research laboratory or a creative genius. Nevertheless, the intrinsic value of an invention does not necessary lead to a business because the evaluation of the innovation by customers is often a big question mark (Veryzer, 1998). The reason is that radical innovation frequently brings new level of functionality that the customers may not figure out immediately; also such innovation often implies drastic changes in consumption patterns (O’Connor, 1998). Anticipating the changes that a radical innovation will bring to the market requires foresight (Hamel & Prahalad, 1994) and vision. Sony’s founder, Akio Morita, always contended that “the public does not know what is possible, but we do…” (Rosenbloom & Cusumano, 1987). Consequently, the traditional methods that are used to identify particular market segments must be adjusted. To determine the potential customers to whom these radical innovations may be directed, marketers must anticipate and understand the needs that these innovations satisfy as

496

well as the products that will materialize them. They have to figure out, through brainstorming and creativity techniques, the potential customers who may find some value in an innovation whose existence they do not even suspect today. A very effective approach is to target lead users, companies, organizations or consumers (Pitta & Alii, 1996) that have needs that go far ahead of the average users and who may even have started to develop a prototype (Von Hippel & Alii, 2000). It is hard for would-be customers to identify the needs that a disruptive innovation may fulfill, especially if this innovation is presented under the form of a concept (Mullins & Sutherland, 1998). Thus the marketing organization should select key potential customers who are interested in the product innovation and give them the opportunity to test various prototypes (Beta testing) (Dolan & Matthews,1993).The best way to recognize their needs is to partner with the customers (Dunn & Thomas, 1994) and have them test a prototype (Leonard & Rayport, 1997). Actually, it has been shown that when individuals play a part in the design of the technology their involvement increases (Barki & Hartwick,1989) and becomes more positive adding to the need and value of the technology (Guimaraes & Alii, 1999). The ultimate goal of a Beta-testing is to evaluate how well the prototype fits the customers´ needs (Lilien & Alii, 2002). Accordingly and in parallel with R& D, the marketing organization monitors the beta tests. Furthermore, by working closely with test customers, the marketers may gain not only a better knowledge of their needs but also some insights into the price the market will be ready to accept, as well as some ideas about the most efficient way to advertise and distribute the future product. Companies like 3M or Google have developed an unparalleled core competence in continually testing new ideas with their current and prospective customers. The Post-it Picture Paper—that let people stick their photos to a wall on display—or the “mash-ups”

Taxonomy of Marketing Core Competencies for Innovation

which combines Google’s map with interesting location websites are some of the recent fruits of their ability to openly interact with their customers and stakeholders.

Marketing Core Competence 3: Positioning the Offer for the Target Segment Among all the skills which have a strong competitive advantage, innovation positioning is probably the most difficult to achieve. It starts with the marketing organization´s capacity to select, among the various market segments identified, the best customers target to aim at when introducing the innovation on the market (Guiltinan, 1999). This is crucial because all customers’ segments do not share the same importance. The first element of selection is the level of acceptance of the innovation by the customers belonging to the segment (Easingwood & Lunn, 1992). But marketers have to also take into consideration other strategic elements such as • •

•

the evaluation of the segments´ potential— in terms of attainable volume and profit, the segments’ accessibility according to the company’s resources, their strategic significance for the company’s mission, the position of competitors, and the level entry barriers, in particular, administrative and governmental stumbling blocks.

Sometimes, the high introductory price of an innovation, due to the need to optimize R&D costs and to the lack of an economy of scale at the beginning of the manufacturing process, immediately determines the choice of segments with a high purchasing power. Within the selected segments, marketers define the most significant customers who will be targeted first. They have two choices: either making a concentrated marketing or making a differentiated marketing. Concentrated marketing selects

only one or a very few number segments. Smaller companies often prefer having a smaller number of niches rather than having a small market share of a large market. Differentiated marketing selects several segments with marketing methods adapted to each segment. Large high-tech companies such as HP, SAP or Orange, for instance, address a large, diverse group of users in different sectors (banking, insurance, industrial) with varied financial resources, ranging from small companies to large multinationals. Each segment has its own type of product, price, place, and promotion that definitely require the involvement of more resources. A concentrated marketing is less expensive but riskier than marketing that is divided over several segments. The choice also depends upon technical possibilities and the company’s capacity to quickly put a quality product with a truly competitive advantage on the market. The choice depends as well upon the company’s overall strategy. For instance, some companies wish to postpone entering a market segment until the pioneers have shown their existence. Finally, on each selected market segment, comes the “positioning” of the innovation in order to ensure that it is well perceived, identified, and recognized by the customers of the key selected segments. Positioning is the creation of the innovation’s perceived image in customers’ minds. Positioning is the ultimate step in differentiating between existing and would-be competitors. The positioning reflects the innovation´s value for the customer and its main competitive advantage. Usually, the innovation provides a very high value due to its novelty (differentiation) or a value equal to more traditional solutions but at lower cost (cost advantage). Novelty is very obvious in the case of an innovation. In consumer electronics, Samsung has successfully applied the fresh fish “sashimi” approach: it markets the most sophisticated products ahead of the competition and charges premium prices before the product is no longer fresh and the competition is there (Xuefeng, 2009). But the rise of developing economies has

497

Taxonomy of Marketing Core Competencies for Innovation

seen the coming of “low cost” innovations because of the lower purchasing power of their customers (Prahalad, 2002). Today, innovative Chinese or Indian companies are coming up with new products and services that are dramatically cheaper than their Western equivalents such as $300 computers, and $30 mobile phones that provide nationwide service for less than 2 cents a minute. A good positioning statement should be able to change or even reverse the mindset of customers (Jaworski & Alii, 2000). However, the positioning of an innovation, especially a radical one is always difficult. This is because customers often have difficulties understanding how a new radical product can be an improvement, especially as long as they have not experienced the product nor figured out how the product or service will meet their need. This makes the communication of the benefits even more indispensable. Additionally, customers often have difficulties distinguishing between the best and the rest within the large number of frequent new product announcements Once the positioning is defined, it is translated into the marketing mix of the innovation (i.e., the design and the associated services of the product, the distribution channels, the communication campaign, and the price). Then the innovation is ready to be launched.

ing the most effective use of the latest innovations in the marketing tools and techniques to engage with the largest number of potential customers in order to enlarge the market.

THE MARKETING CORE COMPETENCIES AFTER THE LAUCH OF AN INNOVATION

•

When the innovation has been launched on the market, the role of Marketing is to facilitate its adoption rate in order to accelerate the growth of its market share. This requires the activation of a new set of skills and competencies. The first skill is the capacity to reach new customers beyond the original target market. The second competence is the ability to leverage the brand equity of an innovation to accelerate its market penetration. Finally, the third capability is the talent for mak-

498

Marketing Core Competence 4: Moving Beyond the Initial Category of Customers Once the innovation has reached the initial category of customers, marketing has to shift the attention to other segments that are getting more attracted by an innovation which is no longer ground-breaking (Moore & McKenna, 1999). Building on different adoption and diffusion models, one can distinguish between six classes of customers: the Innovators, the Forerunners, the Mainstream users, the Followers, the Traditionalists, and the Rebels. •

•

Innovators usually have an enduring involvement based on an interest or arousal for a given product on a day to day basis (Richens & Block, 1986). Actually some researcher argue that over time technological innovation can encourage a psychological addiction to high technology for some category of users, either at home or in the work environment (LaTour & Roberts,1992). Forerunners often are respected opinion leaders who are more careful than innovators. They consider the ownership of a high tech product mostly as a status symbol to assert their difference with the rest of the society. Mainstream users will purchase a product not because it is innovative or different but because it fulfills a need, such as saving time or money, being more practical, or more reliable than the existing solution. They crave for references and testimonials from actual customers. They try to minimize the risk and usually go for the lead-

Taxonomy of Marketing Core Competencies for Innovation

•

•

•

er, boosting the external network effects (Shapiro &Varian, 1999). Followers go along with the Mainstream users but much later. They are under the influence of the incapacitating FUD (Fear, Uncertainty, and Doubt) factors. Like Saint Thomas, they need to touch and see the solution functioning elsewhere –either at relatives or friends’ houses for consumers and customers or competitors’ locations for businesses- before thinking to purchase it. Innovations often make those customers nervous and they normally look for fully packaged and easy-to-use products. Traditionalists are skeptics who do not buy a product until it has become part of tradition. They are technology averse and will buy this category of product only when they do not have any other choices. Finally, the Rebels will always reject a product because of its very nature. Such an allergy to innovation may be driven by cultural or religious reasons like in the case of the well-known Amish in the US. In that case, the numbers are not important. But sometimes, the rejection of an innovation maybe based on security or ethical reasons which may create a significant number of rebels such as in the case of genetically modified organisms protested by a large number of European consumers.

Less than one innovation out of ten is making it on the market (Clancy & Stone, 2005) because usually companies cannot expand beyond those the two first categories of customers, namely the Innovators and the Forerunners, who are always enticed by an innovation. Many firms have difficulties to cross the rift between forerunners and mainstream users. The real marketing challenge is there. Innovators and Forerunners need to be acquired; therefore they are a necessary condition to succeed on the market, but not a sufficient one.

As a consequence, the market penetration of an innovative new product can be accelerated by informing and educating Mainstream users and Followers so that they will know the product, be able to measure its superiority over other existing products, and describe its benefits to other people. But studies show that the more complex an innovation is, the more time it will take for the innovative product to be accepted (Easingwood & Beard, 1989). For any new product, the more important the extensive retraining required, the higher the risk to be rejected because of the high switching costs (Pae & Hyun, 2002). Mainstream users and Followers usually want their product/ usage skills that they have developed with one product, to be transferable across to another original product. If it is not the case, they may decide not to learn how to use the new product (Alba & Hutchinson, 1987). A classic example is the QWERTY typewriter keyboard that has persisted as a standard for years, despite the availability of superior alternatives.

Marketing Core Competence 5: Leveraging the Brand Equity Some innovation-driven companies have managed to develop a specific competence in leveraging their brand equity in order to increase the penetration of their new products or services (Halliday & Trott, 2010). A commonly accepted definition of brand equity, an off balance-sheet resource, is the value added by the brand name to a product (Farquhar, 1999). This added value can be defined as an increase in awareness, positive associations, perceived quality and loyalty from the customers (Aaker, 1991). Leveraging the various components of the brand equity provides an effective way to defer some of the restraints which inhibit customers to adopt a new product or service (Temporal & Lee, 2000; Corkindale & Belder, 2009). First, when an innovation is unknown, some would-be customers are not even aware that such a product is available

499

Taxonomy of Marketing Core Competencies for Innovation

on the market. Additionally, innovation tends to worry many customers or external parties (Boyd and Mason, 1999) for different reasons. Some others are afraid that the innovation will be difficult to learn or will not work. Others consider that the quality is an issued since the innovation has not been tested long enough on the market. Others believe that the innovation will become obsolete quickly. All are always postponing their decision to adopt it. Many consumers view radical product innovations as risky purchases (Gregan-Paxton & Roedder, 1997), but this is also true for organizations. They choose a company they can trust and that they know will be around for a sufficient length of time to guarantee the solution´s durability. A qualitative survey of 50 marketing directors of innovative high tech firms has shown that, when considering the relative importance of the purchasing factors for an innovative product, the confidence in the vendor is more important than the technology used and has the same weight as the price of the product (Viardot, 2004). Consequently, managing efficiently the brand equity of an innovation helps to reassure individuals or industrial buyers. A strong brand facilitates the identification of the innovation while attaching a quality image and a personality that bonds with the customers and facilitates their loyalty (Urde, 1999). This was the strength of IBM in the computer industry of the 1970s, DEC in the 80´s, Microsoft in the 90´s, and Dell during the first half of this decade. While brand equity can increase the value of an innovation, researches have shown that product innovation can inversely have a significant, positive effect on brand equity (Aaker, 1996) because it can create differentiation, expand usage contexts, prevent competitors and enlarge the personality of the brand. For instance, Google is perceived as a clean, friendly but credible path to accessing the tremendous wealth of the Internet. Cisco’s image is associated with being a visionary and an expert in Internet telecommunication as well

500

as a partner with its clients. And the Apple brand personality is about lifestyle, imagination, innovation, passion, and aspirations. It also suggests also “power-to-the-people” through innovation thanks to simplicity and the removal of complexity from people’s lives (www.marketingminds, 2010). More specifically, significant product innovations may be particularly useful for attaining drastic improvements in brand equity over a shorter period when they are meaningful to consumers (Sriram & Alii, 2007). Ultimately, brands have to innovate to maintain their relevance and their customer base. Figure 2 illustrates this dual relationship which may generate a very positive feedback loop as brand equity increases market penetration of the innovation which in turn enhances the brand equity. The process starts with the triggering of brand equity through advertising as the marketing literature suggests that advertising can affect brand equity (Keller 1998). But the building of a strong brand image for an innovation does not always require big advertising budgets. Some highly successful companies have managed to achieve recognition through creativity and publicity like Facebook or Google, which have achieved this position mostly through word-of-mouth and quality. E-bay, Amazon, or Yahoo have also received top-of-mind recognition on a low advertising budget. Those web based firms have been able to generate “buzz” among “influencers” instead of relying solely on traditional advertising. The excitement and passion they have generated has translated into sales afterwards. In that matter, they just follow the previous generation of successful innovators such as Intel, Microsoft, Compaq, Cisco, and others; these firms were first talked about in the pages of the Wall Street Journal, the Financial Times, Business Week, Forbes and Fortune magazines. Once their brand image was made, they started to spend money in advertising to maintain their image and notoriety. When promoting an innovation, brand equity management is not exclusive to private companies.

Taxonomy of Marketing Core Competencies for Innovation

It has been used very effectively by some alliances to promote an innovation in order to make it a standard. Consider the case of Bluetooth, a short-range networking protocol for connecting all types of digital devices (mobile phone, computer, GPS, etc) or accessing the Internet by wireless signals at short range. In 1998, five companies founded the Bluetooth Special Interest Group (SIG): Ericsson, IBM Corporation, Intel Corporation, Nokia and Toshiba Corporation. Its goal was to promote the development of the new protocol as the standard solution for wireless connections. Very early the decision was made to develop a strong brand so as to communicate with end–consumers in order to accelerate its recognition and to step up its adoption by other industrial companies. From the beginning, Bluetooth has been actively promoted by members of the SIG among the end users. The average brand awareness level in the United States, United Kingdom, Germany, Japan and Taiwan has risen

from 60% in 2004, to 85% in 2009. Such a high level of recognition has pushed many companies to adopt Bluetooth as the standard wireless connection. In 2004, the Bluetooth SIG had 3400 members; today it has more than 10,000 member companies in the telecommunications, computing, automotive, music, apparel, industrial automation and network industries (www.bluetooth.com).

Marketing Core Competence 6: Mastering the Latest Innovative Marketing Tools to Connect with the Markets Finally, in order to enlarge the market for an innovation, the marketing organization has to be able to use the latest innovations in the marketing tools and techniques to engage with the largest number of potential customers. In the very recent years, the most striking innovations are in the Internet and the social networks. Internet has changed

Figure 2. The dual relationship between brand equity and innovation

501

Taxonomy of Marketing Core Competencies for Innovation

the marketing platforms of companies (Chaffey & Alii, 2009). It is a powerful communication tool which allows an instant, interactive and personalized exchange with the customer; it is also a virtual distribution channel; it contributes to create new services around an existing hard product, it permits to receive customers´ feedback very quickly so that they can “co-create” a product with the company. It plays also a leading role in CRM programs as it establishes a vital link with customers… But in the last two years, the Internet has paved the way to an even more important innovation for marketers: the raise of the social networks, most notably MySpace, Facebook, and Twitter (Trusov & Alii, 2009). Building on the needs and desires for intense and constant communications, those networks have managed to aggregate millions of users while altering their daily lives. They now offer a credible, less expensive alternative to massive advertising expenditure when marketers envisage enlarging the market of an innovation. Indeed, the “viral campaigns” are just traditional “word of mouth” campaigns but amplified by the scope and the speed of the Internet and the dynamics of the network structure (Stephen & Toubia, 2010). Twitter, which allows users to “tweet” about anything they wish via posting a message, not exceeding 140 characters, on their account on-line is revolutionizing the way people communicate. It is now incorporated in nearly all cellular phones and some businesses have already used it as a platform to reach its current 190 million users worldwide and still growing very fast. With Tweets and SMS combined with the latest advanced in geo-marketing, marketers are able to leverage the vast potential of the Smartphone as the new vessel for offering product information, updates, special offers, or even specific discounts. As the field of innovation in marketing tools is shifting from the personal computer to the mobile phone (Ratten, 2009), this provides marketers with cheaper and more effective ways to engage with new prospects.

502

CONCLUSION: THE PLACE OF THE MARKETING WITHIN INNOVATION ORIENTED FIRMS As the marketing is one of the Organization´s Creative Areas which contributes to develop core competencies, it is important to consider its place within innovation oriented firms. This is made even more important because numerous innovation failures are the result of a disastrous lack of cooperation between the marketing and R&D areas. Indeed, the rivalry between those two areas can derail the most promising future of innovations as R&D’s people tend to underuse or even ignore the information from the Marketing department (Maltz & Alii, 2001). One of the first basic recipes for success is to foster the collaboration between R&D and marketing, but this is easier said than done (DeLuca & Atuahene-Gima, 2007). One of the main reasons is because of the multiple walls between marketing and R&D, especially cultural that make them two different and separate worlds (Griffin & Hauser, 1996). Marketing professionals usually have a business background, even if it is also good to have a technical background as well. They are trained to combine data and intuition in order to answer general problems and to make profit-oriented business decisions, generally within a short time frame. They talk of markets, product benefits, and perceptual positioning for customers. Conversely, research and development professionals generally have an engineering or sciences background. They are trained to generate and then test hypotheses in order to resolve technical problems and to pro mote scientific development on a long-term basis. They talk in product specifications and performance. All these differences may be frequently intensified by structure (Leonard-Barton, 1992) and by geography when R&D departments are located on an outside campus, while marketers are close to markets or at headquarters. This leads to less interpersonal activity and hardens disparate worlds of thought. However the integration of

Taxonomy of Marketing Core Competencies for Innovation

Figure 3. The core competencies for the successful marketing of product innovations

R&D and marketing is excessively important especially to enforce the effectiveness of new product development (Souder & Sherman, 1998). On one hand, R&D needs marketing’s market vision and guidance for the general direction of research. On the other hand, marketing needs R&D to invent products that correspond to the customer needs it has identified. Some companies have managed to integrate the Marketing and R&D departments to work together in developing and marketing innovative products. Each time it starts the development of a new car, the 200 to 300 project teams´ members are relocated from their various location to the “Forschungs und Innovationszentrum” (Research and Innovation Center) in Munich, Germany, for up to three years. This unique capability allows BMW to facilitate communication and prevent last minute conflicts between R&D and Marketing. It has contributed to BMW the success of its most recent models (Riege, 2007). To conclude this chapter, Figure 3 summarizes the specific marketing core competencies that have been identified in this chapter as some of the key capabilities which have to be developed in order to contribute to the market success of a product innovation and subsequently to the overall profitability of a company. They have been mapped out along a sequential phase in the innovation process mostly for a goal of clarification. They represent

a sequential and logical continuum of independent stages while in reality they are continually interacting with each other. For example, the use of social networks may drive a new segmentation process which then may impact the positioning of the offer and consequently the brand management. This categorization of Marketing Core Competencies (MCC) can be considered as the foundation for constructing an expanded typology where each of the six main core competencies could be broken down into more precise subcompetencies. It could be useful for companies, and educators, who would like to build or to strengthen marketing competencies (Wellman, 2010) in order to increase the market acceptance of their innovative products and to amplify their competitive advantage for achieving superior profitability. Additionally, as this CCM model is theoretically informative but practically untested, this would open a new avenue for future research.

REFERENCES Aaker, D. A. (1991). Managing brand equity. New York, NY: The Free Press. Aaker, D. A. (1996). Building strong brands. New York, NY: The Free Press.

503

Taxonomy of Marketing Core Competencies for Innovation

Adner, R., & Kapoor, R. (2010). Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strategic Management Journal, 31(3), 306–333. doi:10.1002/smj.821 Alba, J. W., & Hutchinson, J. W. (1987). Dimensions of consumer expertise. The Journal of Consumer Research, 13(41), 411–414. doi:10.1086/209080 Arndt, M., & Einhorn, B. (2010). The 50 most innovative companies. Retrieved from http://www. businessweek.com/ magazine/content/ 10_17/ b4175034779697.htm Barki, H., & Hartwick, J. (1989). Rethinking the concept of user involvement. Management Information Systems Quarterly, 13(1), 53–63. doi:10.2307/248700 Boudreau, K. (2010). Open platform strategies and innovation: Granting access vs. devolving control. Management Science, 56(10), 1849–1872. doi:10.1287/mnsc.1100.1215 Bower, J. L., & Christensen, C. M. (1995). Disruptive technologies: Catching the wave. Harvard Business Review, 73(1), 43–53. Boyd, T. C., & Mason, C. (1999). The link between the attractiveness of extra-brand attributes and the adoption of innovations. Journal of the Academy of Marketing Science, 27(3), 306–319. doi:10.1177/0092070399273002 Businessweek.com. (n.d.). Retrieved from http://www.businessweek.com/magazine /content/06_17/b3981401.htm Chaffey, D., Ellis-Chadwick, F., Johnston, K., & Mayer, R. (2009) Internet marketing: Strategy, implementation and practice (4th Ed.) Harlow, UK: Financial Times Prentice Hall

504

Christensen, C. M. (1997). The innovator’s dilemna: When new technologies cause great firms to fall. Boston, MA: Harvard Business School Press. Christensen, C. M., Raynor, M. E., & Anthony, S. D. (2003). Six keys to creating new-growth businesses. Harvard Management Update, 8(1), 3–7. Clancy, K. J., & Stone, R. (2005). Don’t blame the metrics. Harvard Business Review, 83(6), 26–28. Corkindale, D., & Belder, M. (2009). Corporate brand reputation and the adoption of innovations. Journal of Product and Brand Management, 18(4), 242–250. doi:10.1108/10610420910972765 DeLuca, L. M., & Atuahene-Gima, K. (2007). Market knowledge dimensions and cross-functional collaboration: Examining the different routes to product innovation performance. Journal of Marketing, 71(1), 95–112. doi:10.1509/jmkg.71.1.95 Dolan, R. J., & Matthews, J. (1993). Maximizing the utility of customer product testing: Beta design management. Journal of Product Innovation Management, 10, 318–330. doi:10.1016/07376782(93)90074-Z Dunn, D., & Thomas, C. (1994). Partnering with customers. Journal of Business and Industrial Marketing, 9(1), 34–40. doi:10.1108/08858629410053461 Easingwood, C., & Beard, C. (1989). High technology launch strategies in the UK. Industrial Marketing Management, 18, 125–138. doi:10.1016/0019-8501(89)90029-1 Easingwood, C., & Koustelos, A. (2000). Marketing high technology: Preparation, targeting, positioning, execution. Business Horizons, 43(3), 27–34. doi:10.1016/S0007-6813(00)89198-3 Easingwood, C., & Lunn, S. (1992). Diffusion paths in a high-tech environment: Cluster commonalities. R & D Management, 22(1), 69–80. doi:10.1111/j.1467-9310.1992.tb00789.x

Taxonomy of Marketing Core Competencies for Innovation

Farquhar, P. (1989). Managing brand equity. Marketing Research, 1, 24–33.

Keller, K. L. (1998). Strategic brand management. Upper Saddle River, NJ: Prentice Hall.

Gregan-Paxton, J., & Roedder, J. D. (1997). Consumer learning by analogy: A model of internal knowledge transfer. The Journal of Consumer Research, 24(3), 266–284. doi:10.1086/209509

LaTour, M. S., Hanna, J. B., Miller, M. D., & Pitts, R. E. (2002). Consumer involvement with personal computer technology: A multi-sample analysis. American Business Review, 20(2), 1–12.

Griffin, G. A., & Hauser, J. R. (1996). Integrating R&D Mmarketing. Journal of Product Innovation Management, 13(3), 191–215. doi:10.1111/15405885.1330191

LaTour, M. S., & Roberts, S. D. (1992). Cultural anchoring product diffusion. Journal of Consumer Marketing, 9(4), 29–34. doi:10.1108/07363769210037060

Guiltinan, J. P. (1999). Launch strategy, launch tactics, demand outcomes. Journal of Product Innovation Management, 16(6), 509–529. doi:10.1016/S0737-6782(99)00013-2

Leonard, D., & Rayport, J. F. (1997). Spark innovation through empathic design. Harvard Business Review, 75(6), 102–115.

Guimaraes, T., Gupta, Y. P., & Rainer, R. K. Jr. (1999). Empirically testing the relationship between end-user computing problems information center success factors. Decision Sciences, 30(2), 393–413. doi:10.1111/j.1540-5915.1999. tb01615.x Halliday, S. V., & Trott, P. (2010). Relational, interactive service innovation: building branding competence. Marketing Theory, 10(2), 144–160. doi:10.1177/1470593110366901 Hamel, G., & Prahalad, C. K. (1994). Competing for the future. Harvard Business Review, 72(4), 122–129. Hardey, M. (2009). The social context of online market research: An introduction to the sociability of social media. International Journal of Market Research, 51(4,) 562-564.

Leonard-Barton, D. (1992). Core capabilities core rigidities: A paradox in managing new product development. Strategic Management Journal, 13(5), 111–126. doi:10.1002/smj.4250131009 Lilien, G. L., Morrison, P. D., Searls, K., Sonnack, M., & Von Hippel, E. (2002). Performance assessment of the lead user idea-generation process for new product development. Management Science, 48(8), 1042–1060. doi:10.1287/ mnsc.48.8.1042.171 Maltz, E., Souder, W. E., & Kumar, A. (2001). Influencing R&D/marketing integration: The use of market information by R&D managers. Journal of Business Research, 52(1), 69–83. doi:10.1016/ S0148-2963(99)00096-X Marketingminds.com (n.d.). Retrieved from Marketingminds.com.au/branding /apple_branding_strategy.html

Jaworski, B., Kohli, A. K., & Shay, A. (2000). Market-driven versus driving markets. Journal of the Academy of Marketing Science, 28(1), 45–54. doi:10.1177/0092070300281005

Meldrum, M. J., & Millman, A. F. (1991). 10 risks in marketing high-technology products. Industrial Marketing Management, 20(1), 43–51. doi:10.1016/0019-8501(91)90040-M

Katz, J. E. (2003). Machines that become us: The social context of personal communication technology. New Brunswick, NJ: Transaction Publishers.

Moore, G. A., & McKenna, R. (1999). Crossing the chasm: Marketing selling high-tech products to mainstream customers. New York, NY: Harper Business.

505

Taxonomy of Marketing Core Competencies for Innovation

Mullins, J. W., & Sutherland, D. J. (1998). New product development in rapidly changing markets: an exploratory study. Journal of Product Innovation Management, 15(3), 224–236. doi:10.1016/ S0737-6782(97)00081-7 O’Connor, G. C. (1998). Market learning and radical innovation: A cross case comparison of eight radical innovation projects. Journal of Product Innovation Management, 15(2), 151–166. doi:10.1016/S0737-6782(97)00078-7 O’Rourke, J. S. IV, Brynn, H., & Ogilvy, A. (2007). Google in China: Government censorship and corporate reputation. The Journal of Business Strategy, 28(3), 12–22. doi:10.1108/02756660710746229 Pae, J. H., & Hyun, J. S. (2002). The impact of technology advancement strategies on consumers’ patronage decisions. Journal of Product Innovation Management, 19(5), 375–384. doi:10.1016/ S0737-6782(02)00154-6 Pitta, D. A., Franzak, F., & Prevel, L. (1996). Redefining new product development teams: Learning to actualize consumer contributions. Journal of Product and Brand Management, 5(6), 48–60. doi:10.1108/10610429610152831 Porter, M. (1985). Competitive advantage. New York, NY: Free Press. Prahalad, C. K. (2002). Strategies for the bottom of the economic pyramid: India as a source of innovation, reflections. Reflections: The SoL Journal, 3(4), 6–18. doi:10.1162/152417302760127192 Ratten, V. (2009). Adoption of technological innovations in the m-commerce industry. International Journal of Technology Marketing, 4(4), 355–367. doi:10.1504/IJTMKT.2009.032181 Reid, S. E., & de Brentani, U. (2010). Market vision and market visioning competence: Impact on early performance for radically new, high-tech products. Journal of Product Innovation Management, 27(4), 500–518. doi:10.1111/j.15405885.2010.00732.x

506

Richens, M. L., & Block, P. H. (1986). After the new wears off: The temporal context of product involvement. The Journal of Consumer Research, 13, 280–285. doi:10.1086/209067 Riege, A. (2007). Actions to overcome knowledge transfer barriers in MNCs. Journal of Knowledge Management, 11(1), 48–67. doi:10.1108/13673270710728231 Rogers, E. M. (1983). Diffusion of innovations. New York, NY: The Free Press. Rosenbloom, R. S., & Cusumano, M. A. (1987). Technological pioneering competitive advantage: The birth of the VCR industry. California Management Review, 29(4), 51–77. Sandberg, B. (2002). Creating the market for disruptive innovation: Market proactiveness at the launch stage. Journal of Targeting. Measurement & Analysis for Marketing, 11(2), 184–197. doi:10.1057/palgrave.jt.5740076 Seo, D., & Hashem Sherif, M. (2009). Some implications of an overly used word: Convergence. International Journal of Technology Marketing, 4(4), 316–337. doi:10.1504/IJTMKT.2009.032179 Shapiro, C., & Varian, H. R. (1999). Information rules: A strategic guide to the network economy. Boston, MA: Harvard Business School Press. Souder, W. E., & Sherman, J. D. (1998). Environmental uncertainty, organizational integration, and new product development effectiveness. Journal of Product Innovation Management, 15(6), 520–534. doi:10.1016/S0737-6782(98)00033-2 Sriram, S., Balachander, S., & Manohar, U. K. (2007). Monitoring the dynamics of brand equity using store-level data. Journal of Marketing, 71, 61–78. doi:10.1509/jmkg.71.2.61 Stephen, A. T., & Toubia, O. (2010). Deriving value from social commerce networks. JMR, Journal of Marketing Research, 47(2), 215–228. doi:10.1509/jmkr.47.2.215

Taxonomy of Marketing Core Competencies for Innovation

Story, V., Hart, S., & O’Malley, L. (2009). Relational resources and competences for radical product innovation. Journal of Marketing Management, 25(5/6), 461–481. doi:10.1362/026725709X461803 Talke, K., & Salomo, S. (2009). Launching technological innovations: The relevance of a stakeholder perspective. International Journal of Technology Marketing, 4(2/3), 248–274. doi:10.1504/IJTMKT.2009.026873 Temporal, P., & Lee, K. C. (2000). Hi-tech hitouch branding: Creating Br power in the age of technology. Singapore: John Wiley & Sons. Thomke, S., & Von Hippel, E. (2002). Customers as innovators: A new way to create value. Harvard Business Review, 80(4), 74–82. Trott, P. (2008). Innovation management and new product development (4th ed.). Upper Saddle River, NJ: Prentice Hall. Trusov, M., Bucklin, R. E., & Pauwels, K. (2009). Effects of word-of-mouth versus traditional marketing. Findings from an Internet Social Networking Site, 73(5), 90–102. Urde, M. (1999). Brand orientation: A mindset for building brands into strategic resources. Journal of Marketing Management, 15(1-3), 117–133. doi:10.1362/026725799784870504 Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1), 1–17. doi:10.1509/ jmkg.68.1.1.24036 Veryzer, R. W. (1998). Key factors affecting customer evaluation of discontinuous new products. Journal of Product Innovation Management, 15(2), 136–150. doi:10.1016/S0737-6782(97)00075-1 Viardot, E. (2004). Successful marketing strategy for high tech firms (3rd ed.). Boston, MA: Artech House.

Viardot, E. (2005). Six principles to make a technology standard. Business Strategy Review, 16(3), 23–28. doi:10.1111/j.0955-6419.2005.00370.x Von Hippel, E., Thomke, S., & Sonnack, M. (2000). Creating breakthroughs at 3M. Health Forum Journal, 43(4), 20–27. Wellman, N. (2010). Relating the curriculum to marketing competence: A conceptual framework. Marketing Review, 10(2), 119–134. doi:10.1362/146934710X505735 Xuefeng, L. (2009). The shifts of technological paradigms and the evolution of firms’ dynamic capabilities. International Journal of Technology. Policy and Management, 9(3), 209–221.

KEY TERMS AND DEFINITIONS Brand Equity: The value added by the brand name to a product (Farquhar, 1999) in terms of an increase in awareness, positive associations, perceived quality and loyalty from the customers (Aaker, 1991). Innovation Positioning: The creation of the innovation´s perceived image in customers’ minds. The positioning reflects the innovation’s value for the customer and its main competitive advantage. A good positioning statement should be able to change or even reverse the mindset of customers (Jaworski & Alii, 2000). Market Segments: Groups of customers with similar wants, desires, or buying behavior who attribute a similar value to an innovation (Thomke & Von Hippel, 2002). Marketing Core Competencies (MCC) for Innovations: The key capabilities which have to be developed in order to contribute to the market success of a product innovation and subsequently to the overall profitability of a company (Story & Alii, 2009; Reid & de Brentani, 2010).

507

508

Chapter 27

Self Regulation on Innovative Products Choice Paulo Henrique Muller Prado Federal University of Parana, Brazil Danielle Mantovani Lucena da Silva Federal University of Parana, Brazil Jose Carlos Korelo Federal University of Parana, Brazil

ABSTRACT This chapter explores how choice goals influence consumers’ innovativeness in a product category domain. The intentions to adopt new products are guided by promotion and prevention self-regulation systems. Thus, two of the choice goals were classified as promotion goals—justifiability and choice confidence—and two were classified as prevention goals – anticipated regret and evaluation costs. Two groups emerged from the analysis: one named “most innovative” and another called “less innovative.” When comparing the groups, the results show that the “most innovative” cluster demonstrated higher choice confidence, higher justifiability and was more capable of avoiding a possible choice regret. The differences found in the group analysis highlight the need of understanding in further detail how consumers behave during the choice process of innovative products. Therefore, the Regulatory Focus Theory has been shown to be very important for understanding the choice process, especially for the innovation adoption.

INTRODUCTION Consider two individuals. One is Peter, who is worried about avoiding negative consequences. Thus, when he uses his cell phone he is probably more concerned about losing any information, DOI: 10.4018/978-1-61350-165-8.ch027

such as his contacts, calls, e-mails and any other thing that may be important to him. On the other hand, John always approaches positive results in his daily life, and he uses his cell phone to try to achieve these positive results, such as be in contact with his friends, be able to check his e-mail wherever he is and register some good moments by using his cell phone to take pictures. Peter and

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Self Regulation on Innovative Products Choice

John use their cell phones with the same goals (e.g. make calls, surf the internet, check e-mails, send messages to their contacts). However, they are very different in the way they try to achive a goal. Peter is more concerned about avoiding negative consequences whereas John probably seeks to achieve positive ones. One day, Peter and John decide to upgrade their equipments to a better one, with new attributes and services. In this situation, these consumers will be faced with a lot of options and alternatives that will make their choice more difficult. Their choice process will probably be very different as well. Peter will prefer attributes that fit his prevention-focused orientation and John will prefer attributes that fit his promotion-focused orientation. Peter and John might end up buying different cell phones or maybe one of them may abdicate upgrading, just because he could not find any option that fits his self-regulation orientation. When people pursue a goal, they begin with some motivational orientation, some concerns or interests that direct the goal pursuit, and the selfregulation orientation is one of these concerns (Freitas & Higgins, 2002). The two scenarios above illustrate two distinct goals highlighted in regulatory focus theory (Higgins, 1997), which builds on the general hedonic notion that people approach pleasure and avoid pain. The theory distinguishes between two major categories of desired goals: those that relate to attaining positive outcomes such as advancement, achievement, and aspirations (termed promotion goals), and those that relate to avoiding negative outcomes, such as responsabilities, obligations and security (termed prevention goals). According to the regulatory focus theory, individuals with a promotion focus will regulate their behavior toward positive outcomes, and those with a prevention focus will regulate their behavior away from negative outcomes (Liberman et al., 2001). There are some studies that have explored the choice process topic of research (Coupey, 1994; Dhar; Nowlis; Sherman, 1999; Chernev,

2006; Thompson; Hamilton; Rust, 2005) and specifically, some studies (Herzenstein; Posavac; Brakus, 2007; Alexander; Lynch Jr; Wang, 2008) emphasize that it is important to understand consumer’s behavior that are more interested in trying new products and services. Bettman (Bettman, 1979; Bettman, Luce, & Payne, 1998) proposed that consumers usually have a set of goals which are pursued during most of the choice situations. Furthermore, studies of the choice process must consider the choice goals in order to understand the heuristict strategies that consumers use to decide which product to buy (e.g. Bettman; Johnson; Payne, 1991; 2000; Heitmann; Lehmann; Herrmann, 2007). These goals may influence consumers in a different way, depending on the individual differences or on the characteristics of the choice context (Kahn, Luce, & Nowlis, 2006). Thus, the impact of the choice goals on the innovativeness process has not been studied yet. Therefore, it has become relevant to understand how choice goals influence consumers’ innovativeness, and how this relationship applies to the organizational strategy. In order to achieve this goal, an extension of part of the model proposed by Heitmann, Lehmann and Hermann (2007) is suggested in this study, relating the innovativeness in a product category domain to the choice goals. The choice goals are analyzed from the self-regulation perspective (Higgins, 1997). The self-regulation approach to studying the innovation and decision processes highlights the possibility of exploring how these two variables relate to each other in the consumer behavior context. The importance of Heitmann, Lehmann and Herrmann (2007)’s study to understand the choice goals is that they have classified these goals according to the regulatory focus theory, which was proposed by Higgins (1997). Thus, there are goals that are pursued in order to avoid negative consequences of the choice, and goals that are pursued so as to achieve positive results of the choice process.

509

Self Regulation on Innovative Products Choice

The use of the regulatory focus theory to study the innovation adoption process highlights the possibility to explore how the two regulatory foci (promotion and prevention) are related to consumers’ behavior. For instance, Herzenstein, Posavac and Brakus (2007) found that when risks associated with a new product are not specified to consumers, promotion-focused consumers state higher purchase intentions than prevention-focused consumers. Nevertheless, when the judgmental context makes the risks salient, prevention and promotion-focused participants are equally unlikely to purchase the product. Therefore, Peter, who is more prevention-focused and John, who is more promotion-focused, will have different decisions regarding an innovation. However, we do not know yet how Peter and John achieve their goals in order to become more innovative. That is what we are going to understand in this chapter.

THEORETICAL DEVELOPMENT Innovativeness Rogers (2003) explains that an innovation is an idea, practice or object that is perceived as new by the individual. Thus, a product will be considered an innovation only if it adds new attributes and/ or benefits, and consumers are more likely to adopt an innovation if it is perceived as useful and important to the individual. In a series of studies, Okada (2006) demonstrates that consumers with existing products are more likely to upgrade when the enhanced product is generally dissimilar to the existing product. For instance, a new cell phone will be considered an innovation and thus more likely to be adopted if it is perceived as dissimilar to the existing version of the product. However, when we analyse individuals’ innovation adoption, we need to consider the innovativeness behavior. Rogers (2003, p.22) defined innovativeness as the “degree to which an individual is relatively earlier in adopting an

510

innovation than other members of this system.” In an earlier study, Hirschman (1980) had stated that this author conceptualized innovativeness as a variable that all individuals have, in a greater or lower degree. Thus, it is a construct that can be generalized to all product categories. Roehrich (2004) explains that the novelty seeking is measured in a series of activities, which leads to three different types of innovativeness behavior: (1) innovativeness information, that is the information acquisition of a new product; (2) innovativeness adoption, that is the adoption of the new product; and (3) the innovativeness use, that expresses the product use in a different way or all the ways of using the product. This categorization increases the interest consumers will have toward new products. Another important innovation characteristic is that it has two dimensions: symbolic and technological (Hirschman, 1980). The symbolic innovation communicates a different social meaning than it previously did. Its physical form remains predominantly unchanged but the meaning assigned to that form is novel. The technological innovation possesses some tangible features never previously found in that product category and can be adopted because of the features’ performance and new functionalities (Hirschman, 1980). As individuals do not adopt an innovation all at the same time, they can be classified in an adoption categorization (see Figure 1). These categories are: (1) innovators; (2) early adopters; (3) early majority; (4) late majority; (5) laggards. Rogers (2003) proposed this categorization to facilitate group comparisons. Rogers (2003) explains that the innovators are adventurous. The innovators can deal with the uncertainty about an innovation and are experts in the innovation adopted. They represent only 2.5% of the population. The early adopters, which represent 13.5% of the population, are more integrated to the social system than the innovators because they act locally. This group is closer to other members of the social system and work as an example to the other groups. The early major-

Self Regulation on Innovative Products Choice

Figure 1. Innovativeness categorization (Source: Adapted from Rogers [2003, p. 281])

ity (34% of the population) adopt a new idea before the average of the members of the social system. They interact with the early adopters and among their group, but they are not opinion leaders. The late majority adopt new ideas after the majority of the members of the social system. The adoption, for this group, is a result of an economic need or due to a pressure of their group. They are not used to adopting an innovation, until the majority of their group has adopted it. The laggards are the last group in a social system to adopt an innovation and do not have any leadership opinion. They are very isolated inside the social system and their reference point is the past. They usually interact with people with traditional values and their decision process to adopt an innovation is slower than the other groups. In addition, their resources are limited and they need to be certain that the new idea is going to work to be adopted (Rogers, 2003). During the 90’s, some researchers began to consider the innovativeness in a product category as different construct of the innate innovativeness, which is an individual characteristic (Goldsmith; Hofacker, 1991; Goldsmith; Freiden; Eastman, 1995). Goldsmith and Hofacker (1991) state that the innovativeness construct is very specific, and a consumer that is innovative in a product category,

may not be innovative in another. The authors proposed the Domain Specific Innovativeness (DSI) scale, with six items that measure the innovativeness in a product category. In our study, we follow the perspective of the innovativeness in a product category because we are analysing techonological product, which is a specific product category.

Self-Regulation The value given to pursue a certain goal varies due to its importance to the individual (Higgins et al., 2003). As a result, people pursue goals that fit their values. This prediction is based on the Regulatory Focus Theory (RFT) (e.g., Higgins, 1997; Freitas; Higgins, 2002). Higgins (1997) proposed this theory, which introduces the concept of regulatory focus, a principle that underlies the hedonic principle that people seek pleasure and avoid pain. The RFT demonstrates that there are different ways of approaching pleasure and avoiding pain. The differences in performance, emotions and in decision making may occur as a result of the individual’s self-regulation. This theory has two foci: promotion and prevention, which are different in their strategies to achieve a final end state. The promotion-focused

511

Self Regulation on Innovative Products Choice

individuals favour approach strategies, so they frame goal pursuit in terms of gains and nongains; prevention-focused individuals do so with respect to losses and nonlosses because of their preference for avoidance strategic means. Under a promotion focus, the individual’s strategic inclination is to approach matches to end states he or she would like to achieve (Freitas & Higgins, 2002). Such individuals are more eager to avoid errors of omission (i.e., missing an emerging opportunity to accomplish something), resulting in an initial inclination to act (Liberman et al, 2001). In contrast, a prevention focus fosters a tendency to avoid mismatches to end states he or she would like to attain, with an orientation toward maintaining the status quo and shielding oneself from losses. Such individuals therefore prefer cognitive or behavioral courses that avoid errors of commission (i.e., making mistakes).

Self-Regulation and the Role of the Choice Goals in Innovativeness Bettman (1979) proposed that consumers have a hierarchy of goals, which they seek to achieve during the choice process. Bettman, Luce and Payne (1998) argue that these goals are the most important motivational aspects to the decision making process. The authors explain that these goals are inherent to most of the choice contexts and determine the main aspects of the choice process analysis. In order to understand how consumers assess their choices, Heitmann, Lehmann and Herrmann (2007) related the choice goals proposed by Bettman (e.g., Bettman, 1979; Bettman, Luce, & Payne, 1998) to the Regulatory Focus Theory (RFT). Two of the goals were classified as promotion goals—justifiability and choice confidence—and two were classified as prevention goals—anticipated regret and evaluation costs. Consumers will value a goal if it is important for them (Higgins et al., 2003). Therefore, people pursue goals and get more engaged in the choice process that fit their values (Freitas; Higgins,

512

2002; Lee; Keller; Sternthal, 2010). This prediction comes from the RFT, which suggests that the regulatory fit that people experience when the manner of their engagement in an activity sustains their goal orientation or interests regarding that activity, their motivation to pursue that goal increases. This prediction is also based on the selfregulation. More promotion-focused individuals will be more engaged to achieve promotion goals whereas prevention-focused individuals will be more engaged to achieve prevention goals. When we analyse the promotion goals (choice confidence and justifiability), we find that they are related to each other and also impact the prevention goals (evaluation costs and anticipated regret) (Heitmann; Lehmann; Hermann, 2007). Bettman, Luce and Payne (1998) state that the confidence during the choice process is a consequence of the use of more compensatory choice strategies. Thus, the justifiability also increases the choice confidence. H1: Consumers’choice confidence is a positive function of the higher justifiability during the choice process. When analyzing the impact of the choice confidence on the other choice goals, we must bear in mind that the negative emotions that result from a bad choice is a consequence of the lack of confidence in the decision process (Bettman; Johnson; Payne, 1991; Landman, 1993; Tsiros; Mittal, 2000). After the decision is made, individuals that are not confident about the right choice, often ask themselves if they should have looked for a better option. In addition, the application of the anticipated regret goal in the innovation context, Bettman, Luce and Payne (1998) and Heitmann, Lehmann and Herrmann (2007) state that decision makers feel that they are being evaluated by others (e.g., family and friends) and by themselves about their decisions. As a consequence, consumers try to anticipate regret and do this by searching for more

Self Regulation on Innovative Products Choice

information, in order to maximize the accuracy of their decision. Some studies (e.g., Stone, 1994; Chernev, 2006; Heitmann; Lehmann; Herrmann, 2007) also demonstrate that uncertainty about the choice leads to a lack of confidence, which increases the probability of regretting the choice. Studies (e.g., Stone, 1994; Chernev, 2006; Heitmann; Lehmann; Herrmann, 2007) also demonstrate that consumers that are more uncertain about a choice are also less confident, which increases the probability of regretting the choice after the decision is made. Hence, we propose our second hypothesis. H2: The higher the choice confidence, the higher the anticipated regret. The evaluation cost of the choice process can be defined as the cost associated with the information search and analysis of a decision process of a product or service (Burnham; Frels; Mahajan, 2003). This cost is not just about the economic aspects, but also about the time spent searching information, analysing the alternatives and learning how to use the new product. Thus, time and effort are associated with collecting the information needed to evaluate potential alternative providers. Mental effort is required to restructure and analyse available information in order to arrive at an informed decision (Burnham; Frels; Mahajan, 2003). Consumers are also likely to perceive higher evaluation costs when products are complex, because the difficulty in understanding the product leads to uncertainty, and increases the perception that a negative outcome may occur (Holak; Lehmann, 1990; Luce; Bettman; Payne, 1997). Similarly, the large number of attributes associated with complex products makes both information collection and direct comparison attributes more costly (Shugan, 1980) Herzenstein, Posavac and Brakus (2007) state that those consumers guided by the promotionfocused self-regulation are more innovative, once

they are more confident in the choice process. When the promotion goals are achieved, it is easier to achieve the prevention goals (Higgins, 2003). Therefore, for consumers that have higher decision difficulty, the choice confidence becomes more important and will have a stronger impact on the evaluation costs. H3: The lower the choice confidence, the higher the perception of the evaluation costs during the choice process. Individuals that feel more insecure about the choice often have more difficulty in anticipating regret. Even after the decision is made, these individuals are not sure about the best alternative or option for that moment. As a consequence, they question themselves about the possibility of searching more information and invest more time to get a better option (Heitmann; Lehmann; Herrmann, 2007). These consumers are also less confident and believe that a longer decision process might be better (Bettman; Luce; Payne, 1998). Consumers that are more worried about avoiding regret are more motivated to get engaged in order to reduce the possibility of a negative consequence of a decision (Zeelenberg, 1999). H4: The perception of the evaluation costs is a negative function of the anticipated regret during the choice

Choice Goals Influence on the Innovativeness The literature demonstrates that the adoption intentions for new products are guided by promotion and prevention self-regulation systems (e.g., Herzenstein, Posavac, & Brakus, 2007). Concerning the promotion goals, the confidence during the choice process is a consequence of the use of more complete and compensatory choice strategies (Bettman; Luce; Payne, 1998).

513

Self Regulation on Innovative Products Choice

Promotion-focused consumers are more likely to purchase new products than prevention-focused consumers because they demonstrate higher choice confidence (Chernev, 2006; Herzenstein, Posavac, & Brakus, 2007). The choice confidence is related to the thought that positive results may arise from the choice process. Therefore, the choice process is constructive (Bettman; Johnson; Payne, 1991; Bettman; Luce; Payne, 1998), and when consumers are faced with the possibility of upgrading to a better product, they will probably remember the rules that were applied to choose the last product. Cowley (2001) states that individuals use only one piece of this information. However, this recovered information is more reliable and influences the current choice process. Concerning this process, there are situations where the assortment of options and features is high, such as in the case of technological products, which decreases consumer’s confidence in the decision process. In spite of this situation, those consumers with a promotion-focused selfregulation are more confident, because they expect positive results (Chernev, 2006). As a result, they become more innovative. We summarize this discussion with the following hypothesis: H5: The innovativeness in a product category is a positive function of the choice confidence. It is possible that the justifications that consumers use during the choice process are above certain aspects, such as the trade-off between cost and benefits. In some situations, the lack of justifiability may lead the consumer to stop the choice process and abdicate the idea of buying the product (Hsee et al., 2003; Okada, 2005; Amir; Ariely, 2007). Chernev (2001) also proposed that consumers evaluate common features in a manner that confirms their already established preferences. When the consumer is in a choice situation, he is

514

more likely to justify his decision, for instance, by the preference that he already has for a particular brand. This decision behavior demonstrates that individuals try to find reasons that are consistent and acceptable both for themselves and for others. Thus, choice confidence is a positive function of the justifiability (see H1). Murray and Häubl (2007) analysed this behavior and demonstrated that consumers tend to keep a product or a brand to try to avoid switch and search costs for a possible better alternative. In addition, as consumers already know the current product they have been using, it is easier to justify their decision when they keep this product. The upgrade decision may be more difficult to justify if the consumer is not innovative in this product category. In addition, the comparison within the options is more difficult to be evaluated if there are a lot of different alternatives or if the differences among the options are not easy to be distinguished by the consumer (Thompson; Hamilton; Rust, 2005). In the case of technological products, it is possible that consumers will have more difficulty to compare the options, because the new features may be difficult to use. Thus, if the consumer is able to justify the decision and explain why he is buying these new features, he will probably be more innovative. This prediction is summarized in the following hypothesis: H6: The innovativeness in a product category is a positive function of the justifiability. Concerning the prevention-focused goals, Herzenstein, Posavac and Brakus (2007) demonstrated that prevention-focused consumers are less likely to adopt a new product. This effect is due to the way these consumers deal with the prevention goals (evaluation costs and anticipated regret). These consumers are more worried about possible negative outcomes and try to protect themselves. The result is that they abdicate adopting a prod-

Self Regulation on Innovative Products Choice

uct or decide to adopt it later in a social system. Therefore, if the consumer is not able to achieve the prevention goals, he will be less likely to adopt an innovation. The prevention goal related to anticipate regret predicts that consumers feel they are being evaluated by others all the time (Bettman; Luce; Payne, 1998; Heitmann; Lehmann; Herrmann, 2007). If we analyse this goal in an innovation adoption decision, this prediction may be even more evident. Innovative consumers are opinion leaders (Gatignon, Robertson, 1991; Foxall, 1994; Rogers, 2003) and they feel required to show they are able to make good choices based on cognitive aspects. When the decison context, as an innovation for instance, requires a previous knowledge about the product category, the anticipated regret will be more difficult to be executed or it will take a longer time if the consumer does not know too much about the product category. In this situation, it will be more difficult to achieve this goal and it will explain, partly at least, why consumers may not adopt an innovation. This behavior leads to a lower innovativeness in a product category. Thus, our seventh hypothesis is: H7: The innovativeness in a product category is a positive function of the anticipated regret. An extensive choice process probably will have higher evaluation costs (Burnham; Frels; Mahajan, 2003). For innovative consumers, the evaluation about the product category in which they are innovators is not done at the moment they are going to make a new purchase. The evaluation of new alternatives, information search and other activities related with the choice process is constantly made by this group (Gatignon, Robertson, 1991; Christia, 2000; Rogers, 2003); it is part of its behavior. As a consequence, the evaluation costs are not perceived as high by the group of innovators, but for the laggards it may be.

Hirschman (1980) characterized the novelty seeking individuals as those that are always searching information, and they are really interested in searching this information. Although the innovators spend more time on this activity, they do not perceive the evaluation cost to be high. On the other hand, for non-innovators these costs will seem much higher. The influence of the evaluation costs in a decision to upgrade and adopt a new product may take into consideration some specific characteristics. The innovativeness in a product category may be evaluated by the consumers’ interest to adopt the enhancements proposed in the new version of the product. However, the consumer already has a product and is used to it. The switch to an enhanced product increases the evaluation costs to find the best new alternative (Okada, 2006). In this situation, if the consumer’s perception of the evaluation costs is not high, the probability of innovating will be higher. The literature (e.g., Midgley; Dowling, 1978; 1993; Goldsmith; Hofacker, 1991; Roehrich, 2004; Alexander; Lynch Jr; Wang, 2008) shows that the innovativeness is a consequence of a series of activities performed during the decision making process. Hence, the lower the perception about the evaluation costs, the higher the innovativeness. H8: The innovativeness in a product category is a negative function of the evaluation cost perception. We represent the specific hypotheses described above in Figure 2.

EMPIRICAL ANALYSIS Method and Scale Measurement The participants in this study were 366 undergraduate students from a Federal University in the south of Brazil (59% female), who had purchased an

515

Self Regulation on Innovative Products Choice

Figure 2. Framework of choice goals and innovativeness

electronic device in the last three months. The most frequently reported purchases were cell phones and digital cameras, but others were also reported, such as MP3 players. Data were collected using a self-administered paper survey. The scale purification and measurement followed the work of Churchill (1979) and Anderson and Gerbing (1988). Existing measures were adapted for the model constructs. The innovativeness in the product category was measured based on the Goldmith and Hofacker (1991) and Goldsmith and Flynn (1992) scales. We also applied Midgley and Dowling’s (1978) innovativeness measurement, asking respondents how many and which were the electronic equipments they already had. This question was used later to classify the respondents according to the innovativeness profile. The choice goals were measured in accordance with the work of Bettman, Luce and Payne (1998), which argues that this construct is essential to the choice process. As in other studies on choice goals, we also followed other authors to measure choice 516

goals. Thus, the choice confidence was measured with the scale proposed in the study of Urbany et al (1997). The justifiability followed the work of Simonson (1989) and Heitmann, Lehmann, and Herrmann (2007). The measurement of the anticipated regret followed the work of Schwartz et al (2002) and Tsiros and Mittal (2000). The measurement of the evaluation costs followed the work of Burnham, Frels and Mahajan (2003). As in other surveys on purchase decisions and search behavior, we rely on the recall of prior experiences (e.g., Srinivasan; Ratchford, 1991; Ratchford, Lee, and Talukdar, 2003; Heitmann; Lehmann; Herrmann, 2007). Following the work of Srinivasan and Ratchford (1991), we tested whether “forgetting” had a significant impact on the data by splitting the sample into three groups: those who reported purchasing a product within the month, between one and two months before this participation, and between two and three months before this participation. None of the comparisons showed significant differences.

Self Regulation on Innovative Products Choice

Furthermore, the cluster based on the innovativeness profile was run using the Multiple Components Analysis, following the work of Bagozzi (1995). This analysis generated two groups: one named “Most Innovative” and another called “Less Innovative.” The internal consistency analysis presented good results, following the recommendation of Hair et al (2005): Justifiability (α = 0.72), Choice Confidence (α = 0.76), Anticipated Regret (α = 0.79), Evaluation Costs (α = 0.75) and Innovativeness (α = 0.73). Most of the data were analyzed using Structural Equation Modeling (Hair et al, 2005), with the Amos 6.0 (SPSS, 1993). Before the model verification, we run the Confirmatory Factorial Analysis (CFA), which presented acceptable reliability values: Choice Confidence (0.72); Justifiability (0.75); Evaluation Costs (0.81); Anticipated Regret (0.89) and Innovativeness (0.89). The Average Variance Stracted (AVE) was also accepted: Choice Confidence (0.52); Justifiability (0.52); Evaluation Costs (0.58); Anticipated Regret (0.63); Innovativeness (0.63). The analysis demonstrated that there was no significant correlation between the constructs. The results denote a CFA model that includes the multi-item measures selected after scale purification: χ²= 264.069; d.f = 137; p<.001; χ²/d.f = 1.928; NFI =.921; RFI=.901; CFI =.960 and RMSEA =.045.

Innovative Profile Evaluation In order to evaluate the differences concerning the innovative behavior, an innovative score was created, based on the number of equipments the respondents owned (e.g., cell phones, digital cameras, players; etc) and the features that each product had (basic, intermediary and advanced features). The results showed two different groups. As mentioned before, those respondents with higher scores were named “Most innovative” (G1 – 186 respondents) and those with lower scores were the “Less Innovative” (G2 – 180 respondents).

An independent-sample t-test was conducted to compare the variables for the two groups. The results are presented in Table 1. There were significant different scores for most and less innovative groups. The most innovative respondents reported higher scores of Innovativeness, Choice Confidence, Justifiability and Anticipated Regret. This group also reported a lower score of Evaluation Costs. For instance, the most innovative group seems to be more promotion-focused and the less innovative one is more prevention-focused. These results show that the Most Innovative group has equipments with more innovative features. They are also more confident about their choice, which increases their justifiability. In addition, they perceive that the evaluation costs are not as high as the Less Innovative group thinks.

Model Evaluation The structural model presented in Figure 2 was tested for the two groups, using the Amos 6.0. The results and the tested hypotheses are presented in Table 2. The first hypothesis predicts that there is a positive relationship between justifiability and choice confidence. This relationship was empirically demonstrated in the work of Heitmann, Lehmann and Herrmann (2007), and had been proposed by Bettman (e.g., Bettman, Luce, Payne, 1998). In our study, this hypothesis was statistically significant for both groups (ß=.621, p<.001 for the Most Innovative and ß=.549, p<.001 for the Less Innovative). The Most Innovative group reported a higher standardized score (ß), which demonstrate that this group is better able to justify its choices as a consequence of the choice confidence. The second hypothesis proposes that the higher the choice confidence, the higher the anticipated regret is. This prediction was confirmed for the Most Innovative (ß =.176; p<.05) and was more significant for the Less Innovative (ß =.326;

517

Self Regulation on Innovative Products Choice

Table 1. Innovator cluster means Variables

G1 (186)

G2 (180)

t

p

Innovativeness

7.14

4.28

18.27

.000*

Choice Confidence

7.45

6.26

4.92

.000*

Justifiability

7.98

6.83

2.26

.000*

Anticipated Regret

7.32

6.58

4.10

.001*

Evaluation Costs

4.13

4.81

-3.42

.001*

G1 (group 1) = most innovative; G2 (group 2) = less innovative *p <.01

Table 2. Framework variable standardized coeficients (Paths) Dependet Variables with Predictors

G1 (186) Standardized

G2 (180) t

Standardized

t

Δ χ² (d.f.)

Choice Confidence 0.621

6.227*

0.549

4.602*

1.42 (1); p = n.s.

0.176

2.313**

0.326

2.971*

4.54 (1); p<.05

Choice Confidence

-0.217

-2.958**

-0.103

-1.316

0.20 (1); p= n.s.

Anticipated Regret

-0.216

-2.815*

-0.277

-4.008*

6.17 (1); p<.01

0.218

1.950**

0.162

1.386

0.89 (1); p = n.s.

Justifiability Anticipated Regret Choice Confidence Evaluation Costs

Inovativeness Choice Confidence Justifiability

0.214

2.792*

-0,080

-0.698

1.87 (1); p= n.s.

Anticipated Regret

0.214

2.792*

0.125

1.754

1.35 (1); p= n.s.

Evaluation Costs

-0.286

-2.565*

-0.291

-2.291**

0.25(1); p = n.s.

G1 (most innovative): χ² = 106.559, d.f = 92; χ²/ d.f = 1.158; NFI =.862; CFI =.978; RMSEA =.036 G2 (less innovative): χ² = 118.339 d.f = 92; χ²/ d.f = 1.286; NFI =.904; CFI =.976; RMSEA =.036 * p<.01 **p<.05 n.s. = not significant.

p>.01). The Less Innovative group is more concerned about having choice confidence in order to avoid regretting the decision. As the Most Innovative group is more confident in the choice process (see Table 1), they are not so worried about anticipating regret. In fact, this group seems to be more interested in the positive outcomes of the choice process. The third hypothesis suggests that the lower the choice confidence, the higher the perception of the evaluation costs is during the choice process.

518

The results reported a significant relationship only for the Most Innovative group (ß = -.217; p<.05). This relationship did not reach statistical significance for the Less Innovative group (ß = -.103; p=n.s). These results highlight the effect of the promotion goals over the prevention goals. Promotion-focused consumers tend to be more innovative, because they are more confident during the choice process (Herzenstein, Posavac, Brakus, 2007). In addition, when the promotion goals are achieved, the consumer can also achieve

Self Regulation on Innovative Products Choice

the prevention goals easily (Higgins et al., 2003), which explains why the H3 was not significant for the Less Innovative. The fourth hypothesis is about the relationship within the prevention goals. Thus, it predicts that the perception of the evaluation costs is a negative function of the anticipated regret during the choice. This hypothesis was also found in the work of Heitmann, Lehmann and Herrmann (2007). It was confirmed for both groups (ß= -.216, p<.01 for the Most Innovative and ß=-.277, p<.01 for the Less Innovative). Although this hypothesis was confirmed in both groups, we may note that the Less Innovative group reported a higher standardized score (ß). The literature have shown the relationship among the prevention goals (e.g., Bettman; Luce; Payne, 1998; Zeelenberg, 1999), because consumers try to protect themselves against negative outcomes. Therefore, they get more engaged in information search, especially for products with new features, large assortment size and that are always being upgraded. This behavior seems to be consistent for both groups. The fifth hypothesis predicts that the innovativeness in a product category is a positive function of the choice confidence. This prediction was supported only by the Most Innovative group (ß=.218, p<.01). The Less Innovative did not show statistical significance concerning this relationship (ß=.162, p= n.s). These results demonstrate that the Most Innovative respondents are more confident in the choice process because they are more promotion-focused (Herzenstein; Posavac; Brakus, 2007). The sixth hypothesis is about the justifiability and its impact on the innovativeness behavior. Only the Most Innovative group showed significant results for this relationship (ß=.214, p<.01). The Less Innovative did not show statistical significance (ß=-.080, p=n.s). For innovative products, consumers that can justify their choice are more likely to innovate. The seventh hypothesis, which predicts that the innovativeness is a positive function of the anticipated regret, was

confirmed only in the Most Innovative respondents (G1: ß=.214, p<.01G2: ß=.125, p=n.s). As predicted, consumers that are less worried about the possible negative outcomes are more likely to be innovative. These consumers are more concerned about achieving positive results, instead of avoiding negative ones. The eighth hypothesis, which suggests that the innovativeness in a product category is a negative function of the evaluation cost perception was statistically significant for both groups (G1: ß= -.286, p<.01; G2: ß= -.291, p<.05). For extensive choice processes, such as in the case of innovative products, the evaluation costs are higher. In this situation, consumers need to get more engaged in the choice process in order to compare the differences between the products (Burnham; Frels; Mahajan, 2003). The results described above confirm that the choice goals are antecedents of the innovativeness in a product category. As the groups presented statistically different means in all variables (see Table 1), an analysis of which variables could contrast the groups in the framework was run. Thus, each path of the proposed model was analysed separately, following the recommendations of Byrne (2001). The results are presented in the right column (Δ χ² [d.f.]), Table 2. The relationship between the choice confidence and the anticipated regret indicates that there is a significant difference between the groups. The difference between the value of the free model and the restricted model suggests a Δχ² = 4.54 (Δd.f. = 1; p <.05). In addition, the impact of the goal to anticipate regret on the evaluation costs was also significant between the groups (Δχ² = 6.17 (Δd.f. = 1; p <.01). These results suggest that the less innovative group needs to feel confident in the choice process to not regret the choice. The prevention goals (anticipate regret and evaluation costs) seem to be more important for the less innovative group in relation to the most innovative one. Any of the other paths were statistically significant, which means that expect for the two

519

Self Regulation on Innovative Products Choice

significant paths described above, the groups are not very much different for the paths presented in the framework. Particularly, the impact of the choice goals on the innovativeness did not differentiate the groups. However, the Independent Samples T-test performed to verify the mean differences between the groups suggests that there is a difference for all the variables and that the innovativeness is a construct that distinguishes the groups. Besides that, the behavior pattern of the paths was not different.

DISCUSSION Although recent studies (e.g. Herzenstein, Posavac and Brakus, 2007) have shown that promotionfocused consumers are more innovative than prevention-focused consumers, we have not found yet any study that has identified which goals are more relevant in this process. Studies that work with the RFT (Higgins, 1997; Freitas; Higgins, 2002; Higgins et al, 2003) assume the prediction that individuals seek pleasure and satisfaction, and avoid losses and pain. In fact, this prediction is also applied to the innovativeness behavior in the product category, because the less innovative consumers are more interested in avoiding negative outcomes whereas the most innovative consumers seek positive outcomes. The results indicate that the respondents show a similar pattern of behavior regarding the proposed model. If we analyse the hypotheses that relate the choice goals (H1-H4), we note that the less innovative group has lower standardized score (ß) for most of the hypothesis. On the other hand, the most innovative group showed higher standardized score (ß) for most of the paths. An exception is the predicted relationship between the anticipated regret and the evaluation costs (H4), which had a higher loading for the Less Innovative group. This result reinforces the idea that for this group, the relationship between prevention goals still need to be better established. Another example is the

520

fact that H3, which relates confidence to evaluation cost, was not statistically significant for the Less Innovative group. This finding indicates that these consumers still need to achieve their prevention goals and then have any impact on choice confidence. The H5 and H6, which demonstrated the impact of the promotion goals on the innovativeness, were confirmed only for the Most Innovative group. This result relies on the constructive choice process (Bettman, Luce, Payne, 1998; Payne; Bettman, 2007). The confidence during the choice process is a consequence of the use of compensatory decision strategies. Thus, confident consumers are also more innovative in the product category. Concerning the impact of the prevention goals on the innovativeness (H7 and H8), the fact that only the goal of evaluation costs had a significant impact on the innovativeness for the Less Innovative group is probably due to the choice context. For technological based product, consumers need to be more engaged in the evaluation of the alternatives in order to make comparisons among the options. According to the constructive choice process theory, the negative emotions that may arise from a regreted choice are a consequence of the lack of confidence about the choice. In this situation, the Most Innovative group seemed to be better able to anticipate regret. This ability is probably because they have more expertise about the product category, which makes them more confident. This may be the reason why anticipated regret was not significant for the Less Innovative group.

CONCLUSION AND FUTURE RESEARCH DIRECTIONS The results demonstrate that the choice goals’ achievement is a positive function of Innovativeness in a product category. Therefore, the RFT has proved to be very important for better

Self Regulation on Innovative Products Choice

understanding the choice process and specifically the innovation adoption. The differences found in the groups highlight that the marketing managers need to consider the consumer behavior during the choice process of electronic devices that are constantly being upgraded. The results reported here suggest that the self-regulation could be used as a marketing and segmentation variable. As the self-regulation can be a context variable, a marketing communication can be elaborated with a promotion-focused idea to target promotion-focused consumers. On the other hand, a prevention-focused communication could be elaborated in order to fit with the prevention-focused individuals. It seems reasonable that those with a chronic extreme prevention (vs. promotion) tendency will likely be less susceptible to a promotion (vs. prevention) advertising manipulation. This could influence consumers’ orientation toward positive results about the innovation adoption. In fact, Herzenstein, Posavac and Brakus (2007) have proved that consumers are susceptible for such a manipulation. Thus it might have a have a managerial utility. The fit between the consumers’ regulatory focus and the marketing communication to new products may be particularly interesting to managers. In our study, prevention-focused consumers will be more concerned regarding the possibility of regretting the choice. As a result, a promotionfocused communication will not fit their interest, but a prevention-focused communication may work. As our results show that one of the reasons for the consumer to not adopt a new produt is because they have not achieved the prevention goals, the Less Innovative consumers need first to avoid negative outcomes, and then they try to achieve positive results. Future studies should analyse consumers’ evaluations during the choice process and the subsequent innovation adoption that may arise from these emotional reactions. The innovativeness is a consequence of the results that consumers expect from a new product. The use of heuristic

choice was showed in a study conducted by Pham (1998). The author demonstrates the significant role of emotions in the decision making process. When consumers try to predict possible emotions, they may overstimate the negative emotions of a choice. Further analysis concerning how consumers predict and deal with these emotions requires future studies. Another suggestion is to constrast the framework proposed including samples not only from students. In this situation, a field study would be interesting to demonstrate that the results are consistent with the predictions made in this study.

REFERENCES Alexander, D. L., Lynch, J. G. Jr, & Wang, Q. (2008, June). As time goes by: Do cold feet follow warm intentions for really new versus incrementally new products? JMR, Journal of Marketing Research, 45, 307–319. doi:10.1509/ jmkr.45.3.307 Amir, O., & Ariely, D. (2007). Decision by rules: The case of willingness to pay for beneficial delays. JMR, Journal of Marketing Research, 44(01), 32–49. doi:10.1509/jmkr.44.1.142 Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3). doi:10.1037/00332909.103.3.411 Bagozzi, R. (1995). Advanced methods of marketing research. Oxford, UK: Blackwell. Bettman, J. R. (1979). An information processing theory of consumer choice. Cambridge, MA: Assison-Wesley. Bettman, J. R., Johnson, E. J., & Payne, J. W. (1991). Consumer decision making. In Robertson, T. S., & Kassarjian, H. H. (Eds.), Handbook of consumer behavior. Englewood Cliffs, NJ: Prentice-Hall. 521

Self Regulation on Innovative Products Choice

Bettman, J. R., Johnson, E. J., & Payne, J. W. (2000). Consumer decision making. In Ratneshwar, S., Mick, D. G., & Huffman, C. (Eds.), The why of consumption: Contemporary perspectives on consumer motives, goals and desires. London, UK: Routdedge. Bettman, J. R., Luce, M. F., & Payne, J. W. (1998, December). Constructive consumer choice processes. The Journal of Consumer Research, 25, 187–214. doi:10.1086/209535 Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs: A typology, antecedents, and consequences. Journal of the Academy of Marketing Science, 31, 109–126. doi:10.1177/0092070302250897 Byrne, B. (2001). Structural equation modeling with AMOS: Basic concepts, applications and programming. Mahwah, NJ: Lawrence Erlbaum Associates. Chernev, A. (2001, March). The impact of common features on consumer preferences: A case of confirmatory reasoning. The Journal of Consumer Research, 27, 475–489. doi:10.1086/319622 Chernev, A. (2006, June). Decision focus and consumer choice among assortments. The Journal of Consumer Research, 33, 50–60. doi:10.1086/504135 Christia, J. (2000, December). The effects of alliance image on the relationship between consumer innovativeness and new product adoption. PhD Thesys, Oklahoma State University. Churchill, G. (1979, February). A paradigm for developing better measures of marketing constructs. JMR, Journal of Marketing Research, 16. Coupey, E. (1994, June). Restructuring: Constructive processing of information displays in consumer choice. The Journal of Consumer Research, 21, 83–99. doi:10.1086/209384

522

Cowley, E. (2001). Overconfidence in memory for brand information: A cross-national study, Asia Pacific. Journal of Marketing and Logistics, 13(2), 85–96. doi:10.1108/13555850110764784 Dhar, R., Nowlis, S. M., & Sherman, S. J. (1999, December). Comparison effects on preference construction. The Journal of Consumer Research, 26(3), 293–306. doi:10.1086/209564 Foxall, G. R. (1994, June). Consumer initiators: Adaptors and innovators. British Journal of Management, 5(Special Issue), 3–12. doi:10.1111/j.1467-8551.1994.tb00125.x Freitas, A. L., & Higgins, E. T. (2002). Enjoying goal-directed actions: The role of regulatory fit. Psychological Science, 13, 1–6. doi:10.1111/14679280.00401 Gatignon, H., & Robertson, S. (1991). Innovative decision processes. In Robertson, S., & Kassarjian, H. (Eds.), Handbook of consumer behavior (pp. 316–348). Upper Saddle River, NJ: Prentice-Hall. Goldsmith, R., & Flynn, L. R. (1992). Identifying innovators in consumer product markets. European Journal of Marketing, 26, 42–55. doi:10.1108/03090569210022498 Goldsmith, R. E., Freiden, J. B., & Eastman, J. K. (1995). The generality/specificity issue in consumer innovativeness research. Technovation, 15, 601–612. doi:10.1016/0166-4972(95)99328-D Goldsmith, R. E., & Hofacker, C. F. (1991). Measuring consumer innovativeness. Journal of the Academy of Marketing Science, 19, 209–221. doi:10.1007/BF02726497 Hair, J., Anderson, R., Tatahan, R., & Black, W. (2005). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall.

Self Regulation on Innovative Products Choice

Heitmann, M., Lehmann, D. R., & Herrmann, A. (2007, May). Choice goal attainment and decision consumption satisfaction. JMR, Journal of Marketing Research, 44, 234–250. doi:10.1509/ jmkr.44.2.234 Herzenstein, M., Posavac, S. S., & Brakus, J. J. (2007, May). Adoption of new and really new products: The effects of self-regulation systems and risk salience. JMR, Journal of Marketing Research, 44, 251–260. doi:10.1509/jmkr.44.2.251 Higgins, E. T. (1997). Beyond pleasure and pain. The American Psychologist, 52(12), 1280–1300. doi:10.1037/0003-066X.52.12.1280 Higgins, E. T., Freitas, A. L., Idson, L. C., Spiegel, S., & Molden, D. C. (2003). Transfer of value from fit. Journal of Personality and Social Psychology, 84, 1140–1153. doi:10.1037/0022-3514.84.6.1140 Hirschman, E. C. (1980, December). Innovativeness, novelty seeking, and consumer creativity. The Journal of Consumer Research, 7, 283–295. doi:10.1086/208816 Holak, S. L., & Lehmann, D. R. (1990). Purchase intentions and the dimensions of innovation: An exploratory model. Journal of Product Innovation Management, 7, 59–73. doi:10.1016/07376782(90)90032-A Hsee, C. K., Zhang, J., Yu, F., & Xi, J. (2003). Lay rationalism and inconsistency between predicted experience and decision. Journal of Behavioral Decision Making, 16(4), 257–272. doi:10.1002/ bdm.445 Kahn, B. E., Luce, M. F., & Nowlis, S. M. (2006, June). Debiasing insights from process tests. The Journal of Consumer Research, 33, 131–137. doi:10.1086/500492 Landman, J. (1993). Regret: The persistence of the possible. New York, Oxford: Oxford University Press.

Lee, A. Y., Keller, P. A., & Sternthal, B. (2010, February). Value from regulatory construal fit: The persuasive impact of fit between consumer goals and message concreteness. The Journal of Consumer Research, 36, 735–747. doi:10.1086/605591 Liberman, N., Molden, D. C., Idson, L. C., & Higgins, E. T. (2001). Promotion and prevention focus on alternative hypotheses: implications for attributional functions. Journal of Personality and Social Psychology, 80(1), 5–18. doi:10.1037/0022-3514.80.1.5 Luce, M. F., Bettman, J. R., & Payne, J. W. (1997). Choice processing in emotionally difficult decisions. Journal of Experimental Psychology. Learning, Memory, and Cognition, 23(2), 384–405. doi:10.1037/0278-7393.23.2.384 Midgley, D. F., & Dowling, G. R. (1978, March). Innovativeness: The conception and its measurements. The Journal of Consumer Research, 4, 229–242. doi:10.1086/208701 Midgley, D. F., & Dowling, G. R. (1993). A longitudinal study of product form innovation: Interaction between predisposition and social messages. The Journal of Consumer Research, 19. Murray, K. B., & Häubl, G. (2007, June). Explaining cognitive lock-in: The role of skill-based habits of use in consumer choice. The Journal of Consumer Research, 34, 77–88. doi:10.1086/513048 Okada, E. M. (2005, February). Justification effects on consumer choice of hedonic and utilitarian goods. JMR, Journal of Marketing Research, 42, 43–53. doi:10.1509/jmkr.42.1.43.56889 Okada, E. M. (2006). Upgrades and new purchases. Journal of Marketing, 70(4), 1–16. doi:10.1509/ jmkg.70.4.92

523

Self Regulation on Innovative Products Choice

Payne, J. W., & Bettman, J. (2007). Walking with the scarecrow: The information-processing approach to decision making. In Koehler, D. J., & Harvey, N. (Eds.), Handbook of judgment and decision making. Hoboken, NJ: Blackwell.

Stone, N. (1994). Overconfidence in initial selfefficacy judgments: Effects on decision process and performance. Organizacional Behavior and Human Decision Process, 59, 452–475. doi:10.1006/obhd.1994.1069

Pham, M. T. (1998). Setember). Representativeness, relevance and the use of feelings in decision making. The Journal of Consumer Research, 25, 144–157. doi:10.1086/209532

Thompson, D. V., Hamilton, R. W., & Rust, R. T. (2005). Feature fatigue: When product capabilities become too much of a good thing. JMR, Journal of Marketing Research, 42(4), 431–442. doi:10.1509/jmkr.2005.42.4.431

Ratchford, B. T., Lee, M., & Talukdar, D. (2003, May). The impact of the Internet on information search for automobiles. JMR, Journal of Marketing Research, 40, 193–207. doi:10.1509/ jmkr.40.2.193.19221

Tsiros, M., & Mittal, V. (2000). Regret: A model of its antecedents and consequences in consumer decision making. The Journal of Consumer Research, 26(4), 401–417. doi:10.1086/209571

Roehrich, G. (2004). Consumer innovativeness: Concepts and measurements. Journal of Business Research, 57, 671–677. doi:10.1016/S01482963(02)00311-9

Urbany, E., Bearden, O., Kaicker, A., & Borrero, S. (1997). Transaction utility effects when quality uncertain. Journal of the Academy of Marketing Science, 25, 45–55. doi:10.1007/BF02894508

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

Xia, L. (1999). Consumer choice strategies and choice confidence in the electronic environment. In. Proceedings of the American Marketing Association Conference, 10, 270–277.

Schwartz, A. W., Monterosso, J., Lyubomirsky, K. W., & Lehman, D. R. (2002). Maximazing versus satisfacing: Happiness is a matter of choice. Journal of Personality and Social Psychology, 83(5), 1178–1197. doi:10.1037/0022-3514.83.5.1178 Shugan, S. M. (1980). Setember). The costs of thinking. The Journal of Consumer Research, 7, 99–111. doi:10.1086/208799 Simonson, I. (1989). Choice based on reasons: The case of attraction and compromise effects. The Journal of Consumer Research, 16, 158–174. doi:10.1086/209205 Srinivasan, N., & Ratchford, B. T. (1991). An empirical test of a model of external search for automobiles. The Journal of Consumer Research, 18(2), 233–242. doi:10.1086/209255

524

Zeelenberg, M. (1999). Anticipated regret, expected feedback and behavioral decision making. Journal of Behavioral Decision Making, 12(2), 93–106. doi:10.1002/ (SICI)1099-0771(199906)12:2<93::AIDBDM311>3.0.CO;2-S

KEY TERMS AND DEFINITIONS Anticipated Regret: Bettman, Luce and Payne (1998) and Heitmann, Lehmann and Herrmann (2007) state that decision makers feel that they are being evaluated by others (e.g., family and friends) and by themselves about their decisions. As a consequence, consumers try to anticipate regret and do this by searching for more information, in order to maximize the accuracy of their decision.

Self Regulation on Innovative Products Choice

Choice Confidence: Choice confidence is defined as the self-rated confidence in the correctness of the decision (Xia, 1999). Choice Goals: Choice goals are the ones that people try to attain during a product selection and the attainment of these choice goals determines the satisfaction with the decision-making process (Heitmann, Lehmann & Herrmann, 2007). Evaluation Costs: Evaluation costs are the time and effort costs associated with the search and analysis during the choice process. Time and effort are associated with collecting the information needed to evaluate potential alternative options (Burnham, Frels & Mahajan, 2003). Innovation: Rogers (2003) explains that an innovation is an idea, practice or object that is perceived as new by the individual. Thus, a product will be considered an innovation only if it adds

new attributes and/or benefits, and consumers are more likely to adopt an innovation if it is perceived as useful and important to the individual. Justifiability: The justifiability is the ability to justify the choice (Simonson, 1989). Self-Regulation: Self-regulation introduces the concept of regulatory focus, which underlies the hedonic principle that people seek pleasure and avoid pain (Higgins, 1997). This theory has two foci: promotion and prevention, which are different in their strategies to achieve a final end state. The promotion-focused individuals favour approach strategies, so they frame goal pursuit in terms of gains and nongains; prevention-focused individuals do so with respect to losses and nonlosses because of their preference for avoidance strategic means. (Higgins, 1997).

525

526

Chapter 28

The New Product Development Process as a Communication Web, Part I: Introduction, Concepts, and Spanish Context Pilar Fernández Ferrín Universidad del País Vasco, Spain José Antonio Varela González University of Santiago de Compostela, Spain Belén Bande Vilela University of Santiago de Compostela, Spain Oihana Valmaseda Andia Universidad del País Vasco, Spain

ABSTRACT This chapter contributes towards existing literature by analysing the innovation activities of Spanish companies and by proposing New Product Development (NPD) as a communication web. We propose a model, based on literature reviews, that relates the external communication of cross-functional teams to the performance of NPD programmes. The composition of NPD teams and the external communication activities thereof are a core competency for companies and can provide them with major competitive advantages.

DOI: 10.4018/978-1-61350-165-8.ch028

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The New Product Development Process as a Communication Web, Part I

INTRODUCTION Technological advances, competitive pressures and changes in consumer preferences mean that achieving good new product performance is of vital importance to the survival of businesses. In a study regarding successful factors in new product development (NPD), Brown and Eisenhardt (1995) identified a line of research characterised by considering NPD as a communication web. This trend emphasises the importance of variables relating to the external communication of NPD teams and the use of information from various areas of the firm1. As indicated by Ancona and Caldwell (1997), achieving adequate performance requires a high degree of coordination between the different operating units participating in the process and an optimal sharing of information within the organisation. Firms usually respond to the above requirements by entrusting the NPD process to crossfunctional teams, believing that they present considerable advantages over single-function groups when it comes to the development of successful products. In order to achieve their goals, NPD teams must also gather information from several sources, from both inside and outside the organisation (Kleinschmidt et al., 2010). Thus, Allen (1970, 1984) verified that in successful R&D projects some individuals acted as technological gatekeepers, establishing links between the team and the technological environment and gathering technical information from outside and incorporating it into the group. A broader framework of roles was developed by Roberts and Fusfeld (1981), who believe that the successful finalisation of a development project required five different roles2. The two roles most closely related to the interaction between the team and the outside are that of the previously mentioned “gatekeepers,” and that of product champions: individuals who emerge spontaneously from within an organisation, actively and

enthusiastically push each stage of the innovation process forward and contribute decisively to the company’s success (Lichtenthaler & Ernst, 2009; Schön, 1963; Tushman & Nadler, 1986). The aforementioned roles have both been positively linked to the performance of development projects (Allen, 1970; Katz & Tushman, 1981; Markham & Griffin, 1998). Although some studies (Allen 1970, 1984; Markham & Griffin, 1998; Roberts & Fusfeld, 1981) have shown the importance of communication beyond the boundaries of the NPD team and have identified various roles in this process, the external communication of NPD teams has not received enough attention, nor has its impact on new product performance been sufficiently tested (Ancona, 1990). Another aspect that is associated with NPD success and that is directly related to the external communication of NPD teams is the consideration of lead users in the NPD process. Lead users are defined as users that already possess the characteristics that the majority of consumers will present in the future. For businesses, these individuals are great predictors of the trends and needs that will sooner or later emerge in the market (Droge et al., 2010; Spann et al., 2009; von Hippel, 1986). The aim of this study is therefore to examine the impact of the cross-functional composition of NPD teams, and of their external communication activities, on new product performance. In order to do so, we propose a model in which new product programme performance is influenced by: (1) the cross-functional character of the team responsible for NPD; (2) the presence of product champions in the NPD process; (3) the presence of gatekeepers in the NPD process; and (4) the consideration of lead users in NPD. When the composition of NPD teams and the external communication activities thereof positively influence new product performance and the success of innovation activities, the company is provided with a core competency, which competitors find difficult to emulate.

527

The New Product Development Process as a Communication Web, Part I

The chapter is structured as follows: firstly, we collected the most recent data on the innovation activities of European and Spanish companies (EUROSTAT, 2010; INE, 2010). Secondly, we examined the main contributions towards research on NPD measures. Thirdly, we outlined the principal characteristics of the three main lines of research on NPD success factors and explained why we selected the communication web stream. Fourthly, we analysed the primary evidence supporting the influence of the four selected variables on new product performance and put forward our hypotheses (which will be tested in the next chapter). Lastly, we provided a summary of the chapter under the “Conclusion” heading.

THE IMPORTANCE OF PRODUCT INNOVATION FOR SPANISH ENTERPRISES The Community Innovation Survey (CIS) 2008 evaluated European Union (EU) goods and services companies with ten or more employees and found that more than half of these companies carried out innovation activities between 2006 and 2008. The countries in which a higher percentage of companies performed innovation activities were as follows: Germany (80% of companies), Luxembourg (65%), Belgium and Portugal (58%), Ireland, Estonia, Austria, Cyprus and Czech Republic (56%). In Spain the percentage of companies carrying out innovation activities was lower (43%). The aforementioned data includes various types of innovation activities such as product, process, organisation and marketing activities. The Company Innovation Survey 2008, by the Spanish National Institute of Statistics (INE), assessed Spanish companies with ten or more employees, belonging to four different sectors: agriculture, industry, services and construction. The survey provided further information on the innovation activities of Spanish companies. Between 2006 and 2008 a total of 42,206 companies

528

carried out innovation activities and 44% of them (18,493 companies) performed product innovation activities. The number of companies (15,500) that launched products that were new to their company onto the market exceeded the number of companies (8,125) that launched products that were new to their respective markets. If we use the percentage of revenue expenditure on innovation activities as an indicator of a company’s degree of innovation, the manufacturing industry is the most innovative (1.2%), and, within this industry, aeronautical companies (8.2%), pharmaceutical companies (5.6%) and manufacturers of other transport equipment (5.1%) all stand out. More than half of the companies included in the survey (57%) considered product innovation objectives to be extremely important. These Spanish companies particularly wanted to improve the quality of their goods and services, offer a wider range of products, launch their products on to new markets, replace outdated products and processes and increase their market share. It should be noted that 16% of the sales of Spanish companies investing in product innovation relate to products that are new to their market, 19% relate to products that are only new to the company and the remaining 65% relate to products that are already available on the market. Innovation activities entail significant risks for companies and a large number of companies involved in the survey (7,442 companies) admitted to having to abandon their innovation activities either at the initial phase or after the project had started. Many companies (4,599) also confessed to having to suspend their innovation activities3 (Table 1).

NEW PRODUCT DEVELOPMENT: THE THEORETICAL FRAMEWORK New product development (NPD) is defined as the process through which products are developed within an enterprise4. However, this term is not

The New Product Development Process as a Communication Web, Part I

Table 1. Innovation activities of Spanish companies Number of companies

Agriculture

Industry

Services

Construction

Number of innovative companies

42,206

1,341

14,249

19,207

7,410

% of innovative companies/Total

20.81

19.10

31.13

18.66

15.74

Degree of innovation (% of revenue expenditure on innovation activities)

0.95

0.71

1.24

0.93

0.34

Number of companies investing in product innovation

18,493

630

7,730

8,401

1,732

Number of companies that introduced products that were new to the company

15,500

541

6,226

7,083

1,650

Number of companies that introduced products that were new to their market

8,125

198

3.708

3,752

497

% of companies that consider product innovation objectives as important

56.98

60.15

60.95

58.98

41.18

% of revenue expenditure on new or improved products (all companies)

12.69

4.58

20.49

9.87

6.48

19.23

34.32

18.87

19.84

16.57

% of revenue expenditure of innovative companies on: 1. products that are new to the company 2. products that are new to their market

15.69

8.63

16.74

13.71

23.19

3. products that are already available

65.08

57.06

64.32

66.45

60.25

Number of companies that abandoned their innovation activities

7,442

199

3,090

3,224

924

Number of companies that suspended their innovation activities

4,559

237

2,068

1,925

369

Source: INE. Company innovation survey 2008

employed throughout all expert areas. Although the fields of marketing and management use the aforementioned NPD term, research and development (R&D) prefers to use the term “innovation,” engineering opts for the word “design” and, finally, the field of design refers to NPD as the “design of new products.” However, it is now increasingly common for expert areas to adopt terms that initially arose in other areas. NPD is generally considered as an “invention” when the resulting product (good or service) does not make it onto the market and as an “innovation” when the product is successfully launched onto the market. Within a theoretical framework, NPD is viewed as an ability of the enterprise (Day, 1994); an organisational learning process (Hughes and Chafin, 1996; Kleinschmidt et al., 2010; McKee, 1992;

Moorman and Miner, 1997); a collective process involving the generation of innovative ideas (Nonaka, 1991); or as a means of organisational restructuring (Dougherty, 1992). The development of new products is essential to companies if they wish to secure a sustainable competitive edge in the market, as it contributes to process and product innovation. Bruce and Biemans (1995) consider that NPD can be classified into two organisational levels: (1) project level, involving a project for a specific new product and (2) strategic level, involving the analysis of a company’s general NPD. However, for NPD to provide companies with a competitive edge the products must be successful, with good performance. Existing literature suggests various success or performance measures that can be used.

529

The New Product Development Process as a Communication Web, Part I

Various NPD Performance Measures Griffin and Page (1993) investigated which performance measures are most commonly used by researchers and companies. After conducting a literature review and a managerial survey they found 75 different performance measures, 16 of which are commonly used by both groups (core success/failure measures). These measures can be classified into five categories and measure different aspects of NPD success and failure: a. b. c. d. e.

Measures of firm benefits. Programme-level measures. Product-level measures. Measures of financial performance. Measures of customer acceptance.

Companies tend to prefer to use project level NPD measures (groups c, d and e), while researchers are more interested in the success of the NPD programme and its effect on the company (groups a and b), but both agree that measuring NPD success or failure is a multidimensional process. Cooper et al. (2004) collected results from a study on NPD performance and procedures by the American Productivity and Quality Centre. This study analysed 105 business units from different industries and their respective performance measures, classified into two groups: (1) measures at a business unit level; and (2) measures at a NPD project level. The most commonly used NPD performance measures at a business unit level were as follows: a. Percent of business’s revenue from NPs (69% of business units). b. Percent of growth in sales from NPS (50%). c. Overall profits generated by NPs (40%). d. Number of major launches per year (34%). e. Percent of business’s profits from NPs (32%). f. Return of investment on R&D spending (28%).

530

g. Success rate of launched/developed products (28%) The most commonly used NPD performance/ success measures at a project level were as follows: a. b. c. d. e. f.

Profitability (70%). Revenue vs. forecasted revenue (70%). Customer satisfaction (65%). Profitability vs. forecasted profits (49%). Market share (46%). Performance to schedule (on time launch). (41%). g. Time to market (40%). h. Performance to budget (36%). i. Development cost vs. revenue (27%). j. Time to profit /BE time (26%). k. Percentage of repeat customers (19%).

NPD AS A COMMUNICATION NETWORK: AN EMPIRICAL RESEARCH In their extensive review of studies relating to factors of success in NPD, Brown and Eisenhardt (1995) distinguish three currents of research, which consider NPD as: (1) a rational plan; (2) a communication web and (3) a disciplined problem solving mechanism. Although these three streams share methodologies, the authors highlight factors of differing characteristics as variables that explain new product performance. Thus, the rational plan stream focuses on a very broad set of determinants of the product’s financial performance; the communication web approach highlights the effects of communication in the development of the project; and the problem solving approach deals with the adequate development and conception of the product as a foundation for its success. For Brown and Eisenhardt (1995), each stream presents limitations. The rational plan approach deals with an excessive number of factors, relies on a single source of information and is based on insufficiently defined constructs. The second cur-

The New Product Development Process as a Communication Web, Part I

rent (the communication web) ignores important variables by focussing on communication aspects, uses subjective measures of performance and does not take the radical or incremental nature of products into account. The problem solving current also ignores important variables, is based on poorly defined constructs and is markedly geared towards Japanese companies. Our study falls into the second current, NPD as a communication web, as we believe that despite the importance attributed to the communication of the NPD team in various studies, there are still only a small number of international studies on this subject, especially when it comes to external communication. In this study, we examine the effect that four success factors (identified individually in previous studies) have on new product performance: the cross-functional character of the NPD team, the presence of information gatekeepers, the presence of product champions and, finally, the consideration of lead users in the NPD process.

Cross-Functional Teams Clark and Fujimoto (1990, 1991) developed a series of structures that could be adopted by NPD teams. In their analysis of the automobile industry in the USA, Japan and Europe, they found that firms with better performance (in productivity, development time and product quality) tended to structure their NPD through cross-functional teams led by a project manager with expertise in the products and in translating consumer needs into technical specifications. On the whole, studies suggest that cross-functional teams (i.e. project groups whose members are from different functional areas) are vital in achieving good performance. It is believed that the greater the functional diversity of the team, the greater the quantity and variety of information available for the design of the product and the faster the response to problems such as manufacturing difficulties or market mismatches (Brown and

Eisenhardt, 1995; Ernst et al., 2010; Hirunyawipada et al., 2010; Nakata and Im, 2010). Following this line of thought, we hypothesize a positive relationship between the crossfunctional character of the team and new product performance: H1: The cross-functional nature of NPD teams, which is measured by the number of departments participating in the NPD process, will positively influence new product programme performance.

Information or Technological Gatekeepers Effective communication between NPD team members and external groups has been another factor associated with NPD performance. A substantial part of the information needed for NPD comes from outside a company (Allen, 1970) and it seems obvious that such outside information has to enter the organisation, as without it no research and development unit would be able to survive in the long run. According to Tushman (1977), the survival of a firm is dependent upon its members being aware of the key technological developments the company intends to undergo. Teams have two ways of keeping themselves up to date with outside developments (Katz & Tushman, 1981): through (1) direct contact between all project members and (2) indirect contact via certain individuals (i.e. gatekeepers). Technology gatekeepers is the name given by Allen and Cohen (1969) to NPD team members who are closely linked to areas of external information, but who, at the same time, maintain close contact with their colleagues within the organisation and translate external developments and ideas into codes familiar to NPD team members. Lievens and Moenaert (2000, p. 1097) define information gatekeepers as “employees in contact with the public who undertake boundary spanning activities.”

531

The New Product Development Process as a Communication Web, Part I

The role of the gatekeeper is an informal one (Katz & Tushman, 1981).The organisation cannot formalise it but can promote the presence and participation of gatekeepers in projects and try to find them a suitable position within the company. According to Katz and Tushman (1981), gatekeepers fulfil two basic functions: (1) they represent a primary link with external sources of information; (2) they assume an active role with regards to training, development and social matters in their working groups (i.e. they not only gather, interpret and translate external information into a code understood by the organisation, but also make it easier for other members of the organisation to interact with external contacts). The beneficial role of the gatekeeper was also (although indirectly) analysed by Allen (1970), who compared pairs of individuals that worked on solving identical problems, by dividing them into high and low performers according to their performance. The members of the organisation with a high performance rating: (1) consulted colleagues more frequently; (2) had longer discussions with colleagues; (3) confided in a greater number of people, both in their own technical line of work and in other areas; and (4) were more aware of developments in their field. The above appears to be the characteristics of gatekeepers. Regarding the services field, empirical research highlights that active commitment and participation from personnel in contact with the public is crucial with regards to successful innovations in the banking industry (Rogers & Agarwala-Rogers, 1976; Lievens & Moenaert, 2000). These employees “possess valuable commercial information, particularly about the needs of the targeted customers. They can act as gatekeepers of information and pass on crucial market information to their colleagues inside the bank’s project team” (Lievens & Moenaert, 2000, p. 1086). The aforementioned authors analysed the successes and failures of new services provided by Belgian banks and found that extra-project com-

532

munication by gatekeepers of information was positively correlated to the reduction of consumer uncertainty (r = 0.42, p < 0.001), which, in turn, was positively linked to the financial performance of the new service (r = 0.34, p < 0.05). Based on the evidence available concerning the beneficial role of gatekeepers when they collect information from the environment and incorporate it into the group, we posit that the presence of information gatekeepers will be more beneficial for the results of the NPD process than the gathering of information by all members of NPD teams. Thus, we expect the influence on performance to be significantly greater with the presence of gatekeepers than if information were gathered by all members of the team. H2a:The presence of information gatekeepers will positively influence new product programme performance. H2b:The impact on new product programme performance will be greater with the presence of information gatekeepers than when all members of the NPD project team are in charge of gathering external information.

Innovation or Product Champions The presence of a champion is one of the variables most frequently associated with NPD success. However, Markham and Griffin (1998) state that this figure has attained mythical dimensions and that its direct connection to performance has not yet obtained sufficient empirical support. A product champion is defined as an individual who emerges spontaneously from within an organisation and who, by actively and enthusiastically pushing forward each stage of the innovation process, contributes decisively to its success (Schön, 1963; Tushman and Nadler, 1986). In a first description of this figure, Schön (1963) identified a series of functions performed by product champions: (1) they select an idea, (2) they defend it informally but actively and (3)

The New Product Development Process as a Communication Web, Part I

they risk their position and prestige in order to guarantee the innovation’s success. One of the main characteristics of product champions is their ability to identify with an idea and defend it as if it were their own, going beyond the job requirements in order to promote the idea. Research on product champions highlights their capacity to transmit and share their vision regarding an innovation’s potential, to persevere in the face of strong opposition, to show great self-confidence and to gather the support of their colleagues in relation to a particular idea (Howell and Boies, 2004; Howell et al., 2005; Shane, 2002). Howell and Higgins (1990) find that champions of technological innovation show, to a greater extent than non-champions, characteristics of achievement, persistence, innovation, persuasion and risk taking.5 Markham (2002) described a series of skills that champions require in order to get through what he calls the “valley of death” (the gap between the technical invention or market recognition of an idea and the efforts to commercialise it). He developed a template of nine stages that champions must overcome, though not linearly, in order to successfully promote projects. Some of the skills required by champions are to communicate a project’s potential through a persuasive business strategy; obtain the necessary resources; persist in the face of adversity; get the right people involved and seek the necessary support (Howell et al., 2005; Markham, 2002). Kessler (2000), in a study on the development of new multi-industry products, found that when there were more champions, product development costs were lower. Markham and Griffin (1998) analysed the relation between the presence of champions and the following variables: (1) the performance of the NPD process at programme, firm and project levels; (2) the characteristics of the industry; and (3) the characteristics of NPD in relation to the project and to the firm. They concluded that the presence of champions does not directly affect the performance of the NPD

process at company level, but does so indirectly through its impact on the new product programme performance. In accordance with this last result, we support the role of innovation champions and their positive influence on NPD programme performance. Thus, we posit that the presence of champions will positively affect this measure of performance. H3: The presence of innovation champions will positively influence new product programme performance.

Lead Users Lead users of a novel or improved product, process or service have been defined by von Hippel (1986) as those that display two characteristics: (1) they handle common market needs, even months or years before the majority of the market has become aware of such needs and (2) they significantly benefit from obtaining a solution to these needs. Franke et al. (2006) explain that these two characteristics are conceptually separate since they both originate from different lines of research and have different functions in the lead-user theory: “High benefits expected are associated with innovation likelihood, and a position ahead of the trend is associated with innovation attractiveness” (p. 311). According to von Hippel (1986), the more a lead user will benefit from a product or process that they need, the more effort they will make in order to find a solution (i.e. the more resources they will dedicate to the search for this solution). A lead user has a double-value in the NPD process: not only can they provide information on unfulfilled needs, but they can also offer their own opinions on how to suitably meet such needs. This active role of lead users in the development of product concepts was corroborated in different case studies. Herstatt and von Hippel (1997) found that Swiss machinery firms considered the development of products in cooperation with their users

533

The New Product Development Process as a Communication Web, Part I

to be the most effective way of understanding consumer needs. However, they also verified that this method was rarely used, the main limitation being that it was very complex, costly and difficult to apply. In markets characterised by rapid change, lead users can act as an important element in achieving successful NPD. Lead user involvement “clearly helps to acquire important need and solution information. This information prevents delays in later stages of the NPD process and ensures that the new product provides an advantage to customers” (Langerak & Hultink, 2008, p.165). Von Hippel (1986) proposed a four-stage process in order to incorporate lead users into market research. Further studies have demonstrated the suitability of this method for different industries (Herstatt & von Hippel, 1997; Urban & von Hippel, 1998). Most studies have focussed on a particular industry and a particular product. Lüthje and Herstatt (2004) gathered the results of eight previous studies, centred on different products such as open-air sports equipment and surgical equipment, and verified that the percentage of users that developed improvements or new applications for their own use varied from 10 to 38 per cent. Morrison et al. (2000) found that, for two providers of information search programmes for libraries, at least 20 per cent of the improvements made by users were new to them and interesting from a commercial point of view. Studies have analysed the possible reasons why lead users tend to develop their own product improvements (Lüthje & Herstatt, 2004; Morrison et al., 2000; von Hippel et al., 2000) and even share their results with other users (Morrison et al., 2000). Schreier & Prügl (2008) studied the antecedents and consequences of consumer lead userness in the context of extreme sports. The antecedents included consumer knowledge, user experience and two personality variables: locus of control and innovativeness. The lead users in the study not only showed innovation by offering

534

ideas for new products but they were also quicker and keener to embrace new products. However, we believe that there is no empirical sample study that proves the possible influence of the lead users method proposed by von Hippel (1986), or of any other alternative method, on new product performance. A central problem in these types of studies is that they do not include a measurement scale, or if they do, it is always very simple6. Morrison et al. (2004) analysed the nature of the lead users construct. They proposed a similar construct: LES (leading edge status) and a scale formed by four dimensions and seven indicators. This continuous measure was found to be both reliable and valid when tested on a sample of information search programme users from Australian libraries. This scale was designed to identify lead users of a product, but not to measure the extent to which suppliers or manufacturers of a product use lead users and incorporate their ideas into NPD. This, on the other hand, is precisely what we aim to do in this study. Following von Hippel (1986) as regards the relation between lead users and success in NPD, we hypothesize that a firm’s consideration of these users in the process of NPD will favour NPD performance. H4: The participation of lead users in NPD will positively influence new product programme performance. Figure 1 shows the four relationships hypothesized.

CONCLUSION By analysing the most recent data available on the innovation activities of Spanish companies, this chapter has been able to confirm the importance of general innovation and particularly of product innovation for these companies. Although Spain

The New Product Development Process as a Communication Web, Part I

Figure 1. Cross-functional teams, external communication and new product performance

has a lower percentage of innovative companies compared to other European countries, the findings show that Spanish companies regard product innovation objectives as very important and recognise that a significant portion of their sales are thanks to new products. In the second half of this chapter we suggest considering NPD as a communication web. We hypothesise that there will be increased new product programme performance in firms that use cross-functional teams, rely on the presence of product champions and information gatekeepers and take into account the opinions of more advanced users.

REFERENCES Allen, T. J. (1970). Communication networks in R&D laboratories. R & D Management, 1(1), 14–21. doi:10.1111/j.1467-9310.1970.tb01193.x Allen, T. J. (1984). Managing the flow of technology: Technology transfer and the dissemination of technology information within the R&D organisation. Cambridge, MA: MIT Press.

Allen, T. J., & Cohen, S. I. (1969). Information flow in two R&D laboratories. Administrative Science Quarterly, 14, 12–19. doi:10.2307/2391357 Ancona, D. G. (1990). Outward bound: Strategies for team survival in an organisation. Academy of Management Journal, 33(2), 334–365. doi:10.2307/256328 Ancona, D. G., & Caldwell, D. F. (1997). Making teamwork work: Boundary management in product development teams. In Tushman, M. L., & Anderson, P. (Eds.), Managing strategic innovation and change: A collection of readings (pp. 433–442). Oxford, UK: Oxford University Press. Brown, S. L., & Eisenhardt, K. M. (1995). Product development past research, present findings and future directions. Academy of Management Review, 20(2), 343–378. Bruce, M., & Biemans, W. G. (1995). Product development: Meeting the challenge of the designmarketing interface. Chichester, England: John Willey & Sons.

535

The New Product Development Process as a Communication Web, Part I

Chesbrough, H. W. (2003). The era of open innovation. MIT Sloan Management Review, 4(3), 35–41. Clark, K. B., & Fujimoto, T. (1990). The power of product integrity. In Clark, K. B., & Wheelwright, S. C. (Eds.), The product development challenge: Competing through speed, quality and creativity (pp. 277–296). Boston, MA: Harvard Business Review Book. Clark, K. B., & Fujimoto, T. (1991). Product development performance: Strategy, organisation and management in the world auto industry. Boston, MA: Harvard Business School Press. Cooper, R. G., Edgett, S. J., & Kleinschmidt, E. J. (2004). Benchmarking best NPD practices- I. Research Technology Management, 47(1), 31–43. Day, G. (1994). The capabilities of market-driven organizations. Journal of Marketing, 58, 37–52. doi:10.2307/1251915 Dougherty, D. (1992). A practice-centred model of organisational renewal through product innovation. Strategic Management Journal, 13, 77–92. doi:10.1002/smj.4250131007 Droge, C., Stanko, M. A., & Pollitte, W. A. (2010). Lead users and early adopters on the Web: The role of new technology product blogs. Journal of Product Innovation Management, 27(1), 66–82. doi:10.1111/j.1540-5885.2009.00700.x Ernst, H., Hoyer, W. D., & Rübsaamen, C. (2010). Sales, marketing and research-and-development cooperation across new product development stages: Implications for success. Journal of Marketing, 7(5), 80–92. doi:10.1509/jmkg.74.5.80 Eurostat News release (2010). 6th community innovation survey. More than half of EU27 enterprises are innovative (166/2010).

536

Franke, N., von Hippel, E., & Schreier, M. (2006). Finding commercially attractive user innovations: A test of lead-user theory. Journal of Product Innovation Management, 23(4), 301–315. doi:10.1111/j.1540-5885.2006.00203.x Griffin, A., & Page, A. L. (1993). An interim report on measuring product development success and failure. Journal of Product Innovation Management, 10, 291–308. doi:10.1016/07376782(93)90072-X Herstatt, C., & von Hippel, E. A. (1997). Developing new product concepts via the lead user method: A case study in a low-tech field. In Tushman, M. L., & Anderson, P. (Eds.), Managing strategic innovation and change: A collection of readings (pp. 376–384). Boston, MA: Oxford University Press. Hirunyawipada, T., Beyerlein, M., & Blankson, C. (2010). Cross-functional integration as a knowledge transformation mechanism: Implications for new product development. Industrial Marketing Management, 39(4), 650–660. doi:10.1016/j. indmarman.2009.06.003 Howell, J. M., & Boies, K. (2004). Champions of technological innovation: The influence of contextual knowledge, role orientation, idea generation, and idea promotion on champion emergence. The Leadership Quarterly, 15, 123–143. doi:10.1016/j. leaqua.2003.12.008 Howell, J. M., & Higgins, C. A. (1990). Champions of technological innovation. Administrative Science Quarterly, 35, 317–341. doi:10.2307/2393393 Howell, J. M., Shea, C. M., & Higgins, C. A. (2005). Champions of product innovations: Defining, developing, and validating a measure of champion behaviour. Journal of Business Venturing, 20, 641–661. doi:10.1016/j.jbusvent.2004.06.001

The New Product Development Process as a Communication Web, Part I

Hughes, G. D., & Chafin, D. C. (1996). Turning new product into a continuous learning process. Journal of Product Innovation Management, 13, 89–104. doi:10.1016/0737-6782(95)00112-3 Katz, R., & Tushman, M. L. (1981). An investigation into the managerial roles and career paths of gatekeepers and project supervisors in a major R&D facility. R & D Management, 11(3), 103–110. doi:10.1111/j.1467-9310.1981.tb00458.x Kessler, E. H. (2000). Tightening the belt: Methods for reducing development costs associated with new product innovation, 17, 59-92.

Markham, S. K., & Griffin, A. (1998). The breakfast of champions: Associations between champions and product development environments, practices and performance. Journal of Product Innovation Management, 15, 436–454. doi:10.1016/S0737-6782(98)00010-1 McKee, D. (1992). An organisational learning approach to product innovation. Journal of Product Innovation Management, 9, 232–245. doi:10.1016/0737-6782(92)90033-9 Moorman, C., & Miner, A. S. (1997). The impact of organisational memory on new product performance and creativity. JMR, Journal of Marketing Research, 34, 91–106. doi:10.2307/3152067

Kleinschmidt, E., de Brentani, U., & Salomo, S. (2010). Information processing and firm-internal environment contingencies: Performance impact on global new product development. Creativity and Innovation Management, 19(3), 200–218. doi:10.1111/j.1467-8691.2010.00568.x

Morrison, P. D., Roberts, J. H., & Midgley, D. F. (2004). The nature of lead users and measurement of leading edge status. Research Policy, 33, 351–362. doi:10.1016/j.respol.2003.09.007

Langerak, F., & Hultink, E. J. (2008). The effect of new product development acceleration approaches on development speed: A case study. Journal of Engineering and Technology Management, 25(3), 157–167. doi:10.1016/j.jengtecman.2008.06.004

Morrison, P. D., Roberts, J. H., & von Hippel, E. (2000). Determinants of user innovation and innovation sharing in a local market. Management Science, 46(12), 1513–1527. doi:10.1287/ mnsc.46.12.1513.12076

Lichtenthaler, U., & Ernst, H. (2009). The role of champions in the external commercialization of knowledge. Journal of Product Innovation Management, 26(4), 371–387. doi:10.1111/j.15405885.2009.00666.x

Nakata, C., & Im, S. (2010). Spurring crossfunctional integration for higher new product performance: A group effectiveness perspective. Journal of Product Innovation Management, 27(4), 554–571. doi:10.1111/j.1540-5885.2010.00735.x

Lievens, A., & Moenaert, R. K. (2000). Communication flows during financial service innovation. European Journal of Marketing, 34(9/10), 1078–1110. doi:10.1108/03090560010342485

Nakata, C., & Sivakumar, K. (1996). National culture and new product development: An integrative review. Journal of Marketing, 60, 61–72. doi:10.2307/1251888

Lüthje, C., & Herstatt, C. (2004). The lead user method: An outline of empirical findings and issues for future research. R & D Management, 34(5), 553–567. doi:10.1111/j.1467-9310.2004.00362.x

Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, 69(NovemberDecember), 96–104.

Markham, S. K. (2002). Moving technologies from lab to market. Research Technology Management, 45(6), 31–42.

Roberts, E., & Fusfeld, A. (1981). Staffing the innovative technology-based organisation. Sloan Management Review, 22(3), 19–34.

537

The New Product Development Process as a Communication Web, Part I

Rogers, E. M., & Agarwala-Rogers, R. (1976). Communication in organisations. London, UK: The Free Press, Collier Macmillan Publishers.

von Hippel, E. (1986). Lead users: A source of novel product concepts. Management Science, 32(7), 791–805. doi:10.1287/mnsc.32.7.791

Schön, D. A. (1963). Champions for radical new inventions. Harvard Business Review, 41(marchApril), 77–86.

von Hippel, E., Thomke, S., & Sonnack, M. (2000). Creating breakthroughs at 3M. Health Forum Journal, 43(4), 20–27.

Schreier, M., & Prügl, R. (2008). Extending lead-user theory: Antecedents and consequences of consumers’ lead userness. Journal of Product Innovation Management, 25(4), 331–346. doi:10.1111/j.1540-5885.2008.00305.x

KEY TERMS AND DEFINITIONS

Shane, S. A. (2002). Are champions different from non-champions? Journal of Business Venturing, 9(5), 397–421. doi:10.1016/08839026(94)90014-0 Smith, D. J. (2007). The politics of innovation: Why innovations need a godfather. Technovation, 27(3), 95–104. doi:10.1016/j.technovation.2006.05.001 Song, M., van der Bij, H., & Weggeman, M. (2006). Factors for improving the level of knowledge generation in new product development. R & D Management, 36(2), 173–187. doi:10.1111/ j.1467-9310.2006.00424.x Spann, M., Ernst, H., Skiera, B., & Soll, H. (2009). Identification of lead users for consumer products via virtual stock markets. Journal of Product Innovation Management, 26(3), 322–335. doi:10.1111/j.1540-5885.2009.00661.x Tushman, M. (1977). Special boundary roles in the innovation process. Administrative Science Quarterly, 22, 587–605. doi:10.2307/2392402 Tushman, M., & Nadler, D. (1986). Organizing for innovation. California Management Review, 28(3), 74–92. Urban, G. L., & von Hippel, E. (1988). Lead user analysis for the development of new industrial products. Management Science, 34(5), 562–582. doi:10.1287/mnsc.34.5.569

538

Gatekeepers: In successful R&D projects some individuals acted as technological gatekeepers, establishing links between the team and the technological environment and gathering technical information from outside and incorporating it into the group (Allen 1970, 1984). Lead Users: Are defined as users that already possess the characteristics that the majority of consumers will present in the future. For businesses, these individuals are great predictors of the trends and needs that will sooner or later emerge in the market (Droge et al., 2010; Spann et al., 2009; von Hippel, 1986). Product Champions: Individuals who emerge spontaneously from within an organisation, actively and enthusiastically push each stage of the innovation process forward and contribute decisively to the company’s success (Lichtenthaler and Ernst, 2009; Schön, 1963; Tushman and Nadler, 1986).

ENDNOTES 1



Chesbrough (2003) states that the innovation strategies of companies can be classified into two extremes: “closed innovation” and “open innovation.” Open innovation is where companies value and take advantage of knowledge and experience from outside the company and closed innovation is where the company itself is the source of innovative ideas.

The New Product Development Process as a Communication Web, Part I

2



3



4



(1) generation of ideas for new products or processes; (2) “championing,” or gaining the support of top management for the new idea; (3) project leadership, or the coordination of people and activities to transform the idea into a product; (4) “gatekeeping,” or gathering external information and introducing it into the team; and (5) “sponsoring” (i.e. providing support and resources for the project). Similarly, Smith (2007) suggests that a series of organisational roles would help to minimize the risk of failure of new products. He mentions the organisational roles of the technological gatekeeper, the product champion and the sponsor/coach, all of which have been previously considered in prior studies, but he also introduces a new role, that of the goodfather: a senior, highly respected figure who offers support in overcoming the obstacles encountered in major new product development projects. Data retrieved November 22, 2010 from http://www.ine.es/jaxi/ menu. do?type=pcaxis&path=% 2Ft14/ p061&file=inebase&L=0 Nakata & Sivakumar (1996) define the development of new products, not only as the process by which products are developed, but also as the results of the aforementioned process.

5



6



Some of these characteristics are present in the figure of the “champion of external knowledge exploitation,” defined by Lichtenthaler and Ernst (2009, p. 373) as “an individual who informally emerges in an organisation and makes a decisive contribution to the spreading of knowledge by actively and enthusiastically promoting external knowledge within the organisation.” For these researchers, this type of champion represents an essential success factor since he/she contributes greatly to increasing the communication of external knowledge. Song et al. (2006, p.186) use the item “Compared to our major competitors, our company has a stronger network of lead users” and Langerak y Hultink (2008) use a Likert scale of three items to measure the participation of lead users in the development of new products, in which companies are asked about the various techniques they use throughout the NPD process. Specifically, they were asked to indicate the level of lead user involvement in their NPD processes and the extent to which they employed market simulation techniques and simulated prototype testing.

539

540

Chapter 29

The New Product Development Process as a Communication Web, Part II: Analysis of Spanish Firms Pilar Fernández Ferrín Universidad del País Vasco, Spain José Antonio Varela González University of Santiago de Compostela, Spain Belén Bande Vilela University of Santiago de Compostela, Spain Oihana Valmaseda Andia Universidad del País Vasco, Spain

ABSTRACT In the previous chapter (Part I), we proposed a model relating the composition and external communication activities of NPD teams to the performance of NPD programmes. In this chapter (Part II), through the use of structural equations analysis, we compare the model to a sample of 136 managers from different functional areas at 121 innovative Spanish firms. The results indicate that the impact of explanatory variables on new product programme performance differs according to the measure of performance considered. The cross-functional nature of NPD teams, the presence of product champions in NPD teams and the gathering of information by all NPD team members were all shown to positively influence new product performance. Firms should be aware of the importance of the aforementioned variables.

DOI: 10.4018/978-1-61350-165-8.ch029

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The New Product Development Process as a Communication Web, Part II

INTRODUCTION

HYPOTHESES

In Part I of this chapter we suggested considering New Product Development (NPD) as a communication web, contributing towards the innovation activities of companies and providing them with a sustainable competitive advantage. The external communication activities and cross-functional nature of NPD teams positively influences new product programme performance and provides companies with attributes that competitors find difficult to emulate. The aim of this chapter is to compare the proposed model and examine whether or not new product programme performance is influenced by: (1) the cross-functional nature of NPD teams; (2) the presence of product champions in the NPD process; (3) the presence of gatekeepers in the NPD process; and (4) NPD lead users. We tested the aforementioned model using a sample of 136 managers from different functional areas at innovative Spanish firms. The results obtained from a structural equations analysis indicated that the impact of explanatory variables on new product programme performance differs according to the measure of performance considered. Our study contributes towards existing NPD literature as, unlike other studies on the communication web approach, it takes a development programme of three years as its unit of analysis and examines explanatory variables whose effects on performance have not yet been studied together, in firms that belong to different sectors and can provide data from cross-functional sources. The chapter is structured as follows: firstly, we recapitulated the hypotheses proposed in Part I. Secondly, we described the method used, tested the model and commented on the main findings. We subsequently identified the implications of the findings for NPD managers and, finally, discussed the chapter’s limitations, as well as possible future lines of research.

Based on previous evidence (Clark & Fujimoto, 1990, 1991; Katz & Tushman, 1981; Markham & Griffin, 1998; Von Hippel, 1986), we propose that new product programme performance will be influenced by the cross-functional nature of NPD teams and their external communication activities. Specifically, we hypothesise the following: H1: The cross-functional nature of NPD teams, which is measured by the number of departments participating in the NPD process, will positively influence new product programme performance. H2a:The presence of information gatekeepers will positively influence new product programme performance. H2b:The impact on new product programme performance will be greater with the presence of information gatekeepers than when all members of the NPD project team are in charge of gathering external information. H3: The presence of innovation champions will positively influence new product programme performance. H4: The participation of lead users in NPD will positively influence new product programme performance.

RESEARCH METHODOLOGY Sample The sample was selected from the innovative firms database of the Centre for Technological Development of Industries (CDTI): an organisation that promotes the innovation and technological development of Spanish firms. In order to form part of the sample firms had to meet two requirements: belong to one of the industries shown in Table 11 and have two or more people dedicated to R&D tasks. These conditions were met by 600 of the firms. 541

The New Product Development Process as a Communication Web, Part II

Two questionnaires were posted to each of the 600 firms, one addressed to the R&D manager and the other to his/her co-worker in the commercial or marketing department. A total of 121 firms (20.2 per cent of those contacted) responded to the questionnaires. Although the letters were addressed to the R&D and marketing managers, in some cases the responses came from managers in other areas2. A total of 136 questionnaires were received from 121 companies.

Measures All the measurement scales are subjective and reflect the perceptions of managers from different areas (above all from R&D and marketing departments) on new product programme performance in the last three years, the average number of departments participating, the presence of information gatekeepers and product champions and, finally, the consideration of lead users. To measure new product programme performance we used the scale designed by Cooper (1984), consisting of six items or indicators corresponding to three dimensions: the overall programme performance (three items), the impact of

Table 1. Industries in the sample Industry

Number of companies

Food and Beverage industry

5

Chemical industry

50

Rubber and plastic material manufacture industry

21

Glazed tile and ceramics floor tile manufacture industry

4

Machinery and mechanical equipment industry

24

Electrical, electronic and optical material industry

26

Motor vehicles, trailers and semi-trailers manufacture industry

3

Telecommunications industry.

2

Metallurgy industry

1

542

the programme on the firm (two items) and the new products overall success rating (one item). The measurement scales for the variables (presence of gatekeepers, presence of product champions, consideration of lead users, physical proximity and cross-functionality) were developed for the study on the basis of the definitions of previous studies. The measurement scale used for the presence of gatekeepers was based on the evidence presented in previous research papers regarding the benefits of using a limited number of key people within the development project in order to obtain external information, as opposed to all team members being equally responsible for keeping up with changes in the environment (Allen and Cohen, 1969; Allen, 1970). For this reason, rather opposing suggestions were made (see Appendix): “In my firm there are one or more people who gather and interpret external information on changes in the environment and make it more accessible for us (V9).” “All members of the NPD project teams are expected to keep up with changes in the environment” (V10). The one-item measure used for the presence of product champions was based on the principal characteristics of this figure as highlighted in previous research papers. Therefore, the managers of different departments were asked to express how much they agreed or disagreed with the following statement: “In each of our project teams there is at least one person who actively and enthusiastically drives forward each NPD stage, takes risks and does not give up when faced with obstacles” (V8). Consideration of lead users in NPD is summarised by the variable V11: “To seek out market opportunities the firm pays special attention to “pioneering” consumers (i.e. those who identify

The New Product Development Process as a Communication Web, Part II

general market needs, but identify them months or years before the majority of the market). For this measure we took into account the definition by von Hippel (1986), but opted to replace the term “lead users” with that of “pioneering consumers,” in case managers were unfamiliar with the former. The gatekeeper, product champion and lead user scales were reviewed by 14 managers, who did not observe any inconsistencies in the measures proposed. These variables were measured by Likert type scales of seven points (1= totally disagree; 7= totally agree) Finally, the cross-functional nature of NPD teams was measured using managerial estimates of roughly how many departments would participate in the NPD teams in the following three years (V7).

ANALYSIS AND RESULTS The industry with most cases in the sample is that of the chemical sector (50 cases), followed by the electronics sector (26 cases), the machinery construction sector (24 cases) and finally the plastic manufacturing sector (21 cases). The means and standard deviations of the indicators of the study enable us to verify that, in general, managers strongly agree that: (1) the NPD programme greatly influences company sales and profits; (2) the objectives of the programme have been achieved; (3) costs have been covered by generated profits; and (4) the programme has been a success with regards to overall profitability (see Appendix). In mean values, approximately one third of the firms’ sales come from products launched onto the market in the last three years and more than half (59 per cent) of the new products have been a commercial success in the last three years.

Validation of the Measurement Scales We removed four items from the new product performance measurement scale (the only one with various indicators). The items’ corrected item-total correlation was below the recommended 0.3. The alpha value rose substantially when only V1 and V2 were considered (alpha = 0.82). The percentage of variance extracted on carrying out a principal components factor analysis with these two indicators was very high (84.72%). Therefore, from the NPD programme performance scale initially proposed (i.e. one with six indicators), a two-indicator scale was developed: (1) from an overall profitability standpoint, our new product development programme has been successful; and (2) the overall performance of our new product programme has met our objectives. The proportion of new, commercially successful products in the last three years and the proportion of sales as a result of new products were only slightly related to the other indicators on the scale. In order to somehow capture the three dimensions of the performance of new products scale proposed by Cooper (1984), we considered three different measures. Performance 1 corresponds to the overall programme performance and has the two indicators that passed the reliability analysis; Performance 2 measures the impact of the programme on the firm; and Performance 3 is an overall success rating of new products. Convergent validity of the only scale with more than one indicator was examined using exploratory factor analysis. The items substantially load onto their respective factors. The loads of the two indicators of the first measure of new product performance (Performance 1: overall programme performance) are equal to 0.92, which indicates convergent validity.

543

The New Product Development Process as a Communication Web, Part II

Testing of the Hypotheses To test the hypotheses we proposed a structural model that considered the influence of four independent variables: cross-functional nature of the team, presence of product champions, presence of gatekeepers and consideration of lead users on new product performance. Firstly, an estimate of the model (using the AMOS 4.0 programme) had to be made, considering the first measure of new product performance (Performance 1), and as a measure of the presence of gatekeepers a single indicator (V9). The crossfunctional nature of the NPD team, measured by the number of departments that usually participate in the NPD process, was excluded from the analysis after it was found that it did not affect performance. The gatekeeper variable was not significantly related to performance, while the gathering of external information by all members of the NPD project teams (V10) did positively influence performance p < 0.1 (see Table 2). The relation of the other two independent variables (consideration of lead users and presence of product champions) with new product performance was significant for p < 0.01.

The presence of champions positively and substantially influenced performance (b = 0.52), while consideration of lead users when developing a new product (contrary to what we presumed) is negatively related to performance (b = -0.22). This is paradoxical and contradicts evidence presented in former studies (Von Hippel, 1986; Herstatt and Von Hippel, 1997). In view of the above results, and considering the first measure of new product performance (Performance 1) (see Table 2 and Figure 1), we can accept H3 (the presence of champions positively influences performance), but cannot accept the three remaining hypotheses, as neither the cross-functional nature of the team (H1), the presence of information gatekeepers (H2a), nor the consideration of lead users (H4) favour the programme’s overall performance. We cannot accept H2b either because the presence of information gatekeepers does not benefit performance more than the collection of external information by all team members. In fact, the opposite appears to be true (i.e., the gathering of information by multiple parties favours the performance of the NPD project) whereas the presence of information gatekeepers has no influence on performance.

Table 2. Structural equation model results: parameter estimates (Performance 1) Effect of

On

Estimate

S.E.

C.R.

Standardised Estimate

H2b

All members (V10)

Performance 1

0.13

0.07

1.90

0.17

H3

Champions (V8)

Performance 1

0.43

0.07

5.73

0.52

H4

Lead users (V11)

Performance 1

-0.17

0.06

-2.61

-0.22

Performance 1

V1

1.00

-

-

0.94

Performance 1

V2

0.70

0.12

6.06

0.70

Champions-lead users

0.63

0.19

3.31

0.31

Champions-All members (V10)

0.93

0.20

4.65

0.46

Lead users-All members (V10)

0.67

0.21

3.28

0.31

Convariance

Chi-squared . 1.44; d.f. = 2; p = 0.49

544

Chi-squared/ d.f 0.72

R2 0.34

CFI 1.00

S.E.

GFI 0.99

AFGI 0.97

C.R.

NFI 0.99

Correlation

TLI 1.02

RMSEA 0.00

The New Product Development Process as a Communication Web, Part II

Figure 1. Structural model for the first measure of performance (Performance 1)

Table 3. Structural equation model results: Parameter estimates (Performance 2) On

Effect Of H1 H2b

Cross-functional teams

Estimate

Performance 2

2.06

S.E. 1.18

C.R. 1.75

Standardized Estimate 0.16

All members (V10)

Performance 2

2.66

1.37

1.94

0.17

Performance 2

V5

1.00

-

-

1.00

Chi-squared 0.86; g.1 = 1; p = 0.35

Chi-squared/ d.f. 0.86

R2 0.05

CFI 1.00

GFI 0.99

AGFI 0.97

NFI 0.89

TLI 1.08

RMSEA 0.00

Figure 2. Structural model for the second measure of performance (Performance 2)

When the measure of performance in question is the proportion of total sales thanks to new products (Performance 2), only two out of the initial four variables are statistically and significantly connected to new product performance (i.e. p < 0.1) (see Table 3 and Figure 2). Given that R2 is low, the input of development teams, as well as of the gathering of information from the external environment, are fairly limited, but still significant.

When considering “the proportion of commercially successful new products in the last three years as a measure of performance (Performance 3: V6), two variables are distinctly connected to new product performance (V8 and V11), but the model is not identified (as there is not enough scope in order to estimate it). With the aim of solving this problem, we recommend a multiple regression with Performance 3 (V6) as a dependent variable and V8 (champions) and V11 (lead users) as independent variables.

545

The New Product Development Process as a Communication Web, Part II

Table 4. Regression results (Performance 3)ª Model 1 a

R 0.29

R squared 0.08

Corrected R squared

S.E.

0.07

30.31

Independent variables (Constant term), V8 (champions); V11 (lead users).

Table 5. Estimatesª Estimates Model 1

a

Standardized Estimates

B

S.E

t

Sig.

Beta

(Constant term)

43.48

12.20

3.56

0.00

Champions (V8)

6.95

2.22

0.30

3.12

0.00

Lead users (V11)

-4.24

1.96

-0.21

-2.16

0.03

Dependent variable: Performance 3.

The analysis carried out using the SPSS statistical programme is shown in Table 4 and Table 5. Although R2 is not very high, the coefficients of the independent variables are significant and show: on the one hand, that the presence of product champions positively influences the proportion of new products that have achieved commercial success in the last three years; and, on the other hand, that consideration of the needs of lead users negatively affects new product performance.

DISCUSSION AND MANAGERIAL IMPLICATIONS The cross-functional nature of NPD teams (measured by estimating the average number of departments participating in the NPD process) positively influences one of the measures of new product performance (i.e. the total percentage of sales represented by new products) (Performance 2), but does not influence the other two measures (overall programme performance and new products overall success rating). The frequency distribution of this variable allows us to confirm that only three managers use single-function teams within their firms, eight managers make use of the participa-

546

tion of two departments, and 97 (out of a total of 130 responses) use cross-functional teams from three to five different departments (the number of managers that use cross-functional teams from five departments is considerably low). Given that virtually all contacted firms use cross-functional teams for NPD, we cannot verify the advantages of this option over that of single-function teams. The variable is therefore not proven to be significant when it comes to explaining performance. As a result, it can be concluded that innovative Spanish firms have faith that teams formed by people from different functional areas can carry out the development of new products. A direct and positive link between managers’ views on the presence of product champions in NPD teams and the performance of the programme has also been found to exist, both when overall programme performance was considered (b=0.52) and when success of new products was considered (b=0.30) (see Table 6). These results are consistent with previous studies (Markham, 1998; Markham and AimanSmith, 2001; Markham and Griffin, 1998) and highlight the importance of product champions. For some authors, cross-functional teams and the formalisation of NPD processes do not eliminate

The New Product Development Process as a Communication Web, Part II

Table 6. Summary of the main results €€€€€Effect of

€€€€€On €€€€€Performance 1: €€€€€Overall programme performance

€€€€€Performance 2: €€€€€Impact of the programme on the firm

€€€€€Performance 3: €€€€€Index of success of new products

€€€€€1. Cross-functional teams

€€€€€NO

€€€€€YES (+)

€€€€€NO

€€€€€2a. Gatekeepers

€€€€€NO

€€€€€NO

€€€€€NO

€€€€€2b. All members

€€€€€YES(+)

€€€€€YES(+)

€€€€€NO

€€€€€3. Champions

€€€€€YES(+)

€€€€€NO

€€€€€YES(+)

€€€€€4. Lead users

€€€€€YES(-)

€€€€€NO

€€€€€YES(-)

the need for product champions, “those passionate individuals who believe in the stated innovation strategy of the organisation and recognise the potential in an idea or opportunity” (Markham and Aiman-Smith, 2001, p.47). The gathering of information from the environment by all the members of NPD teams was also shown to positively influence performance, especially overall programme performance and sales of new products (b = 0.17 in both cases). These results are supported by previous studies (Ancona, 1990; Ancona and Caldwell, 1997). However, the presence of information gatekeepers was not significantly related to new product performance, contrary to what previous studies have found (Allen, 1970; Katz and Allen, 1981; Lievens and Moenaert, 2000). This could be due to the measure used or to the characteristics of the sample. However, we believe that, in addition to the aforementioned reasons, there are also other reasons. Allen (1966) verified that, despite the apparent benefits associated with consulting colleagues, in the projects studied, more members resorted to obtaining ideas from external sources than from within their own organisations by simply consulting a member of technical staff. The performance achieved after acquiring information from outside was, however, rather poor. It is ironic that a high number of employees used sources of informa-

tion that ultimately led to a poorer performance. Perhaps they did so as they felt embarrassed about admitting to one of their colleagues that they needed help in solving a problem. It may also be the case that gatekeepers are not as equally valuable in some situations as they are in others. For Katz and Tushman (1981) the key can be found in the distinction between research projects or projects with a universal orientation, and development projects or projects with a local orientation. When technological activities have a local perspective, individuals that take part in them share the same language, and communication is quick and easy. However, the acquisition and interpretation of information from external sources that use another language, makes communication more difficult. Projects with a local orientation require gatekeepers to establish a link with external areas, meaning contact with the outside environment is indirect. Projects with a universal orientation, on the other hand, use the same language that is used externally. As there are no communication barriers there is also no need for gatekeepers. Communication with the outside occurs by all members of the group directly. Overall, research projects without gatekeepers and development projects with gatekeepers were associated with higher performance.

547

The New Product Development Process as a Communication Web, Part II

In their recent study, Whelan et al. (2010) questioned the individual role of gatekeepers. These researchers recommend that the gatekeeper concept be re-examined in view of the latest advances in Internet technology, which have significantly changed the way people acquire and share information. Although we may think that thanks to the Internet the circulation of and access to information on technological advances is within reach for all members of new product development teams, Whelan et al. (2010) found that, even though searching for information is a great deal easier due to the Internet, the verification, translation and internalization of such information requires skills held only by a select few. Whelan et al.’s case-study on a medical devices company demonstrates how the role of gatekeeper can divide a workforce into two: the external communication stars, who are in charge of searching the Internet, informing the group of the latest technological developments and verifying the reliability of the information before discussing it with the internal communication stars, in turn, are in charge of finding a possible use for such information within the group and translating it into comprehensible terms for those that intend to use it. This kind of work presents new and interesting opportunities in relation to future research. Finally, our findings indicate that Spanish firms’ employment of lead users in NPD negatively influences two of the three measures of performance considered, mainly the overall programme performance and the new product success. These results do not correspond to those of previous studies, which draws attention to the incorporation of information from consumers into the project team (Hong et al., 2004; Lüthje and Herstatt, 2004; Morrison et al., 2000; Von Hippel, 1986; Von Hippel et al., 2000), but they are consistent with the research of Song et al. (2006), who found that the use of lead user networks is negatively associated with the acquisition of new NPD knowledge.

548

The lead users method is proposed as a solution for those firms that wish to carry out radical improvements but that, single-handedly, are only able to develop line extensions and incremental innovations. Von Hippel et al. (2000) state that the lead user method is used in eight out of the 55 3M firm divisions and those cross-functional teams that take lead users’ opinions into account are very satisfied with the result. However, these researchers also posit that the use of this method does not guarantee success. A lack of management support or a team’s inability to carry out the process can cause project failure. We believe that this negative impact of the consideration of lead users on NPD could be due to several reasons: •

Firms may not be following an appropriate method/process for studying company needs and identifying users. The method proposed by von Hippel (1986), developed in later studies (Lüthje and Herstatt, 2004; von Hippel et al., 2000) discusses the need for development projects with lead users to go through four phases: (1) initiation and establishment of bases; (2) determination of tendencies; (3) identification of lead users and (4) development of product concept. Enkel et al. (2005) also put forward four phases to involve the customer in the NPD process. These researchers argue that companies need to understand how and when to use a lead-user approach in order to reduce the risks involved in radical innovations. In this respect, the Internet provides ways to incorporate potential customers into the NPD process. Active participation by NPD managers in virtual communities of bloggers and readers who are interested in certain types of products could also provide very valuable information in relation to the main marketing-mix variables (product, price, channel and promotion) and assist in the identification of

The New Product Development Process as a Communication Web, Part II

•

•

lead users and early adopters (Droge et al., 2010). Additionally, the use of virtual stock markets or information markets could help to identify those lead users with a greater ability to forecast the market success of new products (Spann et al., 2009). One of the method’s theories may not be accurate. It may assume that the perceptions and preferences of lead users are similar to those held by non-lead users once the market for a particular product has developed. However, current users could decide that they do not like the product concept that lead users have helped to develop. In this case, one of two possibilities are likely to arise (Urban and von Hippel, 1998): a. The new concept will not be appreciated immediately, but will be in the future when the needs of non-lead users have evolved and come to resemble those presented earlier by lead users. b. The concept will never be appreciated by non-lead users. The involvement of lead users in the generation of ideas for new products can be very useful if a company is seeking radical innovations. However, if a company requires incremental changes, the use of ordinary users through the guided user approach (where information on the technology behind the new product is given) may be more effective (Magnusson, 2009).

We believe it is essential for future studies to analyse the link between lead users and performance. Should firms study lead users and incorporate their needs and ideas into product improvements or new products? Do firms have a long-term outlook? Are they willing to wait for the market to appreciate the products designed on the basis of lead user contributions? Is it easy to identify lead users? Are firms capable of using

the lead user method? These and other questions need to be answered, particularly in relation to Spanish firms.

CONCLUSION This chapter gathers the results of a study on a sample of innovative Spanish companies. It forms part of a line of research that regards NPD as a communication web. It posits that new product programme performance will be greater in firms that use cross-functional teams, rely on the presence of product champions and information gatekeepers and take the opinions of more advanced users into account. The results, obtained from a sample of 136 managers from different functional areas (principally R&D, marketing and manufacturing) partly support the hypotheses put forward, and allow us to conclude that: 1. The three dimensions proposed in the measure of new product programme performance are perceived by managers as three distinct measures: (1) the overall programme performance; (2) the impact of the programme on the firm and (3) an index of the success of the new products. 2. The use of cross-functional teams in NPD is a general practice in innovative Spanish firms and positively influences the impact of the programme on the firm. 3. The presence of champions is important, both in achieving good overall programme performance and in obtaining a high successful product rate. 4. The collection of outside information by all members of cross-functional teams helps to improve overall programme performance and its impact on a firm’s results.

549

The New Product Development Process as a Communication Web, Part II

5. The presence of information gatekeepers is not associated with any of the three measures of performance. 6. The consideration of lead users in NPD has a negative influence on overall programme performance and on the index of success of new products.

LIMITATIONS AND FUTURE LINES OF RESEARCH In our opinion, this study presents various limitations. The first is that virtually all of the explanatory variables were measured using a single indicator, which obviously affects their reliability and validity. However, studies available on new products have yet to suggest ways in which concepts associated with teams’ external communication can be suitably measured. Multi-sector empirical studies have also yet to be carried out. Secondly, we believe that the possible moderating effect of the degree of product innovation on the connection between some of the explanatory variables and new product performance should be measured. In our opinion, whether or not the beneficial effect of gatekeepers (verified by previous studies) is greater in incremental innovations than in radical ones should also be calculated. Finally, we believe that qualitative studies should be performed in order to develop adequate measures for the constructs considered in this study, as well as better understand the traits of innovative Spanish firms, which have not yet been properly identified.

REFERENCES Allen, T. J. (1966). The use of information channels in R&D proposal preparation. Working paper, no. 97-64, Sloan School of Management, M.I.T, Cambridge, MA.

550

Allen, T. J. (1970). Communication networks in R&D laboratories. R & D Management, 1(1), 14–21. doi:10.1111/j.1467-9310.1970.tb01193.x Allen, T. J., & Cohen, S. I. (1969). Information flow in two R&D laboratories. Administrative Science Quarterly, 14, 12–19. doi:10.2307/2391357 Ancona, D. G. (1990). Otward bound: Strategies for team survival in an organisation. Academy of Management Journal, 33(2), 334–365. doi:10.2307/256328 Ancona, D. G., & Caldwell, D. F. (1997). Making teamwork work: Boundary management in product development teams. In Tushman, M. L., & Anderson, P. (Eds.), Managing Strategic Innovation and Change: A Collection of Readings (pp. 433–442). Oxford, UK: Oxford University Press. Buesa, M., & Molero, J. (1992). Patrones del cambio tecnológico y política industrial. Un estudio de las Empresas Innovadoras Madrileñas. Editorial Civitas. Círculo de Empresarios (1988). Actitud y Comportamiento de las Grandes Empresas Españolas ante la Innovación. Clark, K. B., & Fujimoto, T. (1990). The power of product integrity. In Clark, K. B., & Wheelwright, S. C. (Eds.), The product development challenge: Competing through speed, quality and creativity (pp. 277–296). Boston, MA: Harvard Business Review Book. Clark, K. B., & Fujimoto, T. (1991). Product development performance: Strategy, organisation and management in the world auto industry. Boston, MA: Harvard Business School Press. Cooper, R. G. (1984). The strategy-performance link in product innovation. R & D Management, 14(4), 247–259. doi:10.1111/j.1467-9310.1984. tb00521.x

The New Product Development Process as a Communication Web, Part II

Droge, C., Stanko, M. A., & Pollitte, W. A. (2010). Lead users and early adopters on the Web: The role of new technology product blogs. Journal of Product Innovation Management, 27(1), 66–82. doi:10.1111/j.1540-5885.2009.00700.x Enkel, E., Perez-Freije, J., & Gassmann, O. (2005). Minimizing market risks through customer integration in new product development: Learning from bad practice. Creativity and Innovation Management, 14(4), 425–437. doi:10.1111/j.14678691.2005.00362.x Fundación COTEC para la Innovación Tecnológica. (1997). Patrones y Comportamientos de Innovación Tecnológica en las PYMES del País Vasco. Análisis de Casos. Herstatt, C., & von Hippel, E. A. (1997). Developing new product concepts via the lead user method: A case study in a Low-Tech field. In Tushman, M. L., & Anderson, P. (Eds.), Managing strategic innovation and change: A collection of readings (pp. 376–384). Oxford, UK: Oxford University Press. Hong, P., Doll, W. J., Nahm, A. Y., & Li, X. (2004). Knowledge sharing in integrated product development. European Journal of Innovation Management, 7(2), 102–112. doi:10.1108/14601060410534393 Katz, R., & Allen, T. J. (1981). Investigating the not-invented here syndrome. In Pearson, A. (Ed.), Industrial R&D strategy and management. London, UK: Basil Blackwell Press. Katz, R., & Tushman, M. L. (1981). An investigation into the managerial roles and career paths of gatekeepers and project supervisors in a major R&D facility. R & D Management, 11(3), 103–110. doi:10.1111/j.1467-9310.1981.tb00458.x Lichtenthaler, U., & Ernst, H. (2009). The role of champions in the external commercialization of knowledge. Journal of Product Innovation Management, 26(4), 371–387. doi:10.1111/j.15405885.2009.00666.x

Lievens, A., & Moenaert, R. K. (2000). Communication flows during financial service innovation. European Journal of Marketing, 34(9/10), 1078–1110. doi:10.1108/03090560010342485 Lüthje, C., & Herstatt, C. (2004). The lead user method: An outline of empirical findings and issues for future research. R & D Management, 34(5), 553–567. doi:10.1111/j.1467-9310.2004.00362.x Magnusson, P. R. (2009). Exploring the contributors of involving ordinary users in ideation of technology-based services. Journal of Product Innovation Management, 26(5), 578–593. doi:10.1111/j.1540-5885.2009.00684.x Markham, S. K. (1998). A longitudinal examination of how champions influence others to support their projects. Journal of Product Innovation Management, 15, 490–504. doi:10.1016/S07376782(98)00031-9 Markham, S. K., & Aiman-Smith, L. (2001). Product champions: Truths, myths and management. Research Technology Management, 44(3), 44–50. Markham, S. K., & Griffin, A. (1998). The breakfast of champions: Associations between champions and product development environments, practices and performance. Journal of Product Innovation Management, 15, 436–454. doi:10.1016/S0737-6782(98)00010-1 Morrison, P. D., Roberts, J. H., & von Hippel, E. (2000). Determinants of user innovation and innovation sharing in a local market. Management Science, 46(12), 1513–1527. doi:10.1287/ mnsc.46.12.1513.12076 Schön, D. A. (1963). Champions for radical new inventions. Harvard Business Review, 41(2), 77–86.

551

The New Product Development Process as a Communication Web, Part II

Song, M., van der Bij, H., & Weggeman, M. (2006). Factors for improving the level of knowledge generation in new product development. R & D Management, 36(2), 173–187. doi:10.1111/ j.1467-9310.2006.00424.x Spann, M., Ernst, H., Skiera, B., & Soll, H. (2009). Identification of lead users for consumer products via virtual stock markets. Journal of Product Innovation Management, 26(3), 322–335. doi:10.1111/j.1540-5885.2009.00661.x Tushman, M. (1977). Special boundary roles in the innovation process. Administrative Science Quarterly, 22, 587–605. doi:10.2307/2392402 Urban, G. L., & von Hippel, E. (1988). Lead user analysis for the development of new industrial products. Management Science, 34(5), 562–582. doi:10.1287/mnsc.34.5.569

Lead Users: Are defined as users that already possess the characteristics that the majority of consumers will present in the future. For businesses, these individuals are great predictors of the trends and needs that will sooner or later emerge in the market (Droge et al., 2010; Spann et al., 2009; von Hippel, 1986). Product Champions: Individuals who emerge spontaneously from within an organisation, actively and enthusiastically push each stage of the innovation process forward and contribute decisively to the company’s success (Lichtenthaler & Ernst, 2009; Schön, 1963; Tushman & Nadler, 1986).

ENDNOTES 1



2



von Hippel, E. (1986). Lead users: A source of novel product concepts. Management Science, 32(7), 791–805. doi:10.1287/mnsc.32.7.791 von Hippel, E., Thomke, S., & Sonnack, M. (2000). Creating breakthroughs at 3M. Health Forum Journal, 43(4), 20–27. Whelan, E., Teigland, R., Donellan, B., & Golden, W. (2010). How Internet technologies impact information flows in R&D: Reconsidering the technological gatekeeper. R & D Management, 40(4), 400–413. doi:10.1111/j.1467-9310.2010.00610.x

KEY TERMS AND DEFINITIONS Gatekeepers: In successful R&D projects some individuals acted as technological gatekeepers, establishing links between the team and the technological environment and gathering technical information from outside and incorporating it into the group (Allen 1970, 1984).

552

The following activity sectors were considered: (1) those highlighted as innovative in earlier studies of innovative firms in Spain (Círculo de Empresarios. 1988), Madrid (Buesa and Molero, 1992) and the Basque country (Fundación COTEC, 1997); or (2) with a considerable number of firms receiving public aid for R&D projects (CDTI’s data base of innovative firms: www.cdti.es). We believe that the questionnaires, initially addressed to R&D and marketing managers, once within the firm, were subsequently forwarded on to other managers with adequate knowledge of the NPD process and its performance. An ANOVA analysis showed that there were no significant differences in the values of the study variables among the following groups of areas: (1) R&D; (2) marketing; and (3) manufacturing and other areas.

The New Product Development Process as a Communication Web, Part II

APPENDIX Figure 3. Measure scales, items and mean values

553

Section 7

Finance and Innovation

555

Chapter 30

Innovations and Financing of SMEs, Part I:

SME Financing and Credit Rationing: The Availability of Funds David S. Walker The University of Birmingham, UK Horst-Hendrik Scholz The University of Birmingham, UK

ABSTRACT Small and Medium-sized Enterprises (SMEs), as a major sector of the economy, have unique characteristics in terms of organisational and financial structures; reflecting the interest and strategy of the owner and financiers. With regard to the recent global financial crisis, the terminology ‘Credit Crunch’ describes a shortage in financial funds and concerns most businesses as well as financiers. On the one hand, financiers (lenders) complain about weak financial structures (especially lack of equity) and high risks investments of innovations and on the other hand SMEs (borrowers) accuse financiers for a shortage of financial funds or non-transparent and demanding credit conditions. This chapter describes various financing options and gives rationales for the credit rating process and credit conditions building the base for financing decisions. Furthermore, by discussing the topic of ‘Credit Rationing’, the authors demonstrate the impact of credit conditions on management decisions in order to justify the rationing of credits. This chapter also provides the necessary introduction and background to the understanding of the next chapter “Part II: Case Study of German SMEs in 2010”.

DOI: 10.4018/978-1-61350-165-8.ch030

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovations and Financing of SMEs, Part I

INTRODUCTION This chapter introduces definitions and financing alternatives of ‘Small and Medium-Sized Enterprise’ (SME). A comparison and validation of different SME definitions is presented to demonstrate the complex categorisation of a heterogeneous set of firms. Finance as an ‘Organisations Creative Area’ supports innovation processes by overcoming barriers that exist especially for SMEs. These barriers are not just a lack of resources (especially financial resources), but also lack of expertise in fields outside the core competencies. For instance a manufacturer may have a lack of distribution knowledge and contacts. Therefore, a non-traditional financier (e.g. Venture Capitalist) may solve some of these problems and support innovation by delivering ‘Value-Added Services’ (e.g. contacts, experience and managerial competencies). Depending on the long-run targets a firm may not need the expertise of any Private Investor and may be able to be innovative with traditional financing (e.g. Project-oriented bank loans). Therefore, choosing the right financing options, not just to optimize a firm’s financial structure, can have a synergetic effect on innovations. This chapter presents rather a theoretical background on financing SMEs, while the next chapter presents a closer focus on financing and its contribution to innovations in SMEs. In order to obtain a holistic view of what a credit crunch is and how it is caused, this chapter presents rationale of the credit market and a general description of the credit rating process. Additionally, non-traditional financing options are validated concerning the SME applicability.

BACKGROUND In Europe, the degree of bank financing is high in comparison to financing through financial markets—especially compared to the USA. In the USA, bonds take an 80% share of debt financing

556

and bank financing only 20%--while in Europe bank loans have an 80% share of debt financing (Schinkel, 2010). Therefore banks play a very important role in financing in Europe and it is worth it to have a closer look to the credit market and credit rationing. Due to the fact that most Small and Medium-Sized Enterprises (SMEs) are limited companies, rather than quoted companies, the access to financial markets is limited. Looking at the current financial crisis with a focus on the interplay of financiers and SMEs, companies are complaining about the so called Credit Crunch causing a shortage in funds. Financiers on the other hand complain about weak financial structures in terms of debt/equity ratios causing higher risks of losing loans. Non-traditional financing, with a potential to fill traditional financing gaps, offers especially to entrepreneurs an improved business framework; even though there are concerns about the dependence on financiers.

SME FINANCING AND CREDIT RATIONING A Literature Review on Small and Medium-Sized Enterprises Structural and economic performance characteristics of Small and Medium-Sized Enterprises (SMEs) differ not only within different nations, but also within different industries. Therefore it is important to identify differentiation criteria (quantitative and qualitative) and to contrast definition approaches; addressing the question ‘which type of firm is included in the term SME?’ Sometimes the grouping structure of cooperating enterprises makes it complicated to distinguish between legally independent entities. While some organisation’s out-sourced departments and services appear to be independent, other business units corporate to an extend that contradicts to a quantitative separated definition. Most literature about small firms was originated from America

Innovations and Financing of SMEs, Part I

The Quantitative Approach of the UK Companies Act

before the Bolton Committee defined 1971 ‘model 1’ (Bolton Report) containing quantitative as well as qualitative criteria to define a SME (Stanworth, 1981, p.3). This model is based on the UK market. More recent, the Companies Act of 2006 (UK) and the European Commission defined quantitative criteria. Other qualitative models have been developed by the Committee for Economic Development (US) and IfM Bonn1 (Germany).

A broadly accepted and quoted UK-based definition of small companies is described in the Companies Act of 2006 (chapter 46, part 15, sub-chapter 1, section 382). According to this act, a company qualifies as ‘small’ when it meets at least two of the following requirements (Table 2). The turnover values refer to the company’s financial year and any occurring maximum figures have to be adjusted proportionately. The balance sheet total is the aggregated amount of assets from the company’s balance sheet and the number of employees is calculated by the average ‘persons employed under contracts of service’ per financial year. Furthermore, a company is excluded from the “small companies regime” if during the financial year the company is either a public company, an authorised insurance company, a banking company, an e-money issuer, an ISD2 investment firm, an UCITS3 management company, or a member of a group that does not comply with required criteria (Companies Act 2006, chapter 46, part 15, sub-chapter 1, section 384).

The Quantitative and Qualitative Approach of Bolton Depending on the type of industry, Bolton et al. (1971, p.3) defined quantitative threshold criteria which can be either the number of employees or the annual turnover. Further criteria (as shown in Table 1) are ‘percentage of all firms in industry’, the ratio of total employment to small firm’s employment and the ‘average employment per small firm’. The Bolton Report model (1971, pp.1-2) defined besides quantitative criteria also qualitative characteristics. For instance the company should have a relatively small market share of its market, be managed in a personalised way (mostly by the owner), have no formal management structure and the principal decision-making-process shall not directly be externally influenced (e.g. not part of a large scale enterprise).

Table 1. Industry specific SME threshold criteria (Bolton, 1971, p.3) Industry

Statistical definition of small firms

Small firms as a % of all firms in the industry

Proportion of total employment in small firms

Average employment per small firm

Manufacturing

≤ 200 employees

94%

20%

25

Retailing

≤ £ 50,000 annual turnover

96%

49%

3

Wholesale trades

≤ £ 200,000 annual turnover

77%

25%

7

Construction

≤ 25 employees

89%

33%

6

Mining/ Quarrying

≤ 25 employees

77%

20%

11

Motor trades

≤ £ 100,000 annual turnover

87%

32%

3

Miscellaneous services

≤ £ 50,000 annual turnover

90%

82%

4

Road transport

≤ 5 vehicles

85%

36%

4

557

Innovations and Financing of SMEs, Part I

Table 2. UK threshold criteria according to the Companies Act 2006 (chapter 46, part 15, subchapter 1, section 382.3) Criterion

Values

Turnover

≤ £ 5.6 million

Balance sheet total

≤ £ 2.8 million

Number of employees

≤ 50

The Qualitative Approach of the US Committee for Economic Development According to the American Committee for Economic Development (CED), a small business has to meet at least two of the following for requirements (Recklies, 2001, p.2): a. Since the manager usually owns the business, the management has to be independent b. The ownership is held by one individual or a few individuals which supply the capital c. The operating area is mainly (but not necessarily) local d. The SME has to be smaller than large competitors in its industry

SME Definition According to the European Commission In accordance with the latest publication of the European Commission4, micro, small and medium- sized enterprises include all together firms that employ less than 250 employees, have a annual turnover of less than 50 million and an annual balance sheet total of less than 43 mil-

lion (Official Journal of the European Union, L 124/36, 2003, Annex, Title 1, Article 2.1). Table 3 provides quantitative threshold criteria for a closer differentiation of the three categories: The so called ‘staff headcount criterion’ (employees) takes, as the main criterion, different structures and characteristics of different branches into consideration. For example manufacturing firms usually have more employees with a certain turnover compared to firms working in the distribution or logistic sector (Official Journal of the European Union, L 124/36, 2003, p. 1, paragraph 4). The turnover threshold values are being adapted to changes in price and productivity. Furthermore, the so called turnover ceilings can be regarded as a statistical ratio between the balance sheet total and staff headcount. (Official Journal of the European Union, L 124/36, 2003, p.2, paragraph 6). According to the EU Commission, another criterion for an enterprise to be regarded as a SME is the relative share of external shareholder; not more than 25% of shares should be owned by another external company.

SME Definition According to the IfM Hauser5 (2005, p.3) points out that SMEs are limited to a size in which owners can manage to have a rather holistic control of the business—in contrast to Large Scale Enterprises (LSE). Due to the fact that the relative share and ‘weight of decision’ of private investors (like share holders) usually decreases with the size of enterprise, the incentive to get detailed information and the commitment decreases as well.

Table 3. SME threshold criteria of the EU Commission (c.f. Official Journal of the European Union, L124/36, 2003, Annex, Title1, Article 2.1-2.3) Size

Employees

Annual turnover

Annual balance sheet total

Medium

< 250

≤ € 50 million

≤ € 43 million

Small

< 50

≤ € 10 million

≤ € 10 million

Micro

< 10

≤ € 2 million

≤ € 2 million

558

Innovations and Financing of SMEs, Part I

the group may have different characteristics than SMEs according to quantitative definitions (e.g. annual turnover, number of employees).

Besides these limiting figures, the IfM and the OECD Statistics Directorate published a meeting document about “a qualitative definition of SMEs” (Hauser, 2005, p.2-3), in which three types of enterprises are differentiated (Table 4): •

•

•

Continuing Discussion and Critics on Presented Definition Approaches

Type 1 enterprise: An enterprise in which short- and long term decision are made by the manager who is the owner and a member of the family. The decisions are made only for the benefits and interests of the enterprise. The manager’s personal commitment and identification with the enterprise is very high. Type 2 enterprise: An enterprise in which the manager is only authorized to make short-term strategic decisions, but prepares long-term decision for the board of owners. The board of owners can also consist of private investors. Interests are to maximise their profits and profits of enterprise. Type 3 enterprise: An enterprise that is part of a group. Strategic decisions are made in favour of the group rather than the enterprise. The decision making process is influenced by the structure and interaction of group members. The affiliation can have legal, financial and knowledge advantages. The enterprise as a member of

A validation of the EU Commission’s proposal of SME classification has been conducted by the IfM to check the applicability to German SMEs -as a key player of the European Union. The following table (Table 5) shows the average annual turnover and average amount of employees in each sizegroup. The survey was conducted with German Manufacturing enterprises; employing at least 20 people. Hauser (2005, p.9) states that distortion of empirical data occurs by taking corporate enterprises (being incorporated into a group) into consideration. These enterprises act therefore in the group’s interests rather than own interests. To solve this issue, the IfM statistics look at legal units, which are clearly independent businesses, rather than incorporated group members. Comparing Table 5 with Table 3 shows that the threshold criteria of the EU Commission are suitable for instance for SMEs (as legal units) in the Manufacturing sector in Germany. The three types of enterprises described in the section “SME definition according to the IfM” have all pros and cons depending on the resources they require in operation. The most flexible enterprise category is type I due to the fact that decisions do not have to be co-ordinated to large extend and can be quickly executed through the owner/manager. On the other hand the risk of wrong decisions and prioritising can rise without the co-ordination

Table 4. SME threshold criteria of the IfM Bonn (Institut für Mittelstandsforschung (IfM), 17.07.2010) Size

Employees

Annual turnover

Large

≥ 500

≥ € 50 million

Medium

10 - 499

≤ € 10 million

Small

≤9

≤ € 2 million

Table 5. Average annual turnover and employment of German enterprises as legal units Size classes:

20-49

50-99

100-249

250-500

500-1000

1000+

Average

Turnover (million €)/ enterprise:

3.3

7.9

20.3

53.6

121.0

1540.7

50.4

Employees/ enterprise:

32

69

150

333

662

6518

210

559

Innovations and Financing of SMEs, Part I

of decisions. Modularization and the principle agent problem rise with the size of company and when grouping enterprises6 because one business unit may act on behalf of its own interests rather than the whole firm’s interests; furthermore this problem is related to Asymmetric Information. Concerning the availability and maximisation of resource capacities, the type III enterprise has an advantage over the other two types due to the fact that group members can shift their resources to each other. Therefore the assessment of financial and productivity performances is rather difficult when looking at type III enterprises. Type I and type II enterprises have less complex allocation of resources -which makes it easier to assess SMEs quantitative. Qualitative characteristics are very difficult to unify, categorize and access for externals. Therefore different definitions have been developed applicable for different nations. The more detailed contribution of the IfM (Hauser, 2005) contrasts structural aspects of organisations and demonstrates that enterprises, interacting in a group, are difficult to assess. Furthermore, SME threshold criteria based on statistical data need to be adopted according to legal units rather than single companies; that appear to be independent. An example related to the work of Hauser (2005, p. 4-9) is a company that has outsourced its Research and Development (R&D) and dispatch department (for taxation- or cost saving reasons). Looking at the single performance of all three business units (production department as a residual department and the two new independent business units) will show that one will generate most likely a profit and the other will reveal a very low operating profit. These three independent enterprises would contribute equally to a statistical result of a SME survey looking at each of them as a single entity; because interrelations are difficult to detect for externals. Therefore the relation between employment, machine capacities and financial ratios of different entities can be misleading regarding unifying definitions. Furthermore, it is difficult to define

560

SMEs as enterprises in which the owner has the overall control of the business. When looking at companies with more than 100 employees it is very likely to find assistant managers in several departments with certain competencies and room for manoeuvre.

The Difference between Small and Entrepreneurial Businesses The terminology SMEs is often wrongly associated with entrepreneurial businesses. Due to the fact that most businesses started out small, some can be in the position of an innovative-, entrepreneurial- or start-up business. While the aim of most entrepreneurial businesses is to grow, to gain market share and to maximise profits; some SMEs follow the strategy of staying in a niche market and maintain their size. Nevertheless, Bridge (2003) describes a classification of innovative businesses in relation to the growth of business. One class of business are the ‘lifestyle’ businesses that have “...no-growth aspiration”; “...often home-based, sole trader operations employing no more than one additional person...” (Bridge, 2003. pp. 276-277). Furthermore, he states that a remarkable number of entrepreneurs aim at moderate growth due to the fact that in a firm with an arithmetical growth, the occurring problems grow geometrically. In addition, owner of SMEs may prefer a smaller size because of a less aggressive competitive environment and more stable economic development following personal management goals. Concerning technological innovations, small enterprises have most likely an increased flexibility to adopt the product or service faster than LSE due to their key account management and dependence on their customer. Furthermore the management structure and decision making process as well as customer relationship management differ significantly from LSE that started out as an entrepreneurial business. While an entrepreneurial business is expected to have an

Innovations and Financing of SMEs, Part I

early return, covering research and development cost and serve share holders, an aim of a small business might rather be a stable business basis that is capable to be managed by a single person or in a partnership. A major advantage that small firms have is the ability to be innovative and to take up new technologies within a short time (further details in the next chapter). As there is now need to wait for the decision making process involving several people within the management structure. Due to the fact that a SME is able to react flexible to changes and opportunities, the customer relationship can be defined as much closer, personal and supporting.

The Economic Role of SMEs Alambritis (2010) who is a member of Britain’s Federation of Small Businesses states that “Small businesses are the lifeblood of the economy...”. General speaking SMEs can be regarded as a key player in each nation’s economy; especially in terms of GDP- and employment contribution. According to the European Commission, SMEs represent 99% of all enterprises and provide 75 million jobs in Europe. The “…support for SMEs is one of the European Commission’s priorities for economic growth, job creation and economic and social cohesion” (European Commission, 2003, p.5). The global financial crisis has proved that SMEs can absorb economic shocks better than LSE and have a stabilising function in the economy (Borger, Kiener-Stuck, 2010, 1-27). “Cutting off their credit poses a very real threat to the economic recovery” (Alambritis, 2010). Due to their management structure with a high grade of personal commitment and responsibility as well as flexibility in the decision making process, SMEs generally have the ability to provide stable employment conditions and stable tax payments. Besides assistance programmes of governments and private investors, a group of SMEs is less likely to get as much governmental help as a LSE being in the centre of public attention

-even though a group of SMEs together are more resistant to economic recession and provide more stable jobs and tax payments than a single LSE. To cover own costs and finance innovations, SMEs often form collective group agreements to profit for instance from large-orders discounts. Smaller scale organisations often offer the opportunity to the management to resolve employment related problems on an individual base rather than being confronted with a strong labour union and are less likely be confronted with labour strikes. On the one hand LSEs are more likely confronted by the ‘monopolies and mergers commission’, but on the other hand they can deal easier with environmental and social and governmental requirements due to their organizational structure. In order to survive in a general competitive environment, SMEs marketing strategies are often focused on an innovative, customer oriented and high quality product rather than low price products.

Financial Interests and Characteristics of SMEs Financing of SMEs is major challenge due to limited financial-, personnel- and production resources. Due to the fact that most small firms exist in the legal form as limited companies (rather than public companies) access to new capital is limited. Furthermore owner/ manager of SMEs prefer to keep the overall control of their firms and therefore equity capital is not the most favourable financing option. According to Hauser (2000), small firms have more difficulties to cover temporary losses than larger firms –even though their turnover yield is larger. In addition small companies have a lower non-operational income and lower equity capitalization. Therefore it is particularly difficult to finance R&D as well as capacity related investments. Due to the fact that SMEs often employ temporary labour as well as leased equipment (sometimes even provided by the customer) and use single machines rather than complex production lines, the variable cost

561

Innovations and Financing of SMEs, Part I

are compared to the fix costs relatively high. As a consequence the operation leverage tends to be lower which reduces the risk to pay back debts making SMEs more reliant and attractive to short term loans and overdrafts than to equity finance (Harrison, 1994). Investment loans are required by SMEs to renew work equipment and to expand the business. According to a study of SMEs in the financial crisis, the demand for investment loans decreased within an economic recession due to spare production capacities and a slow order situation (DSGV, 2010, p. 28). While the demand for investment loans decreases, the demand for working capital loans rises in a recession. This is due to the fact that SMEs need to cover raw material costs and some overheads by advance payments. Due to a low cash flow, the need for working capital loans rises. Concerning the interests of SMEs, it can be stated that an owner who manages an enterprise identifies himself to a wide extend with the business and does not like to disclose business information. Therefore a confidential so-called ‘house-bank’7 with one assigned account manager is more favourable than different banks –all having the whole set of information. Especially in a financial crisis, it can be important to build on a long –term relationship with a bank to “soften budget constraints” (Revest, 2010, p.6). In general, managers of SMEs have a good knowledge and experience about their new investment’s potential, whereas bankers might not be specialist in this particular field; making it more difficult for bankers to assess an investment’s risk. There is a trade-off between the tax payment and credit rating. While taxes might be reduced through the transformation of profit into so called inventory provisions and accruals, the bank/ financier cannot assess the value of these positions and therefore the credit rating downgrades as well. According to the opinion of an executive of a leading German bank, foreign banks entered loan markets of other countries during the last

562

years and tried to gain market share by employing competitive bidding strategies. This led for instance in Germany to relatively low interest rates. While the industry was used to relatively favourable loan conditions, the banks struggle to justify higher cost for similar services. Due to the fact that the latest economic crisis and recession affected the whole world, financiers had to raise the risk premium and formal requirements, which make the money cost rise as well; impaired by a low equity ratio of SMEs. In a financial crisis, equity equals safety. In Germany the average equity ratio of SMEs in the trading sector was 2008 12.6% and in the producing sector 19.7% (DSGV, 2010, appendix p. 8-9). Medium-size enterprises8 are known to have higher equity ratios and higher inflexible overheads. SMEs are often incorporated into a network with other SMEs and LSE causing not only dependencies, but also profits (e.g. higher purchasing power). The higher the dependency on one major customer, the more similar is their economic development and the higher the necessity to adopt capacity utilisation. Especially in manufacturing firms, the need for flexible and capable technology (often CNC-machines, measuring equipment) can cause the necessity not only to monitor costs, but also financial reorganisation. Older technology with lower fix costs (e.g. costs for maintenance, electricity and tools) and higher variable costs/ unit costs need to be replaced by costly new technology with higher fix costs and lower unit costs. To comply with capacity and flexibility requirements the firm has not only to invest into new technology but also cover higher fix costs/ overheads—requiring a sufficient cash flow. In times of an economic recession solutions like credit factoring, diversified investments and additional private capital can be very useful. According to Schneider (2004, p.8), most SMEs have “…low company capital [which] influences the credibility towards banks…” and investors. In case of Entrepreneurs the uncertainty about future

Innovations and Financing of SMEs, Part I

development of innovations makes the financing unattractive to private investors According to Moore (1993), financial constraints are the most significant barrier to growth.

Traditional Financiers Traditional Financiers may vary within different nations. In Scandinavian countries, Germany, France and Japan especially bank financing represents traditional financing. Especially innovationfinancing dependents on the financial system in a certain country (further reading in Revest, 2010, Financing technology-based small firms in Europe: what do we know? Pp.2). In order to focus on Europe, banks are regarded as traditional financiers. Banks are often defined as institutions that have the permission to carry out regulated and controlled activities of accepting deposits and executing loan transactions. They play an essential role in the economic cycle: Collecting and administer money (deposit business) to invest it in other businesses (lending business); for the original purpose of a macroeconomic profit maximisation as well as an achievement of own profit (depending on the purpose and type of bank institution). In addition, they provide payment services like money changing and support of monetary transactions. Another service banks provide is transforming assets in corporation with firms and investors acting as financial intermediary (FI). General speaking, this works through the aggregation and change on the asset side to create a new product on the liability side9. Other key functions are managing risks (e.g. loan-, liquidity- and interest rate risks) and associated monitoring of borrowers; as well as the information processing. There are different types of financiers competing with each other. One example are the so called ‘invoice finance and asset based lenders’, which provide services like factoring to firms in order to support their maintenance of cash flow. These institutions, working as non-traditional financiers, take over gradually market share from the banks.

Central Bank Authorities are responsible for macroeconomic services (monetary policy) as well as microeconomic services (support and control of financial market). Examples of Central Bank Authorities are European Central Bank (EU), Federal Reserve System (USA), Bank of China (China), Bank of Japan (Japan) and Bank of England (UK). Not all Central Bank Authorities are dependent on governmental decision. The banking system needs regulation due to many different reasons. One important reason is the existing ‘systemic risk’ (c.f. Thompson, 2004, p. 339) which can arise when a bank has liquidity problems (like it happened to many banks in different nations in the financial crisis in 2009). A structural key problem of banks is their balance between liabilities and assets. Bank’s liabilities are liquid and their assets are not liquid due to problematic repayments at short notice. In case a depositor get informed about an economic crisis of the bank institution or market, it is likely that he will withdraw his deposit at short notice, assuming it is safer not keeping it in the bank. This applies not only to one particular bank which is in trouble, but also to other banks—as most depositors cannot differentiate between bank institutions and their economic wealth. This can lead to liquidity problems of banks and a systemic collapse, because even banks will refuse to lend money to each other. Therefore national laws define the bank legislation and policies for banking operations in each constitutional state. To mention some of them: “Banking Act” (UK) and “Kreditwesengesetz” (Germany). These laws are being continuously revised by governmental institutions. A major aspect of banking regulations is the ratio of which loans are backed-up with equity (e.g. Basel I-III10).

Credit Rationing Since a credit is a non-uniform product, the demand and supply relationship is very complex- and so is the relationship of lender and borrower. According

563

Innovations and Financing of SMEs, Part I

to Freixas (1997), instead of a graphical analysis looking at demand and supply, a new equilibrium concept is required to describe the output of a competitive credit market; since the demand and supply curve simple will not intersect with high-level interest rates. Furthermore, the level of interest rate is limited according to a bank’s interests (see section “Types and phenomena of Credit Rationing”). Assuming a borrower is offered a loan to a given interest rate, he cannot just extent the amount of the loan in order to optimize his marginal cost—because the lender’s risk of losing money rises with the amount lent. Therefore “the equilibrium interest rate may be a nonlinear function of the loan size.” (Freixas, 1997, p. 138). The discussed influence of the interest rate on the demand of loans is called ‘price factor’. In addition, there are non-price factors, like collateral requirements, influencing the likelihood of getting a loan granted. Credit rationing (CR) is a phenomenon that occurs “...if in equilibrium the demand for loans exceeds the supply at the ruling price (interest rate).” (Voordeckers and Steijvers, 2005, p.2). In the literature the term CR is not used in a consistent way. CR is referred to describe the rationing of loans when looking at the inter-banking-relationship as well as bankcustomer relationship. Nevertheless, it has been proven that CR has an impact on SME’s financing opportunities (Voordeckers and Steijvers, 2005, p.2). In general it can be stated that the reduction of available loans reduces the availability of funds for potential projects of SMEs due to the fact that bank loan financing is still an important financing source (especially in Europe). The characteristics of the credit market differ significantly from consumer market characteristics covered in microeconomics. In the usual consumer market (or perfect market), a monopolist seller can (simplified) sell as much products as required as long as he is willing to lower the product price. Simultaneously, a monopolist buyer

564

can buy as many products as he wants as long as he is willing to pay the price. Clower (1995, p. 311) describes this as the ‘thick market hypothesis’ of the banking market. Depending on the pricing strategy of a company in the consumer market, the product price rises usually when the demand is high. In order to pursuit profit maximisation, chronic excess demand should be avoided (Gowland, 2010, p.1). To put it in Keynesian terminology, which have nowadays perhaps even more general validity: “If we assume that the lending of money takes place according to the principles of a perfect market, it is evident that, given the demand schedule of borrowers, the effective bank rate and bond rate must uniquely determine the production of capital goods and hence, generally speaking, the volume of investment. So far, however, as bank loans are concerned, lending does not—in Great Britain at least—take place according to the principles of a perfect market. There is apt to be an unsatisfied fringe of borrowers, the size of which can be expanded or contracted, so that banks can influence the volume of investment by expanding or contracting the volume of their loans, without there being necessarily any change in the level of the bank rate, in the demand schedule of borrowers, or in the volume of lending otherwise than through the banks. This phenomenon is capable, when it exists, of having great practical importance.” (Keynes, 1930, vol.1, p.190) In contrast to a “perfect market,” the credit market is called ‘thin market’, where the bank offers a “price-quantity-package on a leave-it or take-it basis...” (Gowland, 2010, p.1). There are several reasons that justify why loans for business customer are being rationed by a bank (three main reasons are described in paragraphs 6.2.3).

Innovations and Financing of SMEs, Part I

Types and Phenomena of Credit Rationing As Pawlowska (1997, p. 1-8) points out, there are different types of influences shaping the loan contract: Interest price terms, non-interest price terms and non-price terms. Interest price terms are defined by the interest rate. Non-interest price terms contain collateral, compensation balances, equity requirements and commitment fees. The third type of influence on the loan contract deals with standards of creditworthiness, long-term customer relationship, borrower’s intended loan use and restrictive covenants. Varying the interplay of influencing aspects leads to two different categories of CR: The so called “weak- or non-interestprice CR” appears when the interest rate is kept constant but the non-interest price terms increase. The other category of CR is “Strict- or non-price CR” which is based on the idea that interest rate and non-interest price terms are kept constant while non-price terms increase. Gowland (2010) suggest more general to differentiate between two additional types of CR: Type I rationing occurs if a bank grants a customer just a proportion of the requested loan. Whereas type II rationing occurs when a banks refuses to grant a loan to a customer at all; even when the customer has apparently the same profile like another customer who has been granted a loan. The so-called Asymmetric Information (AI) problem occurs between the customer and supplier of financial services (Canals, 2002, p. 307). The bank acting as a lender might not know the real risk when it grants a loan to its customer and a depositor might not be fully informed about the real risk of losing deposited money. In both cases there have been solutions developed to solve or to downsize the insecurity. First for the lenders (bank) security, CR standards (Basel I - III10) and continuous analysis of balance sheets have been developed in order to collect, compare and categorize companies. Concerning the other aspect of the phenomenon, there are institutions

that carry out standardised test (e.g. Stress Test of European Banks in 2010) and define rules for banks to achieve transparency for the customers. The Bank for International Settlements (BIS) and the Committee of European Banking Supervision (CEBS) have achieved indicators for a bank’s financial health. One example is the rules on the minimum value of a bank’s capital (Canals, 2002, p.307). Another problem related to AI is the so called Moral Hazard (MH) problem. It can be explained as the consequential choice of a higher risk project with higher expected payoffs. Most textbooks (e.g. Mullineux, 1992, p. 71-72) explain the MH problem with the underlying assumption that a borrower can go bankrupt in case of project failure. Thus the borrower will at most pay back a proportion of the loan (depending on the limited liability). This assumption might be applicable to very large projects requiring a large loan. Due to the fact that the long term relationship with a bank (especially house-bank relationship) and a borrower’s credit history are important aspects for the availability of reasonably priced loans in the future, it should not be the original aim for a borrower to use loans with higher cost for higher risk projects. Furthermore, SMEs often have multiple small projects that do not lead to a bankruptcy on its own and therefore the borrower (SME) will still have to pay back high cost loans accepted for higher risk projects. Nevertheless, a start-up company financing an innovative idea by the means of a higher cost loan, the assumption that the borrower will go bankrupt might be applicable, supposing the bank grants at all a loan to a new high risk project. The problem with rising interest rates above the bank-optimal interest rate (where the bank’s average return is the highest) is the attraction of higher risk borrowers (Adverse Selection effect). According to Voordeckers and Steijvers (2005, p.2) borrowers that know their limit of capital costs will reject loans with higher interest rates, but entrepreneurial SMEs or established companies

565

Innovations and Financing of SMEs, Part I

with higher risk investments are attracted. This effect leads to a lower average return for the lender and makes the lending business less attractive.

Risk Assessment and Credit Rating The risk assessment and risk management is very important when it comes to financing innovations. To assess the risk taking behaviour of entrepreneurs (Pawlowska, 1997) it is important to relate it to the offered loan conditions. As Pawlowska points out, loans offered to higher interest rates are more frequently accepted by enterprises that are funding higher risk innovations and providing lower assets than the inverse. Established enterprises with higher assets and innovations of lower risk are more likely to avoid high interest rates. Furthermore, the risk premium naturally rises within a financial crisis. The banks need to have their own rating system in order to judge investments. In this example, lending money to a SME can be seen as the investment. Therefore the bank rates the lender’s ability to pay back the borrowed money including a provision. Every bank has its own rating system, criteria as well as grade system. According to an in-depth interview with Starke (2010)11, rating systems are concerned with loan behaviour, account behaviour, financial analysis, master data, external data and qualitative factors (grouping). However, a more detailed description of the credit rating process is described later on. Credit rating agencies (CRAs) are profit-oriented private companies offering financial services. The main service is the assessment of companies from different industries as well as states to assess its financial situation and creditworthiness. The service helps investors and financiers to obtain an impartial impression of the likelihood that an investment succeeds with a profit. Nowadays ratings are a substantial subject to finance- and banking regulations. There are just a number of CRA which are allocated by financial institutions like banking supervisions.

566

In the inter-banking businesses CRAs play an important role, whereas in the bank-consumer (private and business) businesses this third-partyservice is not as important, due to the fact that banks have their own credit rating processes. The so called ‘credit crunch’ is a phenomenon describing a situation where hardly any loan (investment loan and working capital loan) are available to enterprises. According to the DSGV12 (2010, p. 28), the rising risk premium proofs that the credit market works efficiently concerning risk differentiation. Furthermore, the existence of difficulties to obtain a loan in single cases has been confirmed, but a general credit crunch had not taken place—according to Starke (2010). Due to the fact that the real economy and financial markets have international crosslink, the recession was imported even to countries with a healthy, stabilizing financial market structure, according to DSGV. Such a credit crisis is a stress test for the lender-borrower relationship (e.g. with house-banks), proving the dependence on a healthy relationship. Sometimes even a company’s survival can depend on the house-bank relationship, because the banks has detailed information as well as experiences about the potentials and weaknesses of the business and might be the only available financier.

Non-Traditional Financing Expanding firms (especially entrepreneurial businesses) are likely to utilise non-traditional financing means after the personal resources, such as partner’s share, friends and family credits (“cradle equity”), are utilized (Benjamin, 2005). Figure 1 presents an overview of the major financiers for SMEs. Some of the non-traditional finance options are equity financing through Venture Capital firms, Business Angels13 and governmental loan guarantees. As Benjamin points out, “...earlystage ventures have the best chance for funding, survival, retention of a larger share of venture ownership and control, and long-term success by

Innovations and Financing of SMEs, Part I

developing an efficient capitalization strategy to find and approach Angel Investors.” (Benjamin, 2005, P. XXXVIII). According to Metrick (2010, p. 4-7), so called Business Angels use their own capital and tend to focus on younger companies in an earlier stage with smaller investments. Venture Capital firms on the other hand, tend to focus on larger firms that are easier to exit and to take over some control (usually taking over 1 board member position). Both financiers can help to boost product innovations or existing businesses by providing ‘Value-Added Services’ like using their contacts and experience in development, managerial control and distribution. A major issue for both groups (Venture Capital firms and Business Angels) are information barriers (Mason, 1992). The firm’s owner needs information about the expertise, experience and contacts of the future shareholder and the Business Angel needs to assess the risk of investment. According to Goff and Cohen (2010) companies even use other (non-traditional) funding channels to refinance bank loans. Due to a higher equity ratio, the financial structure and a firms Credit Ration is improved. “Thus, venture capital investment provides the cash to drive innovation forward within small companies at a faster rate than would ordinarily be possible and it provides a rigorous and ongoing monitoring process that responds by killing failure Figure 1. Major financiers of SMEs

early.” (Barnes, S. in Tidd, J. and Bessant, J. (2009) Managing Innovation: Integrating Technological, Market and Organizational Change, pp. 446-447)

Private Equity and Mezzanine Financing for Unquoted Firms In order to stabilize a business and make it economically sustainable, the equity ratio is an important ratio. A major factor, influencing the ability to get funds (through an improved credit rating) and overcome a credit crunch, is an equity buffer. The equity ratio is also an indicator showing that a business grows naturally by its own funds. A simplistic definition of private equity as providing “...long-term, committed share capital, to help unquoted companies grow and succeed” is given by Cumming (2010, p. 54). Nevertheless, in the literature the range of application for the term private equity is however much wider than covered by this given definition. Fraser-Sampson (2010) points out the problematic use of using the term ‘equity’ and ‘unquoted company’ by asking the following questions: “What about investments which are structured as convertible debts... [and]... What about companies which are publicly listed but are taken private?” (Fraser-Sampson, 2010, p.2). These questions lead to the following categorisation of private equity according to Wickel (2010, p. 20): The first category is “direct investing,” which occurs either by an increase of capital or acquisition of shares. The second category is Mezzanine capital occurring by a ‘typical’ or ‘atypical’ silent partnership, subordinated loan or profit-sharing rights. Direct investing offers longrun equity from a determined partnership with a financial partner14. In contrast to bank financing with debt capital, there are no securities required and the financial partner will not just share profits, but also losses. The financial partner has the right to a say in monitoring-, supervisory- and affirmative -matters –depending on the negotiated terms of contract. When the predetermined target is reached, the financial partner has the

567

Innovations and Financing of SMEs, Part I

option to sell its shares to the original owner or other investors (exit strategy). Mezzanine capital is generally speaking a mix of equity and debt, therefore Mezzanine equity and Mezzanine debt can be legally differentiated. When capital is regarded as equity rather than debt the interest rates are higher, but the credit rating improves. In a silent partnership the interest rate and the degree of transparency offered by the firm’s management are relatively high. To sum up, Mezzanine capital is a financing tool that can improve a firm’s capital structure by the right balance of debt and equity; depending on the financial partner’s preferences for risk and control.

Online Marketplaces for Direct Loans New types of short-term SME financing are direct loans from online marketplaces or ‘online social lending communities’. One example of such an online marketplace for businesses in the UK is ‘Funding Circle’ which has been launched in August 2010 (Financial Times, Companies – UK, 13.08.2010, p. 14). This platform offers 1-3 year loans from £5,000 up to £50,000 for expected interest rates of 6-9% (Fundingcircle. com15, 14.08.2010). With lower total cost of finance (annual review fees, monitoring fees and security fees) banks can be undercut (Funding Circle, 14.08.2010). Nevertheless, only borrowing companies that pass the initial accreditation assessment can participate; which make this service appear in a similar light to the lending service of banks. The default rates are expected to be only between 0.6% and 1.5% according to Funding Circle. Furthermore, they are classified in risk categories (‘C, B, A, A+’). The base of information about companies is according to Funding Circle similar to the ones that banks use (e.g. ‘Experian’). Private lenders, as the source of financial funds, cannot just choose the sectors they want to invest in, but also diversify their investment to reduce the overall risk.

568

SOLUTIONS AND RECOMMENDATIONS The dependence on short-term bank loans seems to be a major problem of SMEs especially in Europe. In a financial crisis, the credit conditions are being adopted for instance by the means of risk premium and collateral requirements. Other alternatives to bank lending should be taken into consideration to reduce this dependence. Nevertheless, bank financing tend to improve by a further developed rating system; looking at a single organisation rather than generalising it as part of a branch. Therefore SMEs with a unique selling point or product innovation are more likely to be granted a loan. However, there are alternatives like Direct Loan Markets and Equity and Mezzanine Financing. A main problem making financing of SMEs more difficult is the information barrier. With the tax- saving transformation of profits into inventory provisions and accruals, the assessment of these positions and a company’s credit rating is sometimes rather difficult. To improve a company’s bank lending, a reliable house-bank relationship, in which a borrower complies with the information assessment requirements, has to be established. Similar to bank financing, direct investments and equity financing require a management of information and a transparent decision making structure to be attractive to investors. Once this information barrier is vanquished, the SME can profits from synergy and expertise to support its strategic development. The financial structure and credit rating can be improved by Equity- and Mezzanine Financing.

FUTURE RESEARCH DIRECTIONS Future research should address the problem of achieving transparency of risks and opportunities related to innovations in the early stage. Furthermore transparency is needed in the financial structure and evaluation of inventory and

Innovations and Financing of SMEs, Part I

accruals. A survey (e.g. an in-depth interviews with manager of SMEs) could help to clarify why traditional financing options are more employed than non-traditional; with a differentiation between European countries and the USA. In order to improve the accuracy and efficiency of governmental support programmes, new branch characteristics on the base of the Bolton Report should be defined.

CONCLUSION This chapter presented various definitions of SMEs, with qualitative (personalised management, market share, independence of decision making) as well as quantitative (e.g. number of employees and turnover) characteristics. With a focus on various markets, different approaches to differentiate business types have been described. Different sectors do not only have different numbers of employees and turnover, but also differences in the management structure and decision making process. It can be concluded that the term SME is defining a diverse group of heterogeneous firms. Due to the fact that firms sometimes source-out departments or cooperate closely with legally independent units, a low level of differentiation can adulterate statistics about SMEs which are based on threshold criteria (like turnover and number of employees). Therefore it is important to look at legal units with a clearly defined structure; where allocation of resources and financial ratios are possible. The major financiers of SMEs are Private Investors (e.g. Business Angels), Private Banks, Non-Profit Banks, Governmental organisations (Funds, Guarantees) as well as Asset and Invoice Financiers. Due to the fact that bank financing is still very common for European SMEs, the rationale of credit rationing in the credit market has been described. In contrast to the consumer market equilibrium, the credit market equilibrium is not defined by demand and supply. In order to

maximise the profit from the lending business, a bank will define and adjust lending conditions. There are 3 major phenomena that occur in the credit market: Asymmetric Information, Moral Hazard, and Adverse selection. The Asymmetric Information problem occurs when the bank acting as a lender does not know the real risk of losing its deposited money when granting a loan. Therefore, Credit Rationing standards (e.g. Basel I-III 10) have been developed to reduce this risk. Another phenomenon is the so called Moral Hazard problem. A borrower will consequently choose the higher risk project with higher expected payoff when the loan costs are high as well. The assumption that a borrower is likely to take the risk of going bankrupt in case the project fails and will therefore not be able to payback the loan; is limited applicable. SMEs have to maintain a long run relationship with their so called ‘house-bank’ and have often multiple projects. However, for an entrepreneurial business the success of the first projects might be critical and therefore the Moral Hazard Problem is applicable. The third phenomenon is the Adverse Selection effect, which states that an established firm which is aware of its ‘appropriate’capital costs will reject a loan if the lending conditions do not reflect the perceived project risk. Therefore only firms with higher risk investments are attracted. The loan contract is influenced by: Interest price terms, non-interest price terms and nonprice terms. Interest price terms are defined by the interest rate. Non-interest price terms contain collateral, compensation balances, equity requirements and commitment fees. The third type of influence on the loan contract deals with standards of creditworthiness, long-term customer relationship, borrower’s intended loan use and restrictive covenants. The credit rating of a firm is crucial because in some cases it can decide about the existence of the firm; due to the dependence on bank financing. The credit rating system of banks rates the lender’s ability to pay back the borrowed money including a provision. Even though rating- and

569

Innovations and Financing of SMEs, Part I

grade systems differ from each other, most of the systems take loan behaviour, account behaviour, financial analysis, master data, external data and qualitative factors (a firm’s grouping) into consideration. Non-traditional financing is especially attractive to expanding firms, but also firms with insufficient cash-flow. Some of the non-traditional finance options are equity financing through Venture Capital firms, Business Angels and governmental loan guarantees. However, the limited use of non-traditional financing can be explained by the organisational structure of a ‘one-manshow’ often to find in SMEs and a conservative attitude towards publishing confidential business information (information barrier). Further details about ‘SMEs and non-traditional financing’ are described in the next chapter.

Borger, K., & Kiener-Stuck, M. (2010). Die konjunkturelle Lage kleiner und mittlerer Unternemen, Konjunkturelle Stabilisierung im Mittelstand – Aber viele Belastungsfaktoren bleiben. Mittelstandsmonitor 2010 – Jaehrlicher Berich zu Konjunktur- und Strukturfragen kleiner und mittlerere Unternehmen. Frankfurt am Main: KfW, Kreditreform, IfM, RWI, ZEW, p.1-27

REFERENCES

Companies Act. (2006). UK, 46-1(15), 382.

Alambritis, S. (2010). Britain’s federation of small businesses. Financial Times: The manager says no, 31.08(2010), 9.

Cumming, D. (2010). Private equity: Fund types, risks and returns, and regulation (p. 54). Hoboken, NJ: John Wiley & Sons Ltd.

Banking Act of the Federal Republic of Germany. (2009). Kreditwesengesetz. KWG.

Finanzgruppe Deutscher Sparkassen- und Giroverband (DSGV). (2010). Diagnose Mittelstand 2010 (Report): Blick nach vorn – Sparkassen begleiten Mittelstand durch die Krise (pp. 5–28). Berlin: DSGV.

Barnes, S. (2009). The role of venture capital in innovation. Managing Partner of Tate&Lyle Ventures LP. In Tidd, J., & Bessant, J. (Eds.), Managing innovation: Integrating technological, market and organizational change (4th ed., pp. 446–447). UK: Wiley&Sons Ltd.

Bridge, S., O’Neil, K., & Cromie, S. (2003). understanding enterprise, entrepreneurship and small business (2nd ed., pp. 276-277). Basingstoke, UK: Palgrave Macmillian Ltd. Canals, J. (2002). Universal banking: International comparison and theoretical perspectives (p. 307). Oxford, UK: Oxford University Press. Clower, R. W. (1995). Economic doctrine and method: Selected paper of R. W. Clower (p. 311). US: E.Elgar.

Fraser-Sampson, G. (2010). Private equity as an asset class (2nd ed., p. 2). Hoboken, NJ: John Wiley & Sons Ltd.

Benjamin, G., & Margulis, J. (2005). Angel capital: How to raise early-stage private equity financing. Hoboken, NJ: John Wiley & Sons.

Freixas, X., & Rochet, J.-C. (1997). Microeconomics of banking (p. 137). Cambridge, MA: MIT Press.

Bolton, J. E. (1971). Small firms: Report of the Committee of Inquiry on Small Firms (p. 1). London, UK: Her Majesty’s Stationery Office.

Funding Circle. (2010). Reasons to become a borrower. Retrieved from http://www.fundingcircle. com/borrow/ [Accessed 14 August 2010] Goff, S., & Cohen, N. (2010). Financial Times: The draw of bonds, 31.08(2010), 9.

570

Innovations and Financing of SMEs, Part I

Harrison, R. T., & Mason, C. M. (1992). The roles of investors in entrepreneurial companies: A comparison of informal investors venture capitalists. In Churchill, N. C., Birley, S., Bygrave, W. D., Muzyka, D. F., Wahlbin, C., & Wetzel, W. E. Jr., (Eds.), Frontiers of entrepreneurship research 1992 (pp. 388–404). Wellesley, MA: Babson College. Hauser, C. (2005). A qualitative Definition of SMEs. Institut für Mittelstandsforschung (IfM) (pp. 2-4). Bonn, Germany. Institut für Mittelstandsforschung IfM. (2010). KMU-Definition des IfM Bonn. Retrieved on 17 July, 2010, from http://www.ifm-bonn.de/index. php ?utid=89&id=101 Metrick, A., & Yasuda, A. (2010). Venture capital & the finance of innovations (2nd ed., pp. 4–7). Hoboken, NJ: John Wiley & Sons. Moore, B. (1993). Financial constraints to the growth and development of small high-technology firms. In Storey, D. J., & Hughes, A. (Eds.), Finance and the small firm (p. 13). London, UK: Routledge. Mullineux, A. W. (1992). European banking (pp. 71–72). Oxford, UK: Blackwell. Pawlowska, A. E. (1997). Bank financing of small and medium size enterprises: An empirical investigation of credit rationing in Poland (1989 – 1995). Doctoral Dissertation, University of Birmingham, UK. Recklies, D. (2001). Small Business – Size as a chance or handicap (p. 2). Retrieved on July 18th, 2010, from http://www.themanager.org/ pdf/ Small%20Business.PDF Reichwald, R., & Wigand, R. T. (2008). Information, organisation and management (pp. 211–213). Berlin/Heidelberg, Germany: Springer-Verlag.

Revest, V., & Sapio, A. (2010). Financing technology-based small firms in Europe: What do we know? (11.07.2010, p. 6). Napoli, Italy: Universtà di Napoli Parthenope. Journal DOI 10.1007/s11187-010-9291-6 Schinkel, K. (2010). Frankfurter Allgemeine Zeitung, Trend zu Eigenkapital ist intakt, 15.07.2010(161), 19. Interview with Klaus Schinkel, Royal Bank of Scotland, Schneider, B. (2004). The successful management of small and middlesized enterprises in a specific sector. München, Germany: Rainer Hampp Verlag. Stanworth, J., Watkins, D., & Lewis, J. (1982). Perspectives on a decade of small business research: Bolton 10 years on (p. 214). Hampshire, UK: Gower Publishing Company Ltd. Storey, D. J., & Hughes, A. (1994). Finance and the small firm (pp. 3–5). London, UK: Routledge. The Commission of the European Communities. (2003). Official Journal of the European Union: Commission Recommendation of May 6th 2003 Concerning the Definition of Micro, Small and Medium-Sized Enterprises, L124/36, 20.05.2003. Retrieved on October 25th, 2010, from http:// eur-lex.europa.eu/LexUriServ /LexUriServ. do?uri=OJ:L:2003 :124:0036:0041:EN:PDF The Organisation for Economic Co-operation and Development. (1998). Globalisation and Small and Medium Enterprises (SMEs). [). Paris, France: OECD.]. Country Studies, 2, 117–136. The Organisation for Economic Co-operation and Development. (2004). Promoting Entrepreneurship and Innovative SMEs in a Global Economy: Towards a more responsible and Inclusive Globalisation. 2nd OECD Conference of Ministers Responsible for Small and Medium-Sized Enterprises (SMEs) (p. 8). Istanbul, Turkey: OECD. Thompson, J., & Buckle, M. (2004). The UK financial system: Theory and practice (4th ed., p. 339). Manchester, UK: Manchester University Press.

571

Innovations and Financing of SMEs, Part I

UK Banking Act. (2009). Hansard Reference: Lords: Vol. 707, Column 1223 (part 1.2). The Stationery Office Ltd. Verheugen, G. (2005). The new SME definition, user guide and model declaration (pp. 5-15). European Commission, Enterprise and Industry Publications. Retrieved on July 17th, 2010, from www.euresearch.ch/fileadmin /documents/PdfDocuments/ SME_Definition_en.pdf Voordeckers, W., & Steijvers, T. (2005). Credit rationing for SME’s in the corporate bank credit market of a bank-based economy (p. 2). Belgium: Limburgs Universitair Centrum, Department of Business Administration. Retrieved on September 14th, 2010, from http://www.efmaefm.org/ efma2005 /papers/245-steijvers_paper.pdf Wickel, H.-P. (2010). Wie Sie neue Kapitalquellen anzapfen. Das Unternehmermagazin der Haspa, 3/2010, pp.18-21ff

Credit Crunch: A phenomenon describing a situation where hardly any loan (investment loan and working capital loan) is available to enterprises. Credit Rating: A bank’s system to rate the lender’s ability to pay back the borrowed money including a provision. Direct Loan: New types of short-term SME financing are direct loans from online marketplaces or ‘online social lending communities’. Entrepreneur: A person running a business in an early stage and being accountable for the inherent risk. House Bank: A bank that maintains a longterm relationship with a certain firm. Financing decisions of the bank are based on experiences and insight-knowledge of the firm’s business. Venture Capital: Venture Capital firms tend to focus on larger firms that are easier to exit and to take over some control (usually taking over 1 board member position).

KEY TERMS AND DEFINITIONS

ENDNOTES

Adverse Selection: The problem with rising interest rates above the bank-optimal interest rate (where the bank’s average return is the highest) is the attraction of higher risk borrowers (Adverse Selection effect). Asymmetrical Information: The so-called Asymmetric Information (AI) problem occurs between the customer and supplier of financial services (Canals, 2002, p. 307). The bank acting as a lender might not know the real risk when it grants a loan to its customer and a depositor might not be fully informed about the real risk of losing deposited money. Business Angel: Individuals investing in highrisk-investments in order to gain a profit and/or to develop a strategic association. In the US it is known as ‘Angels’.

1



2



572

3

4



5



6

7



IfM stands for ‘Institut fuer Mittelstandsforschung’ a German institute carrying out SME-research (Hauser, 2005). ISD: Investment Service Direct UCIT: Undertakings for Collective Investments in Transferable Securities ‘European Commission’ quoted in the following parts as ‘EU-Commission’ Hauser: Member of the IfM Bonn For further reading: Reichwald, R. et al in “Information, organisation and management,“ 2008. Springer-Verlag Berlin Heidelberg, P. 211-213 ‘House-bank’: A bank that maintains a long-term relationship with a certain firm. Financing decisions of the bank are based on experiences and insight-knowledge of the firm’s business.

Innovations and Financing of SMEs, Part I

8



9



10

11



Medium-sized Enterprise: Annual turnover of €100-500 million Further reading: Microeconomics of banking. Freixas and Rochet 2008, p. 4 Basel I, Basel II, Basel III: Banking standards defining for instance to what degree a bank loan has to be backed up with equity; for security reasons Business Customer Account Management at the Commerzbank in the following quoted as Starke.

12



13



14



15



DSGV: Finanzgruppe Deutscher Sparkassen- und Giroverband Business Angels: Individuals investing in high-risk-investments in order to gain a profit and/or to develop a strategic association. In the US known as ‘Angels’ Financial partner is sometimes called ‘Investor’ or ‘LP- Limited Partner’ (US) A video explaining how ‘Funding Circle’ works is available at http://www.fundingcircle.com/

573

574

Chapter 31

Innovations and Financing of SMEs, Part II:

Case Study of German SMEs in 2010 David S. Walker The University of Birmingham, UK Horst-Hendrik Scholz The University of Birmingham, UK

ABSTRACT Financing is one of the most critical boundaries for the establishment and growth of a Small and Medium-sized Enterprise: SME (Moore, 1993). This chapter describes traditional and non-traditional financing opportunities for SMEs in Germany by focusing on its applicability. The disclosure of financial business information and giving a say to an equity financier is a difficult topic for owners of Small and Medium-sized Enterprises (SMEs), because these companies are often run as a ‘one-man-show’ (by a single manager) and this person identifies itself with the company. The request for external funds is in that perspective still regarded as a disability of a business to be self-financed. A comparison of the organisational structure of a SME and that of a Large Scale Enterprise (LSE) reveals the structural weaknesses in terms of research and development (R&D) activities. While LSE have an extra department, budget and procedures to develop product and process innovations similarly to a knowledge push, in SMEs, innovations are often originated from customers—similarly to a need pull process (Tidd & Bessant, 2009). Furthermore, CEOs and customer contribute to a great extend to innovations in SMEs (BDI, 2010). The results of an online-based survey presented in the BDI-Mittelstandspanel 2010, show that less than 13% of innovations are originated by external scientists, R&D organisations and consultants. This proofs that external R&D sources (to compensate missing internal resources and structures) are rarely employed; impeding or slowing down the development of innovations.

DOI: 10.4018/978-1-61350-165-8.ch031

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Innovations and Financing of SMEs, Part II

INTRODUCTION

BACKGROUND

There are various financing options available to Small and Medium-sized Enterprises (SMEs) that can be classified generally in traditional and non-traditional financing as introduced in the previous chapter. Due to a rather conservative attitude towards dependence on shareholders, non-traditional financing options (e.g. private equity) are not very common within SMEs (especially in Europe); aggravating the amelioration of the company’s financial structure and therefore creditworthiness. In order to get a rather holistic view, a case study based on a survey presents the structural development and economic situation of SMEs- and its financiers in Germany. German Banks offer SMEs rather medium or long-term bank loans than project related loans. Therefore, the control and monitoring of banks over the efficient use of borrowed money is low compared to project financing. Looking at finance as an ‘Organisation’s Creative Area’ (OCA), non-traditional financing can be more suitable to develop core competencies and promote product innovations. Sometimes they are even the only financial source available when it comes to highrisk project financing. In order to support SMEs and generate a high profit, Private Investors are more likely to take part in project related (e.g. for a product innovation) financing. The level of control and monitoring, in order to ensure that a product or service innovation is turned into money, is high. By the financial and managerial support, Private Investors especially promote the ‘knowledge push’ innovation model. Due to lack of resources, the ‘knowledge push’ innovation model is rarely used compared to the ‘need pull’ innovation model in which the innovation is originated from customers.

The financing sector in Germany is highly competitive with the three types of banks (private banks, banks governed by public law and cooperative banks) trying to maintain and gain market share and the non-traditional financiers (private equity and debt financiers). Therefore, the credit conditions have been favourable in Germany during the last decades. CEOs of SMEs tend to have a conservative attitude concerning additional shareholders and financial independence. Therefore, medium- and long-term bank financing has been in Europe (especially in Germany and France) a major financing option for SMEs. However, with respect to the financial crisis of 2008/2009, the credit conditions (especially risk premium) changed, impeding the availability of loans. While financiers accuse SMEs for having a weak financial structure, SMEs representatives accuse the financiers (especially banks) for the so called ‘credit crunch’ with unacceptable credit conditions.

SME-FINANCING AND INNOVATIONS Financial Resources and Innovation Boundaries of SMEs The BDI1 announced in its latest report (BDI, 2010), based on an online survey, the developments and weaknesses of German SMEs in 2009 and expectations for 2010. These weaknesses include innovative boundaries, based on fundamental problems of the organisational structures and resources. Therefore, finance can also be regarded as an ‘Organisation’s Creative Area’ (OCA) that helps develop core competencies especially with the support of Private Investors, controlling and monitoring the realisation of product and service innovations.

575

Innovations and Financing of SMEs, Part II

The funding of a SME is regarded as one of the most difficult process from the management point of view. Because the owner or manager identifies itself with the business, asking for external funds indicates helplessness and dependence on others. As discussed in the section “Financial interests and characteristics of SMEs” of the previous section, there are several trade-offs between financial figures. One example for a trade-off is the reduction of tax payments and establishment of a good credit rating. Additionally, the financier requires an extensive disclosure of detailed business information, which is sometimes perceived as a potential risk of plagiarism due to changing account managers of banks and their wide range of customers and financial services. Furthermore, the development of interest rates and lending conditions as well as the term of loans are important factors to take into consideration when making a financial decision. As presented in the BDI-Mittelstandspanel (2010, p.19) 71.8% of SMEs have trouble with getting new credit lines granted, 48.35% complaint about strict documentation and safety requirements when applying for a loan, 55.85% gained a lower credit rating in 2009 and just 16.5% of SMEs have an own budget for R&D. Nevertheless, most SMEs do R&D activities within the framework of customer orders (BDI, 2010, p.25). The insufficient innovation performance of some SMEs is not only caused by a lack of external funds, but also by detrimental organisational structures. Just 16.5% of SMEs have a special budget to execute R&D (BDI, 2010, p.25). The establishment of a R&D department, definition of its responsibilities, systematic collection and evaluation of innovative ideas and the method budgeting are regarded as useful auxiliary activities for innovations.

last 2 years- one product innovation. In order to assess the innovative capability of SMEs under existing structures, it is worth it to have a look at the different types of innovations. Concerning process innovations, a third of consulted SMEs apparently have been successful within the last 2 years (BDI, 2010, p.25). The business models of most SMEs have evolved within time, but are based on traditional management ideas and structures (Figure 1); therefore, a strategic reorientation and the receptiveness towards non-traditional financing are rarer to find. In addition, every new reorientation is associated with a risk of failure. According to the report, just 1 out of 200 ideas are successful on the market. Innovation ideas originate from a diverse range of sources. The main source of innovation in established SMEs (in contrast to entrepreneurial businesses) are customers and suppliers. The customer and supplier (BDI, 2010, p.25) initiate for instance in Germany on average 64.4% of innovations. In contrast to LSE, where resources enable ‘knowledge pushes,’ in SMEs, innovations are more likely originated from customers in a ‘need pull process’ (Tidd & Bessant, 2009, pp.232236). In SMEs where the CEO is involved in the product- or service development process and customer relationship management, this person causes major innovative stimulation. Furthermore, on average 55% of innovations are originated from the CEO. Other external sources on the other hand are rarely used. Scientists and R&D organisations as well as external consultants account for less than 10% each for innovations. Compared to LSE, employing R&D staff, this can be regarded as a competitive disadvantage or respectively potential.2

Innovation Sources of SMEs

Historical Background of German SMEs

There are three main areas where innovations can take place: Product, Process and Business Model. According to the BDI (2010, p.25) four out of ten firms are working on- or released within the

576

Due to socialistic influences, SMEs located in the east of Germany have been challenged to rebuild old company structures from the time before the

Innovations and Financing of SMEs, Part II

Figure 1. Time-to-market failure

German Democratic Republic3; or create completely new company structures. During the era of the DDR, small enterprises were nationalised and forced into central planning structures, which were rather ineffective; in terms of not only innovations and expansion plans. Limited foreign trade caused a lack of spare parts for machines, which blocked growth and innovations down. Due to the fact that unemployment was higher and the minimum wage lower than in western parts, SMEs needed help from the federal- and Länder (states) government and banks to finance the development of companies in the post-war period. According to Mullineux (1994, p.7), the government provided SMEs in the east with investment and depreciation allowances. Additionally, local saving banks and community-type banks (like ‘Volks- and Raif-

feisenbank’) supported SMEs by lending small loans. Larger loans mainly came from official banks of the Länder (OECD, 1982). In the western parts, the Federal Ministry of Economics and Technology (‘Bundesministerium für Wirtschaft und Technologie’) launched a Primary Innovation Scheme from 1972 to 1979 by spending 114 million on 230 projects covering 50% of high risk new technology costs. These loans are repayable if the projects have been successful (OECD, 1982). Additionally, the government-backed risk capital bank (‘Wagnisfinanzierungsgesellschaft’) bought shares of firms with a minimum participation of DM4 400,000 per firm. Furthermore, Private and State supported participation banks (‘Beteiligungsgesellschaften’) provided risk capital to SMEs. Low interest rate

577

Innovations and Financing of SMEs, Part II

loans have been offered to SMEs through the European Recovery Programme (ERP) Funds. This budget was DM 500 million in 1978. In 1979, the federal Government aid programme raised capital with low interest rates in order to fund SMEs for 20 years. The so-called Länder (states) offered capital guarantee schemes backed by official Länder banks supporting new companies. A programme by the Ministry of Economic Affairs announced in 1979 the law, that SMEs with a lower turnover than 150 million and less than 1000 employees can subsidise 40% of R&D cost (up to DM 300,000) and 25% of excess costs (up to DM 400,000) per year. In 1980, the budget was increased to DM 390 million. To sum up the development of SMEs in east and west it can be stated that profited from a diverse range of supporting programme in the post war period. The following paragraph will present the current situation of the ‘Mittelstand’5 in Germany mainly influenced by post-war support programmes.

Regional Differences of SMEs in Germany Analysing SMEs in Germany, two regions with similar SME-patterns can be distinguished: The new- and old federal states of Germany6. Additionally, Baden-Württemberg and Bavaria (as states of the west) should be mentioned as major locations for the engineering industry, mainly characterised by suppliers (SMEs) for the automobile industry. Furthermore, the Rhine-Ruhr metropolitan region with services in the financial, insurance, high tech and multimedia sectors has the third highest GRP in the EU (Eurostat, 2010). Furthermore, the citystate Hamburg has one of the biggest harbours in Europe and is an important place for the aviation industry As described in the previous paragraph, SMEs in the east have evolved their organisational structures differently due to socialistic influences and make still more use of governmental subsidies. According to Boerner (2008, p.8) 49% of firms

578

in the east and just 21% of firms in the west use public funds. This phenomenon can be explained not just by the increased availability of subsidies in the east, but also by the fact that the need for subsidies is even 20 years after reunification higher. The government funded and supported Universities and Technical Universities in rural areas (especially in the East of Germany) to provide companies with highly trained staff and promote innovations (Broekel, 2009, p.7). Nevertheless, most eastern states suffer from movement of labour from east to west and demographic changes. According to a newspaper article by Astheimer (FAZ, 05.08.2010, no.179, p.10), the highest predicted emigration rate of 25% until 2025 will take place in parts of Saxony-Anhalt and will cause a critical shortage of specialised employees in this area. According to Haselhoff (FAZ, 05.08.2010, no.179, p.10), 90% of 59,000 firms have less than 20 employees and a low wage level compared to the western standard. Therefore, many specialised and trained workforces emigrate to western states. Figure 2 shows the median7 equity ratios of different size classes of the non-financial industry in east and west of Germany. With an average value of 9.5% in the east and 6.6% in the west, SMEs in the east have shown higher equity ratios during the last years. Since 2007 the equity ratio increased minimal stronger in the east than in the west. When it comes to investment decisions, SMEs located in the so-called ‘neue Bundesländer’ (literally translated ‘New States’ which are located in the east) tend to regard the necessity of liquidity protection as more important than SMEs in the west (Boerner, 2008, p. 8). The equity ratio is a major part of quantitative factors influencing a firm’s Credit Rating and therefore access to bank credits. A higher equity ratio indicates a better financial situation and a better ability to overcome a crisis. Presumably, the recession will have an impact on the more current upcoming equity ratios. Due to the fact that the recession can be regarded as an imported recession, businesses

Innovations and Financing of SMEs, Part II

which are more focused on the domestic market (like many businesses in the east) will be belated affected from the recession (DSGV, 2010, p. 55). In the western states, the automobile industry is a very important sector. LSE in this industry are very export oriented and therefore subject to economic fluctuation. This fluctuation has a strong impact on many SMEs which are supplier of LSEs. The Net Profit (NP) ratio8 is, unlike the equity ratio, a figure direct linked to the economic situation of a business. As shown in Figure 3, the decrease of NP ratios since 2006 indicates the effect of the recession clearly for all size classes of the non-financial sector in east and west. Not just SMEs, but especially larger companies in East Germany have problems with their net profit ratios. This can be explained by a relative increase of material and labour costs during the last years (Plattner, 2008, p.11). However, today there are many successful and specialised firms in the east; closing the gap between the two areas continuously.

The German Banking System Banking systems have different structures according to the history and needs of nations. In Germany there is a system based on three pillars (Figure 4). Private Banks as one pillar of the banking system aim at a profit maximisation; serving either private- or business customer. Their core businesses are depositing- and lending. Banks governed by public law, in contrast to private banks, do not aim at profit maximisation but are subject to governmental guarantee schemes to support businesses. Especially during the recovery after WW2 or in a financial crisis, these institutions play a vital role. Due to the fact that major Private Banks, small Private Banks, credit associations and state banks all target business customer, there is a high competitive pressure arising leading to relatively low prices for banking services in Germany. On the other hand, the system approved its cushioning effects in the financial crises and recession 2009 thanks to different functions and diverse product/service portfolio of each bank type (Starke, 2010). The small local banks gov-

Figure 2. Development of equity ratios (DSGV, 2010, appendix p. 5)

579

Innovations and Financing of SMEs, Part II

Figure 3. Comparison of net profit ratios (DSGV, 2010, appendix p. 10)

erned by public law (Sparkassen and Volksbanken) are serving local companies and because of their independence from the international banking business, they are less affected than other larger bank institutions. Some larger banks have to revise their risk assessment methodologies because of the credit crunch and low lending costs; in order to be able to target new customer. Serving private-, business-, and corporate customer, large private banks (also called universal banks) helped to get through the financial crisis. Nevertheless, some institutions needed governmental help.

The Credit Rating Process The banks need to have an own rating system to judge investments. In this example, lending money to a SME can be seen as the investment. Therefore, the bank rates the lender’s ability to pay back the borrowed money including a provision. Every bank has its own rating system, criteria, and grades. Nevertheless there are institutions like the “Initiative Finanzstandort” that provide reference and comparability information. At the beginning of every relationship between the business customer and banks, the customer (borrower) needs to offer information to issue a file

Figure 4. Three- pillar based structure of the German Banking System

580

Innovations and Financing of SMEs, Part II

generated by a rating programme. According to an executive of a leading German Private Bank, the rating programme can consist of the following modules: Loan behaviour, account behaviour, qualitative factors, external data, finance analysis and master data. The ‘Finance analysis’ is based on collected and automatic evaluated balance sheets. Due to changing financial ratios, a certain economic development can be interpreted. In order to execute such a financial analysis, at least two annual balance sheets are required. Key figures are equity ratio and ‘Earnings before Interest and Taxes’ (EBIT). The account behaviour is dealing with the customer’s overdraft history, capitalisation of credit line and booked turnovers. Master data is set of information put together by a ‘key of professional categories’ (according to the industry of customer), evaluation of industrial sector, as well as the length of customer relationship and the time that the company is on the market. When judging about short- and long-term loans, the behaviour of borrowers is particular of interest. Furthermore, qualitative factors are being judged by an expert’s evaluation of the market, competition, and management. The last module is presented by external data, which are information from other financial service providers like ‘Kreditreform.’ All six modules are being evaluated according to its importance to generate a result that gives an approximate value. Even if the business itself generates attractive financial ratios, the Master data factor, which judges for instance the company’s industry, can influence the result towards a low credit rating. According to Starke (2010), previous rating systems used to evaluate financial ratios with qualitative factors each with a fixed weighting. For example, all financial ratios account for 85% and the qualitative factors for 15% of the overall score. However, in some cases it is possible to change the credit rating manually (known as “overruling”) to either improve or adulterate it; which of course requires documented rationales. The next important step of current credit rating processes is the evaluation of

the corporate structure and dependence on linked organisations or owners having a right to take or influence decisions. If the company is a subsidiary of another company, it is important to look at the level of dependence on the holding company. If the dependence is strong and the subsidiary is strongly integrated, the credit rating of the holding applies to the subsidiary as well. A subsidiary which is rated as ‘weakly integrated,’ gets its own credit rating. An additional agreement to improve (or rather not to adulterate) the credit rating, is the agreement of the transfer risk. This agreement has the advantage, that a bank lending a loan to a company has the security to refund itself by the central bank. Therefore, the company (borrower) needs also to provide the central bank with its balance sheet as a security. In case the borrower disagrees, the credit rating slightly adulterate, because it is more difficult for the bank to refinance itself. The firm’s credit rating can be represented by a range of grades between 1 and 14 or 1 and 6. Each grade represents a certain Probability of Default (PD) for a company with an investment project (Table 1). Additional to the working instructions according to the final score of the rating, some banks have superordinated working instructions. According to Starke (2010), an example for such instructions would be an “industry-traffic-lightschematic,” where certain industries have a red light; meaning they are not being granted financial services (no matter how good the credit rating score is). The idea is to reduce the overall Probability of Default concerning payback of loans. This is a problem for companies in the industry that have loyal customers and a product with a unique selling point to generate profit even in difficult times. Utilizing an “industry-traffic-lightschematic” can lead to a loss of profit; therefore the rating systems are getting more precise focusing on individual firms rather than just branches.

581

Innovations and Financing of SMEs, Part II

Table 1. IFD rating scale in Germany (Reichling, 2007, p. 96) IFD-rating-level

Deutsche Bank

Commerz-bank

Dresdner Bank

Hypo-Vereinsbank

PD-Area

I

iAAA to iBBB

1.0-2.4

1 to 5

1+ to 3

Up to 0.3%

II

iBBB to iBB+

2.6 to 2.8

6, 7

3- to 4-

0.3% to 0.7%

III

iBB

3.0 to 3.4

8

4- to 5-

0.7% to 1.5%

IV

iBB to iB+

3.6 to 3.8

9 (or 10)

5- to 6

1.5% to 3%

V

iB to iB-

4.0 to 4.8

11 (or 10)

6 to 7

3% to 8%

VI

iCCC and more

5.0 and more

12 to 14

7 and more

8% and more

Survey to Assess the Financial Structure and Financing of SMEs Focus Group and Type of Survey In the focus of the conducted survey were 30 non-financial businesses from different states in Germany. These SMEs, (according to the definition of the European Commission, described in paragraph 6.1.4.) were questioned by the mean of a questionnaire. The questionnaire, as a type of survey, was chosen because of limited resources and because questionnaires are easy and confortable to answer and submit (via email, fax, letter). Moreover, the evaluation of a standardised questionnaire is likely to be free of errors and simple to administer. The questions were designed in a defined sequence in order not to influence the respondent’s answers. The first questions were easy to answer and helped to classify the business; whereas the later ones were more detailed (e.g. about the use and knowledge of specific financing options). Besides questions about financial key figures (e.g. equity ratio), also questions about financing needs and preferences were raised to evaluate the firm’s financial situation. Furthermore, the perception of funds availability was of particular interest. The questions take the last three years, the current- and future situation into consideration. The results of the survey do not raise the claim of representing all German SMEs in every state and sector with a respective statistical relevance, but it is rather used to validate first of

582

all theories presented in literature and secondly larger surveys that have been conducted (like the survey of the BDI).

Discussion and Results of the Survey The average polled firm has an age of 55 years, employs 30 people and earns less than 10 million p.a. in 85% of cases. Leaving the financial crisis behind, 92% of polled firms claimed to be in a ‘good and stable’ economic situation, whereas 8% claimed to be in a ‘not stable and close to crisis’ situation. These results raise hope for SMEs and underline the perceived importance of a high equity ratio. According to the survey, 64% of polled firms have an equity ratio above 31%, which can be regarded as an outstanding result. 27% had an equity ratio between 10% and 30% the last 9% had a ratio below 10% (Figure 5). According to an in-depth interview with an executive from a leading German bank, most of SMEs in the producing sector only have equity ratios below 20% and in the trading sector between 5% and 10%. The highest equity ratios of polled trading firms are between 10% and 30%. Furthermore, to put it in an international perspective, German SMEs have been spoilt by favourable credit conditions during the last years due to the competition between financiers (especially foreign banks entering the market). In addition to an increased risk premium due to the crisis, the banking regulations (Basel I – III) prescribe ratios in which a credit must be based on equity. Therefore,

Innovations and Financing of SMEs, Part II

Figure 5. Equity ratios of polled SMEs

the requirements for credits rose during the last years. The survey confirmed that not a single firm rated the lending requirements as ‘rather low’; not to mention the options ‘low’ or ‘very low.’ Compared to the last years influenced by the recession, polled firms judged the requirements to gain a credit as slightly higher in the next 3 years. Nevertheless, the perceived availability of financial funds shows that in future the majority of polled firms (64%) are expecting no changes; nevertheless, 27% stated that it would be more difficult to receive the traditional financing funds like bank credits. In accordance with the ‘Moral Hazard’ and ‘Adverse Selection’ effect, described in the theoretical analysis of credit rationing in chapter 6, most firms (73%) agreed on the fact that the risk taken for an investment depends on the credit conditions. This leads to an increase of higher risk projects with worsening credit conditions. The most common financing options of polled SMEs were long- and short-term bank loans as well as leasing. Medium-term bank loans in the second place and deposits by partners in the third place (Figure 6). Factoring as well as types of private equity (as some non-traditional financing

options) do not seem to be common financing tools at this stage. This can be explained either by the fact that firms do not want to give any financial information to external bodies or simply by not knowing their financing options. 40% of polled firms stated that they have a lack of information concerning non-traditional financing options. As shown in Figure 7, the credit rating of 36% of firms has improved during the last 3 years, while 18% of firms stated that their credit rating has decreased. A reason for this negative development might be the fact, that 46% of polled firms do not employ financial experts for their financial planning and do not have a strategy to improve their credit rating (30%). A critical result of the survey was the statement that 60% of firms do not regard offered financial solutions as being based on the firm’s needs.

Recommendations and Possible Solutions The lack of expertise in financing as well as research and development is a major barrier for SMEs. According to the executed survey, most firms do not seek advice from financial experts to

583

Innovations and Financing of SMEs, Part II

Figure 6. Importance of financing options

Figure 7. Credit rating of polled firms

develop a strategy to improve the credit rating and cash flow. With a clear strategy employing nontraditional financing options, SMEs can become less dependent on bank financing. However, firms

584

have to be ready to give away some confidential business information in order to overcome the information barrier. Therefore, the creation of a long-term relationship with financiers based on

Innovations and Financing of SMEs, Part II

trust should be aimed. The classical ‘house-bank’ relationship is especially important during a credit crunch because lending conditions make it difficult for SMEs to obtain funds. In order to stabilize the business for the future, lack of innovations and resources can be compensated by Strategic Alliances and ‘Business Angels’; profiting from the expertise and resources of others. In order not to loose too many shares of the business, exit strategies for investors and business partner might be helpful.

FUTURE RESEARCH DIRECTIONS Future research could address the problem of achieving transparency of risks and opportunities related to innovations in order to ease the credit application process. Furthermore, it would be helpful to analyse why firms employ non-traditional financing rarely and how non-traditional financing can fill gaps of traditional financing. Furthermore, future research could address the following questions: •

•

•

What criteria does a Credit Rating System have to fulfil to be focused on individual firms rather than branches? To what extend should firms be financed through bank loans and what are the influencing factors (comparing USA and Europe)? How to develop an investor’s exit strategy to regain independence?

CONCLUSION Boosting the economy by supplying SMEs with loans and maintaining a risk sensitive credit rating system can be a trade-off for banks in the lending sector. While during a financial crisis the risk premium of loans rises, the media ask for

more financial funds to support struggling SMEs. Therefore, it is critical how a lender’s credit rating system judges the credit worthiness of firms. As the in-depth interview with the executive of a leading German Private Bank confirmed, some banks apply a so called “industry traffic light schematic” which looks at the economic situation of specific sectors rather than at individual firms. This might lead to a scenario where an innovative firm with a ‘core competency’ is refused a loan because of its branch ranking. Fortunately, the credit rating systems evolve towards a more individual and differentiated rating. On the other hand, bankers complain about low equity ratios and in-transparent capital structures of SMEs due to grouping structures, creating of reserves and assessment of materials and “semi-finished products” in order to minimize taxation (by lowering retained earnings). Besides the traditional banking loans, there are other options for SMEs to obtain funds. Especially for start-ups or entrepreneurial businesses, so-called Private Investors provide funds, expertise and contacts in exchange for a business share. This funding process has to be carefully planned as it has a bigger impact on the business than a traditional bank loan (especially in terms of independence). Two critical aspects (which are sensitive topics for owner/manager of SMEs) are the necessity for transparency of business information and operational interference. Finance can also be regarded as an Organisation’s Creative Area (OCA) that can develop core competencies especially with the help of Private Investors, controlling and monitoring the realisation of product and service innovations. Other types of non-traditional financing are short-term direct loans from online market places offered by private persons. Major aspects influencing SME financing: •

Capital structure (e.g. Equity Ratio)

585

Innovations and Financing of SMEs, Part II

• • •

Grouping (acting on behave of group interests rather than own interests) Traditional financing (long-term ‘housebank’ relationship) Non-traditional financing (Knowledge Management, Mezzanine capital)

Drawing a conclusion from the conducted survey and the literature review, it has been confirmed that most SMEs do not use much non-traditional financing options; missing out an opportunity to improve their capital structure for instance by the mean of Mezzanine capital. Simultaneously to the improved capital structure, the credit rating would improve as well and the dependence on traditional bank financing through loans can decrease. Especially for German SMEs, being in favour of a highly competitive lending market within the last decades, the use of non-traditional financing options seems to be crucial to adapt to changed credit conditions impaired by the financial crisis.

REFERENCES Astheimer, S. (2010). In sechs Jahren wird es brutal. Frankfurter Allgemeine Zeitung (Newspaper), 179(05.08.2010), 10. BDI. Bundesverband der Deutschen Industrie e.V. (2010). BDI-Mittelstandspanel: Ergebnisse der Online-Mittelstandsbefragung Fruehjahr 2010. Report by BDI, Ernst & Young GmbH Wirtschaftspruefgesellschaft, IKB Deutsche Industriebank AG, IfM Bonn. Retrieved on July 24th, 2010, from http://www.bdi.eu/Mittelstandspanel _Mittelstandspanel-8-Juni-2010.htm

586

Broekel, T., & Brenner, T. (2009). Regional factors and innovativeness: An empirical analysis of four German industries (p. 7). Utrecht University: Section of Economic Geography, Philipps University Marburg: Economic Geography and Location Research. (DOI 10.1007/s00168-009-0364-x). Retrieved on October 26th, 2010, from http://www. springerlink.com/content /pg207g54g8n21555/ fulltext.pdf Eurostat, European Commission (2010). Regional Gross Domestic Product table. Retrieved on August 5th, 2010, from http://epp.eurostat. ec.europa.eu/ portal/page/portal/product_details/ dataset?p_product_code=TGS00006 Finanzgruppe Deutscher Sparkassen- und Giroverband. (2010). Diagnose Mittelstand 2010: Blick nach vorn – Sparkassen begleiten Mittelstand durch die Krise (pp. 5–28). Berlin, Germany: DSGV. Institut für Mittelstandsforschung IfM. (2010). KMU-Definition des IfM Bonn. Retrieved on July 17th, 2010, from http://www.ifm-bonn.de/index. php ?utid=89&id=101 KG EOS Holding GmbH & Co. (2008). EOS Finanzpanel; Ergebnisse 2004 bis 2007 (p. 8). Boerner, C. J., Chair of Business Administration and Economics of Heinrich-Heine-University Duesseldorf (Germany). Lowe, R., & Marriott, S. (2006). Enterprise: Entrepreneurship and innovation: Concepts, contexts and commercialization (pp. 287–297). Burlington, USA: Elsevier Ltd. Moore, B. (1993). Financial constraints to the growth and development of small high-technology firms. In Storey, D. J., & Hughes, A. (Eds.), Finance and the small firm (p. 13). London, UK: Routledge.

Innovations and Financing of SMEs, Part II

Mullineux, A. W. (1994). Small and medium-sized enterprise (SME) financing in the UK: Lessons from Germany. London, UK: The Chameleon Press Ltd. Plattner, D., & Freudenberger, A. (2008). KfW Beitraege zur Mittelstands- und Strukturpolitik. Journal der Kreditanstalt für Wiederaufbau (KfW), 02.2008, 11. Frankfurt am Main: KfW. Reichling, P., Bietke, D., & Henne, A. (2007). Praxishandbuch Risikomanagement und Rating (2nd ed., p. 96). Wiesbaden, Germany: GWV Fachverlag GmbH. Starke,R.(2010). In-depth interview with an expert working as an account manager of small business customer. The Organisation for Economic Co-operation and Development. (1982). Innovation in small and medium firms (pp. 133–139). Paris, France: OECD. Tidd, J., & Bessant, J. (2009). Managing innovation: Integrating technological, market and organizational change (4th ed., pp. 232–236). Chichester, UK: John Wiley & Sons Ltd. Verheugen, G. (2005). The new SME definition, user guide and model declaration. European Commission, Enterprise and Industry Publications (pp. 5-15). Retrieved on July 17th, 2010, from www.euresearch.ch/fileadmin /documents/ PdfDocuments/ SME_Definition_en.pdf

KEY TERMS AND DEFINITIONS Adverse Selection: The problem with rising interest rates above the bank-optimal interest rate (where the bank’s average return is the highest) is the attraction of higher risk borrowers (Adverse Selection effect). Asymmetrical Information: The so-called Asymmetric Information (AI) problem occurs

between the customer and supplier of financial services (Canals, 2002, p. 307). The bank acting as a lender might not know the real risk when it grants a loan to its customer and a depositor might not be fully informed about the real risk of losing deposited money. Business Angel: Individuals investing in highrisk-investments in order to gain a profit and/or to develop a strategic association. In the US it is known as ‘Angels.’ Credit Crunch: A phenomenon describing a situation where hardly any loan (investment loan and working capital loan) is available to enterprises. Credit Rating: A bank’s system to rate the lender’s ability to pay back the borrowed money including a provision. Direct Loan: New types of short-term SME financing are direct loans from online marketplaces or ‘online social lending communities.’ Entrepreneur: A person running a business in an early stage and being accountable for the inherent risk. House Bank: A bank that maintains a longterm relationship with a certain firm. Financing decisions of the bank are based on experiences and insight-knowledge of the firm’s business. Venture Capital: Venture Capital firms tend to focus on larger firms that are easier to exit and to take over some control (usually taking over 1 board member position).

ENDNOTES 1



2



3



4



BDI: Bundesverband der Deutschen Industrie e.V. (Federation of German Industries) More about innovative tools and methodologies are described by Lowe and Marriott (2006, p.287-298). in German: Deutsche Demokratische Republik (DDR) 1 Euro = 1.95583 DM

587

Innovations and Financing of SMEs, Part II

5



6



588

The term ‘Mittelstand’ sums up small and medium enterprises with €1-50 million annual turnover and 10-250 employees. New federal states of Germany (East Germany): Former Soviet Occupation Zone located in the east of Germany includes the states: Mecklenburg-Vorpommern, Brandenburg, Saxony, Saxony-Anhalt and Thuringia.

7



8



The median values state that 50% of enterprises (in a particular category) have an equity ratio in the balance sheet of ≤ median value, and 50% of enterprises have an equity ratio of ≥ median value. The Net Profit ratio represents the profitability of firm and indirectly the ability to face a recession.

Section 8

Internationalization and Innovation

590

Chapter 32

The Recent Internationalization of Brazilian Companies Glauco Arbix University of Sao Paulo, Brazil Luiz Caseiro University of Sao Paulo, Brazil

ABSTRACT The recent wave of internationalization among Brazilian companies differs from past experiences, in terms of volume, reach, destination and quality. Brazilian multinationals are not restricting their activities solely to regional markets, nor are their first steps entirely directed towards South America. In amount of investment and number of subsidiaries there are signs they prefer assets and activities in advanced markets—including Europe and North America—where they compete on an equal footing with major conglomerates for a share of these markets. Some Brazilian companies have previous internationalization experience, and a significant portion had been prepared and initiated outward growth in the 1990s, after the economy opened up. However, the boom of internationalization that began in 2004 took place in such unusual conditions as to deserve highlight and special analysis. This chapter discusses the recent expansion of Brazilian multinationals as a result of: (1) the functioning of a more responsive and targeted system of financing, (2) transformation of the Brazilian productive structure, which led to the emergence of a group of companies seeking internationalization as a strategy, (3) preference for seeking more advanced economies as a means to expand access to new markets and suppliers, as well as to absorb innovations and technology, (4) the State’s performance in several dimensions, especially in financing the implementation of policies which support the creation of large national groups with a presence in the globalized market.

DOI: 10.4018/978-1-61350-165-8.ch032

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Recent Internationalization of Brazilian Companies

INTRODUCTION1 After the reduction of Outward Foreign Direct Investment (OFDI) flows in 2009 due to the international economic crisis, the rhythm of expansion by Brazilian multinationals abroad quickly accelerated, accompanied by the resumption of economic growth.2 In just the first nine months of 2010, the sum of acquisitions abroad by Brazilian companies totaled US $17 billion, a value greater than the total international acquisitions made by Brazilian companies throughout the 1990s. According to data from the Brazilian Central Bank, a definite and unprecedented acceleration of investments by Brazilian companies abroad only started in 2004. However, the first movements of this new wave had its roots exactly in the 1990s, after the opening of Brazilian economy, a period of rehearsal and preparation for this more aggressive thrust into the path of globalization, as can be seen in Figure 1. During this same period, companies like Petrobras (oil and gas), Vale (mining), Embraer (aeronautics industry) Braskem (petrochemicals) and JBS (meat processing) established themselves as large international players; other companies—

like Gerdau (steel), WEG (engines), Coteminas (textiles), Marcopolo (buses), BRFoods (food), Votorantim (cement, mining and pulp and paper), Odebrecht (construction) and Camargo Corrêa (textiles, cement, and construction)—which already held leadership positions in South America, consolidated, expanded and diversified their internationalization. Besides this, a number of other companies from different sectors—like Marfrig (food); Totvs, Stefanini e Bematech (information technology); Randon, Sabó and Ioschpe Maxion (cars and car parts); Lupatech, Romi and Tupy (mechanics); Natura (cosmetics); EMS and Eurofarma (pharmaceuticals), among others—elevated their standards of competitiveness and broadened activities abroad. Unlike prior experiences, the more recent internationalization of Brazilian companies possesses particular characteristics: in this most recent migration, the Brazilian multinationals went beyond their niches and their closest market, South America, and pursued targets like the OECD countries, North America and Europe in particular, where they compete directly with large conglomerates for an important slice of the international market (Figure 2).

Figure 1. Brazilian companies’ OFDI

591

The Recent Internationalization of Brazilian Companies

Figure 2. Background information for selected Brazilian multinationals

592

The Recent Internationalization of Brazilian Companies

The main objective of this chapter is to understand this unprecedented activity among Brazilian businesses. Recurring explanations seek to reduce this dynamic to the good moment that the Brazilian economy is currently experiencing, or even advantages due to the low exchange rate, which has facilitated international acquisitions. From a different angle, a substantial portion of academic literature emphasizes individual cases of entrepreneurism and business success stories. These explanations, although pertinent and useful, help to clarify only specific cases and do not address how and why the internationalization movement grew so rapidly, and was incorporated, as a strategy, by a significant number of companies. Our hypothesis seeks to reveal the four factors that work together to make viable and to accelerate the expansion of Brazilian companies abroad: •

•

The capitalization of companies and available financial resources, both foreign and domestic, with special highlight on areas of the economy linked to production of commodities, whose prices have boomed in the international market, basically due to the rise of China. The increase in capacity for innovation and entrepreneurship among Brazilian companies. After the opening of the economy, at the beginning of the 1990s, many Brazilian companies started to gradually adopt standards of international competitiveness, to modernize their management processes, to improve the quality of products and services and to increasingly pursue innovation in every step of their operations. These changes allowed many companies to incorporate exportation into their growth strategies, going beyond a business culture oriented to the internal market and to prepare for a bolder expansion abroad;

•

•

The preference among Brazilian companies to act and establish themselves in the most advanced countries and markets. The data and its analysis allows us to conclude that the internationalization of Brazilian companies does not necessarily follow a linear route, with the assumption of using a regional base, in this case, South America—as a platform for its expansion, nor do, at a basic level, direct themselves to countries with linguistic affinity. Without negating the explicative value of these components, our research reveals, on the other hand, that Brazilian companies have accepted the challenge of competing in OECD countries, where the community of shared language is small. The clearly pro-internationalization position of the Brazilian government, which strongly and formally encouraged internationalization of companies as one of its industrial policy objectives beginning in 2003. Changes in BNDES (Brazilian Development Bank) regulation, sown in 2002, with the first version of the Policy for Industrial, Technological and Foreign Trade Policy (PITCE, 2004) and the Productive Development Policy (PDP, 2008) allowed the bank to play an increasingly important role in supporting internationalization. The Ministry of Development (MDIC), the Bank of Brazil (BB), Petrobras and the Brazilian Agency for the Promotion of Exports and Investments (APEX) worked in harmony with the BNDES.

Beyond this introduction, this chapter is structured into four sections, in addition to the conclusion: Capitalization and Financing; Internationalization and Innovation; Destination of Brazilian OFDI; and New relations between State and Business.

593

The Recent Internationalization of Brazilian Companies

The rapid and aggressive emergence of Brazilian multinationals finds support in these four processes that function in a linked and interdependent manner, within an economic environment distinct from the past, from both a domestic and international perspective.

CAPITALIZATION AND FINANCING In this moment that Brazilian companies intensified their internationalization, Brazil, like many other emerging countries, experienced an extremely positive and rare moment from the point of view of finance, which hadn’t occurred since the 1970s. Starting in 2004, the country benefited from high prices for raw materials and from the solid entry of foreign capital—mainly due to the resumption of economic growth. Prices of raw materials—oil, minerals, and food—have been driven by the accelerated industrialization and vigorous growth of China and India, countries heavily dependent on imported food and basic supplies (Figure 3).

Figure 3. Commodities prices

594

This boom in commodity prices, in turn, contributed to the valuation of companies producing and marketing commodities, and also attracted a great deal of foreign capital to BOVESPA, where it has significant weight (Figure 4). Some of the leading Brazilian multinationals are producers of commodities—including Petrobras, Vale, Gerdau, JBS Friboi, BRFoods, Marfrig, Magnesite—and directly benefitted from these factors. However, other companies also indirectly benefited from the greater international visibility of Brazilian capital markets. Also contributing to the increased availability of financial capital: (1) low interest rates in the main developed countries, which liberated a major portion of capital seeking more profitable applications, and (2) a series of financial innovations that allowed for the multiplication of liquidity and the profitability of high-risk financial securities (Ocampo, 2007; Jenkinson, Penalver & Vause, 2008). It is appropriate, however, to show the importance of strategies adopted by both the Brazilian government and companies in order to maximize this financially favorable moment and use it to

The Recent Internationalization of Brazilian Companies

Figure 4. Domestic market capitalization

stimulate greater competitiveness of the Brazilian economy. Maintaining economic stability and the drastic reduction of external vulnerability (with unprecedented increase in liquid reserves) was fundamental for decreasing country risk and cost of credit for the entire Brazilian economy. The pro-activity of the government in reducing strong economic constraints, coupled with the increasing competitiveness of Brazilian companies, helps to understand the contrasts between capitalization of BOVESPA and the Buenos Aires SE, given that both countries have benefited from high commodity prices. The reentry of a set of industrial policies designed to modernize Brazilian productivity and raise standards of competitiveness—mainly through stimulating innovation, technology and investment—represent significant moments in the resumption of a proactive state. It should be remembered that this new state activism in Brazil has gone beyond the boundaries of economics, and generated social impacts through the restructure of the labor market, in raising minimum wage, expansion of social protection network, and cash transfer programs (e.g. Bolsa Familia), aimed at combating social inequalities and poverty. The

expansion and increase in social policies was shown to be essential for growth in family income in Brazil and improved revenue for companies in order to leverage and maintain domestic demand during the 2008-2009 crisis (Landim Júnior & Menezes Filho 2009; Sant’Anna, Ambrozio & Meirelles, 2010). Brazilian multinationals has adopted new financing strategies to take advantage of the situation and the conducive business environment in several ways, beginning with the myriad initial public offerings to leverage resources to strengthen and expand internationally. From 2004 to the first half of 2010, 30 Brazilian multinationals from various sectors (with the exception of the financial industry), and raised a total R$ 57.2 billion (~ US$ 33 billion) on the BOVESPA (São Paulo Stock Exchange), half of this value coming from foreign investors3. The reduction of country risk linked to increasing international competitiveness also facilitated access to external financing sources for the main Brazilian companies. According to research from Economática Consulting, the trading volume of 32 Brazilian companies listed on the New York Stock Exchange (NYSE) in 2007 was valued at

595

The Recent Internationalization of Brazilian Companies

US$ 555.6 billion, higher than the trading volume of these companies on the Bovespa (US$ 528.9 billion)4. In the same sense, large companies also increased their share of loans from international banks, with interest rates lower than in Brazil. As an example, Vale alone raised US$ 14.6 billion from foreign banks to acquire the Canadian company Inco in 2006, which became the company’s clear advantage in relation to its competitors (Fluriet & Braga 2009:116). During 2009, at the peak of the international financial crisis in Brazil, large firms secured US$25.3 billion abroad, a figure higher than that obtained in the years 2007 and 2008 combined. The fact that record volumes can be achieved in a context of credit restriction shows that the large Brazilian companies were regarded as a safe haven for risk aversion and had acquired robustness, prestige, and confidence in the international market. This was completely unthinkable a decade ago.

INTERNATIONALIZATION AND INNOVATION The opening of the Brazilian economy that began during the government of former president Fernando Collor and continued throughout the Fernando Henrique Cardoso administration, was designed to inject competitiveness into an economy accustomed to protectionism, and generated contradictory or even negative results for many firms in its early phase. While it triggered profound changes in standards of competitiveness in the economy—which drove many companies to restructure to adapt to a more open environment—it destabilized or even lead to the downfall of many companies which could not raise their low productivity to match new times. During this early reorganization of the economy the Brazilian industrial GDP fell by 12% just from 1990 to 1992.5 The companies that survived were forced to quickly and often radically restructure production, to learn advanced management

596

practices and incorporate the diversification of products and services into growth plans, expanding their activities and exporting. On the positive side, from the restricted angle of the economy, (without regard to social costs, for example) in the first four years of the 1990s, industry in Brazil reached a relative gain in labor productivity ten times higher than that obtained throughout the 1980s (Bielschowsky & Stumpo 1996:172). The stabilization of inflation since 1994 has helped to stimulate domestic consumption and allowed for a significant increase in production, but has also attracted more foreign companies to Brazil, increasing local competition The rationalization of organizational practices showed itself to be insufficient to ensure long term competitiveness in the most dynamic sectors, and many companies began to quickly lose ground to foreign competitors. Product differentiation and internationalization of activities were alternatives (sometimes complementary) for cost reduction, and for sophistication of business processes and products incorporated by these companies. Innovation, exportation and internationalization, though not always implemented simultaneously, become more widespread among Brazilian companies. In the second half of the 1990s, even in unfavorable financial conditions and without the support of governmental policies, there was a significant expansion of OFDI. In the last five years of the 1980s, Brazilian OFDI was, on average, US$ 212 million annually. In the first half of the 1990s, this jumped to US$591 million annually (an increase of 178%) and in the second half to US$1.57 billion annually (an increase of 640% compared to the 1980s) (Figure 5)6. It was during this period that Gerdau (metallurgy/siderurgy), which already had subsidiaries abroad since 1980, intensified its internationalization. From 1995 to 1998, Gerdau launched new plants in Canada, Argentina and Chile. In 1999, after an IPO on the NYSE, it aggressively entered the North American market, acquiring AmeriSteel for US$ 872 million. Since then, it has continu-

The Recent Internationalization of Brazilian Companies

Figure 5. First steps of Brazilian OFDI flows

ally increased its market position via several further acquisitions, becoming the second largest producer of steel throughout the Americas. Gerdau also took advantage of cross-borders acquisitions to diversify its operations, transforming itself into one of the largest worldwide suppliers of special steel products, of larger aggregated value (stainless steel, car parts, tools, hospital supplies). This was done through the acquisitions of Spanish companies Sidenor (2005) and GBS Acero (2006) that allowed Gerdau to strengthen its presence in the European’s auto parts and machinery industries. (Fleury & Fleury, 2009). The literature on International Business seeks to show that the relationship between internationalization and innovation is two-way. According to the classic conception of multinationals, based on the Anglo-Saxon experience (Dunning, 1981; 1988), to internationalize successfully a company had to possess some competitive advantage transferable to the host country. Advantages derived from labor cost or a brand only locally known, for example, would not be transferable to other countries. More appropriate would be the advantages linked to technology and innovation (of products and processes). Therefore, the more innovative

the company, the greater its advantage over local firms and the greater its chances of success in internationalization. Recently, however, many studies emphasize other aspects of the relationship between internationalization and innovation, mainly when it occurs in companies from emerging countries (Mathews, 2002; Arbix, Salerno & De Negri, 2004; Child & Rodrigues, 2005; Aykut & Goldstein, 2006; Borba Vieira & Zilbovicius, 2008). For emerging companies, innovation would not be necessarily a prerequisite, but instead a consequence of establishing overseas subsidiaries. When entering new markets—especially more demanding ones such as the American and European—companies would be able to absorb higher standards of competitiveness, capture new trends, become acquainted with new products and processes and even the tastes, habits and demands of new suppliers and customers. Though recent, the studies have already traced trajectories that show the different types of relationships between innovation and internationalization. There are cases—such as Embraer (Miranda, 2007)—where innovation is mainly related to product design and in networks of

597

The Recent Internationalization of Brazilian Companies

international partnerships that ensures access to technology and also the most competitive prices. In others cases, the strategy is to specialize oneself as a preferred supplier of a major multinational, installing factories close to them around the world and taking on new challenges and contracts—as is the case of Sabó (auto parts) in partnership with automakers (Aykut & Goldstein, 2006). A different road leads to acquisition of companies, mainly in developed countries, in order to absorb essential technological assets. This path has been taken by many Chinese companies, which rely on strong state support (Rui & Yip, 2008; Luo, Xue & Han, 2010). This was also, in part, the strategy adopted by Gerdau when it acquired steel mills in Spain, and by Magnesita in acquiring LWB Refractories of Germany, the world leader in basic refractory product, in 2008. Beyond technology, strategy based on acquisitions also helps reduce the negative impact of cultural differences on the productivity of the subsidiary abroad. This means that in addition to tangible assets, technology, and brand, the company has access to contractual relationships established with employees and suppliers, and the habits and demands of customers. There is strong evidence on the complementary relationship between internationalization and innovation in the activities of Brazilian multinationals. In a survey conducted by the Department for Business, Innovation & Skills in the UK in 2008, five Brazilian companies appear among those who invest most in R&D, detailed below (apud FAPESP, 2010). These companies are also among the fourteen Brazilians companies ranked on a Boston Consulting Group (2009) list of 100 emerging companies that vie for global leadership in their respective industries: •

598

Petrobras appears in second place among companies in the oil and gas sector, with investments of £442 million, correspond-

•

•

•

•

ing to 1% of its revenues, in R&D in 2007. It has subsidiaries in 28 countries and about 10% of its assets and jobs are overseas. Vale is in first place in the mining sector, with R&D expenditures of £368 million, or 2.3% of its revenues. It has subsidiaries in 34 countries and 25% of jobs and 39% of assets are outside Brazil. Embraer is the 16th among aerospace and defense companies with £131 million in R&D investment, equivalent to 5% of its revenues. It has subsidiaries in six countries and 12% of jobs and 39% of assets are abroad. Braskem appears in 90th in the chemical sector, with investments of £22 million in R&D, representing 0.4% of its revenues. It has subsidiaries in eight countries and is part of Odebrecht, which has about 56% of their jobs and assets abroad. WEG is the 106th in the electrical equipment and electronics sector, with investments of £21 million in R&D, or 2.1% of its revenues. It has subsidiaries in 26 countries and 11% of jobs and 18% of assets abroad. (FAPESP, 2010 and Valor, 2009).

Although Brazil has fewer companies in the R&D investment ranking than India and China (15 and 9 firms respectively), the above companies are responsible for activities that impact on the entire Brazilian economy. Recent research (De Negri, 2010) states that about 40% of all engineers with formal work contracts in Brazil work for suppliers of Petrobras, a company that has a business plan to invest US$ 224 billion between 2010 and 2014 and expand its production rates of 10% p.a. This link between internationalization and innovation is also evident even when the analysis involves the whole Brazilian industry. Arbix, Salerno & De Negri (2004) crossed statistical data corresponding to 72,000 industrial compa-

The Recent Internationalization of Brazilian Companies

nies in Brazil, relating to the year 2000. While 30.5% of the enterprises of the sample claimed to have done some product or process innovation after 1998, that figure rose to 70.4% among the firms that possessed OFDI. The authors also identified a cluster of approximately 250 companies in which their subsidiary abroad was the main source of information for innovative activity. These companies, despite representing only 0.35% of the sample, accounted for 5.8% of total national industrial exports. Their competitiveness was also demonstrated by the fact that they paid higher salaries and hired more qualified labor than average, generating positive impact for the entire Brazilian economy. Borba Vieira and Zilbovicius (2008) observed a similar phenomenon when conducting case studies of three Brazilian multinationals from the auto parts, petrochemicals and adhesives sectors; they concluded that OFDI is a strategy for them to gain exposure to the most modern technology in foreign markets. Another dimension of the relationship between internationalization and innovation is revealed in research from the Dom Cabral Foundation (2008), of about 100 Brazilian multinationals—that was a reissue of a survey applied in 2002. While in 2002 none of the companies interviewed declared they performed R&D activities abroad, in 2008, one third of the sample stated they had adopted this strategy.

the Brazilian crisis of the 1980s and 1990s and created dynamic competitive advantages based on product diversification, investment in R&D, and internationalization. These mechanisms continued and intensified in recent times, and explain how these companies came to be recognized as global players (BGC, 2009). These companies began their growth with imitation strategies, through intensive licensing of technologies (Embraer), or adapting of products for the domestic market (Marcopolo), or through hiring from large multinationals (Natura). These fast-followers moved into the position of prospectors, and, more recently, began to be guided by offensive strategies, based on a quest for global technological leadership (Griffin, 1997; Freeman & Soete, 1997; Goldstein, 2002, 2007). In the last decade, these companies expanded themselves vigorously in the domestic as well as in the foreign market, showing that that foreign and domestic expansion were not mutually exclusive strategies, as the literature showed during the 1980s and 1990s, but instead more complementary (e.g. Iglesias & Mota Veiga, 2002:19; Cyrino & Tanure, 2009:18). The stronger a company’s position in the domestic market, the greater the muscle for companies to raise the bar. Moreover, the more internationalized a company, the more competitive it is in the global market, as it possesses fast access to new productive knowledge, financial resources, suppliers, and clients.

Three Short Case Studies on Innovation and Internationalization

Embraer

The major goal of this chapter is to understand the strategy transformations that occurred at various Brazilian companies that led to intense acceleration of their internationalization. In the following we present a succinct overview of how three companies developed different strategies for innovation and internationalization: Embraer (aviation), Marcopolo (busses) and Natura (cosmetics). The three are innovative and rapidly growing companies that understood how to respond to

The building of high-technology companies in emerging countries generally involves the incorporation of productive knowledge from foreign markets. The case of Embraer is no different. Its first commercial success, the Bandeirante turboprop (commercial aviation, eight seats) and the Ipanema (agricultural spraying) were developed by foreign technicians brought in to work at the Aerospace Technical Center by the Brazilian government.

599

The Recent Internationalization of Brazilian Companies

In addition to this, in its early years Embraer also learned to manufacture jets and entered into the military segment thanks to a partnership with the Italian company Aermacchi, using technology transfer for the development of the Xavante ground-attack jet (1971) and afterwards the AMX jet fighter in 1985 (Miranda, 2007). It was also through licensing of technology with the North American Piper (1975) that Embraer took its first steps into the executive jet market, now one of its major segments. In both segments, however, the growth of the company was only possible due to continual investment in R&D, and in the diversification of products. In fact, the innovations that Embraer has obtained through its precocious internationalization were as essential for its success as the major state support it received. The first subsidiary abroad was opened in the USA in 1979 and three years later the company already dominated one-third of the North American market for 10-20-seat planes. In 1983, it established a new subsidiary in France, aiming to service the European and Middle Eastern markets, and a couple of years later was already competing for worldwide leaderships of aircraft of 30-40 seats. Beyond this, the strong dependence on the State brought financial difficulties when serious crises hit the country in the 1980s and 1990s. State management also became problematic when the technological capacity of Embraer began to serve foreign policy interests without proper attention to necessary market demands, as was the case with the CBA-123, an expensive turboprop that revealed itself to be a commercial failure in a troubled partnership with Argentina at the end of the 1980s (Goldstein, 2002). With the opening of the Brazilian economy in the early 1990s, the financial situation of Embraer grew more complicated. In 1994, the year of its privatization, its debts surpassed US$1 billion (Miranda, 2007). After privatization, the company adopted a new organizational structure, with sizeable investments in IT and the establish-

600

ment of boards for each specific aircraft project, which begun to operate as semiautonomous cells of the company. The result was optimization of learning and enhanced agility for development of new projects (Vasconcellos et al., 2008). The time for delivery of the EMB-120Brasília (30-seat commercial aircraft) fell from 16 to nine months (Goldstein, 2002). However, the principal innovation of the period occurred during the ERJ-145 project (commercial jet for 50 passengers) that required the creation of a wide international network of 350 vendors and clients participating in diverse steps of product development. Four of its main suppliers were risk partners, that is, they helped to finance the project. The major clients were invited to participate in a pre-project phase, in order to define the characteristics of the aircraft (Vasconecellos, et al. 2008). Besides capturing market trends, the partnerships made Embraer, as supervisor of projects, the main beneficiary of international integration of the R&D routines of its vendors. The strategy was revisited even more intensely with the EMB170/190 family of jets, for up to 122 passengers, when 16 supplies took on a role as partner of risk. These mechanisms were fundamental to stimulate the whole innovation system of the company and could be considered as one of the first successful experiences of Open Innovation, even before the dissemination of this concept by Henri Chesbrough, in 2003. The success of the new commercial jets, in turn, pushed internationalization even more. In 1999, a consortium of French companies—Dassault, Aerospatiale/Matra,Thomson-CSF e SNECMA— acquired 20% of the ordinary shares of Embraer, making possible greater financial solidity and generating new opportunities for technological capacity, especially in the military segment. In the following year, the company executed an IPO on the New York Stock Exchange (NYSE) and opened its first commercial offices in China and Singapore. The year of 2002 saw the opening of the first factory in China, in Harbin, near

The Recent Internationalization of Brazilian Companies

Beijing, for the creation of the ERJ-145 family of jets (Miranda, 2007). In 2004, it bought the Portuguese OGMA and should inaugurate two new plants, with complex structures and composite materials fundamental for the production of more agile aircraft, in 2011. Embraer is today a global company. It is the third largest producer of planes in the world by annual delivery and is the market leader in regional jets. To maintain its competitiveness, Embraer is diversifying its portfolio even further, currently moving in the direction of military aviation segment and aeronautical services offerings. In the newest defense area, the project is a transport and air refueling plane KC-390, with a capacity to transport up to 23 tons. The project, currently in the phase of vendor selection, expects to generate more than 14 technology transfer contracts with foreign companies7. The mechanisms of open innovation developed by the company teaches us that success—beyond state support- is linked to the sources of its own business dynamism and of the close ties maintained with partners, suppliers, and clients around the world.

Marcopolo The Brazilian bus producer was founded in 1949, initially dedicated to the production of artisanal wooden car bodies. It had a trajectory of rapid expansion and at the end of the 1970s, it was exporting steel car bodies to practically all of Latin America and some Africa countries from its three factories in Brazil. Since its first years, the company invested in constant diversification of products for the launch of its lines of microbuses (1972) linked busses (1978) and electric busses (1979). It was also the first company to adapt European bus makers’ innovations for South America, as in the case of the high-decker bus in 1984, and the double-decker, launched in the Argentine market in 1996 (Stal, 2007).

In 1991, when the crisis in Brazil was intense, Marcopolo opened its first factory abroad, in Coimbra, Portugal. The choice of this country was not due just to linguistic and cultural proximity, but the location also functioned as a laboratory to incorporate technology from European factories, principally through access to simultaneous engineering with suppliers outside the Brazilian market. Thanks to this intense learning, coupled with its own efforts in R&D, Marcopolo’s vehicles became capable of competing in whatever country and the company became a worldwide exporter of technology for production of busses (Rosa & Rhoden 2007). Unlike Embraer, Marcopolo was able to obtain success through an elevated level of verticalization, maintaining direct control over its principal Brazilian suppliers (materials, seats, doors, windows, plastic components, etc.) that facilitated the transfer of technology for European vendors to local vendors (Rosa, 2006). Between 1999 and 2001, Marcopolo opened its new productive units in Argentina, Colombia, South Africa, and Mexico, beginning with partnerships with large local chassis manufacturers (Mercedes Benz in Argentina and México; Scania, in South Africa). This model of entry via a joint venture with major local manufacturers was repeated in India and in Russia in 2008, when it established joint ventures with Tata Motors and Ruspromauto, and in Egypt in 2009 in partnership with GB Auto8 In its first internationalization experiences, Marcopolo exported all components manufactured in Brazil and only performed the assembly in the host country. However, starting in 2004, the company began to work to develop new suppliers abroad, to protect against currency oscillations, as the strategy of internationalization for Marcopolo had as its focus the large emerging countries that possessed few consolidated companies and high growth potential, but volatile exchange rates. At each industrial plant, Marcopolo has its own R&D team responsible for adapting products to customer demand. One of the company’s 601

The Recent Internationalization of Brazilian Companies

competitive advantages is the ability to mount bodies on any type of chassis. The high quality of its products and its flexible development capabilities were fundamental for the Indian giant Tata Motors to be convinced to sign a joint venture with a Brazilian company within its own country. Currently the Indian factory is Marcopolo’s leading international operation. With installed production in eight countries and exports to more than one hundred, Marcopolo is now a company with global coverage that holds 40% of the Brazilian market and 7.0% of the world market. It is also an exporter of technology and has an internationalization model that is above all pragmatic and flexible. Control and development of supplier networks and aggressive associations with local champions sustains Marcopolo’s excellence in design and assembly technology of its car bodies.

Natura Natura is a leader in cosmetics, fragrances and personal hygiene in Brazil—the world’s third largest market, behind only the U.S. and Japan, according to data from Euromonitor (apudABIHPEC, 2009), with annual revenues of $ 2.4 billion in 2009. Like the two other cases seen here, this is a young company that had rapid growth based on constant innovation of products and processes. Its internationalization is less intense than in the other two cases examined and the domestic market accounts for 93% of its revenues—while this figure is 60% for Marcopolo and just 7% of Embraer. Its plans, however, are ambitious, and it is important to note that company always tried to absorb knowledge from abroad and strove to integrate the strategies of innovation and internationalization. Natura was founded in 1969 by Antonio Luiz Seabra, a young economist who was manager of a small cosmetic laboratory owned by a French esthetician in São Paulo. Three years later, in 1972,

602

the company hired Anísio Pinotti, an industrial chemist, who had experience in other companies in the cosmetics industry, to lead the development of new products based on herbal extracts and marine compounds (Ghoshal et al., 2002). The rapid growth of Natura began when it joined Pro-Estetica, a company specializing in direct sales at home, in 1974. This business model was clearly inspired by the U.S. company Avon, already used in Brazil for more than a decade. The partnership moved forward. Natura, with its inexpensive, but quality products, saw its revenue jump from $53,000 in 1973 to $ 3 million in 1979, when the company had 1,000 sales consultants (Nakagawa, 2008). Since then, the company’s rapid growth has attracted several other entrepreneurs by creating a set of sister companies including a fragrance and makeup company that used the same vendors as Natura, and two distribution companies that send their products to all regions of Brazil. In the late 80’s, Natura has merged the operations of these four companies as a way of responding to the crisis that affected the Brazilian economy and prepare itself for the market opening that was already being announced. The merger was followed by a deep organizational restructuring in the early 90’s which included the hiring of several executives and consultants who had worked for large multinationals in the sector. Among the new executives hired was Phillippe Pommez, a French citizen, PhD in Physical Chemistry from the Sorbonne who had been vice president at Johnson & Johnson’s headquarters. He took on the role of research director at the company and today he is vice president for internationalization and a major contributor to the French subsidiary of Natura9. It was also after the hire of Pommez that Natura launched some of its main family of products, such as Simbios in 1991, Chronos in 1992, and Mother and Baby in 1993, and Ekos in 2000, which only uses active ingredients extracted from Brazilian biodiversity.

The Recent Internationalization of Brazilian Companies

The importance of innovation in Natura’s success has continued to grow. In 1990, 10% of its revenue was derived on the sale of products created in the previous two years. In 2009, the percentage was 67.5%, revealing a high dependence of innovative activity (Natura 2009). Spending on R&D also increased. Recently, Natura decided to reduce by half the high number of launches per year—which reached 200 annually—to concentrate on innovation efforts on sales of its key products (Frederick & Vasconcellos, 2008). It was also in the 1990s, when it embarked on its most innovative phase that Natura also obtained success in its internationalization process. In 1994, it opened its own distribution centers in Argentina and Peru, where an intensive training program for vendors and a reward scheme for successful management of operations were developed. The same model was replicated successfully in Chile in 2002 and in 2004 a new corporate headquarters was created in Buenos Aires, responsible for operations in the countries of Hispanic America (Lima et al., 2008). It was in 2005, however, that it began its most ambitious international project, entry into the French market, one of the most world’s most competitive markets in this sector. That choice, which at first glance appears to be irrational from the perspective of opportunities for growth, was supported by a strategic vision of leveraging its innovative activity. The French subsidiary is part of a project of relative separation of research and development activities. In this project, research teams are moving towards medium and long–term planning, directed towards radical innovations, while development teams are focused on short-term and on fulfilling the yearly plan of launching new products. To optimize the potential for radical innovation, research activities then began to be allocated in knowledge-intensive areas (Frederick & Vasconcellos, 2008).

Besides having an R&D center, the European subsidiary also had a distinct business strategy. Anticipating difficulties in implementing its system of direct sales in France, Natura opened a “sensory store” in Paris so that customers could try out their products. Today, in addition to the store, the company already has a network of 1,700 salespeople in the country. The strategy of opening a “sensory store” was also replicated in Mexico in 2005 and in the Colombian market in 2007 (Lima et al., 2008). In both countries the activities are still incipient and the company is studying the possibility of changing its distribution strategy for faster penetration abroad, such as establishing partnerships with local companies and outsourcing manufacturing of products abroad (Valor, 2010:62). Despite internationalization of some of its R&D and early production abroad, the company still focuses most of its innovative effort in Brazil. Its main laboratory is located in the city of Cajamar, near São Paulo, and houses about 250 researchers. In 2007, Natura acquired 300,000 square meters of land within the Ciatec 2 Technological Hub, near the University of Campinas (the second largest university in Brazil), to install the company’s newest and most modern R&D center, to accommodate 300 researchers10. Also in 2007, the company created the “Natura Campus Program,” which seeks closer ties with leading university centers in the country. There are now more than 250 research groups registered voluntarily in the initiative, which has received about 100 proposals for university/company cooperation. On the one hand, Natura is recognized as an example of Brazilian innovation and has an intense material and symbolic relationship with national biodiversity, and on the other hand, one of its strengths is precisely its longstanding openness to knowledge flows from other organizations in Brazil and abroad. In the 1990s, it restructured its management activity and R&D by hiring several highly qualified professionals from multinationals

603

The Recent Internationalization of Brazilian Companies

in the sector. Most recently, in the current decade, it looked to France for a chance to renew its innovative activity.

DESTINATION OF BRAZILIAN COMPANIES The predisposition of the Brazilian business elite to follow the path of innovation is also evident if we map out the main destinations of Brazilian multinationals going abroad. Although some authors insist that Brazilian companies concentrate their international activities in South America (e.g. Dunning, Kim & Park, 2008:167), there is no available data to support this hypothesis. Despite the fact that Brazilian multinationals have important influence in this region, evidence suggests that migration is increasingly directed to the more dynamic markets in the United States, Europe, and more recently, China. Two-thirds of Brazilian OFDI is reportedly located in tax havens (Figure 6). With rare exceptions, it is not possible to accurately determine their final destination11. These assets are often used Figure 6. Brazilian MNEs reported OFDI stock

604

to make acquisitions in distant countries, where it is more difficult to achieve success through organic growth (Goldstein 2007:17). In addition to the assets located in tax havens, Brazilian companies state they possess more assets in Europe (16.5%) and North America (8.9%) than in their own region (6.4%). Given the difficulties in determining the real destination of OFDI, this study sought to identify the location of the subsidiaries of Brazilian companies. This exercise was conducted in detail for 88 multinationals across various sectors (Figure 7 and Figure 8). This exercise has limitations because, in the first place, there is no available data on the amounts invested by each company in each destination, and secondly, the sample size does not necessarily represent the full number of enterprises with investments abroad. However, the authors believe that this is a useful exercise to capture important features of expansion by major Brazilian groups. The visual result of the second analysis (Figure 8) is very different from what might be expected from a mapping of OFDI. As is already known, a significant proportion of Brazilian investments are

The Recent Internationalization of Brazilian Companies

Figure 7. Number of Brazilian MNEs in each other

Figure 8. Number of Brazilian MNEs by industry in each region

605

The Recent Internationalization of Brazilian Companies

concentrated in a few large commodity-producing companies, especially Petrobras, Vale, Gerdau12 and more recently JBS Friboi (Fundação Dom Cabral, 2007). This does not underestimate the role of these companies for the Brazilian economy. The mapping, however, shows the number of companies in each sector in each region of the globe, emphasizing a little studied aspect of the recent internationalization process: in other words, it reveals the involvement of a growing number of midsized businesses and sectors of medium-high and high-technology looking at the foreign market as a way to gain competitiveness. The country that attracts the largest number of Brazilian multinationals is the United States, with 59 companies, in contrast to Argentina, which has 51 Brazilian companies. The Central Bank data also points in the same direction: the U.S. is the largest destination country—excluding tax havens—for Brazilian OFDI, with US$10.5 billion, while Latin America accounts for a total of US$ 8.05 billion.13. This preference for the U.S. market questions the interpretations that identify South America as the preferred area for Brazilian multinationals. In a broader sense, this also calls into question, in the Brazilian case, the validity of the gradualist approach of Johanson & Vahlne (1977; 1990) that gives a theoretical basis for many important works on emerging multinationals. The gradualist approach assumes that firms first internationalize themselves close to home, geographically and culturally speaking, as a way to reduce risk and uncertainty for business owners and managers, then expand into more distant markets. In Brazil, the major multinationals in the country do not necessarily follow this pattern when it comes to establishing subsidiaries. By observing the European market, we see that Portugal has fewer numbers of Brazilian subsidiaries when compared with the United Kingdom, and Germany also stands out, contrary to the arguments for preference based on access facilitated by language. In the declared value of

606

OFDI, Spain ranks first among Europeans while Portugal is only the seventh destination. In the Far East, a significant number of companies make efforts to serve the Chinese market, which is already the fifth-largest destination for Brazilian multinationals. Almost all of these subsidiaries were opened in the last decade, with 26% of the sampled companies already having a foothold in China. Despite the importance of cultural factors and linguistic community, it is possible to conclude that the typical destination of Brazilian multinationals, across all continents, shows a preference for admission to the largest and most dynamic markets. This search for more dynamic markets is due, on one hand, to the fact those markets demand more constant and intense presence from firms hoping to succeed through exports and therefore, given its competitiveness, they are the markets that offer greater returns. On the other, however, it is due to the fact that these markets are the privileged locus of innovation, construction and dissemination of new knowledge production, emergence of new trends, and of partnerships and synergies with competitive companies. This is precisely the justification that Marcel Malczewski, former president and founder of Bematech, a Brazilian multinational in the hardware and automation industry, offers in explaining why his company set up subsidiaries in China and Taiwan in recent years, accepting the challenge to participate among fierce Asian competition: “a very important part of our company, of our business, is in Asia, because if we have a hardware company and we want to innovate, we have a presence there.” Malczewski stated that the company invests between 4% and 8% of its net revenues in R&D14. A similar phenomenon occurred with the IT services companies, CI&T and Politec which has subsidiaries in the United States, Britain, China and Japan (Valor, 2009:62; Arruda, Almeida & Casanova, 2009:202), and with the IT sector in general, which tends to always seek the U.S. market.

The Recent Internationalization of Brazilian Companies

It also occurred with several companies from the metalworks and auto parts sectors—WEG, Romi, Lupatech, Gerdau, Tupy, Tramontina, Randon and Sabó—that moved into the competitive German market; with Natura (cosmetics) which opened a subsidiary in France; and Renner Sayerlack (industrial paints) which has a factory and R&D center in Italy, among others. Yet from Figure 8, it is possible to note that Latin America and Africa are preferred targets for a larger number of companies in the engineering, mining and textiles sectors, while the greatest number of companies from the IT, chemical, mechanical and vehicles and auto parts sectors prefer the American, European and East Asian markets. This is another indication that the more knowledge intensive the sector in question is, the more it tends to seek out competitive markets as a source of innovation. Although the first internationalization activities of some of the leading Brazilian multinationals (e.g. Petrobras, Vale, Embraer, Gerdau, Odebrecht, and Andrade Guitierrez, Coopersucar, Tigre, Duratex, and Alpargatas) had their start in the 1970s and 1980s (Guimarães, 1985; Diaz, 1994), the recent expansion, besides being more intense and including a larger number of companies and industries, has three fundamental differences from the past in respect to business strategies. •

•

The first of them is precisely the fact that they are not more concentrated in Latin America, as was the case in the 1990s. (BNDES, 1995; Iglesias & Mota Veiga, 2002). The second is that it is no longer just a situational movement, as it was during the 80s, when, protected by the domestic market some companies became internationalized as an alternative to escape the stagnation and instability that plagued the Brazilian economy.

•

The third is that the companies do not limit themselves to regional or niche markets, and instead compete openly for larger slices of the market with multinationals that have been traditionally better equipped and more powerful.

The internationalization of business strategies in Brazil started with the opening of the economy in the 1990’s due to the need—and also the possibility—of becoming more competitive against foreign competition. This strategy is associated with- as both cause and consequence of—sophistication in production and management standards and a more entrepreneurial stance among the business elite. The argument that Brazilian firms internationalize due to low growth in the domestic market (e.g. Cyrino & Tanure, 2009:18), although it might seem plausible for much of the 1990s, loses strength when we look at the recent boom of Brazilian OFDl, which occurs precisely as the Brazilian economy is growing at a faster pace. Throughout the last decade, OFDI is highest precisely during those years of the greatest GDP growth. This shows that internationalization is no longer merely the result of a tactical choice between domestic and foreign markets. It has evolved into a constant, becoming part of the strategies of a growing group of companies, and connected to a global vision of opportunities in the business world, in which the chains of production value and knowledge are extended across countries, with suppliers, customers and competitors found in the key global markets. This strategic direction among a group of companies in search of internationalization and innovation, the fruit of a new commitment to competitiveness, has been fundamental in the success of recent expansion among Brazilian multinationals. From this point of view, it is important to note that the two-part innovation-internationalization of these efforts could be more intense. The total

607

The Recent Internationalization of Brazilian Companies

Brazilian investment in R&D is still only half the OECD average—around just 1.1% of GDP (FAPESP, 2010)—and the country has struggled to raise this level, despite incentives created over the last decade. For the pathways of globalization identified by this study, we are led to believe that the more innovative firms are, the greater the opportunities to grow in the global market. Therefore, strategies to enhance innovation and internationalization can and should be articulated by both firms as well as public policy-oriented development.

NEW RELATIONS BETWEEN THE STATE AND THE BUSINESS WORLD Some authors (Schneider, 2009; Aman, 2009; and Finchelstein, 2009) analyzed how the Brazilian government, over decades, helped to structure some of the leading corporations today—CSN, Vale, Petrobras, Embraer and a good portion of Braskem. Moreover, the government furnished incentives and protection in the formation of large private groups. Even Gerdau, which justifiably boasts of its entrepreneurship, has expanded its operations with subsidized loans from BNDES (Brazilian Development Bank) since the 1970s (Andrade & Cunha, 2003), and in the early 1990s strengthened itself through the acquisition of three state steel companies, whose privatization was restricted to national capital (Finchelstein, 2009). For this study, we opted to identify only State-implemented devices to encourage internationalization of enterprises from this decade. Emphasizing the important role played by the State is not meant to minimize the companies’ roles as the principal agents in this process. As already explained, the intensification of globalization initially began in the 1990s when there was no type of policy stimulus whatsoever. It was only with the Luis Inácio Lula da Silva administration that the government began to outline a clear direction to support the movement –already a

608

reality for many companies – of expansion abroad. Given the incipient nature of the State role in this process, it is necessary to recognize that, for the most part, efforts to internationalize business are still conducted without direct State aid. However, in some cases this support has been essential. With the return of industrial policies in Brazil in 2004, internationalization incentives for companies officially became part of the government agenda. In this same year, the Minister of Development Luis Furlan stated that “the goal of the government for this mandate is to keep at least 10 Brazilian transnationals in operation15.” In September 2005, BNDES funded for the first time an acquisition abroad by a Brazilian company, disbursing US$80 million to meat processor JBS/ Friboi for the purchase of the Argentine subsidiary of the North American company Swift. (Além & Cavalcanti, 2005). Between 2005 and 2009, BNDES disbursed— via loans and securities underwriting- more than US$8 billion to the meat processing industry, of which at least US$4.5 billion went to the internationalization of the JSB and Bertin groups—which then merged in yet another operation financed by the institution. Thanks to financial support from BNDES, JBS acquired several companies from the United States (including the American companies Swift & Co. and Pilgrim’s Pride), as well as Australia and Italy, making it the largest processor of animal protein in the world16. The vast majority of BNDES resources directly involved in acquisition of companies abroad were allocated to the meat processing industry. In other sectors there have been few operations, with significantly lower values, such as loans of US$80 million to Itautec (IT) to buy the U.S. company Tallard in July 2007, US$17 million to Bematech (IT) to purchase U.S. company Logic Control in March 2010, and US$7.5 million for Eurofarma (pharmaceuticals) to complete the purchase of Argentine company Quesada Pharmaceuticals in June 201017.

The Recent Internationalization of Brazilian Companies

The fact that the BNDES allocated the majority of its investments for internationalization of a low knowledge-intensive sector, thereby reducing potential to transform the Brazilian productive structure, has been a source of much commentary, including some from the authors of this chapter. As explained (Arbix & Caseiro, 2010), although the recent inflexion of Brazilian industrial policy and its decision to support internationalization is considered positive, the authors highlight the urgent need to prioritize innovation and technologyoriented initiatives, in order to break away from the Brazilian dependence on commodities. It is also necessary to recognize that there are various other mechanisms, direct and indirect, by which the State currently still stimulates the growth of Brazilian multinationals. Under the scope of BNDES, it was thanks to the bank’s funding for construction projects in other countries (with the support of Brazilian diplomacy), that construction companies Norberto Odebrecht, Camargo Corrêa and Andrade e Gutierrez—despite their know-how accumulated over decades—could resisted Chinese competitors in Latin America and Angola18.

In another key measure the State supports, via BNDES and Petrobras, the formation of large private groups. From February 2005 to February 2010, the bank offered at least US $10 billion of funding for the strengthening of large companies in the domestic market in various sectors, including some with high innovation potential (Figure 9). In reference to this strategy, the bank’s president, Luciano Coutinho, said, “it is consistent with the government’s industrial policy to enable the development of global players in Brazil, on a worldwide scale.”19. A particularly interesting case is the petrochemical sector, one of the sectors that have recently received more state investment. Largely built in the late 1970s from a complex alliance between the State, Brazilian companies, and multinational companies, it was decentralized in terms of geography and capital control. Throughout the 1980s the industry lost competitiveness and, at the beginning of the following decade, a total of 27 companies were privatized (Montenegro, 2002). In 2001, Odebrecht and the Ultra Group initiated a move to consolidate the sector’s

Figure 9. State financial support to M&A in Brazilian

609

The Recent Internationalization of Brazilian Companies

assets. In 2007, Petrobras entered vigorously into this project, first participating in the acquisition of the Ipiranga Group in a transaction of US$ 4 billion, and incorporating its petrochemical assets in Braskem, part of the Odebrecht Group. Subsequently, it acquired Suzano Petrochemical for US$1.5 billion and merged it with Grupo Ultra, creating Quattor. In early 2010, Petrobras—possessing a 30% stake in Braskem and a 40% stake in Quattor—worked for the merger of the two largest petrochemical companies in the country, spending more than US$1.5 billion in a deal that formed the largest petrochemical company in the Americas, surpassing the North American DOW in production capacity20. In the shareholders’ agreement between Petrobras and Braskem it was established that one of the goals of this partnership was to allow “a process of internationalization through the acquisition of petrochemical assets, with the subsequent increase in its world market share” (p.2). Less than a month after the agreement, Braskem announced the acquisition of the American company Sunoco Chemicals for US$350 million and investments of US$2.5 billion in Pólo Petrochemicals in Coatzacoalcos, Mexico. Petrobras, which owns 36% of the latter company, also gained veto power over any change in its controlling interest21. Other multinationals like Totvs (IT), Votorantim (construction, mining and pulp & paper), BRFoods (food) and Vulcabras (footwear) benefitted from consolidation via participation from BNDES. All of the operations in Figure 9 obtained financing from the bank, via loans and/ or securities underwriting. The operations most frequently combinethe two forms of financing, with the institution also typically receives golden shares as was the case for Vale, Embraer, CSN and Friboi, in order to avoid future acquisition by foreign companies (Mattos, 2008). According to Bovespa’s figures, BNDES is a member of at least 18 Brazilian private capital multinationals across different sectors (Figure

610

10). In 2009 the bank also opened a holding company in London, BNDES Limited, with the goal of facilitating acquisitions of assets abroad by Brazilian companies22. It is also important to note that in the last few years, with the resumption of industrial policies and accumulation of reserves by the Brazilian State, BNDES has enormously increased its activities. Between April 2009 and March of 2010, the bank was responsible for injecting about US$82 billion into the Brazilian economy. The Brazilian multinationals took advantage of this offer of cheap credit—about 6% p.a. against 28% in the market—to increase their operations, therefore gaining the muscle needed to compete abroad (Figure 11). The internationalization of Petrobras (a mixedcapital firm, though under state control), as well its impact on the Brazilian economy in terms of productive investments, R&D, and mobilization of suppliers, is also increasing. Detail on the company’s activities, however, is outside the scope of this chapter’s objectives. Figure 10. BNDES’ share in Brazilian MNEs

The Recent Internationalization of Brazilian Companies

Figure 11. BNDES’ lendings to Brazilian MNEs

Besides BNDES and Petrobras, other institutions linked to public administration, such as the Bank of Brazil and APEX, are also involved in supporting the multinational activities of Brazilian firms. APEX made supporting the internationalization of mainly small and medium enterprises, as one of its three main goals since 2007. Currently, the institution has six “Business Centers” located in Miami, Beijing, Dubai, Moscow, Warsaw and Havana. At these centers, Brazilian companies, in addition to relying on logistical support, can rent offices that serve as an initial commercial base abroad. According to the website of the institution there are now over 150 companies using this service. APEX also works in conjunction with Brazilian diplomacy to negotiate the entry of firms to markets considered more difficult or “closed.” In 2009, APEX negotiated the first establishment of a multinational pharmaceutical in the Cuban market, the Brazilian EMS Sigma Farma. The Bank of Brazil already has branches and subsidiaries in 14 countries and recently acquired the sixth largest bank in Argentina23. In this capacity it helps to secure and transfer funds for the structuring of financial operations and financing activities of several companies abroad24. Despite these measures, which were fundamental for the international success of some companies, the state incentives for the creation of

global players still has a long way to go, especially compared to what Brazil’s competitor economies such as China and India are doing (Pradhan, 2007; Luo, Xue & Han, 2010).

FINAL CONSIDERATIONS Internationalization can potentially generate benefits for all of Brazilian society—by increasing the competitiveness of firms, by establishing new knowledge streams, and by providing access to new technologies and connecting the Brazilian economy to global chains of greater value. This is a process that can invigorate the entire Brazilian industrial structure and that, if well managed, helps to generate more skilled jobs. In the last decade, there has been an unprecedented expansion of Brazilian multinationals. Some such as Petrobras, Vale, Embraer, JBS and Braskem have become big global players. Others, like Gerdau, WEG, Coteminas, Marcopolo, Votorantim, Odebrecht and Camargo Corrêa are leaders in their respective industries. Dozens of other firms, however, are also seeking to internationalize to reach the highest standards of quality and competitiveness. What we aim to demonstrate in this chapter is that the historical phenomenon of the expansion of Brazilian multinationals was: (1) fast and intense,

611

The Recent Internationalization of Brazilian Companies

companies saw more international expansion in just six years than throughout history, (2) large and diverse, reaching different sectors of different magnitudes. Moreover, we seek to explain how the simultaneous linking of four processes, was essential for the economy, corporate strategies and public policy decisions made at the government level: (1) financial conditions and sustainable domestic economic growth, with greater external credibility, (2) a new attitude on the part of the Brazilian business community, marked by an intense and forceful search for higher standards of quality and competitiveness, (3) the preferential choice among Brazilian companies to expand, establish subsidiaries and compete in more dynamic markets, and (4) interaction with the Brazilian State, which has lately intensified its industrial policies and its stimulation of this process. None of these factors alone could have sustained the recent successes. Entrepreneurship and innovation are fundamental for participation in the global market. However, they cannot go very far if they do not find favorable economic and political conditions. Likewise, it does no good to create a favorable environment without strong players to seize the opportunities. The favorable external conditions have occurred throughout all of Latin America, but our companies have stood out more than our neighbors. Our main references have now become the East Asian and developed countries25. Furthermore, as we tried to demonstrate in this chapter, all these factors have endogenous and exogenous causes that have no guaranteed continuity. Many advances have been made, but to sustain and broaden this process, it is critical that the public and private sector continue modernizing and increasing transparency and options for the Brazilian capital market, enhancing investment while maintaining fiscal discipline and, above all,

612

linking internationalization strategies to innovation strategies, which are ultimately the engines of development. Finally, it is necessary to consider that despite all the advances and benefits, the choice of internationalization is neither an easy nor risk-free. For a company, a poorly planned acquisition may bring serious complications and even jeopardize its future, and for the country, the application of public resources must be subject to criteria that are politically healthy, transparent and modernizing. This means that to effectively meet the urgent demand to raise the level of competitiveness of the Brazilian economy, public support should be intensified in areas, sectors and companies most intensive in knowledge, innovation and technology. Today, Brazil’s economy, its companies, and its state apparatus are stronger than they were in the 1990s, but – and partly as consequence of this- the competitive pressures that led the push for internationalization in that period have also intensified. On the one hand, the Brazilian market today is one of the world’s most attractive for foreign capital (UNCTAD, 2010a, 2010b), and on the other hand, the expansion of multinationals from other developing countries, especially China and India, combined with low growth rates in developed countries, has resulted in an increasing number of new players competing for the same space, and introducing rapid and radical changes in the various sectors. We are witnessing a moment of profound international geopolitical redesign in the business world, with Asia occupying an increasingly central place in the global scenario. At this moment, great opportunities and challenges for Brazil and for Brazilian companies are appearing. What is needed is a strong partnership between the public and private sectors to take advantage of these opportunities at the right time and in the best possible way.

The Recent Internationalization of Brazilian Companies

REFERENCES ABIHPEC. (2009). Associação Brasileira da Indústria de Higiene Pessoal, Perfumaria e Cosméticos: Panorama do Setor. Retrieved November, 2010, from http://www.abihpec.org.br/ dadosdomercado_panorama_setor.php Alem, A. C., & Cavalcanti, C. E. (2005). O BNDES e o apoio à internacionalização das empresas brasileiras: Algumas reflexões. Revista do BNDES, 12(24), 43–76. Aman, E. (2009). Technology, public policy and the emergence of brazilian multinationals. In Brainard, L., & Martinez-Diaz, L. (Eds.), Brazil as an Economic Superpower? Understanding Brazil’s Changing Role in the Global Economy. Washington, DC: Brookings Institution Press. Andrade, M. L. A., & Cunha, L. M. S. (2002). O Setor Siderúrgico. In BNDES, BNDES 50 anos – Histórias Setoriais. Rio de Janeiro, Brazil: BNDES. Arbix, G., & Caseiro, L. (2010). Qual internacionalização? In Jornal Valor Econômico, 05/08/2010, p. A14. Arbix, G., Salerno, M., & De Negri, J. (2004). Internacionalização com foco na inovação tecnológica e seu impacto sobre as exportações das firmas brasileiras. Dados – Revista de Ciencias Sociais, 32, 71-102. Arruda, C., Almeida, A., & Casanova, L. (2009). Politec – Brazilian IT services with global reach. In Casanova, L. (Ed.), From multilatinas to global latinas – The new Latin American multinationals. Compilation Case Studies, Inter-American Development Bank.

Bielschowsky, R., & Stumpo, G. (1996). Internacionalização da industria brasileira: Números e reflexões depois de alguns anos de abertura. In Bauman, R. (Ed.), O Brasil e a economia global. Rio de Janeiro, Brazil: Editora Campus. BNDES. (1995). Caracterização do processo de internacionalização de grupos econômicos privados brasileiros (Série Pesquisas Empresariais, 1). Rio de Janeiro, Brazil: BNDES. Borba Vieira, C., & Zilbovicius, M. (2008). The MNC subsidiaries of Brazilian multinational companies. Paper Presented at Portland International Conference on Management of Engineeiring & Technology (PICMET ’08) (p.1759-1763), Cape Town, South Africa. Boston Consulting Group. (2009). The 2009 BCG 100 new global challengers: How companies from rapidly developing economies are contending for global leadership. Boston, MA: BCG. BOVESPA. (2010). Empresas listadas databasis. Retrieved on August, 2010, from http://www. bovespa.com.br Caseiro, L. C. Z. (2009). Mapeamento e Estratégias da Internacionalização das Empresas Brasileiras. Undergraduate Research Report. São Paulo, Brazil: FAPESP. Chesbrough, H. (2003). Open Innovation. The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press. Child, J., & Rodrigues, S. B. (2005). The internationalization of Chinese firms: A case of theoretical extension? Management and Organization Review, 1, 381–418. doi:10.1111/j.17408784.2005.0020a.x

Aykut, D., & Goldstein, A. (2006). Developing country multinationals: South-South investment comes of age. Working Paper No. 257. Paris, France: OECD Development Center.

613

The Recent Internationalization of Brazilian Companies

Cyrino, A., & Tanure, B. (2009). Trajectories of Brazilian multinationals: Coping with obstacles, challenges and opportunities in the internationalization process. In Ramsey, J., & Almeida, A. (Eds.), The rise of Brazilian multinationals. Rio de Janeiro, Brazil: Elsevier. De Negri, F. (2007). Investimento direto e transferência de tecnologia: Argentina, Brasil e México. Doctoral dissertation. State University of Campinas (UNICAMP). Campinas. De Negri, J. (2010). Oportunidades do Pré-Sal para o Desenvolvimento do Brasil. São Paulo, Brazil: Paper Presented at Innovation and Development Cycle, Observatory for Innovation and Competitiveness, University of São Paulo. Dias, V. V. (1994). Las empresas Brasileñas: Internacionalización y ajuste a la globalización de los mercados. Cepal, (Documento de Trabajo, 33). Dunning, J. H. (1981). International Production and the multinational enterprises. London, UK: Allen & Unwin. Dunning, J. H. (1988). The eclectic paradigm of international production: A restatement and some possible extensions. Journal of International Business Studies, 19, 1–31. doi:10.1057/palgrave. jibs.8490372 Dunning, J. H., Kim, C., & Park, D. (2008). Old wine in new bottles: A comparison of emergingmarket TNCs today and developed-country TNCs 30 years ago. In Sauvant, K. (Ed.), The rise of transnational corporations from emerging markets: Threat or opportunity?Cheltenham, UK: Edward Elgar. FAPESP (2010). Indicadores FAPESP de C&T&I em São Paulo (Edição 2010). São Paulo, Brazil: FAPESP.

614

Fichelstein, D. (2009). Different states, different internationalizations: A comparative analysis of the process of firms’ internationalization in Latin America. Paper presented at the 28th Lasa International Congress, Rio de Janeiro, Brazil. Fleury, A., & Fleury, M. T. (2009). The evolution of global production systems and the emergence of Brazilian MNEs. In Ramsey, J., & Almeida, A. (Eds.), The rise of Brazilian multinationals. Rio de Janeiro, Brazil: Elsevier. Fluriet, M., & Braga, C. (2009). Challenges of a Brazilian ‘Translatina’ CFO. In Ramsey, J., & Almeida, A. (Eds.), The rise of Brazilian multinationals. Rio de Janeiro, Brazil: Elsevier. Frederick, B., & Vasconcellos, E. (2008). Fatores de Influência para a Internacionalização da Função P&D: O caso Natura. In Vasconcellos, E. (Ed.), Internacionalização Competitiva. São Paulo, Brazil: Editora Atlas. Freeman, C., & Soete, L. (1997). The economics of industrial innovation (3rd ed.). Cambridge, MA: MIT Press. Fundação Dom Cabral (in press, 2007). A Decolagem das Multinacionais Brasileiras. Nova Lima, Brazil: Fundação Dom Cabral (FDC) & Columbia Program on International Investment (CPII). Fundação Dom Cabral. (2008). Pesquisa Global Players II: Internacionalização de Empresas da América Latina: Desafios, Obstáculos e Perspectivas das Multinacionais Emergentes. Nova Lima, Brazil: Sumário Executivo. Fundação Dom Cabral. (2009). The 2009 transnationality of Brazilian companies ranking. Nova Lima, Brazil: Sumário Executivo. Ghoshal, S., Barros, B. T., Sull, D., Santos, H., Escobari, M., & Cardoso, R. C. (2002). Natura: A magia por trás da empresa mais admirada do Brasil. Case Study. Brazil, UK: Fundação Dom Cabral and London Business School.

The Recent Internationalization of Brazilian Companies

Goldstein, A. (2002). Embraer: From national champion to global player. CEPAL Review, 77, 97–115. Goldstein, A. (2007). Multinational companies from emerging economies: Composition, conceptualization and direction in the global economy. London, UK: Palgrave Macmillan. doi:10.1057/9780230206335 Griffin, A. (1997). PDMA: Research on new product development practices: Updating trends and benchmarking best practices. [New York: Elsevier Science.]. Journal of Product Innovation Management, 14, 429–458. doi:10.1016/S07376782(97)00061-1 Guimarães, E. A. (1986). The activities of Brazilian firms abroad. In Oman, C. (Ed.), New forms of overseas investment by developing countries: The case of India, Korea and Brazil. Paris, France: OECD. Iglesias, R. M., & Mota Veiga, P. (2002). Promoção de exportações via internacionalização das firmas de capital brasileiro. In BNDES (Ed.), O Desafio das Exportações. Rio de Janeiro, Brazil: BNDES. Jenkinson, N., Penalver, A., & Vause, N. (2008). Financial innovation: What have we learnt? Paper presented at Reserve Bank of Australia 2008’s Conference: Lessons from the Financial Turmoil of 2007 and 2008. Retrieved on August, 2010, from http://www.rba.gov.au /publications/confs/2008/ Johanson, J., & Vahlne, J. E. (1977). The internationalization process of the firm: A model of knowledge development and increasing foreign market commitments. Journal of International Business Studies, 8(1), 23–32. doi:10.1057/palgrave.jibs.8490676 Johanson, J., & Vahlne, J. E. (1990). The mechanism of internationalization. International Marketing Review, 7(4), 11–24. doi:10.1108/02651339010137414

Landim Júnior, P. H., & Menezes Filho, N. A. (2009). Os efeitos do programa bolsa família sobre a economia dos municípios Brasileiros. Research Report. São Paulo, Brazil: Fundação Getúlio Vargas. Lima, F., Alburqueque, M., Pavie, J., & Campos Filho, L. (2008). A Relação entre Localização e Motiviação: Estratégia de Internacionalização de uma Empresa do Setor de Cosméticos. In Contextus Revista Contemporânea de Economia e Gestão, 6(1), 19-28. Lopez, A. (1999). El caso Brasileño. In Chudnovsky, D., Kosacoff, B., & Lopez, A. (Eds.), Las multinacionales Latinoamericanas: Sus estratégias en un mundo globalizado. Buenos Aires, Argentina: Fondo de Cultura Económica. Luo, Y., Xue, Q., & Han, B. (2010). How emerging market governments promote outward FDI: Experience from China. Journal of World Business, 45, 68–79. doi:10.1016/j.jwb.2009.04.003 Marcopolo (2009). Company Annual Report. Retrieved on November, 2010, from www.marcopolo.com.br Mathews, J. (2002). Dragon multinationals. Oxford, UK: Oxford University Press. Mattos, P. T. L. (2008). Institutions for industrial development: The state as a risk taker in Brazil. Paper presented at the Faculty Workshop of FGV School of Law, Rio de Janeiro, Brazil. Miranda, I. (2007). O vôo da Embraer: A competitividade Brasileira na indústria de alta tecnologia. São Paulo, Brazil: Editora Papagaio. Montenegro, R. S. P. (2002). O Setor Petroquímico. In BNDES, BNDES 50 anos – Histórias Setoriais. Rio de Janeiro, Brazil: BNDES. Nakagawa, M. H. (2008). Empresa inovadora de base tecnológica: Um modelo de desenvolvimento para o contexto Brasileiro. PhD dissertation, University of São Paulo Engineering School, Brazil.

615

The Recent Internationalization of Brazilian Companies

Natura (2009). Company Annual Report. Retrieved on November, 2010, from www.natura.net Ocampo, J. (2007). La macroeconomia de la bonanza econômica Lationoamericana. Revista de la CEPAL, 93, 7–29. PDP. (2008). Política de desenvolvimento produtivo. Ministério do Desenvolvimento e Comércio Exterior. (MDIC) Brasília. Retrieved on August, 2010, from www.mdic.gov.br PITCE. (2004). Política de industrial, tecnológica e de comércio exterior. Ministério do Desenvolvimento, Industria e Comércio Exterior (MDIC). Brasília. Retrieved on August, 2010, from www. mdic.gov.br Pradhan, J. P. (2007). Growth of Indian multinationals in the world economy - Implications for development. ISID Working Paper No. 2007/04, New Delhi, India. Retrieved on August, 2010, from http://ssrn.com/abstract=1515650 Rosa, P. (2006). Internacionalização da Marcopolo S. A.: Um estudo de caso. Master’s thesis in Management, Federal University of Rio Grande do Sul, Brazil. Rosa, P., & Rhoden, M. (2007). Internacionalização de uma empresa brasileira: Um estudo de caso. Paper presented at 4º Congresso do Instituto Franco-Brasileiro de Administração de Empresas, Porto Alegre, Brazil. Rui, H., & Yip, G. S. (2008). Foreign acquisitions by Chinese firms: A strategic intent perspective. Journal of World Business, 43(2), 213–227. doi:10.1016/j.jwb.2007.11.006 Sant’Anna, A., Ambrozio, A., & Meirelles, B. (2010). Redistribuição de renda e a recuperação do mercado de trabalho Brasileiro. In BNDES: Visão do Desenvolvimento, 85(2 sep. 2010). BNDES.

616

Schneider, B. R. (2009). Big business in Brazil: Leveraging natural endowments and state support for international expansion. In Brainard, L., & Martinez-Diaz, L. (Eds.), Brazil as an economic superpower? Understanding Brazil’s changing role in the global economy. Washington, DC, USA: Brooking Institution Press. Sennes, R., & Mendes, R. C. (2009). Public policies and Brazilian multinationals. In Ramsey, J., & Almeida, A. (Eds.), The rise of Brazilian multinationals. Rio de Janeiro, Brazil: Elsevier. SOBEET. (2008). Empresas transnacionais Brasileiras: Resultados da pesquisa. Carta da SOBEET (Sociedade Brasileira de Estudos de Empresas Transnacionais e da Globalização Econômica) (No. 46, Ano X), São Paulo, Brazil. SOBEET (in press, 2009). Ranking of Brazilian multinationals finds internationalization steadily increasing. SOBEET (Sociedade Brasileira de Estudos de Empresas Transnacionais e da Globalização Econômica), São Paulo, Brazil. Stal, E. (2007). Inovação à Brasileira. Revista Getúlio Vargas Executivo,6(1), jan/fev 2007. UNCTAD. (2009). Assessing the impact of current financial and economic crisis on global FDI flows, Geneva, UN. UNCTAD. (2010a). World Investment Report, Geneva, UN. UNCTAD. (2010b). World Investment Prospects Survey 2010-2012, Geneva, UN. Valor (2008). Anuário das multinacionais Brasileiras, Complemento do Jornal Valor Econômico, November, 2008. Valor (2009). Anuário das multinacionais Brasileiras, Complemento do Jornal Valor Econômico, October, 2009.

The Recent Internationalization of Brazilian Companies

Valor (2010). Anuário das multinacionais Brasileiras, Complemento do Jornal Valor Econômico, October, 2010. Vasconcellos, E., Nascimento, P., Lucas, P., & Nelson, R. (2008). Estrutura matricial-celular para desenvolver novos produtos de alta complexidade em nível internacional: O caso embraer. In Vasconcellos, E. (Ed.), Internacionalização Competitiva. São Paulo, Brazil: Editora Atlas. Williamson, O. (1975). Markets and Hierarchies. New York, NY: Free Press.

ENDNOTES 1



2



3

4





5



6



The authors are very grateful to CNPq and Fapesp for their support. Data from the Central Bank shows that Brazilian multinationals repatriated a total of US$ 10.1 billion from their subsidiaries abroad in 2009, which could be interpreted as regression in the process of internationalization. However, this repatriation came principally in the form of inter-firm loans. In the general computation for 2009, Brazilian companies acquired more assets abroad than they sold in a positive balance of US$ 4.5 billion - a result much above the annual averages before 2004 (Figure 1), despite the difficulties imposed by the crisis. It is fitting it highlight Petrobrás, which made a capitalization in September 2010 of US$68 billion for investment in the Pre-salt, announced by the government as the largest in the World History. Folha de São Paulo, January 6, 2008: “NY negocia mais ações brasileiras que SP” (NY negotiates more Brazilian shares than SP) Data available on the site: www.ipeadata. gov.br. Last accessed 09/2010. Obviously, currency pegging favored this movement, in lowering the costs of foreign

7



8



9



10



11



12



13



14



15



16



17



18



assets. However, the exchange rate cannot be taken as a determining factor of OFDI in the most recent years; foreign investment is ten times higher than the end of the 1990s, despite the elevated exchange rate. “Embraer acelera escolha de fornecedores para o KC-390” (Embraer speeeds up choice of vennders for KC-390)in Jornal Valor Econômico, 22/09/2010 The Russian factory was paralyzed during the crisis of 2009 and has not re-opened yet. “Executivos franceses comandam negócio da Natura em Paris” (French executives led Natura business in Paris) in Jornal Valor Econômico, 12/04/2005 “Natura recebe R$ 34,7 milhões do BNDES para construção de centro tecnológico” (Natura receives R$ 34.7 million from BNDES to construct technology center) in Jornal Valor Econômico, 30/04/2007. In 2006, Vale acquired Canadian mining company Inco for US$ 19 billion. Although declared Brazilian OFDI in Canada never reached US$ 1 billion, in the same year Brazilian OFDI in Bermuda saw an increase on the order of US$ 14.3 billion. Emphasizing that, as we have seen, Gerdau does not produce commodities only. Available at: www.bacen.gov.br (last access in 09/2010) Marcel Malczewaki, president of Bematech. Statement collected by Luis Caseiro on 19/08/2009, during the Five-Diamond Conference in Nova Lima-MG, Brazil. Interview in newspaper Jornal Valor Econômico on: 09/12/2004 Source: BNDES Transparency: www.bndes. gov.br. Consulted in 09/2010 Source: BNDES Transparency: www.bndes. gov.br. Consulted in 09/2010 In return, the bank required that at least 35% of the amount disbursed for works be spent on exportation of Brazilian products (Sennes & Mendes, 2009). Folha de

617

The Recent Internationalization of Brazilian Companies

19



20



21



22



618

São Paulo: “Brasil faz obras nos vizinhos temendo China” (“Brazil makes works in neighbors fearing China”) , 27/09/2009; e “BNDES bate recorde de desembolsos à AL” (“BNDES beats record disbursements to Latin America), 08/03/2010. Luciano Coutinho interview in Valor Econômico on September 22, 2009. Istoé Dinheiro Magazine, edition 642, January 2010: “Braskem agora é Brastudo” (“Braskem is now Bras-everything”). Available at: http://www.braskem-ri.com. br/braskem/web/arquivos/Brakem_AcordoAcionistas20100401_pt.pdf. Consulted on September 6, 2010. Jornal Estado de São Paulo: “BNDES em Londres terá empresa de participações” (“BNDES in London wil have have holding company”), November 17, 2009.

23



24



25



Source: Jornal Estado de São Paulo 22/04/2010: “BB compra sexto maior banco argentino” (“BB buys sixth-largest Argentine bank”). Source: Jornal Folha de São Paulo: 19/01/2010: “BB aumentará oferta de crédito à empresas brasileiras no exterior” (“BB will increase credit to Brazilian companies abroad”). According to UNCTAD (2010a) stock of Brazilian companies’ OFDI is nearly double the OFDI of Mexican and Argentine companies combined. Additionally, Fernanda De Negri (2007) shows that the amount of resources invested by private Brazilian companies in R&D is nine time greater than Mexican and Argentine companies combined. This performance, while a differential in Latin America, is still not sufficient to be equipped against Asian competition.

619

Chapter 33

R&D Internationalization as Mechanism of Innovation in Global Enterprises: A Brazilian Case Study Simone Vasconcelos Ribeiro Galina University of Sao Paulo, Brazil

ABSTRACT Internationalization of Research and Development (R&D) allows transnational companies (TNC) to access different and important resources overseas, which may lead to the improvement of their technological innovation. The literature in this field has been mostly created from studies of TNCs coming from developed countries. This chapter presents some of the main topics the literature addresses on R&D internationalization, then it will explore and verify how companies in developing countries internationalize their R&D activities. In order to do so, a bibliographic review about strategies of internationalization of TNC operations, as well as motivating factors and management of R&D internationalization have been conducted. The chapter finishes by presenting a case study about international R&D conducted in a Brazilian TNC. The results enabled to evidence that, like developed countries TNCs, developing countries’ companies also seem to perform internationalization of R&D activities with very similar characteristics.

DOI: 10.4018/978-1-61350-165-8.ch033

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

R&D Internationalization as Mechanism of Innovation in Global Enterprises

INTRODUCTION The success of technological innovation in enterprises depends on their competences in Research and Development (R&D), since it is one important source of knowledge and innovation. When R&D is decentralized to worldwide subsidiaries, corporations are able to access knowledge and connect to local markets. Therefore, these corporations improve their competitiveness over firms whose innovations are generated on national basis only (Birkinshaw et al., 1998). The spreading of global R&D has grown rapidly over the 1990’s (UNCTAD, 2005); phenomenon resulting from companies originating from advanced economies such as USA, European countries, and Japan (von Zedwitz, 2005). However, “internationalization of R&D from developing countries is on the rise” (von Zedwitz, 2005, p. 127), because MNCs from emerging economies are investing in R&D abroad (UNCTAD, 2005). Inevitably, “most previous research focused on the scenarios of developed economies, thus meaning the issue still needs to be studied from the perspective of developing countries” (Wu, 2007, p. 298). In this manner, this chapter aims at presenting an exploratory research from the Brazilian perspective. In order to do so, it is introduced a literature review addressing relevant aspects of R&D internationalization analyzed in a Brazilian company. This bibliographic review is conducted from two approaches: strategy and management. The first approach is based mainly on the strategies of companies to locate operations abroad by Foreign Direct Investments (FDI) and on the driving forces towards R&D Internationalization. The role of subsidiaries of transnational corporations is the linking topic for strategy and management, once distribution of units globally is strategically determined and the interaction among these global units has to be well managed in order to benefit the whole corporation.

620

The chapter finishes with a case study of Embraco, a Brazilian manufacturer of electricelectronic products for cooling solutions (hermetic compressors, condensers, evaporators and others). This is an innovative company whose manufacturing activities are located in three continents (America, Europe, Asia), also internationalizing product development function. This example allowed us not only to illustrate topics discussed on the literature section, but also to shed light on R&D internationalization by company from an emerging country.

STRATEGIES FOR ENTERPRISES INTERNATIONALIZATION Internationalization of companies is quickly increasing as shown by United Nations Conference on Trade and Development [UNCTAD] (2009, 2005). In 1990, the number of worldwide Transnational Enterprises was about 37,000 and with at least 170,000 foreign affiliates; in 2004 this number increased to 70,000 with at least 690,000 foreign affiliates; and in 2008 the number of MNCs jumped to 82,000 with 810,000 foreign affiliates half of them being located in developing countries. The internationalization of companies is not a recent scenario. In the 18th century, there are accounts of companies, especially European ones, which held business out of their country of origin. However, several aspects of globalization (financial, commercial, productive, economical, institutional) modified the behavior of companies worldwide, thus intensifying their migration. As it is presented, globalization is relatively recent and was originated amidst the significant growth of the post-World War II international business (Baumann, 1996; UNCTAD, 1994), and has consolidated especially due to the technological development of fundamental areas to base global institutional operation: information technology, communication and logistics.

R&D Internationalization as Mechanism of Innovation in Global Enterprises

From works of authors such as Dunning (1993), Bartlett and Ghoshal (1989), and others, it is possible to trace a timeline overview on the global actuation of companies since their first efforts of being overseas to their current globalization strategies. Companies which operate internationally present some important behavior changes. In the 1960’s, the major worldwide activity was related to export operations of output or components to the simplified assembly of products to national/ regional markets. From de 1970’s on, there was the building of manufacturing plants in strategic countries in order to improve the performance of local unities and products. The fierce competition of the 1980’s put pressure on companies to a more emphatic internationalization of production, although not so adjusted as the one witnessed in the 1990’s, when productive activities were fully world-integrated, that is, companies “begin to be described as coordinators of an activity network inter-related to add value” (Dunning, 1994, p. 28). Such history overview also influenced the classification of current global companies. There are a myriad of classifications for worldwide companies, that is, those which hold activities out of their home countries. One of the most renowned is Bartlett & Ghoshal’s (1989), which classify globally operating corporations as follow (Table 1):

•

•

•

•

Multinational Corporations (MNC) or Multidomestic: They work using the whole production chain in an overseas country, with independent unities, and mark strong local presence by means of sensitivity and receptivity regarding domestic differences. Global: They are much more centralized in operational and strategic decisions than the MNCs. They have competitive advantage in terms of costs by means of operations centralized in global scale, dealing with the world market as a whole. International: They explore knowledge and resources from the headquarters by world diffusion and adaptation. The headquarters exert considerable influence and control, but less than in a global company. The domestic units are allowed to adapt products and ideas from the headquarters, although with less autonomy than the MNCs. Transnational (TNC): They integrate processes in global scale, making them improved, rationalizing resources, eliminating redundancies, and operating world spread products. They seek for efficiency in order to achieve global competitiveness, understand local receptiveness as a tool to obtain flexibility in international opera-

Table 1. Organizational characteristics of multinational, global, international, and transnational companies (Adapted from Bartlett & Ghoshal, 1989) Global

International

Transnational

Assets and resources management

Decentralized and Nationally self-sufficient

Multinational

Centralized and globally sited

Centralized basic competencies resources, other multisite ones

Dispersed, interdependent and specialized

Role of the subsidiaries

Perceive and explore local opportunities

Implement headquarters strategies

Adapt and leverage headquarters competencies

Differentiated contributions of domestic units to integrated world operations

Development and spread of knowledge

Knowledge developed and kept in each unit

Knowledge developed and kept in the center

Knowledge developed in the center and transferred to overseas units

Knowledge jointly developed and shared all over the world

621

R&D Internationalization as Mechanism of Innovation in Global Enterprises

tions, and see innovation as result of a process which comprises several members of the company. The differences between these classes can be subtle, and a company may behave in similar manners in more than one of them. In order to make the comparison easier, Table 1 shows a sum up of the organizational characteristics of Multinational, Global, International, and Transactional corporations. “Development and knowledge spread” may be the most clearly distinct. The rest of them present less perceptive difference, for instance, “the role of the subsidiary overseas” of an MNC—to explore local opportunities—is also common to TNC and can also be fundamental to the survival of global and international companies. Another approach to the International operation is of a Metanational company developed by Doz, Santos and Williamson (2001). The Metanational model focuses on companies coming from countries not among the traditional capital holders or leader industries, hence they can appear to be inappropriate environments to allow local companies to take part in global competition. However, according to the same authors, once the know-how the companies of these countries need to compete in a global level is not available in their home countries, they are led to develop competencies in market and technology knowledge in an international perspective. This is a learning opportunity to place them in an advantageous position. Besides organizational characteristics, it is important to undestand the strategies which lead companies to locate units globally. There are manners for a company to enter the international market in terms of business involvement, implying different levels of risk and management complexity. They usually come by exports, contracts (association between company and institution in a foreign country with no assets investments) or by direct investments abroad (when a company installs subsidiaries in a different country than

622

its original one). Business risks and complexity increase as there are more involvement and, consequently, dependence of the company on its foreign businesses. It results according to the means of entrance/operation listed as follows: export, contract, and investment. There are several models/theories of company internationalization, that is, the strategies it adopts when enter international markets (related to entrance by investment), including Bartlett and Ghoshal (1989) presented above. Economic theories are basically related to currents which study firm internalization and the factors which lead corporations to internalize their operations in another country. One of the most notorious theories is Dunning’s eclectic paradigm (Dunning, 1988, 1993, 1994), which “avows that the greater the net benefits of internalizing cross-border intermediate product markets, the more likely a firm will prefer to engage in foreign production itself, rather than license the right to do so (e.g. by a technical service or franchise agreement) to a foreign firm” (Dunning, 2000, p.164). The behavioral theories, whose most known approach is the Uppsala Model (Johanson & Vahlne, 1977), relate the incremental internationalization of a company to the level of its learning abroad. That means that a corporation would follow an established order due to the higher or lower level of know-how required: exports, sales unit, operations subsidiary, and Research and Development (R&D) activities engagement. Nevertheless, despite the relevance of this model and the countless works based on it, this sequence of operation abroad has been questioned by new theories and empirical evidence of corporations’ procedures. It is undebatable that many companies do not follow the sequence determined by the level of knowledge resulting from their work abroad, that is, they do not follow Uppsala’s model presupposition. The network theory itself (Forsgren & Olsson, 1992), also considered a behavioral theory, is an approach showing that the

R&D Internationalization as Mechanism of Innovation in Global Enterprises

need for insertion in a global value-added chain strongly interferes in the manner a company enters and operates on international markets, as well as in the role of each affiliated/subsidiary abroad. Concluding, companies currently operate globally aiming to take competitive advantages in each region/country they locate, and from that on, their management process is substantially changed. An important change refers to technological innovation, approached by means of two trends: products and processes commercialized, developed and manufactured in global scale; and decentralization of their R&D. It modifies not only the management of R&D function itself, but also of other functions related to it such as operations, marketing, and sales. One of the issues emerging from studies on internationalization management is the coordination of subsidiaries distribution and the role of each foreign unit (Bartlett & Ghoshal, 1992; Ferdows, 1997; UNCTAD, 1999). When focusing on R&D internationalization, this subject is highly relevant and it is presented here.

INTERNATIONALIZATION OF R&D ACTIVITIES The roles of TNCs’ subsidiaries out of their headquarters’ origin country are not restrained to the assistance of local market, but organized in integrated network so that they have the necessary conditions to explore capacities or know-how in each country not only in production terms, but also in technology development (Cantwell & Santangelo, 1999). Transnational companies locate their activities in sites where there is competitive advantage, and “besides related to production, these activities are related to distribution, marketing, and R&D” (Reddy, 2000, p. 10). TNCs are the main agents of productive globalization and consequently internationalization of R&D (Cantwell, 1994; Gerybadze & Reger, 1999).

Since the 1990’s, it is observed a strong growth of R&D internationalization within global companies. Several studies show that TNC investments in R&D are increasingly oriented toward subsidiaries located outside the home country (UNCTAD, 2005; Doz, et al., 2006). The exposure of a global company to a variety of environmental stimuli is a great advantage over a national company. Thus, there are several arguments pro-internationalization of R&D, not only to support local manufacturing activities, but also to create interfaces with local innovation systems (Ohmae, 1990). There are different nature of studies related to the internationalization of R&D. Some of them discusses the subject under the point of view of TNC and their strategies to globalize R&D activities, taking advantage from local situations in favor of global development (Ronstadt, 1977; Terpstra, 1977; Hakanson, 1990; Bartlett & Ghoshal, 1989). Influencing these strategies are factors that orient the investment in R&D towards specific countries/ regions, and some other works under this approach were carried out (Cantwell, 1992; Reddy, 1997, 2000; Niosi, 1999; Gerybadze & Reger, 1999; UNCTAD, 2005; Cantwell & Santangelo, 1999; Kumar, 2001; Florida, 1997; Patel & Vega, 1999; Pearce, 1999). Besides these, and yet considering the internationalization of R&D strategies, there are authors who work on market analysis, establishing products characteristics which can be standardized to worldwide markets or need to follow local market contingencies in the world perspective, which may or may not influence the R&D centralization or decentralization (Hult, Keillor, & Hightower, 2000). Some works in this area refer to manners to manage R&D world centers and technologic development activities under different aspects (Chiesa, 2000; Gassmann & von Zedtwitz, 1999), especially on data/information group exchange management (for instance, type, costs, code and infrastructure for the global communication

623

R&D Internationalization as Mechanism of Innovation in Global Enterprises

process) and on the organization of work teams around the world (for instance, organizational structures, leadership, and team formalization). The literature in internalization of R&D also shows that this is not recent practice by companies. Vernon (1966) shows that in the 1960’s the enterprises exploited resources overseas, including to obtain technological know-how. In 1971, the amount that North American enterprises invested in R&D out of their country was 10% of the total invested in R&D (Terpstra, 1977). Reddy (1997) mentioned that the US Tariff Commission had declared in 1973 that North American companies carried R&D in foreign countries yet in the 1960’s. The main industries involved were in the areas of mechanics, electrics, and engineering (including automotive engineering). However, more evidence of this practice emerges only after some works were carried out in the 1970’s, with the famous classification of Ronstadt (1977). It distinguishes the different types of R&D world units, thus validating the practices of internationalization of TNCs development activities. Another work produced in the 1970’s (Behrman & Fischer, 1980) presents evidence of R&D unit allocation in developing countries such as Brazil and India, especially due to some of their characteristics: profitable subsidiaries, growing market, and structure suitable to Science and Technology. The major industries to internationalize R&D during this period were from chemical and food areas. The distributed execution of R&D up to middle 1970’s was difficult, particularly due to some problems to supervise and control international activities. Such issue was minimized when new information technologies and communication were introduced. Although internalization of R&D has begun in the 1970’s, it became a “phenomenon” only by the end of the 1980’s (Cantwell, 1995). Back then, foreign subsidiaries were involved not only in developing processes and products to both local and global markets, but also in basic research (Reddy, 1997). Those were trends introduced in the 1980’s

624

that remains today, especially for companies from developed countries and their growing need for highly qualified manpower. Internationalization led the enterprises to search for new knowledge and technologies abroad. In the 1980’s, the main industries involved in globalization of R&D activities were from microelectronics, pharmacy, and civil aeronautics areas. Adapted from Reddy (1997), Table 2 presents the background process of R&D globalization into enterprises. For each decade relevant to the internationalization of technological development in TNCs, the author shows driving factors, that is, those which leveraged and favored this internationalization, the sort of R&D carried out abroad, and the characteristics of R&D units. As observed, internalization of R&D is a true fact. However, “the country of origin of TNC is usually the most important place to the technological development of the corporation” (Cantwell, 1995, p. 172), although there is solid evidence of the strong growth of R&D expenses in foreign subsidiaries. According to UNCTAD (2005), from 1993 to 2002, these costs rose from 10% to 16% of the whole investment in R&D. The same study shows these expenses were geographically concentrated. In 2002, for instance, the ten major economy investors in R&D represented 86% of the world sum, whereas eight of them are developed countries (China and South Korea, exceptionally). Also according to UNCTAD (2005), the sort of R&D performed overseas may vary depending on the region, whereas Asia prevails with the most innovator R&D (particularly China, India, and Korea). Some new members of the European Community have attracted activities for technology innovation; Latin America and the Caribbean have little direct investment in intensive activities and focus on adaptation of technologies or products to the local market; some African countries (especially Morocco and South Africa) attract limited investments in R&D.

R&D Internationalization as Mechanism of Innovation in Global Enterprises

Table 2. Background process of R&D globalization (adapted from Reddy [1997]) Driving forces

Type of R&D

Forms de R&D

1960s

entry into the local market abroad

adaptation; technology transfer unit (TTU)

own-R&D with manufacturing affiliate

1970s

build-up market share in the local market abroad; national government policies

product development for the local market; indigenous technology unit (ITU)

acquisition or green-field investments in own-R&D and production facilities.

1980s

need for worldwide learning and new technology inputs

products and processes development for global markets & basic research; global and corporate technology units (GTU & CTU)

own R&D affiliates; joint venture R&D; inter-firm cooperation; sponsor university research; subcontract R&D

1990s

access to scarce R&D personnel and increasing R&D costs

products and processes development for global and regional markets & basic research (GTU & RTU & CTU)

own R&D affiliates; joint venture R&D; interfirm cooperation; sponsor university research; subcontract R&D

Great part of the studies on R&D localization by foreign enterprises in Brazil (Dias & Salerno, 2009; Galina, Sbragia, & Plonski, 2005; Gomes, 2006) shows that R&D activities done in the country by local subsidiaries are focused on adaptation of products and processes. However, some TNC have considered this country as a guidance of more relevant investment in R&D (Galina, Camillo, & Consoni, 2010). Considering early discussion, with the worldwide distribution of R&D, companies look for greater competitive advantage. It is known a myriad of arguments favorable to the internationalization of product development not only to support local production, but also to create interfaces of local innovation systems (Ohmae, 1990). In the next section the main reasons that underlie companies’ decision to internationalize R&D are debated.

DRIVING FORCES TO R&D INTERNATIONALIZATION There are many reasons for R&D resources to be directed to countries other than the company headquarters’. Terpstra (1977) summarizes the most frequently found among TNCs: in response to the pressure applied by host countries; in order to improve international relationships; intending

to access foreign skill and resources; to reduce development costs with cheap labor; to obtain advantage on local ideas and products; trying to accelerate development by means of parallel efforts of laboratories working simultaneously; in order to sustain development activities performed by companies acquired abroad; to obtain advantage from domestic laws of government incentive. In general, the pertinent literature presents two major subjects to list the main reasons for R&D internationalization (Chiesa, 1995; Florida, 1997): marketing-related factors (necessity to access markets, responding to local needs and strengthening bonds to clients/consumers), and technology-related factors (qualified labor, outstanding technology). Chiesa (1995) states that factors related to technology and demand are the two main reasons to promote R&D internationalization. There is also factors regarding finance aspects, such as labor cost reduction and local incentive policies; and some other more subjective factors such as the connection between headquarters and subsidiaries in what concerns personal relationship of their respective executives. The market-related factor is motivated to the adaptation of products to foreign markets and to production/operation technical support. When locating their units abroad, the TNCs look for a better service to their client, with more appropriated and faster adaptations of products, essentially.

625

R&D Internationalization as Mechanism of Innovation in Global Enterprises

When establishing development activities in sites next to the clients, the enterprises are better structured in order to understand and to provide local needs more efficiently, especially because in general TNCs have gigantic and extremely red tape organizational structures, thus complicating the decision-making process. The marketing factor is considered less relevant or more superficial, as quoted by Inzelt (2000): “skin-deep collaboration.” The second factor, related to technology, is aimed at guaranteeing access to Science and Technology (S&T) and qualified human capital, and creating bonds with local science communities. Once more intrinsic to the development process, this factor is considered more relevant, since it establishes a deeper relation of dependence between the company and the regions where the subsidiaries are. It is what Inzelt (2000) calls “soul-deep collaboration.” Yet regarding technological factors, Cantwell (1992) mentions two approaches as main reasons to the internationalization of R&D: to obtain advantage from distinct innovations characteristics in different domestic systems, thus gaining access to further technologies, and to have contact with new threads for technological innovation. Despite considered more or less relevant, technological and marketing factors are paramount to attract local investors, thus enabling the transformation of less advanced countries in more advanced ones. It is also common to see companies which consider both factors when guiding their investments in R&D abroad. The internationalization of R&D is often a result of actions non-related to company strategies such as govern requirements, acquisition of foreign units already owning R&D departments, etc. (Granstrand et al., 1992). For Terpstra (1977), governments of countries where MNCs have

626

branches try to maximize the local technological development by means of receiving incentive or pressure. They are more successful with foreign enterprises which buy domestic companies and ensure continuity to R&D processes than pressuring these foreign companies to start new local R&D activities. As for financial factors, despite less relevant, companies have shown they take them into account when spreading their development activities worldwide, especially when they choose developing countries. As mentioned by Reddy (1997), development costs in research centers based in developing countries (India, Brazil) are proportionally lower than in traditional centers. In what concerns the factor of relation between headquarters and subsidiary, the most subjective of all, it is important to consider that if the company staff involved in strategic decision-making handles good relationship with the subsidiary’s executives, chances are for the local unity significantly involve in corporate technological development. For Birkinshaw and Hood (1998), a high quality relationship between headquarters and subsidiaries has a positive impact on “enterprising” subsidiaries, that is, those working for the development of local competencies. Summarizing, factors (or driving forces) considered by companies to increase internationalization of R&D are many. They may be related to some companies’ internal aspects (such as internal competence, relationship among units, historical trajectory/path, etc.), to environmental aspects (such as market characteristics, level of wages or existence of competencies on local universities or research centers) or to public policies (direct incentives to internationalization). These factors are motivated mainly by marketing and/ or technological reasons.

R&D Internationalization as Mechanism of Innovation in Global Enterprises

MANAGEMENT OF INTERNATIONAL R&D Roles of Subsidiaries As previously stated in this chapter, transnational organizations structure themselves in order to obtain most units abroad. To do so, subsidiaries are given strategic roles and responsibilities and are distributed all over the world so the resources of each country can be reasonably exploited. There are several classifications to the subsidiaries roles of global enterprises (Bartlet; Ghoshal, 1989; Birkinshaw, 1996; Ferdows, 1997; Gupta & Govindarajan, 1991, 1994; Pearce & Papanastassiou, 1996; Roth & Morrison, 1992; UNCTAD, 1999). The typology presented by Ferdows (1997) is based on a cross between local competencies (high and low) and three clusters of strategic reasons: low production costs, market proximity, and access to skills and knowledge. This combination lead to six subsidiary roles (Figure 1): Offshore (not innovative and abiding by corporate decisions); Source (autonomous with regard to certain manufacturing activities); Server (produces for the local market); Contributor (has its own process engineering and

products for the local market); Outpost (monitors the local environment for the global corporation); and Lead (creates new processes, products and technologies for the entire organization). In every one of the subsidiary role classifications (models) mentioned, there are company units in charge of generating technology for the subsidiary itself or even for the entire corporation. Ronstadt (1977) shows different types of units which perform overseas R&D (out of the origin country of the company) by TNCs: •

•

•

•

Technology Transfer Units (TTUs): Enable technology to be transferred from headquarters to subsidiary and provide local technical services. Indigenous Technology Units (ITUs): Develop new products to local market using local technology. Global Technology Units (GTUs): Develop new products and processes to major world markets. Corporate Technology Units (CTUs): Generate basic long-lasting exploratory technology to be used by the headquarters.

Figure 1. Strategic roles of subsidiaries (Ferdows, 1997)

627

R&D Internationalization as Mechanism of Innovation in Global Enterprises

Adding to this typology developed by Ronstadt, Reddy (1997) offers, and quite appropriately so, another class of global R&D units as “certain regional clusters are also becoming stronger despite market integration around standards and technologies” (Reddy, 1997, p. 1822): •

Regional Technology Units (RTUs): Develop products and processes for regional markets.

Ronstadt’s classification is a way to understand that subsidiaries play important roles in innovation. Terpstra (1977) suggests that the more a company is engaged in international business, the more significant its businesses are, as well as its R&D activities. Related to the debate on classifications relating transfer of technology/knowledge to corporation strategies, there is a seminal work by Gupta and Govidarajan (1991, 1994), focused on the subsidiary roles in the company structure. It identifies four generic roles for TNCs’ abroad units: •

•

•

•

628

Global Innovator: The subsidiary acts as a leader in the development and knowledge to other unities of a product group particular technology. Integrated Player: The subsidiary is as a source of technology creation as a key user of a technology developed by other unity. Implementer: There is little engagement of the subsidiary to build know-how, and it is strongly dependent of technological transfer from other TNC units. Local Innovator: The subsidiary is responsible for developing technology to key functional areas, although almost totally of local use, there is, the knowledge developed by itself is too idiosyncratic to be used in other countries.

This typology was tested by the authors in North American, European and Japanese companies, and the model was then validated. However, they found internal differences in organizations in what concerns the role of know-how and its flow to the subsidiary. Thus, it shows that the role of technology to TNCs unities does not vary only according to their nationality and industry sector, but also depends on the characteristics of the each enterprise. It indicates that this situation is highly complex and that attempting to create a systematic strategic and practical pattern or model in the transfer and allocation of technology may be very troublesome (Howells, 2000). In short, independently from the typology of subsidiaries roles, a TNC is aimed at coordinating a global network in order to take the best advantage from spatial assets, and once they are specialized and interdependent, the subsidiaries make differentiated contributions to integrated world operations (Blarttlet & Ghoshal, 1989). This logic of the role of operational subsidiaries comprises the development and propagation of knowledge in the world corporation, which is jointly developed by different domestic units and shared all over the world. Since it is important to analyze, that is the subject to be discussed in the next section.

Structure for International R&D In basic, Hakason (1990) suggests that the structure TNCs use to perform world R&D has three basic stages: centralized, decentralized, and integrated. Gammelgaard (1999) presents a model to the work division of international R&D which initially establishes the difference between centralization and decentralization, besides the specification in case the company chooses a decentralized development. In this case, it is necessary to establish whether the company will operate in topto-bottom strategy, when the tasks are assigned by the headquarters, or in bottom-to-top strategy,

R&D Internationalization as Mechanism of Innovation in Global Enterprises

when there is a greater autonomy of the branches, developing products on the subsidiary (bottom) and sending to the headquarters (top), then to the whole organization. In a little wider view, Bartlett & Ghoshal (1990) present four different structures to the management of innovation processes: •

•

•

•

a number of international subsidiaries of world enterprises and the interaction among them, there is a classification with four R&D structures: •

Central-for-Global Innovations: The development of new products and processes is promoted in the home country and transferred to global markets. Local-for-Local Innovation: Independent development of new products and processes occurred in each R&D unit, with worldwide distribution and oriented to the subsidiary local market. Locally-Leveraged Innovations: The development of new products and processes is made in the subsidiaries and distributed to the company as a whole. Globally-Linked Innovations: The development is promoted in collaboration with R&D units located in different countries for operating profits of global markets.

Each of these management modalities presents advantages and disadvantages, and is applied according to the company strategies and its business characteristics. They comprise a number of technological development possibilities in a transnational company, whether centralized or not. However, in order to decentralize R&D, companies make use of different strategies when distributing their activities and control worldwide. Ronstadt’s typology (1977) presented in the previous section does not include intraorganizational relationships, although widely used as pattern of TNCs international R&D. The literature shows many models for decentralized development management, even with central coordination. In the model developed by Chiesa and Manzini (1996), an analysis of

•

Isolated Specialization Structure: A foreign laboratory is totally responsible for the development of certain global technology/product/process. This research center is unique in the TNC on the referred area. It is considered center of excellence, and there is no interaction between units on the course of the project development. The transfer of knowledge is limited mostly to the phase of introduction of products to the subsidiary market, going from the center of excellence to the TNC units. It can be performed in different ways, with temporary transfer from the central unit to the subsidiary (usually when the product is produced in the local unit) or the employees are trained in the center of competency to provide technical support to the introduction of the product in a local market (usually when the product is produces in a local different from the subsidiary). This structure is also known as Center of Excellence Structure (Chiesa, 2000). Supported Specialization Structure: There is a global center responsible for R&D work, as well as in the isolated specialization structure. However, there are many units in different countries which provide the global center with information useful to the innovation and development of new products, originated from requirements technology and marketing) of the local environment. Such structure combines the specialization/concentration benefits (efficiency, scale economy, project coordination low cost) with the possibility of monitoring local opportunities of innovation. “In this structure, the only phase to not imply in transfer of techno-

629

R&D Internationalization as Mechanism of Innovation in Global Enterprises

•

•

630

logical knowledge is development itself (Chiesa, 2000). The phase of creation/ conception takes place in the central unit, but the information originates from other supervision units. The strategies to transfer knowledge are similar to those used in the isolated structure. Specialized Contributors Structure: A division of tasks is established among units, thus maintaining a centralized coordination and each subsidiary is attributed individual activities within the program. The know-how developed in each unit is transferred to the central. In this structure, the interaction between globally spread units is much more complex than the supported specialization structure. In the conception phase, the data flow is ongoing from the units to the center and among the subsidiaries themselves. The phases to define the project and the technical development are performed by international teams and involve different units. That is, in this type of structure, there are much more interaction in the phases of definition and technological, product and process development. Integrated Laboratories Structures: Different laboratories spread across many countries and operating in the same production segments or technological areas. The TNCs holding such structure tend to give autonomy to foreign laboratories, but their initiatives and activities are centrally monitored in order to avoid duplications, coordinate spread efforts, and engage different markets. Just as in the specialized contributors structure, the transfer of knowledge is made with close interaction among the many unities in the phases of planning, formulation and technological development. A second name given to such structure is Network Structure (Chiesa, 2000).

These different structures are more frequently used for the development of products. For the research activities, the network structure is more usual since each unit makes its own program under some coordination, but the effort duplication is, in a certain way, allowed (Chiesa, 2000). The building of similar projects by many units at the same time is a way to accelerate the learning process, since each subsidiary work on different manners and under different perspectives, which can lead to internal competition among independent units, thus increasing their creativity and benefiting the company as a whole (Chiesa, 2000). A classification similar to Chiesa’s was developed by Gassmann and von Zedtwitz (1999), who present five models of structural and behavioral orientation in international R&D organizations: •

•

•

Ethnocentric Centralized R&D: Every R&D activity is concentrated in the headquarters’ country of origin, considered technologically superior to their subsidiaries. Their purpose is “to protect” against their competitors technologies regarded as fundamental to the company. Geocentric Centralized R&D: It centralizes know-how acquired over the world and technologies available in overseas countries by means of sending R&D employees abroad in order to intensify relationships and collaborate to the local production, suppliers and key clients. In this manner, it is adopted in companies more dependent on foreign markets and local competencies than those which make use of the ethnocentric model. Polycentric Decentralized R&D: It is characterized by local development laboratories with no supervision of the corporation center, whose relationship is restricted to the report of activities from the local labs to the headquarters. The subsidiary R&D directors report directly to the manager of their own unit.

R&D Internationalization as Mechanism of Innovation in Global Enterprises

•

•

R&D Hub Model: The R&D central unit, usually located in the headquarters, is the corporation technological leader since it is the major advanced R&D laboratory. All activities are decentralized, though tightly controlled by the head office. These foreign labs are usually involved in local monitoring and focus their activities on predetermined technological segments. Integrated R&D Network: In this structure, each integrated network unit specializes in a product, component, or technological field, thus becoming center of competency in its segment and has world product mandate for both product development and introduction to other markets. Differently from the Hub structure, the R&D foreign units play strategic roles, that is, a center of competency should not only supervise potential changes, but also engage in defining strategies and prospecting businesses, reaching the TNC as a whole. Once connections are established among the participant units, this structure requires a complex coordination of the R&D international activities.

These structures are not definitively established in a company, that is, the international organization can be – and usually is – continuously modified in order to promote the evolution of R&D processes. Gassmann & von Zedtwitz (1999) point five currents to this change, all based in two criteria: allocation of R&D activities (centralized or decentralized), and type of integration among teams (competition or cooperation). The first tendency pointed by the authors emerges from the necessity to align the R&D process with the international market requirements (increasing cooperation in favor of the development of products and processes), so the R&D center starts to gather outer information and feedback. It characterizes the modification of an

ethnocentric to a geocentric structure. Another current presented by Gassmann and von Zedtwitz (1999) intends to create a R&D decentralization, then characterizing the transition from a centralized structure (ethnocentric or geocentric) to a central coordination model (Hub). As the R&D local units across the world increase their technological competencies, a third current of structural change is identified; an evolution based on the autonomy the R&D control center grants to the local units and, due to it, hey become more flexible and free to carry technological development. This change characterizes the transition from a central coordination structure (Hub) to an Integrated Network. A fourth tendency identified by Gassmann and von Zedtwitz is related to enterprises whose international R&D growing and strengthening background based on labs is relatively autonomous. When these companies identify the benefits of integration and interconnection of their international R&D activities, centers of competencies are created, and mechanisms to coordinate them are introduced. This tendency characterizes the transition from a polycentric structure to an integrated network. However, in order to reduce costs, the companies which adopted the Integrated Network structure are forced to focus their efforts on a smaller number of centers of competencies, characterizing a R&D recentralization. This consolidation is aimed at exploring scale effects and improving the coordination of R&D global activities, thus reducing task duplication and intensifying the transfer of technology among laboratories (Gassmann & von Zedtwitz, 1999, p. 246). The polycentric decentralized model must be highlighted: “is the ‘dying model’ among the five forms of international R&D organization” (Gassmann & von Zedtwitz, 1999, p. 241). In this structure, despite the benefits from strong orientation to local markets, the lack of central coordination increases costs and efforts to promote

631

R&D Internationalization as Mechanism of Innovation in Global Enterprises

R&D. According to the authors and creators of such, the polycentric configuration leads to the central control (Hub) or the integrated network. Under Gassmann and von Zedtwitz’s consideration, the similarities between these structures and those developed by Chiesa are stronger. Furthermore, both classifications complete each other. There are common points, in special those regarding clear divisions between the two main characteristics: development centralization (with or without the participation of development local units), and the integration in favor of the development (with a stronger or lighter connection with the development local units). In short, the modes of managing global products development may differ from sector to sector, and company to company. There are a myriad of relevant aspects to consider in the internationalized R&D management process, but two of them are more intensely debated. One are related to the division of work among teams distributed throughout global subsidiaries, and the other refers to the organizational structure required to coordinate these R&D functional unities, both studied in the present section.

R&D INTERNATIONALIZATION OF A BRAZILIAN COMPANY The present section presents an example of international R&D carried out by Embraco, a former Brazilian company now part of the North-American Whirlpool Group. Although it is formally a company from USA, its R&D (like most of its operations) is still managed from Brazil and by Brazilian executives, which make it an interesting case of a ‘Brazilian company’ with North-American capital control. Embraco is a manufacturer of electric-electronic products for cooling solutions, including hermetic compressors, condensers, and evaporators. It employs around ten thousand people, was founded in 1971 and its first FDI was in 1994.

632

The company exports for more than 80 countries and, besides Brazil, it has factories in Italy, China, and Slovakia. In addition to globally locate its manufacturing activities, it also internationalizes product development intentionally (Galina & Moura, 2010).

Methodological Aspects In order to analyze the R&D function within the company, as well as its internationalization, we looked into the following: the structure of R&D functions, how to implement it, how product development activities are conducted by the company in Brazil and, finally, how they are carried out abroad. The case study was made by extensive in-depth face-to-face interviews with the R&D director, the manager of product development and the manager of internationalization. These interviews were made with a semi-structured questionnaire which addresses specific issues contemplated in this study: the driving forces, roles of subsidiaries, and structure for R&D offshore. Data used in this study are not only primary, but also secondary, and they were collected between the years of 2006 and 2007. The sources of secondary data included: news, scientific articles, reports on internationalization process of Embraco compared to other Brazilian multinationals, and documents gathered directly in the organization (reports, contracts, plans, metrics).

Results and Discussion The main drive forces that led Embraco to internationalize R&D were as follows: •

Adaptation of products to local markets: Embraco has, with regard to technologies already dominated by the company, granted autonomy to its subsidiaries to adapt and customize products and manufacturing processes according to the characteristics

R&D Internationalization as Mechanism of Innovation in Global Enterprises

•

•

of local plants and markets. The company has opted for decentralization because it needs to operate closer to the customer and to respond more quickly, and this means identifying customer needs, translating them into projects and implementing these in a shorter time period than it would be possible if development were centralized. Development of partnerships with local suppliers: The internationalization of manufacturing activities at Embraco has enabled its offshore plants to develop a local supplier interface that can not only foster cooperation to improve technology but also improve local product development. Thus, agility is not restricted to the company’s responsiveness to its customers; in fact, it permeates the entire supply chain. Technology monitoring and accessing: Embraco is offshoring R&D activities to China not only because of the rapid growth observed in that market but also because of the large number of engineering graduates and post-graduates entering the job market every year, which is transforming some regions in that country into centers of excellence in technology. The same company also benefits from its local partners to monitor technology development. The company studied indicated that the development of proprietary technology was also a decisive factor behind internationalization. It claimed to have signed contracts with competitors to acquire technology for the ultimate purpose of developing products of higher quality. In other words, the company attempted, from the very beginning, to monitor the overseas technology environment. Many of the technological competencies were internalized from abroad, which then allowed the company to develop its own.

In relation to the role of foreign subsidiaries, two of the three plants owned by Embraco outside Brazil have considered proximity to market as strategic reason for being located in the site, but one of them (Italian unit) creates new processes, products and technologies for the entire organization (in specific niches), being considered ‘Lead’ of the global corporation according to Ferdows (1997). According to Ronstadt’s classification, the Italian subsidiary may be classified as Global Technology Unit, and the other two are Regional Technology Units. It is worth to consider, however, that Embraco’s Server unit in China is going through a process of this kind as the company is considering the possibility of transferring to it certain R&D activities that were handled exclusively in the home country (Brazil). Thus, the plant’s strategic focus is shifting from market proximity to access to skills and knowledge, what may lead it to be reclassified as a ‘Lead’ unit (Ferdows, 1997) and a ‘Corporate Technology Unit’ (Ronstadt, 1977). Still with regard to Embraco, the company’s plant in Italy is undergoing a reverse process. At the time of its acquisition, the plant had a product line that the parent company lacked, which offered an opportunity for the latter to internalize new competencies. Despite the disadvantages, Embraco opted for a “divestment” strategy, causing the plant to shift its focus to high value-add products and thereby to become operationally sustainable. However, if the situation becomes unsustainable, a plant previously classified as a Lead unit can be reclassified as an Outpost. Thus, summarizing, the Italian subsidiary is a global technology unit while the one in Slovakia can be regarded as a regional technology unit. Finally, the plant in China is a regional technology unit that may become a global and corporate technology unit as the company plans to expand the R&D function there. Concerning to the coordination of R&D in Embraco, we may consider that the company shows two R&D configurations: one for the development

633

R&D Internationalization as Mechanism of Innovation in Global Enterprises

of company-dominated technology, and another for non-dominated technology. In the first case, the offshore units are free to engage in product development activities with very little coordination from the parent company because the purpose is to streamline products and processes for local markets. This configuration could therefore be described as polycentric decentralized. However, with regard to technologies not yet dominated by Embraco, R&D is almost entirely conducted by the headquarters in Brazil. The purpose here is to allow the organization to internalize the knowledge first. Once the technology has been mastered, it is then internationalized to the manufacturing units. Thus, this configuration was regarded as ethnocentric centralized. The division of the company in dominatedtechnology and not-dominated-technology proved to be an interesting approach to the management of technological innovations. That management maintains centralized R&D activities for notdominated-technologies at the same time that it establishes mechanisms for transferring this technology, when dominated, to foreign subsidiaries, disseminating knowledge throughout the organization and enabling that further developments of this technology are carried out also abroad.

CONCLUSION This chapter presented a theoretical literature review which demonstrated that transnational companies have accessed important resources abroad by internationalizing R&D, and also their R&D investments into foreign subsidiaries have presented strong growth. Most of literature has been based on studies with TNCs from developed countries. Studies on global R&D are neglected for developing countries (Wu, 2007). Corroborating to this discussion, this chapter shows a study with a Brazilian company that have internationalized its product development.

634

The case study draws two general conclusions: first, Brazilian TNC internationalizes its R&D, thus corroborating with studies pointing tendency to the growing of internationalized R&D in developing countries companies (von Zedwitz, 2005; UNCTAD, 2005). Second, this Brazilian internationalization is performed similarly to developed countries. Similar conclusions are achieved by Wu (2007) in his study on Taiwanese companies, showing that “firms in developing countries appear to follow a similar path towards the globalization of R&D activities” (Wu, 2007, p. 308). The study presented in this chapter was carried out from gathering important issues on global R&D strategies and management. One of these issues is the driving forces towards R&D internationalization, and the results of the Brazilian company are also related to the most known factors that influence corporations: market and/or technology. Another issue is related to the roles of foreign subsidiaries, which are determined by Embraco the same way as companies from developed countries determine specific contributions of affiliates for integrating a global corporative network. Finally, management of global R&D also follows established rules observed in the literature. From the results, we conclude that Embraco has decided to internationalize its product development process by looking for better conditions for meeting the client’s needs in foreign markets, and this organization has been succeed on this purpose. Competencies and experiences of the R&D team abroad were assimilated into the corporation headquarters (in Brazil) in a way they have intentionally decided to locate an R&D unit in China, intending to access skills and knowledge. R&D activities were thus managed in order to have differentiated contributions of domestic units, leading to jointly development of knowledge, similar to transnational model by Bartlett and Ghoshal (1989). Considering this reality, it raises the question whether companies from emerging countries that recently have been globalized (the called late movers) may follow,

R&D Internationalization as Mechanism of Innovation in Global Enterprises

some decades later, the same steps to consolidate TNC in terms of R&D internationalization. The answer is positive for the example here analyzed, but it requires additional research to achieve further conclusions.

REFERENCES Ambos, B. (2005). Foreign direct investment in industrial research and development: A study of German MNCs. Research Policy, 34, 395–410. Bartlett, C. A., & Ghoshal, S. (1989). Managing across borders: The transnational solution. Boston, MA: HBS Press. Bartlett, C. A., & Ghoshal, S. (1990). Managing innovation in the transnational corporation. In Bartlett, C. A., Doz, Y., & Hedlund, G. (Eds.), Managing the global firm. New York, NY: Routledge. Bartlett, C. A., & Ghoshal, S. (1992). What is a good manager? In Barnevik, P., & Kanter, R. (Eds.), Global strategies: Insights from the world’s leading thinkers (The Harvard Business Review Book Series). Boston, MA: HBS Press. Baumann, R. (1996). Uma visão econômica da globalização. In Baumann, R. (Ed.), O Brasil e a economia global. Rio de Janeiro, Brazil: Campus. (in Portuguese) Behrman, J. N., & Fischer, W. (1980). Overseas R&D activities of transnational companies. Cambridge, MA: Gunn & Hain. Birkinshaw, J., & Hood, N. (1998). Multinational subsidiary evolution: Capability and charter change in foreign-owned subsidiary companies. Academy of Management Review, 23(4), 773–795.

Birkinshaw, J., Hood, N., & Jonsson, S. (1998). Building firm-specific advantages in multinational corporations: the role of subsidiary initiative. Strategic Management Journal, 19(3), 221–241. doi:10.1002/ (SICI)1097-0266(199803)19:3<221::AIDSMJ948>3.0.CO;2-P Birkinshaw, J. M. (1996). How multinational subsidiary are gained and lost. Journal of International Business Studies, 27(3), 467–495. doi:10.1057/ palgrave.jibs.8490845 Cantwell, J. (1992). The internationalization of technological activity and its implications for competitiveness. In Granstrand, O., Hakanon, L., & Sjolander, S. (Eds.), Technology management and international business: Internationalization of R&D and technology. Sussex, England: John Wiley & Sons Ltd. Cantwell, J. (1994). Introduction. In Cantwell, J. A. (Ed.), Transnational corporations and innovatory activities. London, UK: Routledge. Cantwell, J. (1995). The globalisation of technology: What remains of the product cycle model? Cambridge Journal of Economics, 19, 155–174. Cantwell, J., & Santangelo, G. (1999). The frontier of international technology networks: Sourcing abroad the most highly tacit capabilities. Information Economics and Policy, 11(1), 101–123. doi:10.1016/S0167-6245(99)00005-0 Chiesa, V. (1995). Globalizing R&D around centres of excellence. Long Range Planning, 28(6), 19–28. doi:10.1016/0024-6301(95)00048-N Chiesa, V. (2000). Global R&D project management and organization: A taxonomy. Journal of Product Innovation Management, 17(5), 341–359. doi:10.1016/S0737-6782(00)00049-7

635

R&D Internationalization as Mechanism of Innovation in Global Enterprises

Chiesa, V., & Manzani, R. (1996). Managing knowledge transfer within multinational firms. International Journal of Technology Management, 12(4), 462–476. Dias, A. C. D., & Salerno, M. S. (2009). Decentralization of research, development and engineering activities in transnational corporations: Contributions to theory from a subsidiary perspective. [in Portuguese]. Gestão e Produção, 16(2), 187–199. doi:10.1590/S0104-530X2009000200003 Doz, Y. L., Santos, J., & Williamson, P. (2001). From global to metanational: How companies win in the knowledge economy. Boston, MA: Harvard Business School Press. Doz, Y. L., Wilson, K., Veldhoen, S., Goldbrunner, T., & Altman, G. (2006). Innovation: Is global the way forward? (Survey Results Report). Fontainebleau, France: INSEAD and Booz Allen Hamilton. Dunning, J. H. (1988). The eclectic paradigm of international production: A restatement and some possible extensions. Journal of International Business Studies, 19(1), 1–31. doi:10.1057/palgrave. jibs.8490372 Dunning, J. H. (1993). Multinational enterprises and the global economy. Boston, MA: AddisonWesley. Dunning, J. H. (1994). Multinational enterprises and the globalisation of innovator capacity. Research Policy, 23, 67–88. doi:10.1016/00487333(94)90027-2 Dunning, J. H. (2000). The eclectic paradigm as an envelope for economic and business theories of MNE activity. International Business Review, 9, 163–190. doi:10.1016/S0969-5931(99)00035-9 Edler, J. (2008). Creative internationalization: Widening the perspectives on analysis and policy regarding international R&D activities. The Journal of Technology Transfer, 33(4), 337–352. doi:10.1007/s10961-007-9051-1

636

Ferdows, K. (1997). Making the most of foreign factories. Boston, MA: Harvard Business Review. Florida, R. (1997). The globalization of R&D: Results of a survey of foreign-affiliated R&D laboratories in the USA. Research Policy, 26, 85–103. doi:10.1016/S0048-7333(97)00004-8 Forsgren, M., & Olsson, U. (1992). Power balancing in an international business network. In Forsgren, M., & Johanson, J. (Eds.), Managing networks in international business (pp. 178–192). Philadelphia, PA: Gordon and Breach. Galina, S. V. R., Camillo, E., & Consoni, F. L. (2010). ((Forthcoming)). International R&D: A typology for brazilian subsidiaries of multinational companies. Ensaios FEE. Galina, S. V. R., & Moura, P. G. D. S. (2010). O processo de internacionalização do desenvolvimento de produtos em empresas multinacionais brasileiras. In Oliveira, M. Jr., (Ed.), Multinacionais Brasileiras: Internacionalização, inovação e estratégia global. São Paulo, Brazil: Artmed. (in Portuguese) Galina, S. V. R., Sbragia, R., & Plonski, G. A. (2005). R&D in the telecom industry in Brazil: Some indicators involving large transnational companies. Innovation: Management. Policy & Practice, 7, 298–309. Gammelgaard, J. (1999). How foreign subsidiaries develop into integrated competence centres (Working paper n. 13). Copenhagen, Denmark: Copenhagen Business School. Gassmann, O., & von Zedwitz, M. (1999). New concepts and trends in international R&D organization. Research Policy, 28, 231–250. doi:10.1016/S0048-7333(98)00114-0

R&D Internationalization as Mechanism of Innovation in Global Enterprises

Gerybadze, A., & Reger, G. (1999). Globalization of R&D: Recent changes in the management of innovation in transnational corporations. Research Policy, 28, 251–273. doi:10.1016/S00487333(98)00111-5 Gomes, R. (2006). Empresas transnacionais e internacionalização da P&D: Elementos de organização industrial da economia da inovação. São Paulo, Brazil: Unesp. (in Portuguese) Granstrand, O., Håkanson, L., & Sjölander, S. (Eds.). (1992). Technology management and international business: Internationalization of R&D and technology. Chichester, UK: John Wiley & Sons. Gupta, A. K., & Govindarajan, V. (1991). Knowledge flows and the structure of control within multinational corporations. Academy of Management Review, 16, 768–792. Gupta, A. K., & Govindarajan, V. (1994). Organizing knowledge flows within MNCs. International Business Review, 3(4), 443–457. doi:10.1016/0969-5931(94)90033-7 Hakanson, L. (1990). International decentralization of R&D: The organizational challenges. In Bartlett, C., Doz, Y., & Gunnar, H. (Eds.), Managing the global firm. London, UK: Routledge. Howells, J. (2000). International coordination of technology flows and knowledge activity in innovation. International Journal of Technology Management, 19, 806–819. doi:10.1504/ IJTM.2000.002845 Hult, G. T. M., Keillor, B. D., & Hightower, R. (2000). Valued product attributes in an emerging market: A comparison between French and Malaysian consumers. Journal of World Business, 35(2), 206–220. doi:10.1016/S1090-9516(00)00033-X

Inzelt, A. (2000). Foreign direct investment in R&D: Skin-deep and soul-deep cooperation. Science & Public Policy, 27(4), 241–251. doi:10.3152/147154300781781913 Johanson, J., & Vahlne, J. E. (1977). The internationalization process of the form: A model of knowledge development and increasing market commitment. Journal of International Business Studies, 8(1), 23–32. doi:10.1057/palgrave. jibs.8490676 Kumar, N. (2001). Determinants of location of overseas R&D activity of multinational enterprises: The case of US and Japanese corporations. Research Policy, 30, 159–174. doi:10.1016/ S0048-7333(99)00102-X Niosi, J. (1999). The internationalization of industrial R&D: From technology transfer to the learning organisation. Research Policy, 28, 107–117. Ohmae, K. (1990). The borderless world: Power and strategy in the interlinked economy. London, UK: Collins. Patel, P., & Vega, M. (1999). Patterns of internationalisation of corporate technology: Location vs. home country advantages. Research Policy, 28, 145–155. doi:10.1016/S0048-7333(98)00117-6 Pearce, R. (1999). Decentralised R&D and strategic competitiveness: Globalised approaches to generation and use of technology in multinational enterprises (MNEs). Research Policy, 28, 157–178. doi:10.1016/S0048-7333(98)00115-2 Pearce, R., & Papanastassiou, M. (1996). R&D networks and innovation: Decentralised product development in multinational enterprises. R & D Management, 26(4), 315–333. doi:10.1111/j.1467-9310.1996.tb00968.x

637

R&D Internationalization as Mechanism of Innovation in Global Enterprises

Reddy, P. (1997). New trends in globalization of corporate R&D and implications for innovation capability in host countries: A survey from india. World Development, 25(11), 1821–1837. doi:10.1016/S0305-750X(97)00079-X Reddy, P. (2000). The globalisation of corporate R & D: Implications for innovation capability in developing host countries. London, UK: Routledge. Ronstadt, R. C. (1977). Research and development abroad by U.S. multinationals. New York, UK: Praeger. Roth, K., & Morrison, A. J. (1992). Implementing global strategy: Characteristics pf global subsidiaries. Journal of International Business Studies, 23(4), 715–735. doi:10.1057/palgrave. jibs.8490285 Terpstra, V. (1977). International product policy: The role of foreign R&D. The Columbia Journal of World Business, 12(4), 24–32. United Nations Conference on Trade and Development (1994). World investment report 1994: Transnational corporations, employment and the work place. New York, NY: UNCTAD. United Nations Conference on Trade and Development (1999). Foreign direct investment and the challenge of development. New York, NY: UNCTAD. United Nations Conference on Trade and Development (2005). World investment report 2005: Transnational corporations and the internationalization of R&D. New York, NY: UNCTAD. United Nations Conference on Trade and Development (2009). World investment report 2009: Transnational corporations, agricultural production and development. New York, NY: UNCTAD.

638

Vernon, R. (1966). International investment and international trade in the product cycle. The Quarterly Journal of Economics, 80, 190–207. doi:10.2307/1880689 von Zedwitz, M. (2005). International R&D in companies from developing countries – The case of China. In UNCTAD, Globalization of R&D in developing countries (pp. 117-140). Genebra, Switzerland: UN. Wu, F. (2007). Internationalisation of research and development: The case of Taiwanese firms. International Journal of Technology Management, 39(3/4), 297–310. doi:10.1504/ IJTM.2007.013497

KEY TERMS AND DEFINITIONS Corporations: Enterprises comprising the headquarters and their foreign affiliates. Developed Countries: Countries with a high level of development according to economic and social criteria. Developing Countries: Nations that have not yet achieved economic and social indicators of a developed country but with evidence of rapid growth and industrialization. Foreign Direct Investments: Investments by a company resident in one economy in assets (structures, equipment, organizations) located in an economy other than that of the investor. Foreign Subsidiaries or Foreign Affiliates: Units of a multinational company located in a different country of its home country.

Section 9

Information Systems and Innovation

640

Chapter 34

Tools That Drive Innovation: The Role of Information Systems in Innovative Organizations Jason G. Caudill Carson-Newman College, USA

ABSTRACT The purpose of this chapter is to examine computer technology as a tool to support innovation and innovative processes. The primary problem that this chapter is intended to address is the multitude of widely held misconceptions that seem to exist regarding technology and innovation; technology is not innovative in and of itself. The primary method of research for this chapter is a literature review and case study method examining how technology is being successfully integrated into innovative processes in industry. Specifically this chapter focuses on technology’s role in communication and creativity, two of the many activities found in an innovative process. Findings indicate that while directly connecting technology use to innovation is difficult, technology can play a substantial role in facilitating the innovative process. Thus, technology is a qualifier for many innovative processes, a resource that is necessary for the work of innovation to take place.

INTRODUCTION In modern, developed countries around the world commerce, and by extension life itself, have changed dramatically in the past few decades. Commerce ultimately touches every aspect of life.

Businesses produce the goods that people need to live and provide the jobs that people work to earn money to purchase what they need. People’s incomes and spending habits, in capitalist markets, drive businesses in what they do to capture market share and generate profits. While this connection

DOI: 10.4018/978-1-61350-165-8.ch034

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Tools That Drive Innovation

between people and economic activity is certainly not new, the way in which much of this interaction occurs is. The rise of ecommerce and the globalization of commerce have changed not only the methods by which people consume goods and services, but the very development of those goods and services. Innovation is central to this change as, “ICTs (information and communication technologies) foster a broad spectrum of innovation activities which involve the individual, organizational, industrial, and national levels of economic productivity” (Ho, Kauffman, & Liang, 2008, p 1). Markets of all types are more dynamic now than at any time in the past. Product development moves more quickly, products change more often, and consumer expectations are for this to happen and continue to happen. Brynjolfsson and Schrage (2009) explain that, “Technology is transforming innovation at its core, allowing companies to test new ideas at speeds—and prices—that were unimaginable even a decade ago.” In today’s digital age innovation and technology are inexorably linked. Baldwin and von Hippel (2009) explain that technologies like the personal computer and the Internet provide more opportunities for innovative activities to occur in more forms. Many people may feel that technology by virtue of its existence is innovative, and that applying technology to any situation means that innovation is taking place. While perhaps understandable this is not at all accurate. This chapter will discuss technology as a tool, an aid to the innovative process. There are many different ways that technology can be appropriately applied to innovation, and innovation has benefitted from these applications, but an innovative process must exist before technology can serve as an aid to it. Technology in this sense is not in itself a creator of competitive advantage, but it does serve as a facilitator to innovative activities through which advantage can be gained. The focus of this chapter is to introduce ideas of technology applications

as tools through which innovative activities can be fostered, and with which efficiencies and effectiveness can be improved.

TECHNOLOGY AS A TOOL Technology is an incredibly powerful force in the developed world. Compounding not only technology’s importance but also its impact, the rise of digital technology and its penetration into the market has been unrivaled in human history. In just a few short years personal computers moved from very expensive diversions for a limited number of technically-engaged hobbyists to a common household appliance. In just a few more years they moved from being stand-alone devices to networked devices that brought the world into living rooms and offices. Ultimately, such connectivity moved from full-sized computers to handheld devices in the form of smartphones. Such devices are constantly changing and the highly competitive marketplace brings new features and new models to customers on a frequent basis. Technology is inherently innovative, particularly where competition among technology providers is concerned. Where misunderstanding often occurs is the idea that just by having technology in a process that process becomes innovative. Technology is, and always has been, nothing more than a tool. Dosi (1988) explains that, “In very general terms, technological innovation involves the solution of problems-for example, on transformation of heat into movement, shaping materials in certain ways, producing compounds with certain properties-meeting at the same time some cost and marketability requirements” (p 1125). Notice that not only does technology solve problems, but it solves problems within the bounds of what is acceptable in the marketplace. The innovation is not the technology, rather the technology helps to find the answers as part of an innovative process.

641

Tools That Drive Innovation

As a tool technology can serve to enhance innovation. Better communications, faster analysis of data, greater ability to assess alternatives, and many other factors make digital technology a great asset to the process of innovation. Technology is not a traditional capital investment, but serves a more general purpose for an organization; investments in information technology can contribute to higher productivity and it is such related contributions that provide a return on technology investments (Brynjolfsson & Hitt, 2000). Not only can technology enhance innovation through providing focused process improvement, it can also impact the innovative nature of an organization as a whole. Bartel, Ichniowski, and Shaw (2007) noted in their study on information technology and innovation that, “…the adoption of new computer-based IT also increases the skill requirements of workers, notably technical skills, while also promoting the adoption of new human resource practices” (p 1723). Not only do tools give workers more options, but the presence of new tools can change the practices and capabilities of those workers. This chapter will be dealing primarily with today’s digital technology, but the concept of technology and integration holds true for all types of technology; effective tools enhance innovative processes.

TECHNOLOGY, INNOVATION, AND COMMUNICATION Sometimes innovation is the result of a single individual finding enlightenment or inspiration to change the way something is done or made. More often, particularly in organizational contexts, innovation is the result of collaboration, teamwork, and ultimately communication. Fagerberg (2005) explains that:

642

Thus, what we think of as a single innovation is often the result of a lengthy process involving many interrelated innovations. This is one of the reasons why many students of technology and innovation find it natural to apply a systems perspective rather than to focus exclusively on individual inventions/innovations (p 4). Historically, communication technologies have been of substantial importance to humanity. From clay tablets to parchment scrolls to Gutenburg’s printing press the written word made archiving and disseminating information ever more accessible (Schneiderman, 2000). Going forward broadcast media, radio and television, and then the Internet have reached people in remote locations all over the world and changed daily lives in society (Schneiderman, 2000). Von Hippel (2002) examines innovation networks as the development mechanism for free and open source software applications. Communication is part of that innovation network, explained in context as, “…individual users do not have to develop everything they need on their own: they can benefit from innovations developed by others and freely shared within and beyond the user network” (Von Hippel, 2002, p 1). The process of innovation is certainly much more than just communication, but communication does play a key role in innovative activities. Increasingly, this communication takes place through the use of technology. Herrmann (2008) discusses the field of Computer Supported Collaborative Work (CSCW), which focuses on using computers to support creativity. Herrmann’s work explores the idea that while different people engage in the creative process in different ways technology tools are flexible enough to support individuals according to their preferred work habits. These technology tools can take many different forms in CSCW, including: supporting the large picture—visu-

Tools That Drive Innovation

alization of rich material, malleability of shared material and stimulation of variations, support of convergence within evolutionary documentation, smooth transitions between modes of creative collaboration, and integration of communication with work on shared material (Herrmann, 2008). Awazu et. al. (2009) identifies five roles of information and communication technologies (ICTs) in innovation: understanding idea sources; documenting ideas and sources; distribution and sharing of ideas for cross-application; idea design, testing, and refinement; and idea commercialization. These ICT roles mirror Herrmann’s (2008) view of the benefits of technology tools in CSCW. Supporting the large picture and visualizing rich material can be support functions for documenting and distributing ideas. Shared material and stimulation of variations can support distribution of ideas as well as idea design, testing, and refinement. Support of convergence can benefit idea commercialization. These tools of technologyenabled collaboration align with the innovation benefits of ICT. In order to successfully fill these roles ICTs must be properly implemented and managed in the firm. This is not a static effort, rather continuing monitoring, assessment, and updating must occur in order for a firm to apply technology towards maintaining continual competitive advantage. McAfee and Brynjolfsson (2008) define a threestep process for doing so: • • •

Deploy: adopt a uniform technology platform; Innovate: design better ways of doing work; Propagate: use IT to replicate process innovations.

If technology is properly managed then it can successfully fulfill its role to support communication and collaboration as a component of the innovative process.

Communication and collaboration may be somewhat interchangeable terms. If people pursuing innovative work are communicating, they are in effect collaborating, and if they are collaborating with others then there must be communication. Regardless of this connection the exchange of ideas is critical to the innovative process. The difficulty in many situations is that in any circumstance teamwork poses challenges to organization and management. In an innovative effort, however, a common space must be developed. The “…abstract territory in which design search takes place…” (p 1297) has been termed the design space (Baldwin, Hienerth, & von Hippel, 2006). Herrmann’s (2008) points about the assistive possibilities of technology and innovation can be part of creating the design space to provide innovation a place in which to happen. Innovation thrives on the input of multiple perspectives, but often such diverse inputs create overly complex decision environments. Inter-organizational collaboration, partnerships between multiple organizational entities, is an important part of business innovation today, but even with such great potential value as many as 60% of such ventures fail (Faems, Van Looy, & Debackere, 2004). As industry continues to progress towards a more global operating environment there are certainly opportunities for more diverse perspectives to act as inputs for innovative processes. Concurrently, there are also many more complicating factors, ranging from global differences in time zone, the impracticality of physical meeting spaces, and language barriers. Additionally, technology can increase participation in innovative processes by better incorporating persons with disabilities into active participation. Technology in the form of CSCW can offer technical solutions to these organizational issues and, by eliminating the barriers, enhance innovative activities. In relation to time zone issues, asynchronous communication technologies are a familiar tool to many today. Discussion boards and other forums, in addition to older technology like e-mail listservs,

643

Tools That Drive Innovation

give contributors the opportunity not only to share their ideas at any time but also to have those ideas archived as a part of the innovative process for later reference. Both the ability to communicate effectively across time zones, effectively creating a 24-hour a day office, and the archiving of conversations can aid everyone involved in the process. If technologies are used that provide for the threading of discussions effectiveness is further enhanced by keeping topics closely connected for better understanding of all involved. Asynchronous exchanges do have their limitations and sometimes the only way to effectively resolve development issues is through live, synchronous exchanges. Globalization has been a complicating factor in such meetings for many years due to the distances separating team members or contributing groups in different countries. Through the economic downturn that began in 2008 this difficulty has been compounded by the critical need for firms to reduce expenditures, travel being one such cost. Virtual meeting spaces are a technical solution to the problem. While time zone complications may make scheduling the meeting difficult there are multiple technologies available that support live audio-visual exchanges among multiple participants from any location while also providing tools to share files, display materials in the group environment, and even share the ability to write and draw on a virtual whiteboard. Such technologies can provide more frequent synchronous work environments than are possible with travel between multiple locations, thus enhancing the innovative process for all involved. Also, many of these virtual workspace technologies can record and archive all activity in the room so that valuable ideas are not lost. Not only does the archive preserve information for future reference of attendees, it also allows those individuals who were unable to attend the meeting to experience the full exchange of ideas for a more thorough understanding of the meeting’s conclusions.

644

Any exchange, whether synchronous or asynchronous, ultimately depends on a common language existing among the participants. While still in its early stages there are technical solutions to language barriers. Software solutions exist that can roughly translate written materials online and display the result in a variety of languages for the reader. Admittedly these technologies are not a substitute for a fluent speaker of the language, but today’s solutions can serve as a stop-gap measure when absolutely necessary. In the future such technologies will hopefully advance to a point that language barriers are virtually invisible through electronically-mediated communication. All of the previously discussed solutions and others can also be very useful in giving individuals with a broad range of disabilities the opportunity to take an active role in the innovation process. Computer-mediated communications provide users with auditory or visual disabilities many opportunities to engage in the exchange of ideas through either text-to-speech or speech-to-text conversion tools. These tools, properly implemented, can provide mediation for such disabilities in both synchronous and asynchronous work environments and, by extension, improve the innovation process by bringing more ideas to the table. Beyond such basic applications technology provides many other valuable opportunities for disabled persons to be incorporated into innovation processes. The live streaming of video and synchronous online communication can serve to bring mobility-impaired persons on-site for projects that they could not physically negotiate. By seeing what the group is seeing and having a medium through which they can communicate in live time with the on-site team this process can include people who in the past would have been forced to rely on photographs or videos after the fact. Also, such technologies are not only limited to serving those with disabilities; these processes can also bring contributors unable to physically attend such a meeting into the process. Regardless

Tools That Drive Innovation

of who is served, the inclusion of more people in the live environment can produce more insights and improve the overall efficiency of the innovative process. Overall, communication in innovation is moving from the traditional Web 1.0 environment to Web 2.0 solutions. Fischer (2009) approaches technology contributions to innovation from a Web 2.0 perspective, explaining that current technologies have driven a shift from information consumer culture to cultures of participation that create content. This participatory culture is seen as an advance in innovative capabilities, explained as, “End-user development is an essential component of this transformation, but its impact is much broader: this transformation represents a change and new opportunity for social production, for mass collaboration, for civic and political life, and for education” (Fischer, 2009, p 4). Collaboration in multiple arenas, facilitated by technology, can enhance innovation efforts. Of particular interest in the incorporation of Web 2.0 technologies is the generational shift occurring in the workforce. As the baby boomers begin to exit the workforce organizations are looking at increasing numbers of Generation X members in leadership positions, a generation much more comfortable and familiar with technology. More important to Web 2.0 integration in organizations is the entry of Generation Y members into the workforce in ever-growing numbers. These workers are easily the most techno-centric workers in history and expect connectivity through social media and online learning to be the standard rather than the exception. As increasing numbers of workers become comfortable with and demanding of Web 2.0 technologies their work, including innovative pursuits, come to depend on such communication technologies. The impact of these technologies is beyond simply giving workers another communication medium. Because of changing work

and social practices social media is becoming a necessary tool to engage people in communication and, by extension, innovation. Communication is the first of the two major categories of technical contributions to innovation. Perhaps the best illustration of the value of communication to technology today is an observation of how many people use computers. Before the Internet became commoditized and commonplace people often spent time on their home computers just working independently. With Internet connectivity an expectation now a computer without access to the network quickly becomes an almost useless device. People expect technology to connect them to others.

TECHNOLOGY, INNOVATION, AND CREATIVITY Leonard and Sensiper (1998) use the definition, “The process of innovation is a rhythm of search and selection, exploration and synthesis, cycles of divergent thinking followed by convergence” (p 116). This innovative process is cyclical, with multiple decision cycles occurring as a part of creative group activity (Leonard & Sensiper, 1998). Leonard and Swap (1999) discuss creativity, and its myths, in relation to innovation. Their definition of innovation is that it is, “…the embodiment, combination, and/or synthesis of knowledge in novel, relevant, valued new products, processes, or services” (Leonard & Swap, 1999, p 7). The process of creativity can be difficult to precisely define, yet there is an inherent understanding of what creativity is; it is the creation of a new idea, new device, or new work, something new. The question for the technologist is how to enhance the creative process, the process of innovation, with technical tools. Leonard and Swap’s (1999) definitions of and myths about creativity are listed in Table 1 for reference.

645

Tools That Drive Innovation

There are multiple approaches in the literature regarding how to support, enhance, and assess creative action and, by extension, innovation. Leonard and Sensiper (1998) explain that creative cooperation is critical to the process of innovation, no matter what the intended product of that innovation may be. By understanding how creativity works it is possible to connect defined actions to support provided by the inclusion of information systems in the process. These connections can then serve to improve the correct application of technologies to the creative process. Huber, Bretschneider, Leimeister, and Krcmar, (2009) introduce the generator of excellence (GENEX) framework for innovation. The framework consists of: • • •

•

Collect: searching and browsing digital libraries, visualizing data and processes; Relate: consulting with peers and mentors; Create: thinking by free association, exploring solutions (what-if tools), composing artifacts and performances, reviewing and replaying session histories; Donate: disseminating results.

While all of these activities have in one way or another always existed as a part of the innovation process technology serves to enhance them to improve innovation.

Schneiderman (2000) continues the exploration of the GENEX process. Specifically, he explains that the four phases of the GENEX framework are not strictly linear, rather they may be cyclical and iterative, repeated multiple times to arrive at a conclusive solution. This discussion mirrors Leonard and Sensiper’s (1998) discussion of the innovative process as being similarly cyclical. Such cycles often occur in group contexts and as such require active and archivable communication methods to support the process. Innovation is certainly more than creativity, but as creativity is a key part of innovation and there are parallels between the creative and innovative processes the role of technology in supporting creativity does feed innovation. Components of the GENEX framework can be identified in other creativity research. Shneiderman (2007) addresses technology as a medium through which to engage in creative activities that lead to innovation, explaining that, “Creativity support tools extend users’ capability to make discoveries or inventions from early stages of gathering information, hypothesis generation, and initial production, through the later stages of refinement, validation, and dissemination” (p 2). Creativity support is defined as a combination of two factors, specific tasks that support discovery and the capacity to generate multiple alternatives (Shneiderman, 2007).

Table 1. Definitions of and myths about creativity (Source: Leonard & Swap, 1999) Definitions of and Myths About Creativity Definitions of Creativity •...that process which results in a novel work that is accepted as tenable or useful or satisfying... •...it is both novel and appropriate, useful, correct, or valuable response to the task at hand... • A company is creative when its employees do something new and potentially useful without being directly shown or taught. •...the production of something that is both new and truly valuable •...involves a process that is extended in time and characterized by originality, adaptiveness, and realization

646

Myths About Creativity • Creative output depends on a few, often flamboyantly different individuals • Creativity is a solitary process • Intelligence is more important than creativity • Creativity can’t really be managed • Creative groups are found only in “The Arts” or in high-technology companies • Creativity is relevant only to Big Ideas • Creativity only involves coming up with new ideas

Tools That Drive Innovation

Gathering information connects to the GENEX framework concept of collecting. Technology’s role in information collection is difficult to overemphasize in today’s connected world. Where only fifteen years in the past a team of researchers might have to make phone calls or written requests via mail to obtain data from past projects performed by others, particularly international works, the same information is now available through digital technology. If the documents are not available directly online then e-mail contact can bring electronic versions of the document as quickly as differing time zones will allow. Such online repositories of knowledge and the digitalization of many older text works greatly enhances people’s ability to collect information. Such technology directly enhances the collection stage of the GENEX framework. One technology currently in use is a branch of computer aided information (CAI) called patent analysis/patent map tools that assists “…the users in searching, collecting, analyzing, and visualizing patent data” (Yu, Wu, & Lien, 2008, p 524). Stage two of GENEX, relate, is a communications aspect of technology. This is a critical component that links the collection of information to the analysis and use of that information. Communication is the process that transforms data in the collection stage to information in the create stage. Creation is the point at which the foundational work of collecting and relating grows into new ideas. This GENEX stage can relate to hypothesis generation, initial production, refinement, and validation. In initial stages what innovators create is ideas. Brown (2008) explores the creative product analysis model, which includes the concepts of novelty, resolution, and style. The primary focus of this work is on the ability of technology to facilitate the creation of more ideas, which by extension lead to more innovative solutions. In support of this concept, Brown cites Linus Paul-

ing’s statement that, “The best way to have a good idea is to have lots of ideas.” Lots of ideas are the foundation of hypotheses. From the generation of hypotheses comes the initial production of concepts. This stage too can benefit greatly from technical innovation. A second branch of CAI, Innovative Solution Generation, is one technology that can help users to create innovative problem-solving models (Yu, Wu, & Lien, 2008). The collaborative benefits of technology have already been discussed, but initial production can greatly benefit from technology in other ways. The virtualization of products, components, or other parts of an innovative product or idea can be greatly enhanced by the use of technology. Rapid prototyping is an industry standard where much time is saved by creating and testing new physical devices in a virtual space. Not only does the speed of the system lead to faster development cycles but the relatively low cost allows for the exploration of many more possibilities. To paraphrase Pauling, lots of ideas better lead to good ideas. Following this initial production refinement takes place. The value of prototyping and investigative technologies cross over from initial production to refinement as many of the same technologies and same processes can help innovative workers to refine their many ideas. As the process progresses many ideas are funneled to fewer, more practical and more probable ideas. Refining, much like other stages of the process, is enhanced in speed and effectiveness by technical tools. Communication and rapid prototyping are both parts of this refinement. Past the rapid prototyping technologies testing technologies enhance refinement. At the refinement stage the bulk of ideas should be eliminated, with the refinement stage finding and defining shortcomings of sub-optimal ideas. Rejected ideas at this stage are not failures, and can improve the ultimate solution, a process that is also technologyenhanced. Failure points, and also positive aspects,

647

Tools That Drive Innovation

of ideas discovered during the refinement process can be archived and assessed using technical tools. Ideally, these individual items will be compiled to enhance the final selection. With technology creating more ideas and faster initial production technology is also needed to organize and capitalize on what is learned by refining the product from so many ideas to only one or a small few. Once that one or small few ideas have been reached through refinement those selected concepts must be confirmed as valid ideas. The same technologies already applied work here and offer many of the same advantages. The validation process can move more quickly through the use of technology and it may also be possible to perform detailed validation analysis of more ideas, thus providing an in-depth analysis of more ideas than would be possible with other methodologies. With validation complete and a final solution identified the donate stage of GENEX, dissemination, is the final part of the innovation process. This may be the easiest technology connection to identify as the communicative and marketplace forces of the Internet make dissemination of new ideas faster and easier than at any previous point in history. Integrating Web 2.0 technologies into the process makes this dissemination even faster as others with an interest in the discovery post and spread the news on their own, independent of the organization. These individual stages of innovation help to produce a map of where and how technology can enhance the innovative process. The goal of technology integration in any field, however, is to create and enhance an overall system of productivity. Hekkert, Suurs, Negro, Kuhlmann, and Smits (2007) look beyond individual technologies and address technology tools as part of an overall innovative system, defining an innovation as, “...the successful combination of hardware, software, and orgware...” (p 414). To understand how innovative systems work, including the role of technology within such systems, Hekkert et al. propose that

648

the activities of an innovation system should be mapped to identify and understand their functions. These functions include: entrepreneurial activities, knowledge development, knowledge diffusion through networks, guidance of the search, market formation, resources mobilization, and the creation of legitimacy/counteract resistance to change (Hekkert, et al., 2007). Hekkert’s (2007) work highlights several important points, not the least of which is the reaction of people in the organization. Regardless of what technologies are applied to the innovative process people are the core resource. If the people involved in the process do not support the technologies being applied to innovation then the system as a whole is likely to fail. With that in mind, creating legitimacy and counteracting resistance to change is an early priority in any innovative process. Human resource management sources often identify employee buy-in as one of the very first steps in any change process and that holds true for innovative processes. Much of the rest of the list proposed by Hekkert, et. al. involves aspects of innovation and their related technology enhancements that have already been addressed here. The important new aspect highlighted by the list is that while these different components have been identified and discussed as individual components in an overall innovation process they are, in practice, parts of an overall system, each depending on the others. In this interdependent system of innovation every part of the process shifts when any part of the process shifts. When examining the role that technology plays in such a system the impact of technology enhancements is greatly magnified. Improving the speed or efficiency of a single part of the process or allowing for more exploration in any stage of development impacts the overall performance of the process as a whole. Thus, the potential impact of technology integration in the innovation process can be exponential.

Tools That Drive Innovation

SOLUTIONS AND RECOMMENDATIONS Utilizing the advantages offered by technology in innovative processes in any kind of organization is no longer an option; rather the question is how much technology will be used. This situation presents many unique challenges to an organization engaged in innovative work. The choices of technology, workers’ use of the technology, and overall structure of the effort must all be carefully determined. Across all categories of technology solutions for innovation training for all involved is highly recommended. At an organizational level there must be decision-makers who understand the role of technology in the organization’s strategy. A fundamental recommendation of the Management Information Systems (MIS) field is that strategy should drive technology; technology should never drive strategy. This means that decision-makers need to be properly trained in how to assess the technical needs of their organizational programs and the best ways in which to apply technology to the problems. Once technology choices are made workers who will interact with the technology must be trained on how to effectively use that technology. For the tools to be effective users must know how and when to apply them, which is where training for personnel enters into the equation. A comprehensive, integrated training program for employees should be established in advance of new technical integrations for innovation processes. Tying into the issue of strategy there should also be a concerted effort towards structuring the use of technology in the organization across all aspects of innovation and other activities. The nature of structure will change for each unique organization as the structure of the technology implementation will need to match the structure of the organization. Executing such a match will require detailed study by a cross-functional team

drawn from throughout the organization. Done properly, this effort will help to ensure a successful use of technology to enhance innovative processes.

FUTURE RESEARCH DIRECTIONS There are many opportunities for future research connecting technology and innovation. Part of the breadth of opportunities connects to the difficulty of measuring innovation. Because innovation is, by its very nature, the creation of something entirely new there is not necessarily an existing point against which to measure the effort. With the lack of a firm starting point assessment becomes much more challenging. This certainly does not mean that effective research cannot be done, but there are many different approaches that could be useful, with some situations benefitting from multiple studies using varied methodologies. Future research should drive deeper into the subject and generate data from innovative fields. Possible models for such research may include broad surveys of professionals engaged in innovative processes to reveal what technical tools they use and how those tools complement each other and the work preferences of the users. Surveys using a basic Likert scale may be used initially, but the richness of the subject matter may demand interviews and ethnographical analysis to reach the best data. There may be interesting opportunities for innovation research to take place in multiple disciplines. Manufacturing, scientific research, software development, and media development firms could all provide unique study opportunities for the integration of technology in innovative processes. Multiple segments within each discipline may offer unique opportunities as well, but at the very least the multiple disciplines should be studied to see how different innovative efforts apply and integrate technology differently.

649

Tools That Drive Innovation

One significant issue that may merit study is that of necessary speed of development. Different industries face very different competitive environments and their products function on different life cycles. One aim of the research could be to determine if industries are more or less likely to use technology enhancements in their innovation processes, or if they use technology differently, in connection to their needs for fast development cycles. The technical skill sets of employees in given industries may also be worthy of investigation. The assumption is likely made that more technical industries are more likely to use technology to enhance their innovation efforts. Research could either prove or disprove such assumptions and could serve a function in guiding industries of different technical skill levels in how to effectively pursue technology-enhanced innovation. These broad opportunities help to define some of the work that may be done in researching the role of technology in innovation. Within each broad category there are many focused opportunities for study, some of which may benefit from being replicated across multiple broad categories. One important factor in designing future research in the role of technology in innovation is that the studies may focus more on strategy than on the technology. With that in mind there are likely good research partnerships to be found between strategic management experts, marketing specialists, and technologists.

CONCLUSION Technology is an important component of almost every modern organization. Similarly, innovation has become an important part of organizations. Technology and innovation have traditionally been closely related, but the perspective is often one of technology being a source or result of innovation versus technology being a valuable tool in the

650

building of innovation. Going forward, innovators need to recognize the value that technology offers as a tool of innovation. Communication and creativity are the primary contributions that technology can make to innovative processes. While speed, efficiency, and other metrics also benefit from a technology-rich innovative environment, but all these positive factors ultimately tie to communication and creativity. By strategically implementing the appropriate technical tools an organization can enhance both communication and creativity, the two of which symbiotically assist each other, and advance the innovative cause of the organization as a whole. The goal of the technologist in an innovative firm should be to successfully align technical tools with the strategy of the organization. Beyond this alignment, training and support should be designed to move organizational members towards effective use of the technology. Ultimately, the approach to applying technology to innovation may of itself be innovative, but the efforts are well worth the positive results.

REFERENCES Awazu, Y., Baloh, P., Desouza, K., Wecht, C., Kim, J., & Jha, S. (2009). Information-Communication Technologies open up innovation. Research Technology Management, 52(1), 51–58. Baldwin, C., Hienerth, C., & von Hippel, E. (2006). How user innovations become commercial products: A theoretical investigation and case study. Research Policy, 35(9), 1291–1320. doi:10.1016/j. respol.2006.04.012 Baldwin, C., & von Hippel, E. (2009). Modeling a paradigm shift: From producer innovation to user and open collaborative innovation. Working Paper No. 10-038, Harvard Business School Finance, Boston, MA.

Tools That Drive Innovation

Bartel, A., Ichniowski, C., & Shaw, K. (2007). How does Information Technology really affect productivity? Plant-level comparisons of product innovation process improvement and worker skills. The Quarterly Journal of Economics, 122(4), 1721–1758. doi:10.1162/qjec.2007.122.4.1721

Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovative systems: A new approach for analysing technological change. Technological Forecasting and Social Change, 74, 413–432. doi:10.1016/j.techfore.2006.03.002

Brown, D. C. (2008). Guiding computational design creativity research. In Proceedings for the NSF International Workshop on Studying Design Creativity ’08, University of Provence, France.

Herrmann, T. (2008). Design issues for supporting collaborative creativity. In Proceedings of the 8th International Conference on the Design of Cooperative Systems.

Brynjolfsson, E., & Hitt, L. (2000). Beyond computation: Information Technology, organizational transformation, and business performance. The Journal of Economic Perspectives, 14(4), 23–48. doi:10.1257/jep.14.4.23

Ho, S., Kauffman, R., & Liang, T. (2008). A growth-theoretic empirical analysis of simultaneity in cross-national ecommerce development. In Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

Brynjolfsson, E., & Schrage, M. (2009). The new, faster face of innovation: Thanks to technology, change has never been so easy-or so cheap. Wall Street Journal and Sloan Management Review, August, 2009. Dosi, G. (1988). Sources, procedures, and microeconomic effects of innovation. Journal of Economic Literature, 26, 1120–1171. Faems, D., Van Looy, B., & Debackere, K. (2004). The role of inter-organizational collaboration within innovation strategies: Towards a portfolio approach. Journal of Product Innovation Management, 16, 333–350. Fagerberg, J. (2005). Innovation: A guide to the literature. In Fagerberg, J., Mowery, D., & Nelson, R. (Eds.), The Oxford handbook of innovation (pp. 1–26). Oxford, MA: Oxford University Press. Fischer, G. (2009). End-user development and meta-design: Foundations for cultures of participation. In Proceedings of the 2nd International Symposium on End User Development (pp. 3-14). Berlin, Germany: Springer.

Huber, M. J., Bretschneider, U., Leimeister, J. M., & Krcmar, H. (2009). Making innovation happen: Tool support for software related communities for innovations. International reports on socio-informatics – Open design spaces supporting user innovation. In Proceedings of the International Workshop on Open Design Spaces (ODS ’09) (pp. 22-33), Bonn, Germany. Hrsg.: Pipek, V., Rohde, M., IISI – International Institute for Socio-Informatics. Leonard, D., & Sensiper, S. (1998). The role of tacit knowledge in group innovation. California Management Review, 40(3), 112–132. Leonard, D., & Swap, W. (1999). When sparks fly: Igniting creativity in groups. Boston, MA: Harvard Business School Press. McAfee, A., & Brynjolfsson, E. (2008). Investing in the IT that makes a competitive difference. Harvard Business Review, (July-August): 2008. Schneiderman, B. (2000). Creating creativity: User interfaces for supporting innovation. ACM Transactions on Computer-Human Interaction, 7(1), 114–138. doi:10.1145/344949.345077

651

Tools That Drive Innovation

Shneiderman, B. (2007). Creativity support tools: Accelerating discovery and innovation. Communications of the ACM, 50(12), 20–32. doi:10.1145/1323688.1323689 Von Hippel, E. (2002). Horizontal innovation networks – By and for users. MIT Sloan School of Management (April). Retrieved from opensource. mit.edu/papers /vonhippel3.pdf. Yi, M., Jackson, J., Park, J., & Probst, J. (2006). Understanding Information Technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43, 350–363. doi:10.1016/j.im.2005.08.006 Yu, W., Wu, C., & Lien, W. (2008). Fast innovation of construction technologies with computer aided innovation tools. In Proceedings of International Symposium on Automation and Robotics in Construction 2008 (ISARC ’08) (pp. 521-527).

652

KEY TERMS AND DEFINITIONS Communication: The exchange of information. Creativity: The process of developing and applying unique solutions. Information Systems: Digital technologies used to record, analyze, and access information resources. Innovative Systems: Technology and strategy utilized in the generation of creative solutions. Technology: Hardware, software, and communication resources.

653

Chapter 35

The Roles of Cognitive Machines in CustomerCentric Organizations:

Towards Innovations in Computational Organizational Management Networks Farley Simon Nobre Federal University of Parana, Brazil

ABSTRACT This chapter proposes innovative features of future industrial organizations in order to provide them with the capabilities to manage high levels of environmental complexity in the 21st century. For such a purpose the author introduces the concept of Computational Organization Management Networks (COMN), which represents new organizations whose principles of operation are based on the concepts of Hierarchic Cognitive Systems (HCS) along with those of Telecommunications Management Networks (TMN). Structured with functional layers and cognitive roles that range from technical and managerial to institutional levels of analysis, and also equipped with operational, managerial and strategic processes, the concept of Computational Organization Management Networks (COMN) plays an important part in the developments of future organizations where cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise. It is in such a context that the new organization COMN will provide customers and the whole environment with innovations such as immersiveness for the production of services and goods that are most customer-centric.

DOI: 10.4018/978-1-61350-165-8.ch035

Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

The Roles of Cognitive Machines in Customer-Centric Organizations

INTRODUCTION This chapter mainly relies on principles of incompatibility, or non-equilibrium, existing between the continuous growth in the level of environmental complexity and the insufficient cognitive capacity of the organization to deal with higher levels of uncertainty, to operate in complex task environments, to attend new market demands, to manage new approaches to customers’ satisfaction and relationship, and to capture effectively information resources from the environment. Such a premise has motivated organizations to pursue higher degrees of cognition, intelligence, autonomy, and learning through principles of organization design (Nobre, Tobias & Walker, 2009a, 2009b, 2009c, 2010; Nobre & Walker, 2011). Therefore, this chapter focuses on the general picture of organizations pursuing high degrees of cognition in order to improve their capabilities of information processing and uncertainty management. It assumes that improvements in the degree of organizational cognition can lead the organization to achieve higher degrees of flexibility and agility, to operate through higher levels of mass customization (Pine, 1999), and to provide customers with immersiveness. In a broader sense, such improvements extend the capability of the organization to manage higher levels of environmental complexity. In such a context, flexibility means capability to reconfigure and to adapt to new operational and management conditions (Toni & Tonchia, 1998); and agility means the ability to manufacture a variety of products, services and goods, at low cost and in a short period of time (Lee, 1998). This chapter supports existing works on manufacturing systems (Kusiak, 2000; Monfared & Steiner, 1997; Rao et al., 1993) and industrial organizations (Nobre et al., 2009a, 2009c), and additionally, it extends past and present concepts by proposing new technological, managerial and organizational capabilities which have to be developed in order to satisfy the requirements

654

and to configure the new face of the industrial organization in the 21st century. First and foremost, this work aims to give insights and answers to the questions in the following whose responses are blended over this full chapter: a. What is the nature of this new industrial organization? b. What steps are required to design this new enterprise? c. What would be the future of these organizations? Chronologically, this work first introduces concepts of organizations and machines which are fundamental for the understating of this research. Such concepts comprise organizational cognition, intelligence, autonomy, and learning, along with uncertainty, environmental complexity, and cognitive machines. Second, it proposes the concept and the features of Customer-Centric Systems (CCS) which were most developed through literature review and analyses of past and current industrial organizations as researched in (Nobre & Steiner, 2002; Nobre et al., 2009a, 2009c); whereas, in these works, the authors outlined the development of manufacturing systems and organizations, especially in the 20th century, through complementary perspectives of technology, management and organizational systems theory, respectively. As a result of the analyses, they indicate limitations of past and current manufacturing organizations which motivated them the proposal of the new frontiers, concept, and features of Customer-Centric Systems (CCS). CCS represent new organizing models of production that pursue high degrees of organizational cognition in order to manage high levels of environmental complexity, to operate through intensive mass customization processes, and to provide customers with immersiveness. Third, from all these interdisciplinary backgrounds, this chapter mainly contributes by presenting the concept, structure and processes

The Roles of Cognitive Machines in Customer-Centric Organizations

of Computational Organization Management Networks (COMN), which are new organizations with the capability to implement the features of Customer-Centric Systems (CCS). In COMN, cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise (Nobre et al., 2009a, 2009b, 2009c).

KEY CONCEPTS OF THE ORGANIZATION Customer-Centric Systems: Main Features of Future Industrial Organizations This subsection introduces the characteristics of Customer-Centric Systems (CCS) which concept was firstly touched in (Nobre & Steiner, 2002), and latterly it was further developed in (Nobre et al., 2009a, 2009c). Briefly, CCS represents organizational models with capabilities to: 1. Manage high levels of environmental complexity. 2. Operate through high levels of mass customization. 3. Pursue high degrees of organizational cognition, intelligence, autonomy, and learning, and consequently, high degrees of flexibility and agility. 4. And provide customers with immersiveness. This chapter proposes that Customer-Centric Systems (CCS) are firm types which strategically organize their resources and competencies around customers’ values and needs, in order to involve customers into their business. By involving customers into their task environments and business, CCS-based organizations have the chance to understand and to produce the real needs, goods and services, to their clients.

Industrial Organizations For the purpose of this chapter, manufacturing organizations are synonymous with industrial organizations; which are classes of organizations that satisfy the concept of open-rational systems (Nobre et al., 2009a; Scott, 1998) and also the perspective of economic organizations (Milgrom & Roberts, 1992). They are highly formalized organizations that pursue specific goals, innovation and sustainable competitive advantage. They produce goods and services. The elements of the organization include goals, social structure, technology, and the participants in the organization (Scott, 1998: 17-23). Moreover, the organization exists in a physical, technological, cultural, and social environment with which the organization interacts (Scott, 1998: 21-23). Participants are the agents who act in the name of the organization and they subsume humans and cognitive machines (Nobre, 2008; Nobre et al., 2009a, 2009b). Technology expands what organizations can do and it supports the connection of the organization to the environment. Goals and sub-goals are what organizations aim to achieve in order to satisfy people’s desires. Social structure refers to the standards and regularized aspects of the relationships existing among the participants in the organization, whereas it comprises normative and behavioral parts (Scott, 1998).

Limitations of Organizations Contingency theory (Galbraith, 1973, 1977, 2002) has defined uncertainty as the variable which makes the organization contingent upon the environment. Hence, organization design, and thus organizational choice, depends on the concept of uncertainty. Briefly, uncertainty can be associated with propositions of bounded rationality theory (Simon, 1982a, 1982b, 1997a, 1997b), when carrying the meaning of (Nobre et al., 2009a: Chapter 2):

655

The Roles of Cognitive Machines in Customer-Centric Organizations

a. Lack of information, which leads the organization to unpredictability of outcomes. b. And, insufficiency of cognitive capacity for general information-processing.

Figure 1. Uncertainty as lack of information

The former, lack of information, means that: •

Definition 1: Uncertainty is the difference between the total amount of information that the organization needs to have in order to complete a task, and the amount of information in possession of the organization.

The latter, insufficiency of cognition, means that: •

Definition 2: Uncertainty is the difference between the degree of cognition that the organization needs to have in order to complete a task, and the degree of cognition in possession of the organization.

These two approaches to uncertainty are complementary to each other since the greater the amount of information that the organization needs to have in order to perform and to complete a task, the greater is the degree of cognition that the organization needs to have in order to process and to manage this information for task execution and completion. Figure 1 and Figure 2 illustrate such concepts of uncertainty using symbolic scales of measurement. Therefore, the question which rises in our quest is: what to do in order to manage the level of uncertainty that the organization confronts and navigates in? Organizational cognition has an important part into such a perspective and therefore it is introduced in the next subsection.

656

Organizational Cognition Research on cognition in organizations has its roots in the publications of Simon (1947) on Administrative Behavior, and March and Simon (1958) on Organizations. In these publications, the organization was associated with information processing systems whose picture resembles a nexus of cognitive agents and processes organized through lateral and vertical relations. In this perspective, the organization benefits individuals and groups by extending their cognitive limitations to more advanced models of rationality (Simon, 1997a, 1997b). However, the meaning of this perspective has been separated by some researchers in two main streams: the computational and the interpretive approaches (Lant & Shapira, 2001). The computational approach investigates the processes by which the organization manipulates information, and it associates the organization with information processing systems. In such a stream, the emphasis is on information and efficiency. This approach is grounded in cognitive psychology, cognitive science and artificial intelligence. The interpretive approach examines how meaning is created around information in a social context, and it is related to social collectives and knowledge systems. In such a stream, the focus is on knowledge and collectivities. This approach has been grounded in the sociology of knowledge, social psychology of organizations,

The Roles of Cognitive Machines in Customer-Centric Organizations

Figure 2. Uncertainty as lack of cognition

From such a context, this chapter proposes new principles, concepts and features of CustomerCentric Systems (CCS) which configure the new face of the industrial organization in the 21st century. These organizations are emerging in order to pursue higher degrees of cognition and greater capabilities of general information processing and uncertainty management.

Degree of Organizational Cognition social cognition, and, most recently, in knowledge management and organizational learning, whereas this latter subject has also been associated with processes for creating, retaining and transferring knowledge in organizations (Argote, 2007). Most of the perspectives on organizational cognition are placed somewhere in the continuous between such computational and interpretive approaches. In this chapter, the authors give special attention to the computational perspective and they use the metaphor of the organization as information processing systems. In such a perspective, organizational cognition is concerned with the processes which provide agents and organizations with the ability to learn, to make decisions and to solve problems. The main agents of organizational cognition are the participants within the organization and the social networks which they form. In organizations, cognitive processes are supported by their goals, technology and social structure. Moreover, organizational cognition is also influenced by inter-organizational processes and thus by the environment. Therefore, the choice of the organization elements (participants, technology, goals, and social structure), and thus organizational design (Galbraith, 2002), plays a fundamental task in organizational cognition. The cognition of the organization can be represented as a matter of degree whose level depends on the choice of the organization elements. A borader review on organizational cognition is presented in (Nobre et al., 2010; Nobre & Walker, 2011).

In a first perspective, researchers in the field of organizational cognition have associated the concept of cognitive complexity with the degree or level of elaboration in which people, groups and organizations perceive their environment and construct their cognitive maps. In such a case, the degree or level of cognitive complexity can be attributed to the number of hierarchical or vertical levels (or deepness) and the number of horizontal constructs which are integrated into a cognitive map (Calori, Johnson & Sarnin, 1994; Nasser-Carvalho, 2004, 2005); whereas in this association, cognitive maps are viewed as systems (Hall & Fagen, 1956). In a second perspective, cognitive complexity can also be associated with the concept of degree of cognition in the organization or degree of organizational cognition as introduced in (Nobre et al., 2009a, 2010); whereas degree of cognition can be symbolically associated with tangible and intangible measures of processes and representations. Through the participant observation approach, Nobre et al. (2009a: 113-162) presented a case study about an international telecommunications and software business corporation, where they associated the degree of cognition in the organization with levels of organizational process maturity and performance, along with organizational learning results. In a macro view, the level of the organization’s process maturity was defined by the level of elaboration, integration and specification of the technical, managerial and organizational processes, routines and norms (Nobre et al., 2009a: 122-132), which were most based on the Capa657

The Roles of Cognitive Machines in Customer-Centric Organizations

bility Maturity Model (CMM) policies, recommendations and guidelines for software process improvement (Paulk, Weber, Curtis & Chrissis, 1994). In this macro part, the degree of cognition in the organization could be associated with one of the five CMM maturity levels. In a micro view, the organization’s process performance was associated to concepts and measures of customer satisfaction and process quality, whereas these concepts were first socially constructed by a group of software project management and engineering experts in the corporation of study; second, these concepts were explicitly represented through mental models described by IF-THEN linguistic rules; and third, these concepts were mapped into a two-dimensional linguistic phase-plane which indicated the implications of antecedents (i.e. independent constructs or variables) to the consequents of customer satisfaction and process quality (i.e. dependent constructs or variables). In this micro part, the organization’s process performance was associated to a set of quantitative indexes about customer satisfaction and process quality which were calculated through the computational modeling and simulation of the IF-THEN linguistic rules. Through these approaches, the authors achieved qualitative analyses and quantitative measurements which indicated that improvements in the levels of organization process maturity and performance were associated with improvements in the degree of organizational cognition; and also that improvements in organizational learning could be associated with improvements in the degree organizational cognition. Similar methods have been adopted by other researchers who associated organizational performance and productivity gains with practices of organizational learning (Argote, 2007). Therefore, in this chapter, the concept of degree of organizational cognition can be understood as synonymous with cognitive complexity at the organizational level of analysis. In such a case, degree of organizational cognition involves a

658

whole picture about the cognitive processes and representations at the organizational level, and this macro picture is greater than the sum of the individual cognitions.

Human vs. Organizational Cognition Organisms of the ecological system have evolved and improved their abilities and mechanisms for fitness and adaptation in the environment. Among such organisms, the human being is the specie that has found the highest probability to survive, to reproduce, and to continue evolving and developing. Such a predominance of humans is a particular privilege provided by the evolution of their brain, emotional, and cognitive processes (Heyes & Huber, 2000; Simon, 1983). Among the results of such a continuous evolutionary path are their abilities to search information, to organize knowledge, to make decisions, to learn, and to solve complex problems. Humans adapt to the environment, and they also change the environment to their own needs. In such a continuum, humans have been transferring some of their abilities to systems, and most important, to machines and organizations (Nobre et al., 2009a, 2009b). Certainly, one of the main rationales for organizing can be explained by the perspective that organizations benefit individuals and groups by extending their cognitive, physical, temporal, institutional, and spatial limitations (Carley & Gasser, 1999). In such a perspective, while human cognition is part of a natural system, cognition in organizations is part of a symbiosis between natural (human) and artificial systems because it involves the art of design (Simon, 1996). Therefore, the cognitive ability in the organization can be changed and improved through processes of organization change and design. Hence, the degree of cognition in the organization is contingent upon the goals, the social structure, the participants, the technology and the environment of the organization.

The Roles of Cognitive Machines in Customer-Centric Organizations

Organizational Intelligence, Autonomy, Learning, and Complexity Like organizational cognition, definitions of organizational intelligence, autonomy, learning, and complexity are proposed in (Nobre et al., 2009a, 2010; Nobre & Walker, 2011). Nevertheless, they are briefly defined in this subsection.

Organizational Intelligence Intelligence is a general mental ability (Schmidt & Hunter, 2000), which depends on rational and emotional processes (Goleman, 1994). Rational process or rationality is the ability to follow procedures for decision making and problem solving in the pursuit of goals (Simon, 1997a). When rational processes lead individuals to satisfactory (satisfice) outcomes, rationality can be associated with intelligence. Emotional process (Scherer, 1982) is less procedural than rationality and it is less purposeful in the context of achieving goals. However, researchers have shown that emotions play an important part to motivate, to direct, and to regulate actions in the service of goal pursuit (Bagozzi, 1998; Keltner & Gross, 1999; Keltner & Haidt, 1999). When emotional processes lead individuals to excel in life, emotion can be associated with intelligence. Complementarily, while emotion influences cognitive processes such as attention, learning, decision making, and problem solving (Goleman, 1994), cognition is in the service of emotion when interpreting stimuli (Plutchik, 1982) and regulating emotional processes and states. Therefore, intelligence, and in particular, intelligent behavior, depends on cognitive and emotional processes. Organizational intelligence can also be associated with degrees of intelligence in the organization. However, while organizational cognitions are associated with cognitive processes and representations in the organization, organizational intelligence is associated with the degree in which the organization satisfy or satisfice (Simon, 1997b)

its goals and sub-goals. Therefore, the greater the degree of cognition in the organization, the greater is its chance to exhibit intelligent behavior (Nobre et al., 2009a, 2010).

Organizational Autonomy Autonomy is the ability of individuals, groups, and organizations to act through the use of cognition. Autonomous organisms are continuously in the pursuit of intellectual independence and therefore they are continuously attempting to improve their cognitive abilities. Similarly to cognition and intelligence, autonomy is a matter of degree. The degree of autonomy of individuals, groups and organizations improves as much as they interact with the environment by capturing, processing, creating, storing, exchanging and managing new resources. In such a view, organizations with higher degrees of cognition have higher degrees of autonomy (Nobre et al., 2009a, 2010).

Organizational Learning Organizational learning has been associated with the creation and management of knowledge in organizations (Argote, 2007; Dierkes, Antal, Child & Nonaka, 2003). In psychology research, learning is the process of making changes in the individuals’ mind and behavior through experiences along with cognitive, emotional, and environmental influences (Bernstein, Penner, Clarke-Stewart & Roy, 2008; Illeris, 2007; Lefrançoies, 1995; Minsky, 1986; Reed, 1988). In such a process, learning involves acquiring, enhancing, or making changes in one’s knowledge, skills, values, and world views. This work supports this definition and it puts forward the perspective that organizational learning is the process of making changes in the organization’s elements (goals, social structure, technology, and participants) and behavior through experience, cognition, emotion, and environmental influences, for the organization benefits. Such a perspective implies relations on the effect of or-

659

The Roles of Cognitive Machines in Customer-Centric Organizations

ganizational learning on organizational cognition, and vice-versa. On one hand, it is plausible to say that organizational learning affects organizational cognition, and more specifically, the degree of organizational cognition, by changing cognitive processes and representations in the organization. On the other hand, it is also plausible to state that organizational learning depends on organizational cognition, and more specifically, on cognitive processes and representations, for the corroboration of change, and for the creation and management of knowledge in the organization. The process of change in the organization follows mechanisms and models which are mostly based on principles of feedback control, adaptive and learning systems originated in the broad fields of cybernetics and general systems theory (Ashby, 1968; Bertalanffy, 1968; Buckley, 1968; Wiener, 1961). Well-known models of organizational learning include singleloop and double-loop types (Argyris & Schön, 1978) along with meta-learning which concept was introduced in Biggs (1985) to describe the state of being aware of and taking control of one’s own learning. Further studies on the concept of meta-learning and its distinction from deuteron and planned-learning are discussed in Visser (2007); and the use of organizational meta-learning for the construct of dynamic core competencies is presented in (Lei, Hitt & Bettis, 1996). In such a view, cognition is what provides individuals, groups and organizations with the ability to learn. Therefore, organizations with higher degrees of cognition have higher capacity or degree of learning (Nobre et al., 2009a; 2010).

Organizational Complexity This chapter defines the level of complexity of the organization as contingent upon its degree of cognition. Therefore, the complexity of organizations are synonymous with their cognitions which are processes used to solve complex tasks. Hence, the greater the degree of cognition of the organization, the greater is its ability to solve complex tasks (Nobre et al., 2010). 660

Environmental Uncertainty and Complexity Environmental uncertainty can be associated with the level of uncertainty that the organization, groups and participants perceive or sense from the environment (Ducan, 1972). The complexity of the environment is contingent upon the level of uncertainty that it represents to the organization. Similarly, the complexity of a task environment is contingent upon the level of uncertainty that it represents to the organization during task execution and completion. Therefore, it can be asserted that the greater the level of environmental complexity, the greater is the level of environmental uncertainty that the organization confronts and needs to manage.

COGNITIVE MACHINES Initial lines of contribution on the perspectives of cognitive machines in organizations were first touched in (Nobre, 2008; Nobre et al., 2009a, 2009b). Cognitive machines are information processing and knowledge management systems which unify computational and cognitive strengths of humans and computers. They are necessary when we need to extend the reasoning or mental capacity of humans, groups and organizations to more advanced models of cognition. Cognitive machines are agents whose processes of functioning are mainly inspired by human cognition. Therefore, they have great possibilities to present intelligent behavior. When participating in organizations, cognitive machines are agents of organizational cognition and they contribute to improve the degree of cognition, intelligence, autonomy, and learning of the organization. Intensive and extensive research on the design and analysis of cognitive machines in organizations is proposed in (Nobre et al., 2009a, 2009b). The design of cognitive machines comprises theories of cognition and informationprocessing systems, and also the mathematical and

The Roles of Cognitive Machines in Customer-Centric Organizations

theoretical background of Fuzzy Systems (FS), Computing with Words (CW) and Computation Theory of Perceptions (CTP) (Zadeh, 1973, 1999, 2001). This class of machines has the capabilities to carry out complex cognitive tasks in organizations, and in particular the tasks which involve representation and organization of knowledge via concept identification and categorization along with the manipulation of perceptions (percept), concepts and mental models. The ability of these machines to manipulate complex symbols described in the form of words and sentences of natural language provides them with higher levels of information-processing than other symbolicprocessing machines; and according to the theory of levels of processing in cognition (Reed, 1988) these machines can mimic, even through simple models, cognitive processes of humans. Similarly to the definitions of organization intelligence, autonomy, learning, and complexity, it can be stated that the greater the degree of cognition of the machine, the greater is its chance to present intelligent behavior; the greater is its autonomy; and the greater is its ability to learn and to solve complex tasks. The concept of cognitive machines plays an important role in the organizations proposed in this research. These machines participate in the organization and they provide the organization with higher degrees of cognition, intelligence, autonomy, and learning as investigated in (Nobre et al., 2009a, 2009b). The next section demonstrates the application of some of the new features of Customer-Centric Systems and it enhances the roles of cognitive machines, Cognitive Information Systems (CIS) along with the concept of immersiveness in the new Computational Organization Management Networks (COMN).

COMPUTATIONAL ORGANIZATION MANAGEMENT NETWORKS (COMN) This section introduces a new kind of organization that implements the main features of CustomerCentric Systems. It contributes by presenting the definition, the structure and the processes of Computational Organization Management Networks (COMN) as proposed in (Nobre et al., 2009a). COMN are new organizations whose principles of operation are based on the concepts of Hierarchic Cognitive Systems (Nobre, 2008) along with those of Telecommunications Management Networks (ITU-T, 2000). Structured with functional layers and cognitive roles which range from technical and managerial to institutional levels of analysis, and also equipped with operational, managerial and strategic processes, the concept of Computational Organization Management Networks (COMN) plays an important part in the developments of future organizations where cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise. Moreover, this section introduces the concept of immersive systems in order to provide the new organization with the capability of immersiveness.

The Scope of the New Organization Computational Organization Management Networks (COMN) fall in the class of organizations that pursue high degrees of organizational cognition, intelligence, autonomy, and learning, and consequently, high degrees of agility and flexibility, in order to manage high levels of environmental complexity, to operate through intensive mass customization, and to provide customers with immersiveness (Nobre et al., 2008, 2009a). This chapter advocates that such a kind of new organization has to be equipped with high levels of automation in order to pursue the necessary capabilities to govern, to coordinate and to con-

661

The Roles of Cognitive Machines in Customer-Centric Organizations

trol cognitive tasks of technical, managerial and institutional levels in the whole enterprise. Hence, it focuses attention to the conception of organizations of this type. Therefore, the creation of COMN requires intensive investments in information technology, artificial intelligence and knowledge management systems. This section shows the steps of design of such new organizations.

Cognitive Information Systems (CIS) The processes with the new organization are managed by Cognitive Information Systems (CIS): •

Definition 3: Cognitive Information Systems (CIS) are Knowledge Management Systems (KMS) that pursue high degrees of cognition, intelligence, autonomy, and learning. They are particular classes of cognitive machines, and they are designed to participate in the organization by performing cognitive tasks of all levels and by fulfilling managerial roles in all the layers of the whole enterprise (Nobre et al., 2008, 2009a, 2010).

Participation of CIS in the Organization Cognitive Information Systems (CIS) participate in the organization by performing cognitive tasks and by fulfilling roles of technical, managerial, and institutional levels. From this point of view, this chapter identifies four major areas of CIS application in the whole enterprise. These areas are classified into four organizational layers: a. Element Layer: The operational level b. Network Management Layer: The primary managerial level c. Service Management Layer: The secondary managerial level d. Business Layer: The strategic level

662

Functional Layers of the New Organization: Steps of Design Functional layers play the fundamental part in the definition of the structure and processes for the new organization of COMN. Their concepts are based on the definition of Hierarchic Cognitive Systems (HCS) as introduced in (Nobre, 2008) along with the principles of Telecommunications Management Networks (TMN) architectures which have been proposed by International Telecommunication Union (ITU-T); where ITU-T is the designation of the United Nations Specialized Agency in the field of telecommunications (ITU-T, 2000). In the organizational architectures of TMN, agents execute tasks in all hierarchical layers of the organization. Similarly, agent technology (Bradshaw, 1997; Watt, 1997) plays important tasks in the functional layers of the new organization of COMN; where in this chapter, agents are also synonymous with cognitive machines and Cognitive Information Systems (CIS). This subsection proposes four functional layers for the new organization. It also introduces the roles of the agents that participate in the COMN by governing, controlling and coordinating cognitive tasks of all levels in all the layers of the whole enterprise.

Step 1: CIS in the Element Layer: The Operational Level The Element Layer (EL) comprises a Network Element Layer (NEL) and an Element Network Layer (ENL). The former part (NEL) comprises functional elements that work upon an individual basis, and, therefore, each individual element carries its own motives and fulfils micro-roles. The latter part (ENL) comprises a set of interconnected functional elements that work in group, and, therefore, they carry common motives and sub-goals, and they also fulfill micro-roles. In this kind of organization, an element is synonymous with an agent, and an agent is synonymous with

The Roles of Cognitive Machines in Customer-Centric Organizations

a cognitive machine; and thus, a group of interconnected elements is synonymous with a group of agents that has the same meaning of a group of interconnected cognitive machines. Figure 3 illustrates the two parts of an Element Layer (EL), where a(1…n) denotes agents, for n integer. The roles of Cognitive Information Systems (CIS) in the Element Layer (EL) are concerned with the execution of cognitive tasks for operation, control and coordination of individual elements as well as of groups of interconnected elements. These elements, as individuals and groups, participate in the whole organization by performing cognitive tasks of technical, managerial, and institutional levels. Therefore, in this particular case, the CIS provide operational, control and coordinative processes to individual agents and group of agents that participate in the organization. The Element Layer (EL) demands high degrees of cognition, intelligence, autonomy, and learning from the individual machines as well as from the groups of machines. For these requests, the technology of cognitive machines, along with the methodologies of Soft Computing (SC) (Zadeh, 1994), Fuzzy Logic (FL) (Zadeh, 1973), Computing with Words (CW) (Zadeh, 1999), and Computational Theory of Perceptions (CTP) (Zadeh, 2001), play an important part in the conception of Cognitive Information Systems (CIS). Applications at the level of Element Layer (EL) have received some attention, for instance,

Figure 3. NEL as a controller of individual agents a(1…n) and ENL as a controller of a group of integrated agents

by researchers who have developed information and decision-support systems for manufacturing operations through the background of fuzzy logic, neural networks and genetic algorithms (Kusiak, 2000; Monfared & Steiner, 1997; Rao et al., 1993; Wu, 1994). Nevertheless, despite achieving some successful results, these managerial and decisionsupport tools of mathematical and computational background have been constrained by the limitations of cognition, intelligence, autonomy, and learning of the existing machines which are mostly encountered in the organizations of today. The application of these machines in Flexible Manufacturing Cells and Systems (FMS) and their coordination through Computer Integrated Manufacturing (CIM) technology, have reached thresholds and limitations of contributions because of their insufficient degrees of cognition, intelligence, autonomy, and learning (Nobre et al., 2009a, 2009b).

Step 2: CIS in the Network Management Layer: The Primary Managerial Level The united work of individual agents and groups of agents in the Element Layer (EL) forms a set of patterns or clusters which represent the main macro-roles in the organization. Each pattern or cluster is synonymous with a functional network. The Network Management Layer (NML) comprises the set of individual functional networks in the organization; and it is equipped with an organizing system constituted by normative structure, processes, technologies, agents and sub-goals, in order to provide management to each functional network upon an individual basis. Therefore, the NML provides the individual functional networks of the organization with coordination, control and management of processes, operations and information that flows through the clusters of agents and groups of agents that participate in the whole enterprise. Figure 4 illustrates a NML managing individual Functional Networks FN(1…m), for m integer. 663

The Roles of Cognitive Machines in Customer-Centric Organizations

The roles of Cognitive Information Systems (CIS) in the Network Management Layer (NML) is concerned with the effective and efficient use of the NML’s organizing system resources in order to execute cognitive tasks for coordination, control and management of the functional networks upon an individual basis; where, in this case, a functional network is synonymous with a network of agents and also with a network of cognitive machines. In such a perspective, functional networks (and thus networks of cognitive machines) participate in the organization by performing cognitive tasks of technical, managerial and institutional levels; and they fulfill operational, management and strategic roles in the whole enterprise. It is important to emphasize that while Cognitive Information Systems (CIS) participate in the Network Management Layer (NML) by managing each individual functional network in the organization, they participate in the Element Layer (EL) by operating and controlling individual agents and groups of agents that participate in the functional networks of the organization. Therefore, the NML comprises the management of the EL in the organization. The performance of managerial roles in the organization is contingent upon the capabilities of the managers and also upon the capabilities of the individuals and groups that the managers supervise. Therefore, it can be stated that the higher

Figure 4. NML as the manager of individual FN(1…m)

664

the degree of cognition of Cognitive Information Systems (CIS), the higher is their capability to manage Functional Networks (FN) in the organization; and that the higher the degree of cognition of the elements of a Functional Network (FN), the higher is the capability of CIS to manage the FN.

Step 3: CIS in the Service Management Layer: The Secondary Managerial Level The set of functional networks in the organization forms vertical and horizontal processes and involves sub-goals and goals, where sub-goals represent means for the achievement of more complex goals. Therefore, a managerial system is needed in order to coordinate, to control and to mediate all the operations, processes and information that flow between the functional networks in the organization. The Service Management Layer (SML) comprises the set of functional networks in the organization; and it is equipped with an organizing system constituted by normative structure, processes, technologies, agents, goals and subgoals, in order to provide management for the set of functional networks. Therefore, the SML provides the organization with a managerial system with the capability to coordinate, to control, to integrate, and to mediate all the operations, processes and information that flows between the functional networks in the whole enterprise. Figure 5 illustrates an SML managing a set of integrated Functional Networks FN(1…m). The roles of Cognitive Information Systems (CIS) in the Service Management Layer (SML) is concerned with the effective and efficient use of the SML’s organizing system resources in order to execute cognitive tasks of integration, coordination, control and thus management of the relations, operations, processes and information that flows through and between the functional networks in the organization; where, in this case, the set of functional networks is synonymous with the set of networks of agents and consequently with the

The Roles of Cognitive Machines in Customer-Centric Organizations

Figure 5. SML as the manager of integrated FN(1…m)

greater contributions in the proportion of the continuous advancements in Cognitive Information Systems (CIS) of high degrees of cognition, intelligence, autonomy, and learning; and thus CIS will play an important role in the SML of new organizations.

Step 4: CIS in the Business Management Layer: The Strategic Level set of networks of cognitive machines in the organization. In such a domain, each functional network can be synonymous with a cluster of services, or in short, a service. Therefore, the Cognitive Information Systems (CIS) in the Service Management Layer (SML) can also be viewed as agents of management of the whole services in the organization. It is important to emphasize that while CIS participate in the Service Management Layer (SML) by managing the operations, processes and information between all functional networks in the organization, they participate in the Network Management Layer (NML) by managing each functional network upon an individual basis. Therefore, the SML comprises the management of the NML in the organization. Applications at the SML and NML have received some contributions with the advances in Enterprise Resources Planning and Management Systems (EPR) that emerged from the 1970’s. ERP are classes of information technology and management systems which are applied to, and implemented in the whole organization with the purposes of integration, control and automation of data, information and processes. Examples of areas of application of ERP systems include: Manufacturing, Supply Chain, Financials, Customer Relationship Management (CRM), Human Resources, Warehouse Management and Decision Support System. Applications in the level of the Service Management Layer (SML) will receive

The Business Management Layer (BML) comprises all the operations, management processes, strategies and services of the previous layers (i.e. the EL, NML and SML respectively); and it is equipped with an organizing system constituted by normative structure, processes, technologies, agents and goals, in order to provide the organization with capabilities to manage the environment. More specifically, the BML provides the enterprise with a managerial system with the capability to coordinate, to control and to mediate the operations, processes and information between the organization and the environment. Figure 6 illustrates the role of the BML in the organization. The roles of Cognitive Information Systems (CIS) in the Business Management Layer (BML) are less obvious and less present in the organizations of today. It is concerned with the effective and efficient use of the BML’s organizing system resources in order to execute cognitive tasks for coordination, control and thus management of the relations, operations, processes and information in between the organization and the environment. To enhance this application, this chapter presents the concept of immersiveness which idea was first spoken in (Nobre & Steiner, 2002), and further developed in (Nobre et al., 2009a).

The Concept of Immersiveness It was stated in this research that organizations have to be equipped with structure, processes, goals, agents and technologies which are able to

665

The Roles of Cognitive Machines in Customer-Centric Organizations

provide them with the capability to pursue high levels of immersiveness, where: •

Definition 4: Immersiveness represents the ability of the organization to interact with agents of the market (either humans or machines) in a friendly way, by immersing them into the organization’s operations through approaches such as virtual reality, simulation or via real world protocols; and it aims to satisfy customers by capturing their exact needs, by customizing and managing the design, engineering and production of their goods and services, and by delivering their products with efficacy and efficiency.

More specifically, either manufacturing or service organizations, they can immerse their customers by providing them with the scope to interact with some of the life cycle stages of their processes of design, engineering and production, including those processes of requirements analysis, product design, test, prototyping, demand specification, volume and variety choice. Under this perspective, virtual reality will play an important task in the customer immersiveness; the technologies of cognitive information systems and cognitive machines will provide important contributions in the execution of cognitive tasks such as pattern recognition and vision, natural language processing, decision-making, problemFigure 6. BML as the manager that mediates between the organization and the environment

solving, learning, and management; additionally, the internet will play an important part in the connection of customers into the new organization. This perspective is illustrated in Figure 7 and it is assumed that such an illustrative immersive system can be configured to provide customers with different levels of access and interaction to the technical and managerial operations of the processes of design, engineering and production in the organization. The dotted lines symbolize the internet which connects customers within the organization; and the continuous lines denote the system operational levels that clients can interact with, in order to capture customers’ exact needs and even emotions, to customize and to manage the design, engineering and production of their goods and services.

Definition of COMN •

Definition 5: Computational Organization Management Networks (COMN) are organizations whose structure, processes, participants, goals and technologies are designed according to the concepts of Functional Layers which include Element Layer, Network Management Layer, Service Management Layer and Business Management Layer. COMN pursue high degrees of organizational cognition and their main participants subsume Cognitive Information Systems (CIS) and cognitive machines.

Structure and Processes of COMN Figure 8 illustrates the structure of Computational Organization Management Networks (COMN) which is composed by Element Layer (EL), Network Management Layer (NML), Service Management Layer (SML) and Business Management Layer (BML) respectively.

666

The Roles of Cognitive Machines in Customer-Centric Organizations

Figure 7. Illustration of an immersive system

CONCLUSION This chapter is the result of the analyses of past and current manufacturing organizations through three complementary perspectives of technology, management and organizational systems theory, as researched in (Nobre et al., 2009a, 2009c); whereas it was found that the convergence of manufacturing organizations to the new features of Customer-Centric Systems (CCS) is contingent upon the continuous growth in the level of environmental complexity. The chapter emphasized that Customer-Centric Systems (CCS) configure the new technological, managerial and organizational faces which industrial organizations need to have if they want to manage higher levels of environmental complexity in the 21st century. The contributions proposed in this research were motivated by the principle of incompatibility, and the non-equilibrium state, existing between the continuous growths in the level of environmental complexity and the insufficient cognitive capacity of current manufacturing organizations. Therefore, this chapter focused on the general picture of organizations pursuing high degrees

of cognition in order to improve their capabilities for information processing and uncertainty management. It assumed that improvements in the degree of organizational cognition can lead the organization to achieve higher degrees of flexibility and agility, to operate through higher levels of mass customization, and to provide customers with immersiveness. In its broader sense, it assumed that such improvements can extend the capability of the organization to manage higher levels of environmental complexity. In such a context, this chapter contributed by presenting the concepts of Customer-Centric Systems (CCS) and Computational Organizational Management Networks (COMN). COMN are new computational organizing models with the capability to implement the features of CCS. The main contributions and further research are highlighted in the next paragraphs.

On Cognitive Machines, Organizations and the Environment Cognitive machines are agents of organizational cognition and they contribute to improve the degree of cognition of the organization. Consequently, improvement in the degree of organizational cognition contributes to manage the level of environmental complexity and uncertainty that the organization confronts.

On Computational Organization Management Networks Computational Organization Management Networks (COMN) implements the new features of Customer-Centric Systems. COMN are organizations whose structure, processes, participants, goals and technologies are designed according to the concepts of Functional Layers which comprise Element Layer, Network Management Layer, Service Management Layer and Business Management Layer. COMN pursue high degrees of organizational cognition and their main partici-

667

The Roles of Cognitive Machines in Customer-Centric Organizations

Figure 8. Structure of computational organization management networks (COMN)

pants comprise Cognitive Information Systems (CIS) and cognitive machines. Such a kind of new enterprise will play a fundamental part in the processes of engineering, production, logistics and management of goods and services along with the processes of management of transactions, business and electronic commerce in the future organizations and markets. According to Nobre et al. (2009a), COMN will be legally supported with nexus of contracts that assign the responsibilities to, and define agreements between, the organization and the designer of the cognitive machines (and cognitive information systems) which are the main participants in the layers of the whole organization. The roles of these new participants will be defined in the normative structure of the organization. The creation of COMN requires intensive investments in information technology, artificial intelligence and knowledge management systems. This chapter introduced the steps of design of such new organizations.

668

Nevertheless, some implications of Computational Organizational Management Networks (COMN) must be further investigated. COMN may also be used by some corporations and power-holders for their own benefits, who want to reinforce and to continue supporting the contemporary society, and a political and economic model of maximization of production and consumption which has generated cultural alienation and intense materialism. These have, in turn, destroyed environmental resources and eroded the values and social conditions of humanity.

Further Extensions On Cognitive Machines and Emotions The topic of machines with emotions and emotional processes in organizations was left for further research. However, it deserves some comments due to its importance in the literature. Whether machines should exhibit emotional behavior, and whether they are able to have emotions or not, are

The Roles of Cognitive Machines in Customer-Centric Organizations

controversial topics among the researchers of artificial intelligence, cognition and social sciences. By assuming that machines may indeed be able to have emotional processes and emotional behavior, the question of whether emotions are important to machines or not depends on the motivations of their designers and upon the environment with which they relate. On the one hand, machines with emotions, or emotional machines, might form better relations and social networks with humans in organizations than other machines. In such a view, machine emotion would be relevant for researchers on organizational behavior. On the other hand, machines with emotions might have their own motives and might represent additional agents of dysfunctional conflicts in organizations. In such a view, machine emotion would be a problem for researchers of rational theories. Among the institutions which have been researching the field of emotional machines include The MIT Artificial Intelligence Laboratory at Massachusetts (Breazeal, 2000).

On Cognitive Machines vs. Humans in Organizations Are cognitive machines better agents of organizational cognition and organizational learning than humans? Are they better agents of organization performance and productivity than humans? Such questions rely on the statement that: if we assume that the cognitive roles in organizations have performance and outcomes which can be attributed to either humans or machines, without any distinction, then we are ready to consider machines as participants within the organization similarly to people. This perspective involves a rational comparison between machines and human’s performance if we assume that they compete for the same roles in the organization. Such questions need to be further investigated in order to derive conclusions about the economic, political, social and technological implications of cognitive machines for the society (Nobre et al., 2009a).

Challenges and the Future of the Industrial Organization While the characteristics of the elements of the organization will change, evolve and develop continuously towards higher levels of cognition and complexity, the purpose of existence of the organization will remain the same or will not change in the same proportion of its elements (Nobre et al., 2009a). The former part, which is concerned with the elements of the organization, will move towards high levels of automation, and it will include machines with high degrees of cognition, mainly in those areas at upper layers and levels of the organization; and thus they will provide organizations with more capabilities of computational capacity along with knowledge and uncertainty management. Therefore, new organizations of this kind will be able to operate in, and to manage higher levels of environmental complexity and uncertainty than organizations of today. These transformations towards new organizations will have implications for the society and this is a topic of further research (Nobre et al., 2008, 2009a, 2009b). The latter part, which is concerned with the purpose and the existence of organizations, will remain the same and for sure will not change in the same proportions to the evolutions in the organization elements. This is because the individual motives and the organizational goals which are pursued by human kind will not change over time into the political, economical and social facets of this society. One day, perhaps not so far in the 21st century, worldwide organizations and their executives will have the ability to perceive, to sense, to decide and to act based on new models of organizing and management thought which are grounded in concepts of systemic sustainability; whereas these new models should require the reconciliation of environmental, social and economic demands—the “three pillars” of sustainability. It is in such a new context that organizations and their participants will be challenged to decide on whether they are ready to create competitive advantage without 669

The Roles of Cognitive Machines in Customer-Centric Organizations

affecting the balance and equilibrium of such a triad. It raises the question about the endurance and survival of the human species.

REFERENCES Argote, L. (2007). Organizational learning: Creating, retaining and transferring knowledge. Springer. Argyris, C., & Schön, D. A. (1978). Organizational learning: A theory of action perspective. Addison-Wesley. Ashby, W. R. (1968). Principles of the SelfOrganizing System. In Buckley, W. (Ed.), Modern Systems Research for the Behavioral Scientist (pp. 108–118). Aldine Publishing Company. Bagozzi, R. P., Baumgartner, H., & Pieters, R. (1998). Goal-directed Emotions. Cognition and Emotion, 12(1), 1–26. doi:10.1080/026999398379754 Bernstein, D. A., Penner, L. A., Clarke-Stewart, A., & Roy, E. J. (2008). Psychology (8th ed.). Houghton Mifflin Company. Biggs, J. B. (1985). The role of meta-learning in study process. The British Journal of Educational Psychology, 55, 185–212. doi:10.1111/j.2044-8279.1985.tb02625.x Bradshaw, J. M. (1997). Software agents. AAAI Press. Breazeal, C. (2000). Sociable Machines: Expressive Social Exchange between Humans and Robots. Sc.D. Dissertation, Department of Electrical Engineering and Computer Science, MIT. Buckley, W. (1968). Modern systems research for the behavioral scientist. Aldine Publishing Company.

670

Calori, R., Johnson, G., & Sarnin, P. (1994). CEO’s cognitive maps and the scope of the organization. Strategic Management Journal, 15(6), 437–457. doi:10.1002/smj.4250150603 Carley, K. M., & Gasser, L. (1999). Computational Organizational Theory. In Weiss, G. (Ed.), Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence (pp. 299–330). The MIT Press. Daft, R. L., & Noe, R. A. (2001). Organizational Behavior. Harcourt, Inc. Dierkes, M., Antal, A. B., Child, J., & Nonaka, I. (2003). Handbook of Organizational Learning and Knowledge. Oxford University Press. Ducan, R. B. (1972). Characteristics of Organizational Environments and Perceived Environmental Uncertainty. Administrative Science Quarterly, 17(3), 313–327. doi:10.2307/2392145 Galbraith, J. R. (1973). Designing Complex Organizations. Addison-Wesley. Galbraith, J. R. (1977). Organization Design. Addison-Wesley. Galbraith, J. R. (2002). Designing Organizations - An executive guide to strategy, structure, and process. Jossey-Bass. Goleman, D. (1994). Emotional Intelligence: Why it can matter more than IQ. Bantam Books. Hall, A. D., & Fagen, R. E. (1956). Definition of System. In W. Buckley (Ed.), Modern Systems Research for the Behavioral Scientist: 81-92. Aldine Publishing Company. Heyes, C., & Huber, L. (2000). The Evolution of Cognition. The MIT Press. Hitt, M. A., Ireland, R. D., & Hoskisson, R. E. (2008). Strategic Management: Competitiveness and Globalization, Concepts and Cases. SouthWestern College Pub.

The Roles of Cognitive Machines in Customer-Centric Organizations

Illeris, K. (2007). How We Learn: Learning and non-learning in school and beyond. Routledge. ITU-T. (2000). Principles for a telecommunications management network. Recommendation M.3010. International Telecommunication Union. Keltner, D., & Gross, J. (1999). Functional Accounts of Emotions. Cognition and Emotion, 13(5), 467–480. doi:10.1080/026999399379140 Keltner, D., & Haidt, H. (1999). Social Functions of Emotions at Four Levels of Analysis. Cognition and Emotion, 13(5), 505–521. doi:10.1080/026999399379168 Kusiak, A. (2000). Computational Intelligence in Design and Manufacturing. John Wiley & Sons, Inc. Lant, T. K., & Shapira, Z. (2001). Organizational Cognition: Computation and Interpretation. Lawrence Erlbaum Associates. Lee, G. H. (1998). Designs of Components and Manufacturing Systems for Agile Manufacturing. International Journal of Production Research, 4(36), 1023–1044. doi:10.1080/002075498193507 Lefrançoies, G. (1995). Theories of Human Learning. Brooks Cole Publishing Company. Lei, D., Hitt, M. A., & Bettis, R. (1996). Dynamic Core Competences through Meta-Learning and Strategic Context. Journal of Management, 22(4), 549–569. doi:10.1177/014920639602200402 March, J. G., & Simon, H. A. (1958). Organizations (1st ed.). John Wiley & Sons, Inc. Milgrom, P., & Roberts, J. (1992). Economics, Organizations & Management. Prentice-Hall Inc. Minsky, M. (1986). The Society of Mind. Picador. Monfared, M. A. S., & Steiner, S. J. (1997). Emerging Intelligent Manufacturing Systems. International. Journal of Flexible Automation and Integrated Manufacturing, 5, 151–170.

Nasser-Carvalho, L. F. (2004) Cognition in Organizations: Cognitive Complexity and Its Impacts on Organizational Performance. MSc Dissertation. Getulio Vargas Foundation (FGV) / School of Management, Sao Paulo-SP, Brazil (in Portuguese). Nobre, F. S. (2008). Cognitive Machines in Organizations: Concepts and Implications. Germany: VDM-Verlag Publishing. Nobre, F. S., & Steiner, S. J. (2002) Beyond the Thresholds of Manufacturing: Perspectives on Management, Technology and Organizations. Proceedings of the IEEE International Engineering Management Conference (pp. 788-793). Cambridge-UK. Nobre, F. S., Tobias, A. M., & Walker, D. (2009a) Organizational and Technological Implications of Cognitive Machines: Designing Future Information Management Systems. New York: Information Science Reference, IGI Global. Nobre, F. S., Tobias, A. M., & Walker, D. (2009b). The Impact of Cognitive Machines in Complex Decisions and Organizational Change. Journal of AI & Society: Springer, 24(3), 365–381. Nobre, F. S., Tobias, A. M., & Walker, D. (2009c). The Pursuit of Cognition in Manufacturing Organizations. Journal of Manufacturing Systems: Elsevier, 27(3), 145–157. Nobre, F. S., Tobias, A. M., & Walker, D. (2010). A New Contingency View of the Organization: Managing Complexity and Uncertainty through Cognition. Brazilian Administration Review, 7(4), 379–396. doi:10.1590/S180776922010000400005 Nobre, F. S., & Walker, D. (2011) A Dynamic Ability-based View of the Organization. International Journal of Knowledge Management, 7(2):86-101. DOI:10.4018/IJKM. ISSN:1548-0666.

671

The Roles of Cognitive Machines in Customer-Centric Organizations

Paulk, W. Curtis & Chrissis (1994) The Capability Maturity Model: Guidelines for Improving the Software Process. Addison-Wesley.

Simon, H. A. (1982b). Models of Bounded Rationality: Behavioral Economics and Business Organization (Vol. 2). MIT Press.

Pine, B. J. (1999). Mass Customization: The New Frontier in Business Competition. Harvard Business School.

Simon, H. A. (1983). Reason in Human Affairs. Stanford University Press.

Plutchik, R. (1982). A psychoevolutionary theory of emotions. Social Sciences Information. Information Sur les Sciences Sociales, 21, 529–553. doi:10.1177/053901882021004003 Porter, M. E. (1998). Competitive Advantage: Creating and Sustaining Superior Performance. The Free Press. Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91. Rao, M. (1993). Integrated Distributed Intelligent Systems in Manufacturing. Chapman & Hall. Reed, S. K. (1988). Cognition: Theory and Applications (2nd ed.). Brooks-Cole Publishing Company. Scherer, K. R. (1982). Emotion as a process: Function, origin, and regulation. Social Sciences Information. Information Sur les Sciences Sociales, 21, 555–570. doi:10.1177/053901882021004004 Schmidt, F. L., & Hunter, J. E. (2000). Select Intelligence. In Locke, E. A. (Ed.), The Blackwell Handbook of Principles of Organizational Behavior (pp. 3–14). Blackwell Publishers Ltd. Scott, W. R. (1998). Organizations: Rational, Natural, and Open Systems. Prentice Hall, Inc. Simon, H. A. (1947). Administrative Behavior: A Study of Decision-Making Processes in Administrative Organization. New York: Macmillan. Simon, H. A. (1982a). Models of Bounded Rationality: Economic Analysis and Public Policy (Vol. 1). MIT Press.

672

Simon, H. A. (1996). The Sciences of the Artificial (3rd ed.). MIT Press. Simon, H. A. (1997a). Models of Bounded Rationality: Empirically Grounded Economic Reason (Vol. 3). MIT Press. Simon, H. A. (1997b). Administrative Behavior: A Study of Decision-Making Processes in Administrative Organizations. The Free Press. Toni, A., & Tonchia, S. (1998). Manufacturing Flexibility: A Literature Review. International Journal of Production Research, 6(36), 1587– 1617. doi:10.1080/002075498193183 Visser, M. (2007). Deutero-Learning in Organizations: A Review and A Reformulation. Academy of Management Review, 32(2), 659–667. doi:10.5465/AMR.2007.24351883 Von Bertalanffy, L. (1968). General system theory: Foundations, development, and applications. Allen Lane. Watt, S. N. K. (1997) Artificial Societies and Psychological Agents. In Nwana and Azarmi (Ed.), Software Agents and Soft Computing: Towards Enhancing Machine Intelligence (pp. 27-41). Springer. Wiener, N. (1961). Cybernetics or control and communication in the animal and the machine (2nd ed.). MIT Press. doi:10.1037/13140-000 Wu, B. (1994). Manufacturing Systems Design and Analysis: Context and Techniques (2nd ed.). Chapman & Hall.

The Roles of Cognitive Machines in Customer-Centric Organizations

Zadeh, L. A. (1973). Outline of a New Approach to the Analysis of Complex Systems and Decision Process. IEEE Transactions on Systems, Man, and Cybernetics, 3(1), 28–44. doi:10.1109/ TSMC.1973.5408575 Zadeh, L. A. (1994). Soft Computing and Fuzzy Logic. IEEE Software, (November): 48–56. doi:10.1109/52.329401 Zadeh, L. A. (1999). From Computing with Numbers to Computing with Words – From Manipulation of Measurements to Manipulation of Perceptions. IEEE Transactions on Circuits and Systems, 45(1), 105–119. Zadeh, L. A. (2001). A New Direction in AI: Toward a Computational Theory of Perceptions. AI Magazine, (Spring): 73–84.

ADDITIONAL READING Alavi, M., & Leidner, D. E. (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. Management Information Systems Quarterly, 25(1), 107–136. doi:10.2307/3250961 Ichijo, K., & Nonaka, I. (2006). Knowledge Creation and Management: New Challenges for Managers. Oxford University Press.

KEY TERMS AND DEDINITIONS Cognitive Information Systems (CIS): Are Knowledge Management Systems (KMS) that pursue high degrees of cognition, intelligence, autonomy, and learning. They are particular classes of cognitive machines, and they are designed to participate in the organization by performing cognitive tasks of all levels and by fulfilling managerial roles in all the layers of the whole enterprise (Nobre et al., 2008, 2009a, 2010).

Cognitive Machines: Are special classes of Information Technology (IT) and Knowledge Management Systems (KMS). They operate based on, but not limited to, one or more principles among electrical, mechanical, analogue, digital, optical, biological-natural, hybrid and artificial cognitive-neural signals and processes. Their cognitive abilities unify strengths of humans and computers for general information processing. Cognitive machines are necessary when we need to extend the computational capacity of humans, groups and organizations to more advanced models of cognition. Cognitive machines are agents whose processes of functioning are mainly inspired by human cognition. Therefore, they have great possibilities to present intelligent behavior. When participating in organizations, cognitive machines are agents of organizational cognition and they contribute to improve the degree of cognition in the organization (Nobre et al., 2009a, 2009b). Competitive Advantage: A position that a firm occupies in its competitive environment and it also represents the organization’s capability to create superior value for its customers and superior profits for itself (Porter, 1998). Computational Organization Management Networks (COMN): Are organizations whose structure, processes, participants, goals and technologies are designed according to the concepts of Functional Layers which include Element Layer, Network Management Layer, Service Management Layer and Business Management Layer. COMN pursue high degrees of organizational cognition and their main participants subsume Cognitive Information Systems (CIS) and cognitive machines (Nobre et al., 2009a, 2009c). Core Competencies: Are capabilities which are valuable and unique from a customer’s point of view, and also inimitable and non-substitutable from a competitor’s point of view (Prahalad & Hamel, 1990; Hitt, Ireland & Hoskisson, 2008). Core competencies can represent a set of tacit and collective knowledge which is developed through learning processes and which provides the organi-

673

The Roles of Cognitive Machines in Customer-Centric Organizations

zation with particular strengths and superior value relative to other organizations. They are sources of innovation, customer benefits and sustainable competitive advantage (Lei, Hitt & Bettis, 1996). Customer Centric Systems (CCS): Represent new organizing models of production that pursue high degrees of organizational cognition in order to manage high levels of environmental complexity, to operate through intensive mass customization processes, and to provide customers with immersiveness. Immersiveness: Represents the ability of the organization to interact with agents of the market (either humans or machines) in a friendly way, by immersing them into the organization’s operations through approaches such as virtual reality, simulation or via real world protocols; and it aims to satisfy customers by capturing their exact needs, by customizing and managing the design, engineering and production of their goods and services, and by delivering their products with efficacy and efficiency (Nobre et al., 2009a, 2009c).

674

Manufacturing Organization: Are synonymous with industrial organizations; which are classes of organizations that satisfy the concept of open-rational systems (Nobre et al., 2009a; Scott, 1998) and also the perspective of economic organizations (Milgrom & Roberts, 1992). They are highly formalized organizations that pursue specific goals, innovation and sustainable competitive advantage. They produce goods and services. Organization Elements: The elements of the organization include goals, social structure, technology, and the participants in the organization (Scott, 1998: 17-23). Sustainable Competitive Advantage: The organization’s competitive advantage becomes sustainable when its value evolves with basis on the strategic resources management along with the development of dynamic core competencies (Lei, Hitt & Bettis, 1996).

675

About the Contributors

Farley S. Nobre (PhD, MSc, BSc) is Professor at the School of Management of Federal University of Parana, Brazil. His research interests include organizations, knowledge management systems, innovation and sustainability. He received his PhD at The University of Birmingham (UK) with thesis On Cognitive Machines in Organizations, and he participated in the ARMMS project. He was Guest Researcher with the Institute of Organization Theory and the Artificial Intelligence Research Group of the Humboldt University of Berlin, and he participated in the Socionics project. With the multinational NEC he worked in the areas of software process improvement. He received the 1998 NEC Industrial Honor Prize for his contributions in the areas of innovation and quality. Dr. Nobre has authored international books, chapters and papers in journals and conferences worldwide. He is first author of “(Nobre, Tobias & Walker, 2009) Organizational and Technological Implications of Cognitive Machines: Designing Future Information Management Systems, IGI Global, USA.” He is member of SERVAS (a voluntary worldwide institution in support of peace and multi-cultural integration). David S. Walker is Senior Teaching Fellow at the Business School of The University of Birmingham UK, where he has taught since 1995. Previous to this he was Professor of Marketing, Head of the Marketing Department and Director of Business Research at Wolverhampton Business School. He commenced his academic career at Aston Business School where he completed his doctorate in marketing as a Foundation for Management Education Research Fellow. He has throughout his professional life founded and managed several extensive companies in the industrial cleaning and chemical industries, besides current appointments as an external examiner at the Chartered Institute of Marketing, Southampton Business School, Westminster Business School, Northampton Business School and Brighton Business School. He has published extensively in numerous business and management journals both individually and in co-authorship with Dr. Andrew Tobias and Dr. Farley Nobre. Robert J. Harris is Associate Director of the Institute for Innovation and Enterprise at the University of Wolverhampton (UK). He has provided consultancy support to over 500 organisations since 1993, working with Banks, Business Link and Regional Development Associations. He currently manages all of the University of Wolverhampton Business School’s Knowledge Transfer Programmes. In 2007 he was presented the Lord Stafford Knowledge Transfer Champion Award in recognition of his work with small and large businesses both in the UK and overseas. He has managed a number of businesses over the last 20 years. Dr. Harris’s research has focused on knowledge transfer and in particular the

About the Contributors

development of capabilities and innovation within the SME sector. His specialist academic areas are International Business Development and Small Business Marketing and he regularly lectures in these areas in the UK, Europe and S.E.Asia. He is currently external examiner at University of Northampton. *** Nelson Guedes de Alcântara is an Associate Professor of DEMa - UFSCar and Executive Director of the Center for Materials Characterization and Development – CCDM. He was hired by the University in 1976 when he finished his course in Materials Engineering. In 1978 he completed his master’s degree in Mechanical Engineering from the University of Campinas in 1982 and obtained his PhD from the University of Cranfield, England. Since 1982, he established the laboratory for teaching and research in welding in DEMa, and since 1991 he worked in the laboratories and Materials Characterization of the CCDM. In 2008 he conducted his postdoctoral studies at Michigan State University in Management of Technological Innovation, and in 2009 he received the Executive Certificate in Strategy and Innovation from MIT / Sloan School of Management, both in the United States. He is currently Vice President of ABM - Brazilian Association of Metallurgy and Materials and Chief Editor of the Book Collection Metallurgy and Materials, ABM. Thomas Andersson is Professor of International Economics and Industrial Organisation at Jönköping International Business School since 2004. From 2004 to 2009 he served as President of Jönköping University. Andersson holds several other international board and advisory positions in Europe, Asia and the Middle East. Among these, he is Senior Advisor of Science, Technology and Innovation Policy in the Sultanate of Oman, member of two expert groups of the European Commission, Vice Chairman of division XI of the Royal Swedish Academy of Engineering Science (IVA) on Education and Research Policy, board member of the Swedish Programme on ICT in Developing Regions (SPIDER), and serves on the Steering Committee of the Global Forum. Andersson was previously deputy director of science technology and industry at the OECD, where he headed the technology part of the OECD Jobs Study and co-coordinated the OECD growth study. He has also been assistant under-secretary in the Ministry of Industry and Commerce in Sweden. Andersson graduated in 1983 in Economics at Stockholm School of Economics where he earned a PhD in 1989 and was appointed Associate Professor in 1993. He has been published widely on international economics and industrial organisation and has been a visiting fellow at Harvard University, Bank of Japan, Hitotsubashi University and the University of Sao Paulo. Oihana Valmaseda Andia is an Assistant Professor of Marketing at the Basque Country University and an Assistant Researcher at the Institute for Advanced Social Studies, which belongs to the Spanish National Research Council. Her research interests include new product and process development, industry-university collaboration for innovation and academic entrepreneurship. She has taken part in various R&D projects. Glauco Arbix is Full Professor of the Department of Sociologyof the University of São Paulo (USP). He is a member of (Brazilian) National Council of Science and Technology (CCT) and General Coordinator of the Observatory for Innovation of the Institute for Advanced Studies at USP. He is President of the (Brazilian) Institute of Applied Economic Research (IPEA, 2003-2006), General Coordinator of the

676

About the Contributors

Center for Strategic Affairs of the Presidency (NAE, 2003-2006), a member of the Group of Advisers of the United Nations Development Programme (UNDP / UN, 2006 -2009) and Fulbright New Century Scholar (2009-2010). He is a Professor of the Department of Political Science, UNICAMP (1996-1997) and Fundação Getúlio Vargas (FGV-SP, 1995). Theodora Asimakou is a Senior Lecturer in Organization Studies at London Metropolitan Business School, UK. She has a PhD in Management from Manchester Business School. She has researched and consulted in a number of projects on management practices, in the areas of CSR, Organizational Knowledge, Learning, and Innovation, and Organizational Change for academic and business purposes in the UK and Greece. Her research interests lie in the area of organizational discourses, and organizational knowledge and innovation management; in particular how various and transforming concepts and practices affect the workplace. Mário Otávio Batalha graduated in Chemical Engineering and MSc in Production Engineering from Universidade Federal de Santa Catarina (Brazil). He holds a Doctorate in Genie des Systemes Industriels - Institut National Polytechnique de Lorraine (France). He is Ad hoc consultant to the (Brazilian) National Council for Scientific and Technological Development (CNPq), FAPESP, FINEP, CAPES; a Member of the Technical Chamber of Foods - CTA of the (Brazilian) National Agency for Sanitary Vigilance; Associate Professor III at the Federal University of São Carlos; and Chief Editor of the Book Collection (2004-2009) of the Brazilian Production of Production Engineering. Rachel Bocquet is Assistant Professor of Economics at the University of Savoy, France. Her field of research is centered on the determinants of innovation in small and medium-sized firms. She is also currently investigating the effects of cluster membership on the performance of SMEs. She has published several articles in books and international journals. Sebastien Brion is Assistant Professor at the Institute of Management of the University of Savoy, France, where he mainly teaches the Management of Innovation and Information Systems. He is the Director of the Master Management and Information Technology. His research deals with the explanatory factors of innovation process performance and with the organizational forms facilitating innovation. Michael Brown is Professor of Corporate Reputation and Strategy at Birmingham City Business School and Head of the Centre for Corporate Reputation and Strategy He holds his PhD from York University. For almost 20 years he has headed the research into Britain’s Most Admired Companies (BMAC) survey, published annually in the Economist and Management Today, and the source of numerous academic journal articles. He has been published in British Journal of Management, Long Range Planning, The Service Industries Journal and Measuring Corporate Performance. He is also the co author along with Paul Turner of The Admirable Company in 2008. His industrial experience was gained in the United States. María Catalina Ramírez Cajiao holds a PhD in Management, Economics and Industrial Engineering from the Politecnico di Milano, a MSc in Industrial Engineering from the Universidad de los Andes, and a BSc in Industrial Engineering from the Pontificia Universidad Javeriana. At present, she works as an

677

About the Contributors

Associate Professor at the School of Engineering at the Universidad de los Andes and is the President of Engineers without Borders in Colombia (ISF Colombia). Helio Gomes de Carvalho, Dr., holds a Doctorate degree in Industrial Engineering from the Federal University of Santa Catarina (UFSC), Brazil. He is currently a professor at the Federal Technological University of Paraná (UTFPR), Brazil, where he has advised over 25 graduate students of the Innovation and Technology Graduate Program. He is the lead researcher of the Innovation and Technology Management Group at UTFPR and his research includes Innovation, R&D and Project Management, Competitive intelligence and Strategic management. Luiz Caseiro is a Graduate Student in Sociology at University of São Paulo (USP) and has a Bachelor degree in Social Sciences at the same institution. He has research experience in Sociology of Development, working mainly with the following themes: public policy, multinationals, innovation, emerging markets and socio-economic development. He is currently a researcher at the Observatory for Innovation and Competitiveness of the Institute of Advanced Studies at USP, Brazil. Gregorio Martín de Castro, Dr., is Associate Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain). He has several years of research experience at CIC Spanish Knowledge Society Research Centre, he holds an Expert Diploma in Intellectual Capital and Knowledge Management from INSEAD (France), and he was a Post-Doctoral Research Fellow at Harvard University during 2004–2005. He is author and co-author of several papers concerning Resource-Based View, Intellectual Capital and Knowledge Management. Jason G. Caudill holds a PhD in Instructional Technology as well as a BS in Business Administration and an MBA. He currently serves as an Assistant Professor of Business at Carson-Newman College in the state of Tennessee, USA. Dr. Caudill’s research interests include technology integration, technology management, and online education. Steven Cavaleri has co-authored five books on systems thinking, knowledge management and organizational learning. Steven is former editor of The Learning Organization Journal. He is also former president of The Knowledge Management Consortium International and co-founder of KMCI Press imprint of Elsevier Publishing. Dr. Cavaleri holds a PhD from Rensselaer Polytechnic Institute (USA). He was also a Visiting Scholar in the Learning Center at MIT’s Sloan School of Management. Steven has consulted for many well-known companies, such as IBM and Stanley Tools. He is professor of management at Central Connecticut State University (USA). Steven is also a certified Systems Integrator by the Institute of Industrial Engineers. Claudio Cruz Cázares is an Industrial Engineer who has studied the PhD in Business Economics at the Autonomous University of Barcelona (Spain). He is highly interested in the field of innovation management and firm performance. During the last years he has actively participated in national and international conferences such as ACEDE, ISPIM, EIASM. He has been also involved in several research projects financed by the Spanish Ministry of Education. He is also part of team of the department of Business Economics of the Autonomous University of Barcelona.

678

About the Contributors

Javier Alejandro Carvajal Díaz holds a MSc degree in Engineering (Organisational Management) and Industrial Engineering with emphasis on education from the Universidad de los Andes, Colombia. At present, he works as a researcher and lecturer in Systemic Thinking in Organisations (Pensamiento Sistémico en las Organizaciones) at the Industrial Engineering Department of the Universidad de los Andes. His research areas involve innovation, sustainable development and education in engineering. Friedrich Grosse Dunker is co-founder of the innovation consultancy Dark Horse GmbH, which is engaged in user-centered innovation and Design Thinking, and also gets involved as a coach in innovation and entrepreneurial projects. He graduated at Technische Universität München, Germany, and holds a degree in Business Administration and Engineering. He wrote his diploma thesis on “Sustainability Innovation Cube – A framework to evaluate sustainability-oriented innovations”. His research interests are innovations and innovation management in the field of sustainability and design-based innovations and business strategies. Friedrich obtained broad academic and practical experiences in Australia, Norway, Germany and South Africa. Gustavo de Boer Endo is a graduate in Business Administration from University of Sao Paulo (USP), Brazil. Gustavo de Boer Endo is consultant at TerraForum and advises companies in knowledge management, maturity models, knowledge strategies and innovation network and clusters and strategies. Within innovation management projects, he structured innovation processes for large clients and modeled open innovation structures, partner evaluation and structuring of innovation environments. Niels R. Faber is Researcher at the Department of Social Sciences of the Frisian Academy (KNAW), and Assistant Professor at the Faculty of Economics and Business of the University of Groningen. His research and publications concentrate on the topics of knowledge management, knowledge technology, decision-support systems, and social sustainability, especially within the domain of agriculture. In 1999, he received his MSc in computer science at the University of Twente. His MSc in Industrial Engineering and Management Science was completed in 2002. In 2006, he received his PhD for his thesis “Knowledge in Sustainable Behavior”. Pilar Fernández Ferrín is an Assistant Professor of Marketing at the University of País Vasco. She has a PhD in Business Administration from the University of Santiago de Compostela (Spain). She teaches and carries out research in the fields of new product development, sales management and consumer behavior. Her work has been published in Journal of Product Innovation Management, Technovation, Industrial Marketing Management, European Journal of Marketing, Creativity and Innovation Management, Psychology & Marketing, Revista española de Investigación en Marketig Esic, Revista Europea de Dirección y Economía de la Empresa and Cuadernos de gestión. Diana A. Filipescu holds a PhD in Business Economics from the Autonomous University of Barcelona (Spain). Her main research interests are in firms’ technological innovation and internationalization, R&D strategies, and family business. She has presented various studies in important national and international conferences such as ACEDE, McGill International Entrepreneurship, EIBA, EIASM, and AOM. She is also a Professor of International Business and International Marketing Strategies at the Foundation of the Autonomous University of Barcelona.

679

About the Contributors

Jonas Gabrielsson is Associate Professor in Business Administration at the Centre for Innovation, Research and Competence in the Learning Economy (CIRCLE), at Lund University (Sweden). His teaching and research is primarily focused on issues related to entrepreneurship and innovation. He has also a general research interest in corporate governance, primarily related to companies operating in entrepreneurial contexts. Simone Galina is an Assistant Professor of Innovation and Operations Management at the School of Economics, Business and Accountancy of Ribeirão Preto at University of São Paulo, Brazil. She has a PhD in Engineering from Polytechnic School of University of São Paulo. She is teacher and advisor of Master and Doctorate students at the Graduate Program in Management of Organizations (PPGAO). She leads the Group of Studies on Innovation and Internationalisation of Companies and her main areas of expertise are innovation management, R&D internationalization and globalization of operations. Jorge Cruz González is PhD Candidate in Business Administration at the Business Administration Department in Universidad Complutense de Madrid (Spain) and member of the Strategy, Knowledge and Innovation Research Group (ECI) of this university. Additionally, he is scholarship holder of the Spanish Ministry of Science and Innovation (University Professorship Formation National Plan). His main research lines are about Knowledge Management and Dynamic Capabilities. José A. Varela González is a Professor of Marketing at the University of Santiago de Compostela (Spain). He has a PhD in Business Administration from the University of Santiago de Compostela. His research interests include sales management, new product/new service development and launching, services marketing and marketing orientation. His work has been published in Journal of Organizational Behavior, Marketing Intelligence & Planning, Technovation, Journal of Product Innovation Management, The Service Industries Journal, Creativity and Innovation Management, Revista española de Investigación en Marketig Esic, Revista Europea de Dirección y Economía de la Empresa, Información Comercial Española and Cuadernos de gestión. Sergio Ronaldo Granemann graduated in Civil Engineering from the University of Santa Catarina. He earned MSc in Production Engineering from Federal University of Santa Catarina, MA in Economics from the Université d’Aix Marseille II and PhD in Economics from Université D’Aix Marseille II (France). He is currently a member of the committee of experts from the Ministry of Education, Adjunct Professor at the University of Brasilia and reviewer of Gestão&Produção Journal. Jerald Hage is the Director of the Center for Innovation at the University of Maryland. He is a graduate of Columbia University, he is a former chair of the Department of Sociology at the University of Maryland. He has been a visiting professor at four universities and the winner of three international fellowships. In addition, he is the author of 16 books, over 100 papers and chapters, and has a book forthcoming from Stanford University Press on the need for a new policy model based on innovation. Erik G. Hansen is a senior researcher at the Centre for Sustainability Management (CSM) at Leuphana University Lüneburg, Germany. Prior to this appointment he was a Postdoc researcher at FriedrichAlexander-University Erlangen-Nuremberg, Germany and a visiting researcher at Cranfield University,

680

About the Contributors

Doughty Centre for Corporate Responsibility in the UK. His research interests are innovation, strategy, and governance in the context of corporate responsibility and sustainability. Erik teaches business classes at undergraduate, graduate and executive level. He wrote his doctoral thesis on “Responsible Leadership Systems” at Technische Universität München, Germany. He has also gained broad experience in industry jobs and academic exchanges in Brazil, China, Germany, and Thailand. Ariane Hinça (MSc, PMP) is the coordinator of the Industrial Development Observatory under the Industry Federation of Paraná (FIEP), in Brazil. She’s holds a bachelor degree in Economics from the Federal University of Paraná (UFPR). She obtained her master’s degree in Technology from the Federal Technological University of Paraná (UTFPR) where she is currently a doctoral candidate. She is also a researcher at the Innovation and Technology Management Group at UTFPR. Gretchen Jordan is a Principal Member of Technical Staff with Sandia National Laboratories in the USA. She works with the Sandia Science and Engineering Strategic Management Unit and the US Department of Energy on evaluation and performance measurement and innovative methods of assessing the effectiveness of research organizations. She is Co-Editor of Research Evaluation. René J. Jorna is head of the Social Sciences Department of the Frisian Academy (KNAW) and full Professor in Knowledge Management and Cognition at the faculties of Economics and Business and Behavioural Sciences of the University of Groningen. He studied Analytic Philosophy and Logic (Master in 1981) and Experimental Psychology (Master in 1982) and had his PhD in 1989 in Cognitive Science on knowledge representation. His research and publications refer to cognition, semiotics, knowledge management, sustainability and knowledge technology. In 1994, he published Semiotic Aspects of Artificial Intelligence (de Gruyter). From 1990 until 1995 he was manager of a research project on planning (DISKUS), resulting in commercial software and five PhD’s. From 2001 until 2004, he was program manager of the NIDO project on Sustainable Innovation. In 2006 he published the book Planning in Intelligent Systems (Wiley, New York) and also in 2006 Sustainable Innovation (Greenleaf). He published over 150 journal articles and book chapters. He supervises 10 PhD projects on sustainable innovation, planning, cognition and social simulation. Yuya Kajikawa is a Project Lecturer at the School of Engineering at The University of Tokyo (Japan). He received his PhD degree in Chemical System Engineering from The University of Tokyo in 2004. He also received his BS and MS degrees from the same university in 1999 and 2001, respectively. His research interests include the structuring of engineering knowledge, technology and innovation management, and innovation policy. He has a number of publications in peer-reviewed journals and conference proceedings, which cover a variety of disciplines including engineering, information science, environmental science, and management science. Jose Carlos Korelo (MSc) is a PhD student in the Business Administration Program, concentrating on Marketing and Consumer Behavior at School of Management of Federal University of Parana, Brazil. He holds a Master in Business Administration (concentration in Marketing and Consumer Behavior) from Federal University of Parana, Brazil, 2009. He is interested in consumer’s innovation adoption behavior and consumer behavior.

681

About the Contributors

Valentina Lazzarotti is Assistant Professor at the Institute of Technology of Università Carlo Cattaneo – LIUC (Italy). She teaches Business Economics and Organization and Management Control Systems at LIUC. She holds a PhD in Management Engineering from Politecnico of Milan and a Master Degree in Business Administration from Bocconi University. Her research interest concerns R&D performance measurement and accounting for innovative activities. She has published papers in international journals such as International Journal of Innovation Management and Project Management Journal. Enrique Leff, Mexican born, is a pioneer and one of the main authors on environmentalism, recognized internationally and particularly in Latin America. He got his BA in Chemical Engineering at UNAM in Mexico City and a Doctorat de Troisieme cycle in Economic Development in Paris I-Sorbonne University in France. He works in the fields of Environmental Philosophy, Epistemology and Sociology, Ecological Economics, Political Ecology and Environmental Education. For over 22 years, Enrique Leff was Coordinator of the Environmental Training Network for Latin America and the Caribbean and then Coordinator of the Mexico Office of the United Nations Environment Programme, until May 2008. He is presently full-time researcher at the Institute of Social Research and Professor at the Faculty of Political and Social Sciences at the National Autonomous University of Mexico. He has published extensively in the field of environment and sustainability and is regularly invited as keynote speaker, lecturer and professor to universities throughout Latin America and Spain. Suzana Monteiro Leonardi is consultant at TerraForum and a specialist in innovation and knowledge management helping companies to implement, manage and improve their innovation processes. She is Professor, with a Master’s Degree in Business Administration, she is working hard to get her doctorate degree in Education at UNICAMP, Brazil. José Emilio Navas López, Dr., is Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain) and Chairman of the Strategy, Knowledge and Innovation Research Group (ECI) of this university. He is author and co-author of several books and papers concerning Technology Management, Strategy and Knowledge Management. He has held the first Knowledge Management Chair in Spain at I. U. Euroforum Escorial. Raffaella Manzini is Associate Professor at the Institute of Technology of Università Carlo Cattaneo – LIUC (Italy). She teaches Business Economics and Organization and Technology Strategy at LIUC and Politecnico di Milano. Her research interests concern R&D and innovation management, technology strategy and organization and technological collaborations. She has published more than 40 papers in leading international journals such as R&D Management Journal, Long Range Planning, International Journal of Technology Management, and International Journal of Operations & Production Management. Leonardo J. Melo is an MSc student at the Institute of Economics, Federal University of Rio de Janeiro (IE/UFRJ) and research assistant at the (Brazilian) National Institute of Science and Technology Policy, Strategy and Development (INCT / PPED). Melo has a Bachelor’s Degree in Business Administration (focused on Entrepreneurship and Management and Evaluation of Public Policy) from the Catholic University of Rio de Janeiro (PUC-Rio). He works in the field of project management related to innovation and interaction between universities, government and society. Melo researches in the following areas: public policy, sustainability and the knowledge economy. 682

About the Contributors

Jonathon Mote is an Assistant Professor of Management at Southern Illinois University in Carbondale (USA). His research interests are primarily focused on the interrelationship between organizational environments and the networks of science and innovation. His articles have appeared in The Journal of Engineering and Technology Management, R&D Management, and Research Evaluation, among others. Caroline Mothe is full Professor of Strategic Management at the University of Savoy, where she mainly teaches strategy and innovation management. Interested in interfirm cooperation and in innovative organizations, she actually coordinates several research projects on intra and inter-organizational innovation processes. She has published many articles related to these fields in international journals. Helen E. Muga, PhD, is an Assistant Professor in Civil Engineering at the University of Mount Union, Alliance, Ohio (USA). She worked as a postdoctoral researcher in the Civil & Environmental Engineering department at the University of South Florida, Tampa, Florida. She received a PhD in Environmental Engineering from Michigan Technological University, Michigan, USA, a Masters degree in Chemical Engineering from Curtin University of Technology, Australia, and a Bachelors degree in Chemistry from the University of Papua New Guinea. Her research interests include sustainability, life cycle engineering, green engineering, diffusion and adoption of green technology, and international development work. Hiroko Nakamura is a Project Researcher at the Centre for Aviation Innovation Research at The University of Tokyo (Japan). She previously worked for Nissan Motor Co. Ltd., as a product planner, making the efforts of engineers attractive to the market. She received her MS degree in Environmental and Ocean Engineering from the University of Tokyo in 2006 and a Special Master’s degree in Industrial System Engineering from the Ecole Centrale Paris in 2004. She also received her BS degree from The University of Tokyo in 2003. Her research interests include transition management of innovation. Christina Öberg is an Assistant Professor in marketing at Lund University. She received her PhD from Linköping University. She has an industry background and has previously worked in such positions as financial manager and head accountant. Today, she is an authorized accountant. Her research interests are mergers and acquisitions, innovation management and business relationships. She has previously published in journals such as Journal of Business Research, Construction Management and Economics, International Journal of Innovation Management, and Industrial Marketing Management. In addition, Christina has had articles accepted for publication in European Journal of Marketing and The Service Industries Journal. Luisa Pellegrini, PhD, is Associate Professor of Management Engineering at the faculty of Engineering, University of Pisa (Italy) where she teaches Innovation Management and Business Economics and Organisation. She is actively involved in national and international research projects on Knowledge Management and Continuous Innovation. She is member of the Continuous Innovation Network (CINet) and author of numerous international publications. José Tiberio Hernández Peñaloza has a PhD in Informatics from l’Ecole Nationale Supérieure de Techniques Avancées, and a MSc in Computing and Systems Engineering from the Universidad de

683

About the Contributors

los Andes. He is a former Dean and Vice-Dean of the School of Engineering at the Universidad de los Andes and currently works as an associate professor and head of the Visual Computing R&D Team in the School of Engineering at the Universidad de los Andes, in Colombia. Diamanto Politis is Assistant Professor in Entrepreneurship at School of Business and Engineering of Halmstad University, Sweden. She is member of KEEN and CIEL at Halmstad University. Her research interests include entrepreneurial learning, academic entrepreneurship and the value-adding role of business angels in new firms. Andrew Pollard joined the University of Wolverhampton (UK) in 2002 and was appointed Industrial Professor in 2003 with the responsibility to set up and run the ‘Caparo Innovation Centre (CIC)’, a joint collaboration between Caparo plc and the University of Wolverhampton. The CIC team work with inventors to help them commercialize their ideas, earning a royalty on products launched this way. Prof Pollard also works on a consultancy basis for small and large companies, addressing issues in the area of innovation, new product introduction and internationalisation. He has been appointed a Director of Unibyte ltd, a spin-out company from the University, and also sits on the Caparo Engineering Board responsible for strategic development. Anne Berthinier Poncet is a PhD candidate in Management at the IREGE (Institute of Research in Economics and Management) and teacher at the University of Savoy, France. She’s studying the influence of regional cluster governance on firm’s innovative performance, in particular in technopoles and competitiveness clusters. Her topics of interests cover also innovation in services, and specifically innovation of KIBS. Paulo Henrique Muller Prado, PhD, is Adjunct Professor of Marketing at the School of Management, Federal University of Parana, Brazil. He holds a PhD in Marketing, from FGV – Getulio Vargas Foundation, Brazil, 2004; a MSc in Business Administration, (Concentration in Marketing and Consumer Behavior), from Federal University of Parana, Brazil, 1995; and a BSc in Electrical Engineering, from UNICAMP, Brazil. His research interests include: Satisfaction Models, Relationship Quality and Loyalty, Cognitive Structures and Innovation adoption, Consumer-Brand Relationship, B2B Relationship, Marketing Metrics. David L. Rainey is an internationally-known author, educator, and business consultant. He is a leading authority on sustainable development, strategic leadership, strategic management, strategic innovation, product development, and energy management. He is a strategist and pragmatist developing innovative solutions to the challenges in today’s turbulent business environment. Dr. Rainey has over 35 years of experience and leadership in industry and academia. He is a Professor of Management in the Lally School of Management and Technology at Rensselaer Polytechnic Institute. Dr. Rainey is a Visiting Professor at the Technical University of Munich and an Associate of “the Center for the Study of Corporate Sustainability” in Buenos Aires, Argentina. Dr. Rainey is the author of Product Innovation: Leading Change through Integrated Product Development (2005), Sustainable Business Development: Inventing the Future through Strategy, Innovation and Leadership (2006) and Enterprise-wide Strategic Management: Achieving Sustainable Success through Leadership, Strategies and Value Creation (2010).

684

About the Contributors

The books are published by Cambridge University Press. His next books are Full-Spectrum Strategic Leadership: Achieving Sustainable Success through Solutions, Systems and Relationships and Corporate Strategic Management: Achieving Sustainable Success through Visionary Leadership and Strategic Innovation. Dr. Rainey earned a BS in Mechanical Engineering, a MBA, and Master of Science degrees in Engineering Science and Business Management. He earned a PhD from Rensselaer Polytechnic Institute. Caspar van Rijnbach is Dutch from origin with a Masters degree in Economics and a Masters degree in Political Science. He is a specialist in Innovation Management, partner at TerraForum Consulting in Brazil, Professor at the Brazilian Business School in 2010 and was Professor of the discipline “Innovation Management” in the educational course “Knowledge Management in Pratice” – USP – FIA 2006 (one of Brazil’s major universities). He led many in-company courses on innovation and knowledge management. Co-author of “Innovation: Breaking Paradigms” and “Management 2.0’’ – in which he wrote the chapter “Innovation 2.0” (both books in Portuguese). Caspar has given advice about innovation and knowledge management to large Brazilian companies and multinationals, such as Vale, Sadia, CPFL, Unilever, Syngenta, Citibank and Mahle. Felipe Fontes Rodrigues, MSc, is a Professor of Operations Research at the Department of Applied and General Management at the Federal University of Paraná (UFPR), Brazil. He was granted a research fellowship at the Industrial Development Observatory at the Industry Federation of Paraná (FIEP), and he is a researcher with the Technology Prospective and Regional Technology Development group at the Federal Technology University of Paraná (UTFPR). Renata Lèbre La Rovere is Associate Professor at the Institute of Economics of Federal University of Rio de Janeiro (IE/UFRJ) since 1993, and researcher at the (Brazilian) National Institute of Science and Technology Policy, Strategy and Development (INCT / PPED) since 2009. She holds a PhD in Economic Sciences from Université Paris 7, France, 1990. She was a Visiting Professor at the Management of Information Sciences Department, University of Arizona, between 1991 and 1992; and took a Post-Doctoral research in Innovation Policies for small enterprises at the Management of Information Sciences Department at Rostock University, Germany, between 1995 and 1996. Her main areas of research are: innovation policies for small enterprises, Information Technologies and development, entrepreneurship and local development. Pedro López Sáez, Dr., is Associate Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain) and member of the Strategy, Knowledge and Innovation Research Group (ECI) of this university. Additionally, he has several years of research experience at CIC Spanish Knowledge Society Research Centre and has been Post-Doctoral Research Fellow at Harvard University during 2004-2005. He is author and co-author of several books and articles concerning Resource-Based View, Intellectual Capital and Knowledge Management. Javier Amores Salvadó is Assistant Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain). He holds the Advanced Studies Diploma from Universidad Complutense de Madrid. His main research lines are Innovation, Environmental Innovation and Sustainable Development.

685

About the Contributors

Daniela Tatiane dos Santos graduated in Economics from the Universidade Estadual Paulista Julio de Mesquita Filho (2005). She holds a Masters in Production Engineering from Universidade Federal de São Carlos (2007). Currently she is a PhD student in Industrial Engineering (UFSCar) and has experience in Industrial Economics and Technology Management and Innovation. Horst-Hendrik Scholz received his MSc degree in Engineering Management at The University of Birmingham (UK) after the completion of a BEng degree in Industrial Engineering at the Leuphana Universitaet Lueneburg (Germany). After finishing A-level at the Gymnasium Suederelbe, he worked part-time besides studying on projects like: upgrading an ERP- Systems and implementation of an aviation standard (EN9100) in a manufacturing enterprise. To gain work experience abroad he worked for 9 month in several Canadian and American SMEs in Project- and Customer Relationship Management. To apply academic knowledge in financing he worked as a financial adviser; assisting the management of a SME company in the aviation industry. Laila Del Bem Seleme, MSc, holds a Bachelor degree in Service Management from Mogi das Cruzes University (UMC) and a Master’s degree in Strategic Management from the Federal University of Paraná (UFPR), Brazil. She is a Technical Researcher with the Industrial Development Observatory at the Industry Federation of Paraná (FIEP), and a researcher with the Technology Prospective and Regional Technology Development group at the Federal Technology University of Paraná (UTFPR). Danielle Mantovani Lucena da Silva, MSc, is a PhD student in the Business Administration Program, concentrating on Marketing and Consumer Behavior at School of Management of Federal University of Parana, Brazil. She holds a Masters in Business Administration (concentration in Marketing and Consumer Behavior), from Federal University of Parana, Brazil, 2006. Her research interests concentrate on the analysis of the psychological and cognitive aspects regarding consumer’s decision making process. Gavin Smeilus is a Senior Consultant in Product Innovation at the University of Wolverhampton (UK). He is currently enrolled on the University’s Doctoral programme undertaking research into the Integration of Independent Inventors in Open Innovation. Gavin has undertaken new product introduction related consultancy projects on behalf of numerous businesses from sole traders through to multinational corporations. Marilia de Souza, PhD, is the Manager of the Industrial Development Observatory under the Industry Federation of Paraná (FIEP), Brazil. Prior to her managerial career she obtained her Doctorate degree in Mechanical Engineering Sciences at the Technology University of Compiegne (UTC), France. She is a Guest Senior Researcher for the Technology Prospective and Regional Technology Development group at the Federal Technology University of Paraná (UTFPR). Shinji Suzuki is a Professor at the Department of Aeronautics and Astronautics and Head of the Center for Aviation Innovation Research at The University of Tokyo (Japan). He received his PhD degree in Engineering from The University of Tokyo in 1986, after his research career at Toyota’s Central R&D Labs, Inc., in Japan. He received his BS and MS degrees from the same university. His main research interests are in the design and control aspects of air safety and unmanned aerial vehicles. Shinji Su-

686

About the Contributors

zuki is currently Vice- President of JSASS, the Board Director of JSME, and an Executive Committee Member of ICAS. Ken D. Thomas completed his PhD in Civil & Environmental Engineering from the University of South Florida, Tampa, FL, and BSc in Chemical and Process Engineering & MSc in Environmental Engineering from the University of the West Indies, St. Augustine, Trinidad. During the latter stage of the MSc he worked for the state agency of Environmental Management Authority of Trinidad and Tobago in the capacity of Environmental Protection Officer up until commencing PhD studies at the University of South Florida, Tampa, Florida. Ken is currently a Postdoctoral Fellow of The University Honors College, Auburn University, Auburn, AL where he is engaged in teaching sustainability courses and undertaking research on sustainable development. Paul Turner is Professor of Management Practice at Ashcroft International Business School, Cambridge; a Non Executive Director of Blessing White and a Non Executive Director on the European Advisory Board of OPI. He was formerly President of Europe, Middle East and Africa, Employee Care for the Convergys Corporation, Group HR Business Director for Lloyds TSB, Vice President of the CIPD, a Director of BT and Executive in Residence at Nottingham Business School. He holds his PhD from the University of Sheffield. He is the author of HR Forecasting and Planning (2002), Organizational Communication (2003) and co author of Talent (2007). He is also the co author along with Michael Brown of The Admirable Company published in 2008. Miriam Delgado Verde, Dr., is Assistant Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain) and member of the Strategy, Knowledge and Innovation Research Group (ECI) of this university. Additionally, she has been Post-Doctoral Research Fellow at MIoIR-The University of Manchester during 2009 and University of Edinburgh Business School during 2010. She is author and co-author of several books and articles concerning Resource-Based View, Intellectual Capital and Technological Innovation. Eric Viardot is Permanent Professor of Marketing and Strategy at EADA Business School in Barcelona. He has a Doctorate in Management. He is a graduate of the HEC Business School, Paris, and the Institute of Political Sciences, Paris. He has published various books and articles on strategic management and marketing with a strong focus on Innovation and Technology Management. He is currently the co-editor of the International Journal of Technology Marketing. He is an active consultant and trainer and has worked with several major multinational corporations, notably with various innovation-driven technology firms. Belén Bande Vilela is an Assistant Professor of Marketing at the University of Santiago de Compostela (Spain). She received her PhD in Business Administration from the University of Santiago de Compostela. Her research interests include sales management, consumer behavior and new product development. Her work on these topics has been published in a variety of journals, such as Journal of Organizational Behavior, Journal of Product Innovation Management, Technovation, Industrial Marketing Management, European Journal of Marketing, Creativity and Innovation Management, Revista española de Investigación en Marketig Esic, Revista Europea de Dirección y Economía de la Empresa and Cuadernos de gestión. 687

688

Index

A abductive reasoning 328, 334, 344 Absorptive Capacity 179, 182, 186, 188, 259, 283, 386, 394, 396, 401-406, 429-434, 440-445, 448, 466 Academic Inventors 135 Accreditation Board of Engineering and Technology (ABET) 108, 111-112, 127 adverse selection 565, 569, 572, 583, 587 Advisory Council for Aeronautics Research in Europe (ACARE) 60, 70 Aeronautics Innovation 55 Aerospace Industries Association (AIA) 65 Agency for the Promotion of Exports and Investments (APEX) 593, 611 agroecology 11 agroforestry 11 air transport management (ATM) 57, 59 American Institute of Aeronautics and Astronautics (AIAA) 58, 65, 69-71 American Society For Testing and Materials (ASTM) 62, 65, 71 Analytic Hierarchy Process (AHP) 476, 480, 485486, 488-489 anticipated regret 508, 512-517, 519-520, 524 Asia and Pacific Initiative to Reduce Emissions (ASPIRE) 37, 65, 70, 134, 222 asymmetrical information (AI) 565, 572, 587, 671, 673 attract retain and develop top talent (AADRT) 266 average variance extracted (AVE) 459, 472-473, 517

B Bank for International Settlements (BIS) 565, 586 Bank of Brazil (BB) 593, 611, 618 bioeconomics 8

Biomass to Liquid (BLT) 62 biopiracy 13 bioprospecting 13 biospheric resources 8 bisociation 373 Brazilian multinationals 590-592, 594-595, 598599, 604, 606-607, 609-611, 613-614, 616-617, 632 Britain’s Most Admired Companies (BMAC) 264275, 277 Building Relationships 33 business angel 567, 572, 587 Business Environment 18-20, 27-28, 30-33, 35, 3739, 162, 207, 228, 336, 387, 595 Business Management Layer (BML) 665-667, 673

C Career Experience 245-249, 254, 256-258, 262-263 CDIO cycle 106, 111-113, 126 Centre for Aviation Innovation Research (CAIR) 58, 60, 69 Centre for Technological Development of Industries (CDTI) 541, 552 choice confidence 508, 512-514, 516-520, 524-525 choice goals 508-509, 512-513, 516, 519-520, 525 Civil Aviation Authority of Singapore (CAAS) 65 Clean Technology 38 Cognitive Information Systems (CIS) 278, 280, 287-288, 299, 301, 434, 458, 464, 528, 653, 655, 661-666, 668, 673 cognitive machines 653-655, 660-669, 671, 673 Combinative Capabilities 386, 392, 395, 403, 405406 commercial object 352 Committee for Economic Development (CED) 557558 Committee of European Banking Supervision (CEBS) 565

Index

common, but differentiated responsibilities (CBDR) 57 Community Innovation Survey (CIS) 278, 280, 287-288, 299, 301, 434, 458, 464, 528, 536, 653, 655, 661-666, 668, 673 Competitive Advantage 4, 33, 38, 40, 75, 80, 89-90, 97, 101-103, 106-107, 230-231, 238, 264-265, 273, 276-277, 298, 304, 321, 328, 342-343, 345, 361, 384-385, 387, 390-391, 393, 397, 399, 401-402, 425, 430-432, 443, 445, 448, 467, 497, 503, 506-507, 541, 597, 621, 623, 625, 641, 643, 655, 669, 672-674 competitiveness clusters 457, 463 Computational Fluid Dynamics (CFD) 60 Computational Organization Management Networks (COMN) 653, 655, 661-662, 666-668, 673 Computer Aided Information (CAI) 647 Computer Integrated Manufacturing (CIM) 663 Computer Supported Collaborative Work (CSCW) 642-643 Conference of the Parties (COP) 57, 60, 69, 123 control variables 253, 255, 334, 434, 437, 459, 462 Corporate Sustainability 40-41, 44, 51, 53-54, 71, 85 cost per unit service or utility (COPS) 6 credit crunch 555-556, 566-567, 572, 575, 580, 584, 587 credit rating 555-556, 562, 566-569, 572, 576, 578, 580-581, 583-587 Credit Rating Agency (CRA) 566 credit rationing 555-556, 563-565, 569, 571-572, 583 critical success factors 131-132, 137, 139-140, 143144, 146-148, 159, 161, 163-164, 269 cross-functional teams 526-527, 531, 535, 546, 548-549 Cultural Diversity 3, 13-14 customer-centric organizations 653 Customer-Centric Systems (CCS) 654-655, 657, 667, 674

Dynamic Environment 391, 406

D

Federal Aviation Administration (FAA) 59, 61, 65, 70 Federation of Industries of Paraná (FIEP) 302-303, 305, 310, 312-313, 317, 319-322, 324 Financial Intermediary (FI) 563 financial soundness (FS) 265-266, 268, 271-273, 661 Firm-Specific Factors 167, 170-171, 185 Flexible Manufacturing Cells and Systems (FMS) 663 free riding 235

developing country multinationals 613 Developing Nations 62 digital gap 285 directional risk 42 direct loan 568, 572, 587 Dutch disease 278, 280, 282, 292, 297, 299 Dynamic Capabilities 186, 242, 384-388, 390-391, 393-394, 396-402, 404-406, 466, 507

E Earnings before Interest and Taxes (EBIT) 581 ecoefficiency 8, 11 eco justice 42, 54 economic diversification 278, 282, 294, 299 Economic-Input Output Model (EIO-LCA) 78 Element Layer (EL) 662-664, 666-667, 673 Element Network Layer (ENL) 241, 662-663 EMAS (Environmental Management and Auditing Scheme) 93, 96, 98, 101-102 emissions control 90 Encyclopedia of Philosophy (EoP) 367, 381 entrepreneurial businesses 560, 566, 576, 585 Entrepreneurial knowledge 245-250, 252, 256-257, 263 Environmental Innovation 89-103 environmental management system (EMS) 59, 96, 101-102, 591, 611 Environmental Rationality 1-3, 7, 9-16 Environmental Strategy 38, 90, 97, 102, 401 Environmental Thinking 1 European Recovery Programme (ERP) 494, 578, 665 European Union (EU) 17, 21, 27, 65, 67, 101-102, 156, 188, 233, 253, 282, 284-286, 299-300, 307-308, 366, 436, 494, 528, 536, 558-559, 563, 571, 578 evaluation costs 508, 512-520, 525 Experiential learning 245, 248-249, 257-261, 263 Explorative Learning 384, 386, 391-392, 394, 399400, 406 Extended Enterprise 30-31, 33-35, 39 external communication 526-527, 531, 535, 540541, 548, 550 External Organizational Learning 386, 406

F

689

Index

free riding effect 235 Fuel reduction 66

G Gas to Liquid (GTL) 62 gatekeepers 394, 466, 527, 531-532, 535, 537-538, 541-542, 544, 547-552 geared turbo fan (GTF) 61 General Systems Theory 78, 382, 660 GENEX 646-648 Global Corporation 18, 31, 34, 627, 633 global economic system 8, 19, 21 global economy 5, 18, 20-23, 27-28, 34, 299, 309, 571, 613, 615-616, 636 Globalization 4, 12-13, 18-28, 31-32, 37-39, 128, 410, 591, 608, 620-621, 623-625, 634, 636638, 641, 644, 670 Global Link Network (GBN) 304-306 Globally Harmonized Agreement 55-56, 60 Group on International Aviation and Climate Change (GIACC) 57 Gulf Cooperation Council (GCC) 278-288, 290, 292-294, 296, 299-300

H high-velocity organization 343 house bank 572, 587

I immersiveness 653-655, 661, 665-667, 674 Independent Inventors 131-132, 134-148, 150-151, 153-154, 156, 160-165 Industrial Development Observatory (ODI) 303, 305, 310, 317, 319, 321-322 Information and Communication Technology (ICT) 120, 123, 125, 228, 278, 285-287, 289, 292, 296, 368, 371-372, 643 innovation adoption 508, 510, 515, 521 Innovation Management 52-53, 56, 70, 128, 169, 185-188, 200-201, 204, 221-222, 226-227, 229, 241-243, 275, 347-349, 354, 358, 360-361, 363-364, 405, 408, 425, 443-444, 447, 475, 487, 504-507, 523, 536-538, 551-552, 615, 635, 651 Innovation Network Relationships 191, 202 innovation positioning 497, 507 Innovation Radicalness 384-386, 391, 393-394, 396-401 innovative systems 648, 651-652

690

intangible asset 265-266, 275, 431 integrated course blocks (ICBs) 110 Intellectual Property Protection 137, 141, 151, 158, 161, 213 Internal Organizational Learning 406 International Air Transport Association (IATA) 59, 65-67, 70, 72 International Civil Aviation Organization (ICAO) 56-57, 59-60, 67, 70 International Council of the Aeronautical Science (ICAS) 58, 69-71 internationalization 234, 400, 432, 436-437, 441, 447, 590-591, 593-594, 596-603, 606-617, 619626, 632-638 international R&D 619, 627-632, 636, 638 Inventor-Entrepreneurs 135

J Japan Aerospace Exploration Agency (JAXA) 61, 71 Japan Civil Aviation Bureau (JCAB) 65

K Knowledge Acquisition 368, 372, 384, 393-394, 396-397, 399-400, 448 knowledge acts 338-339, 341 Knowledge Assets 230-232, 234, 361, 444, 447 knowledge claims 330-331, 372 Knowledge Combination 384, 386, 392, 394-397, 399-400 knowledge-intensive business services (KIBS) 455456, 465-466, 469 knowledge life cycle 330-331 knowledge management (KM) 2, 68, 73, 83, 232, 265, 277, 327, 329-336, 338, 343-348, 350, 360-363, 365-372, 374-375, 377-383, 405, 506, 586, 657, 660, 662, 668, 671, 673 Knowledge of Sustainability (KoS) 365, 367, 377380, 383 Knowledge Production 113-114, 168, 183, 230, 235, 359-361, 364, 372, 379, 606

L large scale enterprise (LSE) 558, 560-562, 574, 576, 579 law of entropy 8 lead users 169, 496, 527, 531, 533-534, 536-539, 541-546, 548-552 Liabilities of Newness 245, 247-253, 255-258, 263

Index

Licensing 26, 131, 135-136, 138, 141, 148, 158, 160, 173, 183, 205, 216, 220, 277, 309, 431, 447, 599-600 life cycle assessment (LCA) 42, 52-53, 73-74, 7879, 82, 85 life cycle cost analysis (LCCA) 73-74, 77-79, 85 Location Theory 486, 489

M make-buy 187, 428-430, 432-434, 436-442, 449 Management Information Systems (MIS) 504, 649, 673 Marketing Core Competencies (MCC) 491-493, 498, 503, 507 Material Input per Service (MIPS) 6 Mental Models 73-74, 82-87, 340-341, 658, 661 mezzanine capital 567-568, 586 Middle East and North Africa (MENA) 282-286, 297, 299-300 Millennium Development (MD) 374 Ministry of Development (MDIC) 322, 593, 616 misfuelling 148-149, 151-156, 166 moral hazard (MH) 565, 569, 583 Multicriteria Analysis 474-476, 479-485, 489 Multi-Level Perspectives (MLP) 55, 68-69, 72 multinational enterprises (MNEs) 19-20, 26-27, 604-605, 610-611, 614, 636-637

N National Academy of Engineering (NAE) 107, 111112, 122, 128-129 National Aeronautics and Space Administration (NASA) 59-60, 69, 71, 409-410, 420, 422 National Innovation System (SIN) 17, 114, 258, 260 National Institutes of Health (NIH) 409, 418, 422 National Science Foundation (NSF) 409, 418, 422, 651 National System of Science and Technology (SNCyT) 114 Natura 591, 599, 602-603, 607, 614, 616-617 Natural resource curse 278, 280-281, 292, 296-299 Natural Resource-Rich Economies (NRE) 279, 281282, 286, 296 negative resources 191-192, 195, 197-200 Neguentropic Productivity 1, 11 Net Profit (NP) ratio 579, 588 Network Element Layer (NEL) 662-663 Network Management Layer (NML) 662-667, 673

New Product Development (NPD) 42, 139, 143144, 162, 235, 277, 364, 391, 394, 403, 410, 416, 425, 433, 445, 475, 503, 505-507, 526544, 546-552, 615 New Product Introduction 131, 137-143, 148, 154, 157-159, 161-162 New Venture Creation 245-247, 249, 256-258, 263 New York Stock Exchange (NYSE) 595-596, 600 Next Generation Air Transportation System (NextGen) 59 North American Free Trade Agreement (NAFTA) 27

O OCDIO cycle 105, 107, 112-113, 117, 120, 124-126 Open Innovation Continuum 168, 184, 188 Open Innovation (OI) 50, 127, 131-134, 137, 140, 143, 145-148, 150-151, 153, 162-179, 182-188, 190, 203-209, 214-216, 218-220, 222-228, 429, 431-432, 434, 436, 438, 440, 442, 444, 448, 536, 538, 600-601, 613 Open Innovation Systems 222, 224 Opportunity Recognition 247-248, 261-263 Organisation for Economic Co-operation and Development (OECD) 76, 86, 88, 92, 95, 99, 102, 106-107, 129, 186, 216, 301, 303, 434, 436, 446, 448, 469, 559, 571, 577, 587, 591, 593, 608, 613, 615 Organisation’s Creative Area (OCA) 575, 585 organizational cognition 654-661, 666-667, 669, 671, 673-674 organizational innovation theory 409, 423 organizational intelligence 659 Organizational Networks (ONs) 230 Organizational Structure 83, 177, 179, 207, 222, 423, 561, 600, 632 Organization Networks 191, 202 Outward Foreign Direct Investment (OFDI) 591, 593, 596-597, 599, 604, 606-607, 617-618

P Partial Least Square (PLS) 457 PDCA cycle 341 Performance-Based Navigation (PBN) 61 Politics of Difference 1, 7 Politics of Knowledge 361, 364 Preemptive Strategies 30-31, 33, 39 process and business model 576 product champions 527, 531-533, 535, 538, 540542, 544, 546-547, 549, 551-552

691

Index

Product Development Phases (PDP) 191, 193, 200, 202, 593, 616 Product Innovation 39, 41, 54, 128, 140, 185, 187, 200, 241, 261, 275, 299, 402, 405, 412, 425, 443-444, 447, 456, 458, 460, 462, 492, 494, 496, 500, 503-507, 523, 528-529, 534-538, 550-552, 568, 575-576, 615, 635, 651 Product-Service Systems (Pss) 40-51, 53-54 Project-Based Learning (Pbl) 105, 127 Proprietor-inventors 135 Pultruded Rod Stitched Efficient Unitzed Structure (PRESEUS) 60

Q quality of management (QM) 266, 268-271 quality of marketing (QMar) 266-268 quality of products (QP) 231, 266, 268, 272, 593

R Radical Innovations 35-36, 179, 182, 187, 224, 270, 329, 369, 385-386, 394-400, 406, 433, 437, 440-442, 495-496, 548-549, 603 Radical Technological Innovation 35, 39 R&D activities 182, 188, 429-438, 440-443, 445446, 448-449, 576, 599, 619, 623-626, 628, 631, 633-636 R&D strategy (RDS) 186, 428-442, 448-449, 551 rebound effects 43 Reflective modernity 3-4 Regulatory Focus Theory (RFT) 508-512, 520 Research and Development (R&D) 5, 35-36, 57, 65, 71, 75, 81, 113, 116, 132, 141, 147, 152, 167168, 171-174, 176-179, 182-190, 204-205, 209, 213, 216, 218, 224-226, 231, 237, 241, 251, 253, 275, 279-280, 282-284, 286-287, 290, 292, 294-296, 300, 307-308, 346-348, 352, 355-356, 360, 362, 394, 396, 402, 408, 410, 423-449, 459, 469, 475-478, 497, 502-503, 505, 527, 529-531, 535, 537-538, 541-542, 549-552, 560-561, 574, 576, 578, 583, 598601, 603, 606-608, 610, 618-620, 622-638 Research, Development and Innovation (R,D&I) 203-204, 208, 214-220, 222-223, 225-226 Research Profiles 408, 410-411, 417-420, 423-424 Resource Dependence Theory (RDT) 191-195, 198200, 202 Return On Assets (ROA) 177, 182 Return On Sales (ROS) 177, 182-183

692

S Scenario building 302-306, 309-311, 313-314, 317322, 325 Science Parks (SPs) 227, 230-233, 235-243, 451, 453, 457 self-regulation 508-509, 511-514, 521, 523, 525 sensory store 603 Service Management Layer (SML) 662, 664-667, 673 small and medium-sized enterprise (SME) 20, 162, 172, 186, 188, 228, 240-241, 259, 443, 453454, 457, 463, 489, 555-562, 564-572, 574580, 582-587 Social Innovation 89-94, 99-104, 374, 382 Social Network 73, 80, 83-88, 233, 235 Social Network Analysis (SNA) 73, 80, 82-86, 88 source of innovation 42, 147, 279, 506, 576, 607 Southwest Airlines (SWA) 28 Strategic HQ Allied Powers Europe (SHAPE) 126, 150, 232, 252, 351, 378, 390, 424 Strategic Innovation 18-19, 22, 31, 35-37, 276, 487, 535-536, 550-551 Strategic Niche Management (SNM) 56-57, 62, 68, 70-71 supply-side knowledge management 330 Sustainability of Knowledge (SoK) 365, 367, 377380, 383 sustainability-oriented innovation (SOI) 40-42, 44, 52, 54, 70 Sustainable Aviation 55, 60, 62, 65-66, 69, 71 sustainable development (SD) 4-5, 7, 11, 13, 16, 18-22, 25, 30-34, 37-39, 51-52, 54, 56, 71, 7476, 85, 89-90, 92, 99, 127, 375, 382 Sustainable Solutions 29-32, 37 Sustainable Success 19, 26, 28, 30-32, 37-38 systems of shared use 41, 43-44

T Tacit Knowledge 234-235, 237, 277, 386, 420, 651 Technological Demand 475, 489 Technological Innovation 2, 6, 8, 11, 35, 39, 87, 102, 114, 277, 347, 355, 361, 364, 402-403, 429, 434, 445-447, 452, 456, 465, 467, 477, 487-488, 498, 510, 533, 536, 619-620, 623, 626, 641 Technological Services 475-476, 478-480, 483-484, 487, 489 Technological Supply 489

Index

Technology and Innovation Support Centers (TISCs) 474-477, 479-484, 486-487, 489 Technopoles 450-460, 462-467 Telecommunications Management Networks (TMN) 653, 661-662 Territorial anchoring 450, 452, 454-455, 457, 462463, 467, 469 Theoretical Review 386, 399 theory of fallibilism 335 total factor productivity (TFP) 279, 282, 285, 299300 Total Quality Management 33, 328-329, 332, 341 total yearly material flows (TAPS) 6 traditional financiers 563 Transition Management 55 Transnational companies (TNC) 239, 619, 621-625, 628-629, 631, 634-636

U

United Nations Framework Convention on Climate Change (UNFCCC) 57, 60, 69, 301 use of corporate assets (UCA) 266, 268

V value-added services 231, 556, 567 value as a long term investment (VLTI) 266, 268 Value Chain 36, 44, 98, 216, 287, 290 Value Creation 30, 32, 35, 38-39, 44, 227, 430, 448, 504 Value System 36 venture capital 133, 168, 170, 194-195, 213, 223, 259, 566-567, 570-572, 587

Y yokoten process 333 yokoten system 332-333, 343

United Arab Emirates (UAE) 279, 281, 286, 290, 292, 294, 296, 298, 300

693