Knowledge Management 2.0: Organizational Models and Enterprise Strategies Imed Boughzala TELECOM Business School, France Aurélie Dudezert Ecole Centrale Paris, France
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Library of Congress Cataloging-in-Publication Data
Knowledge management 2.0: organizational models and enterprise strategies / Imed Boughzala and Aurelie Dudezert, editors. p. cm. Includes bibliographical references and index. Summary: “This book provides an overview of theoretical and empirical research on knowledge management generation in the Web 2.0 age, highlighting knowledge management evolution with a global focus and investigating the impact knowledge management 2.0 has on business models, enterprise governance and strategies, human resources, and IT design, implementation, and appropriation in organizations”--Provided by publisher. ISBN 978-1-61350-195-5 (hardcover) -- ISBN 978-1-61350-196-2 (ebook) -- ISBN 978-1-61350-197-9 (print & perpetual access) 1. Knowledge management. I. Boughzala, Imed. II. Dudezert, Aurelie, 1975HD30.2.K63683 2012 658.4’038--dc22 2011012307
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 All work contributed to this book is new, previously-unpublished material.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.
Editorial Advisory Board Antonio Carlos de Oliveira Barroso, IPEN-CNEN/SP, Brazil Nathalie Dupuis-Hepner, Ernst and Young, France Jacques Igalens, TBS Toulouse Business School, France Chris Kimble, Euromed Management, France Meira Levy, Shenkar College of Engineering and Design, Israel Benoit Montreuil, Universite Laval, Canada Nicholas C. Romano, Oklahoma State University, USA Jean-Michel Viola, ESC Rennes School of Business, France
List of Reviewers Ghada Alaa, British University in Egypt, Egypt Myriam Alavi, Emory University, USA Isabelle Bourdon, University of Montpellier, France Karine Evrard-Samuel, University of Grenoble, France Myriam Raymond, French University in Egypt, Egypt
Table of Contents
Preface.................................................................................................................................................... vi Acknowledgment................................................................................................................................. xiv Section 1 KM 2.0 and Web 2.0 Technologies Chapter 1 Collaboration 2.0 through the New Organization (2.0) Transformation................................................. 1 Imed Boughzala, TELECOM Business School, France Chapter 2 Exploring the Impact of Web 2.0 on Knowledge Management............................................................. 17 Thomas Bebensee, Google Ireland Ltd., Ireland Remko Helms, Utrecht University, The Netherlands Marco Spruit, Utrecht University, The Netherlands Chapter 3 Moving Wikis Behind the Firewall: Intrapedias and Work-Wikis......................................................... 44 Lynne P. Cooper, California Institute of Technology, USA Mark B. Rober, California Institute of Technology, USA Chapter 4 Social Networks and Knowledge Management: An Explorative Study in Library Systems................. 64 Bhojaraju Gunjal, University of Mysore, India Panorea Gaitanou, Ionian University, Greece Sarah Yasin, YBP Library Services, USA Chapter 5 Web 2.0 Social Networking Technologies and Strategies for Knowledge Management...................... 84 Edward T. Chen, University of Massachussetts, USA
Chapter 6 Competence Management over Social Networks Through Dynamic Taxonomies............................. 103 Giuseppe Berio, University of South Brittany, France Antonio Di Leva, Università di Torino, Italy Mounira Harzallah, University of Nantes, France Giovanni Maria Sacco, Università di Torino, Italy Section 2 Business Implications of KM 2.0 Chapter 7 Knowledge Sharing in the Age of the Web 2.0: A Social Capital Perspective.................................... 122 François Deltour, LEMNA Research Center, France Loïc Plé, LEMNA Research Center, France Caroline Saris-Roussel, LEMNA Research Center, France Chapter 8 Strategic Knowledge Management System Framework for Supply Chain at an Intra-Organizational Level.......................................................................................................... 142 Cécile Gaumand, Ecole Centrale Paris, France Alain Chapdaniel, ACTIMUM, France Aurélie Dudezert, Ecole Centrale Paris, France Chapter 9 Web 2.0 and Project Management: Reviewing the Change Path and Discussing a Few Cases................................................................................................................ 164 Antonio Carlos de Oliveira Barroso, IPEN-CNEN/SP, Brazil Rita Izabel Ricciardi, IPEN-CNEN/SP, Brazil Jair Anunciação de Azevedo, IPEN-CNEN/SP, Brazil Chapter 10 The Evolution of KM Practices: The Case of the Renault-Nissan International Strategic Alliance............................................................................................................ 190 Nabyla Daidj, TELECOM Business School, France Chapter 11 KMS for Fostering Behavior Change: A Case Study on Microsoft Hohm.......................................... 214 Magda David Hercheui, Westminster Business School, UK & London School of Economics and Political Science, UK Compilation of References................................................................................................................ 233 About the Contributors..................................................................................................................... 256 Index.................................................................................................................................................... 262
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Preface
INTRODUCTION In the last few years, Knowledge Management (KM) practices have evolved in organizations. Due to the introduction of Web 2.0 technologies, new usages of information and knowledge sharing have emerged (Enterprise 2.0). The new generation of employees (Generation Y or Milennials) has new habits at work. They use everyday Web 2.0 technologies (Blogs, Wikis, RSS, Folksonomy, social networking platforms, Mashups, Podcasting, etc.) in the private arena, and therefore, consider that such technologies for ecollaboration and self-organizing are the best means/methods to work. They are eager to simply and quickly find good information/knowledge, anytime and anywhere, and are not intimidated by knowledge complexity and organizational hierarchy. Thus, the concept of KM has been impacted and has evolved towards more human interactions management and interpersonal networking, in addition to traditional information and knowledge processing. Organizations are currently developing a new type of KM which is social-based and may be called KM 2.0. They become knowledge-centric organizations because they focus more on KM and social collaboration, rather than on hierarchy and control. In this new era, all employees can equally participate in creating, using, and sharing information and knowledge. Knowledge is no longer a matter for experts. Every individual (or knowledge worker) plays a central role in this case. Knowledge generated by employees is not only used for designing value-added products or services, but also for inventing new work modes based on people empowerment, user emergent participation and collaboration. Business models, organizational management, work modes, knowledge worker’s skills and behavior, and so forth are intended to be transformed, reviewed, and even sometimes to be rethought. The book aims to give an overview on theoretical and empirical research that investigates the next Knowledge Management (KM) generation (McElroy, 2002) in the Web 2.0 age, which would be called KM 2.0 (Dudezert & Boughzala, 2008). It highlights evolutions of the KM area with a global focus and an international dimension of studies. The objective is also to compare different approaches and practices developed in different countries and cultures.
TRADITIONAL KNOWLEDGE MANAGEMENT The interest in KM dates back to the early 90s when companies realized the strategic value of knowledge as a competitive resource and a factor of stability for their survival (Spender, 1996). There is more than one definition of KM. Mentzas (2004 p.116) defines KM as the “discipline of enabling individuals, teams
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and entire organizations to collectively and systematically create, share and apply knowledge, to better achieve the business objectives”. “KM efforts can help individuals and groups to share valuable organizational insights, to reduce redundant work, to avoid reinventing the wheel per se, to reduce training time for new employees, to retain intellectual capital as employees turnover in an organization, and to adapt to changing environments and markets” (McAdam & McCreedy, 2000) (as cited in Wikipedia). KM is also defined by Dieng et al. (1999) as a range of practices, methods, and techniques used in an organization to identify, analyze, organize, create, memorize, and share knowledge. According to Ikyjiro Nonaka (1994), Knowledge Creation is a spiraling and continuous process of interactions between explicit and tacit knowledge. Explicit knowledge which is codified and transmitted as information in formal and systematic language (e.g. rules, procedures) and tacit knowledge which is personal and deeply internalized, embodied in practice and action and so hard to be formalized and communicated (e.g. talent, hand-turn) (Polanyi, 1966). Spender (1996) has qualified a part of this tacit knowledge as implicit which is the only part that could be codified. The interactions between the explicit and tacit knowledge lead to the creation of new knowledge. The combination of the two categories makes it possible to conceptualize four conversion patterns: Socialization, Externalization, Combination and Internalization (Nonaka, 1994). Socialization enables the conversion of tacit knowledge through direct interaction between individuals through join activities by observation, imitation, practice, and linkage (Polanyi, 1966; Nonaka, 1994; Spender, 1996). The Japanese culture inspired Ikyjiro Nonaka and Noburo Konno to introduce the concept of Ba in 1996 to represent a shared space for emerging relationships that serves as a foundation for Knowledge Creation (Nonaka, 1998). This space can be physical (e.g. office, dispersed business space), mental (e.g. shared experiences, perceptions, ideas and ideals), or any combination of them. This concept, which is difficult to be translated in Western languages, could be defined as the pooling context in which knowledge is shared, created, and used through interaction. Since its emergence, KM focused more on knowledge as such with its space of socialization (Ba) and individuals (knowledge workers) who are holders of knowledge in their behavior, interactions, and relationships. This discipline has for long time emphasized capturing, accumulating, and disseminating knowledge through Knowledge Management Systems (KMS). KMS refer to IT-based systems developed to support and enhance the organizational processes of knowledge creation, storage/retrieval, transfer, and application (Alavi & Leidner, 2001). Yet for many organizations KMS became enormous repositories whose use was hindered by the sheer volume of data and the associated difficulties of keeping the knowledge accurate and up-to-date (Alavi et al., 2005-6). Thus in traditional KM era, KM refers more on knowledge control than on knowledge creation and transfer. We argue that with the arrival of Web 2.0, Knowledge Management has found a new youth, and its study and scope should be redesigned. KM is in the forefront in this evolutionary organizational context as we are moving from the only information processing to human interactions management and interpersonal networking. With the advent of the Web 2.0, the concept of KM has been impacted and has evolved towards a vision based more on people participation and emergence and less on knowledge per say. This implies a new conception of KM that we propose to call “KM 2.0”.
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KNOWLEDGE MANAGEMENT 2.0 According to Stowe Boyd (Gandih, 2008), one of the prominent consultants and bloggers in the Web 2.0 industry, there are three types of knowledge: • • •
Impersonal knowledge which consists of ideas and information made explicit in documents and files (explicit knowledge). Personal knowledge which is tacit and stored in the brains (tacit knowledge). Interpersonal knowledge which is communicated implicitly in the conversations and connections of people (implicit knowledge)
In traditional KM, we focus mainly on the two first types of knowledge. The study of Interpersonal Knowledge related to relationships and interactions of people (Social Capital, Nahapiet & Ghoshal, 1998) is specific to KM 2.0. In the context of collaborative work, it is part of what is called Collaboration Knowledge which includes work process and relational knowledge (Boughzala, 2007; 2010). Socialization is the most important mode of Knowledge Creation in the KM 2.0. With the development of the concept of social organization, a human centered organization based on e-collaboration, social networks and communities with an intensive use of Web 2.0 technologies, it has involved a new concept of KM, the KM 2.0. It describes the changing trends in managing knowledge in the knowledge-based society and economy built on the collective intelligence and social capital, mainly related to the interpersonal knowledge. We adopt Shimazu and Koike’s definition of KM 2.0 as “a model that places collective intelligence at its core and promotes its use by accelerating the distribution of information” (Shimazu and Koike, 2007 p.52). This new generation of KM, KM 2.0 aims to allow incorporated and pervasive management of knowledge for social and virtual organizations (teams, communities, and enterprises). With the introduction of Web 2.0 - social and collaboration technologies, the bases of KM have been updated and in some ways metamorphosed. The Web 2.0 adoption in connecting people (social networks and virtual communities) and online collaborating will succeed where previous approaches of traditional KM had failed in term of socialization. KM 2.0 affects Enterprise Business Models, organizational management, and knowledge worker’s skills and behavior, and may be visible at different dimensions: social, managerial, technical, economic, legal, ecological, et cetera. Compared to the traditional KM, evolution is related to the KM scope, the nature of knowledge, the place of the individual, leadership, the KM governance, and the KM process and technology (Boughzala & Limayem, 2010; Dudezert, 2009). •
KM Scope: Traditional KM focuses mainly on knowledge (Knowledge capital: Impersonal and personal knowledge). KM 2.0 on the other hand focuses not only on knowledge but also on its space of socialization and holders (Social capital: Interpersonal knowledge) through electronic open collaboration, social linking/networking and content sharing (thanks to Web 2.0 technologies) with a new culture of awareness (especially with both mixed and virtual reality) and innovation. At the level of the organization, while traditional KM focuses on intra organizational knowledge, KM 2.0 also covers inter organizational KM (IKM) such as in SCM and e-business where many exchanges and sharing of knowledge are done between partners. These exchanges usually take place between experts of the same field or around the same value chain or network.
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•
•
•
•
•
•
Nature of knowledge: In the traditional KM, knowledge comes mostly from experts (Individual Intelligence). In the context of KM 2.0, knowledge originating from any individual could be interesting. Customer reviews on amazon.com, for example, could be decisive in the purchase of a product. In the traditional KM, knowledge is mainly related to products (outcomes). In KM 2.0 however, knowledge is related to both products and processes. For example, in the case of a team working on the design of a new product, expertise around both the outcomes (individual domain knowledge and skills) and the work processes (collaboration knowledge, capabilities of members to work together and innovate) are important. Place of the individual: In the traditional KM, knowledge workers are mostly users of knowledge. In KM 2.0, people play a more central role by consciously and unconsciously generating knowledge. The connection, interaction, and collaboration of individuals and the nature of their relationships are a source of knowledge (Collective Intelligence), and play a major role in KM 2.0. Consequently, performance and recognition of individuals is done according to their collaborative capabilities to get in touch (connect), to federate others, and to work collaboratively. KM 2.0 is best suited to the new generation of individuals (Gen Y) who are looking continuously for new technology and become Knowledge Contractors, i.e. people who are aware knowledge is crucial to work in new knowledge-centric organizations and choose to develop and promote it (Dudezert et al., 2008; Dudezert, 2009). Leadership: In modern Western countries bureaucratic organizations are edifices built on ideas of rationality and control (Weberian myth) (Feldman & March, 1981). Leadership and hierarchical structure are based on this myth. In KM 2.0 era, knowledge is mainly personal and interpersonal. Thereby this crucial resource cannot be controlled and rationally managed by middle- and topmanagers. Thus KM 2.0 questions the rationality and control myth in bureaucratic organizations and makes business organizations reinventing managerial practices able to consider new foundations of authority. Google for instance developed a peer-assessment for collaborators rather than a hierarchical control of tasks. In this company leadership is based on legitimacy related to expertise and knowledge rather than on rationality and control. KM governance: In traditional KM, knowledge was stored by organizations in order to maintain their competitive advantage. Organizations had a defensive attitude concerning knowledge. In KM 2.0 era, Collective Intelligence is now used to transform stakeholders’ relationships and to improve competitive advantage. Thus, Walmart by developing KM 2.0 practices (Binot & Dudezert, 2008) improved its competitive advantage and developed a new business unit (GAZELEY) specialized in Logistics and Operations Management, which is its core knowledge. KM Process: KM is a structured process involving creating, storing, refining, and sharing knowledge (Knowledge Push). KM 2.0 is less structured, more transparent to the user in all its behavior and interactions and evolves gradually over time (“on the fly”), using technologies to observe and to keep track such as Log files, RFID, GSM/UMTS, or GPS, tagging and profiling (Knowledge Pull). Similarly, traditional KM is a Top-Down approach based on a corporate and normative strategy (centralization), KM 2.0 is a Bottom-Up approach based on individual initiatives and emergence (distribution). KM Technology: Compared to Web 2.0 technologies of today which are user centered, the traditional KMS - task oriented, seems incredibly primitive in terms of interpersonal knowledge. These offer only limited and formal information on experts and explicit knowledge in terms of collaboration. They suffer from their lack of tools of expression, social interaction, and visualization of
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relationships. Traditional KM technologies are often passive with a static content and are generated by professionals. Web 2.0 technologies are participatory and personalized with a dynamic content and are generated by users themselves. Traditional KM technologies are overly complex and rigid. Web 2.0 technologies are flexible and easy to use and to install.
ABOUT THE BOOK The material presented in this book is a collective contribution to the knowledge management area. The book is written for those who want to improve their understanding of challenges associated with KM evolutions due to the emergence of Web 2.0 technologies. It is, in particular, discussing impacts of KM 2.0 practices on: • • • • • •
Business models Enterprise governance and strategies Organizational structures and models Business work practices Human resources IT design, implementation, and appropriation in organizations
This book is meant for those connected with the fields of Management Science, Information Systems, Design Engineering, or anyone interested in the KM paradigms changing through Web 2.0 usages (Enterprise 2.0). It intends to serve as a valuable asset for academics (graduate students, researchers, and professors) in their research and teaching, as well as managers and practitioners in their KM strategy reformulation and Web 2.0 technologies implementation. The book is divided in two sections. The first section of this book analyses how Web 2.0 technologies contribute to KM 2.0 implementation according to the new organization transformation. Chapter 1, “Collaboration 2.0 through the New Organization (2.0) Transformation,” by Imed Boughzala introduces a new holistic organization transformation (i.e. Organization 2.0) caused by changes in the act of collaboration (i.e. mass collaboration or collaboration 2.0) due to the emergence of Web 2.0 technologies and their use by a new generation of people called Gen Y. Organization 2.0 is based on Collective Intelligence and Social Capital. This chapter tries to sort out confusion that may exist between different concepts like Web 2.0, Enterprise 2.0, Collaboration 2.0, Management 2.0, KM 2.0, Organization 2.0, et cetera. Chapter 2, “Exploring the Impact of Web 2.0 on Knowledge Management,” by Thomas Bebensee, Remko Helms, and Marco Spruit, examines the suitability and impact of Web 2.0 applications on KM in organizations. With case studies in two German nonprofit organizations, the authors demonstrate that unbounded collaboration and user-generated content functionalities used in Web 2.0 applications have a strong impact on knowledge capture/creation and knowledge sharing within organizations. Thereby they show that Web 2.0 applications effectively impact the efficiency, quality, and commitment of KM in organizations. Following chapters complete this analysis by focusing on specific Web 2.0 technologies. Chapter 3, “Moving Wikis Behind the Firewall: Intrapedias and Work-Wikis,” by Lynne P. Cooper and Mark B. Robber deals with Wikis and their use for KM in the new KM 2.0 era. This chapter shows that the use of wikis in corporations presents significant opportunities as well as challenges for improv-
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ing knowledge capture and work processes. It identified fundamental characteristics of wikis and how these change between public and corporate wikis, and between wikis intended for knowledge capture (intrapedias) versus supporting work processes. A case study describing two organizational wikis illustrated the power of the individual in instigating knowledge capture and the ability of wiki technology to rapidly and easily support individuals in their work efforts. Chapter 4, Chapter 5 and Chapter 6 examine the use of Social Networks technologies for KM in organizations. Chapter 4, “Social Networks and Knowledge Management: An Explorative Study in Library Systems,” by Panorea Gaitanou and Sarah Yasin, explores the impact of Social Networks technologies on KM in the context of Library Organizations. It shows that Social Networks tools can provide a useful compliment to existing central knowledge repositories. They open wide opportunities for collaboration and interaction and thereby contribute to create Collective Intelligence. Chapter 5, “Web 2.0 Social Networking Technologies and Strategies for Knowledge Management,” by Edward T. Chen, explores how Social Networks technologies can be used for KM in business organizations and propose strategies of use for Knowledge Management 2.0 implementation. Chapter 6, “Competence Management over Social Networks through Dynamic Taxonomies,” by G. Berio, A. Di Leva, M. Harzallah, and G.M. Sacco, examines how social networks information can be used to improve competence management in business organizations. It suggests social networks information can contribute to better value and control knowledge that is shared in organization and thus can contribute to build a more controlled Collective Intelligence. The second section presents the business implications of KM 2.0 transformation. It explores how companies become KM 2.0 organizations and how they used KM 2.0 to achieve their business objectives. Chapter 7, “Knowledge Sharing in the Age of the Web 2.0: A Social Capital Perspective,” by Caroline Saris-Roussel, François Deltour, and Loïc Ple, discusses the main challenges of the “social-turn” of knowledge management. In fact, in the KM 2.0 era, management of relationships based on trust is the core process of knowledge management. Based on social capital theory and on a case study by Schlumberger, this chapter analyzes how this social-turn renewed practices of Knowledge Management in business organizations. Chapter 8, “Strategic Knowledge Management System Framework for Supply Chain at an IntraOrganizational Level,” by Cécile Gaumand, Alain Chapdaniel, and Aurélie Dudezert, emphasizes also the role of interactions and relationships in KM 2.0. Based on an Action-Research in an Italian SME, they show implications of the implementation of a Knowledge Management System (KMS) in a transversal intra-organizational function (Supply Chain). They highlight KM 2.0 implementation which requires business organizations change their managerial practices and to develop a culture of agility based on knowledge sharing, collaboration, and empowerment. Chapter 9, “Web 2.0 and Project Management: Reviewing the Change Path and Discussing a Few Cases,” by Antonio Carlos de Oliveira Barroso, Rita Izabel Ricciardi, and Jair Anunciação de Azevedo, focuses on the synergy of Web 2.0 applications and services, and project management needs. They exam the Brazilian situation of current project management practices and discuss few cases for showing how Web 2.0 can impact project management. Chapter 10, “The Evolution of KM Practices: The Case of the Renault-Nissan International Strategic Alliance,” by Nabyla Daidj, analyzes the transformation of an international company from traditional KM to KM 2.0. More especially, it focuses on the impact of the KM 2.0 impact on the strategic alliance built
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by Renault and Nissan. Thus, this chapter discusses how KM 2.0 can be used to develop a competitive advantage in an industrial context. Chapter 11, “KMS for Fostering Behavior Change: a Case Study on Microsoft Hohm,” by Magda David Hercheui, ends this section and the book with a more critical analysis on KM 2.0. Based on an empirical example (Microsoft Hohm), this chapter analyzes how KMS can be used to foster behavior change. Thus it questions the role of KMS in manipulating people in business organizations. It considers the use of KM 2.0 practices by specific groups of actors to maintain or develop social domination in organizations.
CONCLUSION The chapters in this book discuss different aspects of Knowledge Management and Web 2.0 environment. Each offers a unique contribution to advance our theoretical or practical understanding of the new Knowledge Management (KM) practices in the Web 2.0 environment within and between organizations and individuals. We commend them to your reading, and hope they will inspire your research and practice. Imed Boughzala TELECOM Business School, France Aurélie Dudezert Ecole Centrale Paris, France
REFERENCES Alavi, M., Kayworth, T., & Leidner, D. (2005-2006). An empirical examination of the influence of organizational culture on knowledge management practices. Journal of Management Information Systems, 22(3), 191–224. doi:10.2753/MIS0742-1222220307 Alavi, M., & Leidner, D. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MISQ, 25(1), 107–136. doi:10.2307/3250961 Boughzala, I. (2007). Ingénierie de la collaboration: Théories, technologies et pratiques. Paris, France: Hermès. Boughzala, I. (2010). Mise en perspective de l’e-collaboration comme outil de transformation de l’organisation. HDR report in management science. University of Nantes. Boughzala, I., & Limayem, M. (2010). The new generation of knowledge management for the Web 2.0 age: KM 2.0 . In Lee, I. (Ed.), Encyclopedia of e-business development and management in the digital economy (pp. 1211–1220). Hershey, PA: IGI Global. doi:10.4018/978-1-61520-611-7.ch122 Dieng, R., Corby, O., Giboin, A., & Ribière, M. (1999). Methods and tools for corporate knowledge management. International Journal of Human-Computer Studies, 51, 567–598. doi:10.1006/ijhc.1999.0281
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Dudezert, A. (2009). Vers l’entreprise centrée connaissance ou les conditions d’efficacité de ces nouvelles formes organisationnelles. HDR report in management science. University of Nancy II. Dudezert, A., & Boughzala, I. (Eds.). (2008). Vers le KM 2.0: Quel Management des Connaissances imaginer pour faire face aux défis futurs? Collection Entreprendre Informatique, Vuibert, March 2008. Dudezert, A., Boughzala, I., & Mounoud, E. (2008, October 17). Comment intégrer la génération Millennials à l’entreprise? Etats généraux du management workshop, Sénat/Paris, France. Galbreath, J. (2002). Success in the relationship age: Building quality relationship assets for market value creation. The TQM Magazine, 14(1), 8–24. doi:10.1108/09544780210413219 Gandih, A. (2008). L’entreprise sociale: Utiliser les applications Entreprise 2.0 pour déculper la productivité des travailleurs du savoir. Oracle White Paper, CA, USA. McAdam, R., & McCreedy, S. (2000). A critique of knowledge management: Using a social constructionist model. New Technology, Work and Employment, 15(2). doi:10.1111/1468-005X.00071 McAfee, A. P. (2006). Enterprise 2.0: The dawn of emergent collaboration. Sloan Management Review, 47(3), 21–28. McElroy, M. E. (2002). The new knowledge management: Complexity, learning, and sustainable innovation. Butterworth-Heinemann. Mentzas, G. (2004). A strategic management framework for leveraging knowledge asset. International Journal of Innovation and Learning, 1(2), 115–142. doi:10.1504/IJIL.2004.003715 Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266. Nonaka, I. (1994). Dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. doi:10.1287/orsc.5.1.14 Nonaka, I. (1998). The concept of Ba: Building a foundation for knowledge creation. California Management Review, 40(3). Polanyi, M. (1966). The tacit dimension. London, UK: Routledge & Kegan Paul Ltd. Shimazu, H., & Koike, S. (2007). KM2.0: Business knowledge sharing in the Web 2.0 age. NEC Technical Journal, 2(2), 50-54. Retrieved March 8, 2009, from http://www.nec.co.jp/ techrep/en /journal/ g07/n02/ t070213.pdf Spender, J. C. (1996). Competitive advantage from tacit knowledge? In Moingeon, B., & Edmonson, A. (Eds.), Organizational learning and competitive advantage (pp. 56–73). London, UK: Sage.
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Acknowledgment
Here we, editors, wish to give a special thank you first to all the authors for their contribution to this book. Second to the Editorial Advisory Board, for their feedback regarding the content of the book. Third, the reviewers, for their help and constructive comments. Finally, thanks to IGI Global for agreeing to publish this book Imed Boughzala TELECOM Business School, France Aurélie Dudezert Ecole Centrale Paris, France
Section 1
KM 2.0 and Web 2.0 Technologies
1
Chapter 1
Collaboration 2.0 through the New Organization (2.0) Transformation Imed Boughzala TELECOM Business School, France
ABSTRACT This chapter introduces a new holistic organization transformation (i.e. Organization 2.0) caused by changes in the act of collaboration (i.e. Collaboration 2.0) due to the emergence of Web 2.0 technologies and their use by a new generation of people called Gen Y. Organization 2.0 is based on Social Capital where end-user participation, emergence of social networks and online communities, mass collaboration, and open innovation, have become new levers to put collective intelligence (e.g. crowdsourcing) at the service of the organization, to boost its performance, and to develop its creative capabilities. This chapter tries to sort out confusion that may exist between different concepts like Web 2.0, Enterprise 2.0, Collaboration 2.0, Management 2.0, KM 2.0, Organization 2.0, et cetera.
INTRODUCTION Due to the advent of Web 2.0 technologies in the last few years, new usages of information and knowledge sharing have emerged, i.e. the Enterprise 2.0 (or Enterprise Social Software) which is a new culture of technology usage. Enterprise 2.0 refers to “the use of Web 2.0, emergent social software platforms within companies, or between companies and their partners or customers” as defined initially by Andrew McAfee (McAfee,
2006) but has since evolved to cover further dimensions and areas of application (marketing 2.0, e-government 2.0, health 2.0, research 2.0, etc). The new generation of hypermodern employees (Generation Y or Gen Y) has developed new habits at work. They use everyday Web 2.0 technologies (blogs, wikis, RSS1, social networking platforms, folksonomy, podcasting, mashups, virtual worlds, etc) in the private arena and, therefore, consider that such technologies for collaboration and self-organizing are the best means/methods to
DOI: 10.4018/978-1-61350-195-5.ch001
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Collaboration 2.0 through the New Organization (2.0) Transformation
work. This generation has developed a new type of collaboration practice through intensive Web 2.0 usage, which is emergent (not planned and informal), open (indifferent to the organizational borders) and massive (implies crowds). This collaboration is called Collaboration 2.0 (Coleman & Levine, 2008; § Table 1). Collaboration 2.0 is one of the major activities in Enterprise 2.0. Indeed, these two major developments (Gen Y and Web 2.0) which co-exist today are being transforming the organization deeply towards what we called the Organization 2.0 – a social based organization (Arina 2008). The first one is thus technological with the fast emergence of the Web 2.0 technologies since 2005 (O’Reilly, 2005; Anderson, 2007) in the preamble of the new Internet age (Internet 3D, Internet of things or Ubiquitous Internet) for a Smart World (Walsh, 2001; Ma et al., 2005; Smart et al., 2007; Dodson, 2003, 2008). These technologies also called Social Media (Kaplan & Haenlein, 2010) are user (social) centered, user-friendly, intuitive, flexible, easy to install and less formal. They are participatory and personalized with a dynamic content and are generated by users themselves. Web 2.0 technologies are very useful for self-expression and mass participation, social interaction/networking, visualization of connections (relationships), information/knowledge capitalizing and co-creation, and skills and talents identification. They are affordable to all size of businesses even to the small ones. This new generation of technology has agitated the software market. It is also a good opportunity for organizations to improve best practices sharing, to boost interactions between key individuals and to encourage bottom-up and open innovation (Chesbrough & Appleyard, 2007). The second change is social with the arrival on the job market of the new generation of employees – the Generation Y (Why – i.e. eager for sense-making), Digital Natives or Milennials (Dudezert et al., 2008). A new generation of younger, college- and university-educated workers born between 1978 and 1995 and grown up with the
2
Internet. This generation succeeds to the generation X (anonymous) which came after and is less known than, the baby boomers. These employees are looking continuously for new technology and are eager to simply and quickly find good information/knowledge, anytime and anywhere and from any device; and are not intimidated by knowledge complexity and organizational hierarchy (Forrester Consulting, 2006). This new generation upsets already the traditional organization. It is also a good opportunity for it to integrate enthusiastic and creative employees. These two changes/developments together lead to a deep upheaval at all levels of the organization because they affect its fundamentals and foundations, all its actors and its environments (including all the stakeholders). This seems to be the first time since the industrial age that the organization is so affected in such way (Arina, 2008). These changes impact especially the place and role of individuals next to information and knowledge. All workers in the social age are equal in using, sharing and creating information and knowledge. Knowledge is no longer a matter of expert (Boughzala & Limayem, 2010). Connection, interaction and collaboration of individuals and the nature of their relationships are also a source of knowledge. For example, the behavior of one user on a social platform like Facebook is carrier of knowledge (by profiling, tracing: people contacted, downloads, discussions in which (s) he participated, etc). This is called the Collective Intelligence (also crowdsourcing) which refers to knowledge created from human interactions and interpersonal networking (Smith & Duin, 1994; Malone et al., 2009). All this contributes to the building of the Social Capital (Nahapiet & Ghoshal, 1998) which is the set of resources embedded within the relationships among actors within a network. In the same sense, Shimazu and Koike (2007 p.52) define Knowledge Management 2.0 (KM 2.0) as “a model that places collective intelligence at its core and promotes its use by accelerating the distribution of information”.
Collaboration 2.0 through the New Organization (2.0) Transformation
Table 1. Comparison of traditional organization and organization 2.0 (Boughzala, 2009b)
Technology (extract from Boughzala & Limayem, 2010) and usage
Organization 1.0
Organization 2.0
Web 1.0
Web 2.0
Task oriented tools
User-centered tools
Overly complex tools
Easy to use and to install tools
Rigid tools
Flexible tools
Passive with a static content
Participatory and customizable with a dynamic content
Generated by professionals
Generated by users themselves
More significant investment – usually only for large companies
Less significant investment – even for SMEs
Dedicated technologies
Collaboration IT-based features embedded in technologies
Enterprise 1.0
Enterprise 2.0
Casual use
Intensive and embedded use
Professional use
Private and professional use
Project management
Social networking and mass collaboration
Collaboration 1.0 People and Work mode
Process and Organizational structure
Collaboration 2.0
User of knowledge
Generator of knowledge
Individual action
Social participation
One-to-many
Many-to-many
Programmed information-based collaboration
Emergent and open knowledge-based collaboration
Controlling
Self-organizing
Culture of production
Culture of awareness and innovation
Reactive
Proactive
Production skills
Social and collaboration Skills
Task completion
Purpose sharing
Individualization
Socialization
Standardization
Adoption/Emergence
Structured – modeled process
Freeform – Ad-hoc process
Prescriptive in nature
Emergent in nature
Precise / predefined boundaries
Fuzzy/open boundaries
Production driven process Task oriented
Collaboration driven process Socio-emotional oriented
Siloed and opaque organization
open and transparent organization
Project teams - inclusive
Open teams – progressive Virtual teams/communities
More co-located teams
More dispersed teams
KM 1.0 InformationKnowledge
KM 2.0
Information capital Knowledge capital
Collaboration capital Social capital
Local access to information
Global/Live access to information
continued on following page
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Collaboration 2.0 through the New Organization (2.0) Transformation
Table 1. Continued Organization 1.0
Organization 2.0
Web 1.0 Knowledge Management (extract from Boughzala & Limayem, 2010) Place and role of Knowledge worker
Web 2.0
Knowledge
Knowledge, its space of socialization and holders
Impersonal and personal Knowledge
Impersonal, personal and interpersonal Knowledge
Expert knowledge
Any knowledge from any individual
Individual intelligence
Collective intelligence
Non-central
Central
Intra organizational knowledge
Intra and Inter organizational knowledge
Management 1.0 Management mode
Hierarchy
“Wirearchy” - Network
Vertical organization
Horizontal/Flat organization
Bureaucracy
Agility
Information-centric
Knowledge and People -centric
Authoritarian environment
Collaborative environment
Implied structure
Emergent structure
Long time-to-market cycles
Short time-to-market cycles
Centralization of control
Distribution of control
Separate projects
Holistic approach
Project management
Network and community animation
Decision
Influence
Project manager
Facilitator (Champion/coordinator/animator)
Top-Down planning
Bottom-up planning
Scheduled actions
On demand actions
Limited/Restricted access to the plan
Organized/Unlimited access to the plan
Limited communications within team
Unlimited communications within team
Control
Communication and empowerment
It describes the changing trends in managing knowledge in the knowledge-based society and economy built on the collective intelligence and social capital, mainly related to the interpersonal knowledge through connections and socialization (Dudezert & Boughzala, 2008). It is the new generation of KM allowing incorporated and pervasive KM for social virtual organizations. Socialization enables the conversion of tacit knowledge through direct interaction between individuals through join activities by observation, imitation, practice and linkage (Polanyi, 1966; Nonaka, 1994; Spender, 1996b).
4
Management 2.0
Confusion may exist between different concepts like Web 2.0, Enterprise 2.0, Collaboration 2.0, Management 2.0, KM 2.0, Organization 2.0, etc. The purpose of this chapter is to introduce and clearly define the concept of Organization 2.0 as the new conception of the organization or more the new generation of the organization’s model compared to the traditional one according to several organizational activities and dimensions. All these dimensions must necessarily be reconsidered and the old understanding of the organization should be revised. The bases of organization’s model have to be updated since the organization
Collaboration 2.0 through the New Organization (2.0) Transformation
is currently being metamorphosed. One ultimate research question addressed in this chapter is: •
•
RQ: How to take advantage of the technological change (Web 2.0) by adapting the organization to the social change (Gen Y) towards organizational performance and open innovation? In other words, how to adapt to the changing of Gen Y’s work modes related to their use of Web 2.0 technologies (Enterprise 2.0) without compromising the specific requirements for the survival of the modern organization?
This conceptual chapter is trying to serve as a starting point for future research and further applications in this area. It is apparent that this chapter argued several affirmations/statements and led to more questions than answers. It is hoped that it will initiate a scientific debate around Organization 2.0, its opportunities as well as the challenges that it causes. The remainder of this chapter is structured as follows. The next section introduces the Organization 2.0 model. Section 3 proposes an Organization 2.0 model compared to Organization 1.0 one according to different aspects, and dimensions.
Ways to well integrate Web 2.0 technologies and generation Y through this new organization for an optimal collaboration 2.0 are reported in section 4. The implications to companies, managers, technology designers and researchers are discussed in section 5. The chapter concludes with a summary of key directions for future research.
TOWARD AN ORGANIZATION 2.0 MODEL The main differences between the traditional organization (called Organization 1.0 afterward) and the Organization 2.0 are discussed in this section according to several dimensions. Figure 1 compares the both organization types through five key components of collaboration (Vreede et al., 2009): Information, people, processes, technologies and facilitation. This figure argues that the traditional organization is information/ knowledge centered and the Organization 2.0 is people/social centered. The five key components could also learn us about the transition from traditional Collaboration to Collaboration 2.0 (and thus also from traditional management to Management 2.0) in terms of:
Figure 1. From traditional Organization model to Organization 2.0 model (adapted from Boughzala & Limayem, 2010)
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Collaboration 2.0 through the New Organization (2.0) Transformation
•
•
6
People: The place and role of the individual are also different in the both types of organization. In the traditional organization, people (knowledge workers) are mostly users of knowledge. In Organization 2.0, every “individual” plays a more central role by consciously and unconsciously generating knowledge. People participate in the co-construction of information and knowledge contents. Thus, the notions of user participation, social networks and mass collaboration (2.0) are fundamental in the context of the Organization 2.0. The concept of collective intelligence plays a major role in its model. Consequently, new approaches of performance have to be invented. Recognition and rewarding of individuals have to done according to their social/collaboration capabilities to get in touch (connect), to federate others around an idea or a project, to share knowledge with others, and to work collaboratively (Boughzala, 2007). The generation Y is characterized by a new culture of awareness, knowledge sharing, open collaboration and innovation. Information (knowledge): The traditional organization’s model was based first on information and later on knowledge more generally. Knowledge comes mostly from experts (Individual Intelligence). In the context of Organization 2.0, knowledge originating from any individual could be interesting. Also, the nature of the relationships of individuals is a source of knowledge (Collective Intelligence). For example, with Facebook or LinkedIn – famous social platforms, people could connect with others and build personal and professional relationships through groups of interest, communities of practices and collaborations. The traditional organization is based on knowledge capital mainly com-
•
•
posed by impersonal2 and personal3 knowledge. The Organization 2.0 is based on social capital including knowledge, its space of socialization and holders (Interpersonal knowledge4). Process: In the case of the Organization 2.0, the end-user is much more involved in business processes. One speaks about selfcare when the end-user is brought to execute one part of the process at his/her own expense (Bitner et al., 2002). Airline online check-in is one good example in terms of time and internet connection. Moreover collaboration processes take a more important place in addition to traditional production processes. Informal processes became very crucial for open innovation through social linking/networking, electronic open collaboration, content sharing and knowledge co-construction. The development of Open Source Software is the best example. Like many other Internet players, Google relies heavily on online communities of practice to foster creativity and innovation. Technology: Web 2.0 technologies have agitated both work practices and the software market. The generation Y use everyday these technologies in their private arena and, therefore, consider that such technologies for self-organizing and mass collaboration are the best means to work. Social networks and online communities are for it the best resources to collective problem-solving, to get connections and partnerships and to take advantage of the collective intelligence. This generation wants to choose itself the tools it deems fit to use. These practices are disturbing in somewhat for IT managers. These new collaboration practices with an intensive use of Web 2.0 technologies are called Collaboration 2.0 (§ Table). It refers to the best practices and technologies for success-
Collaboration 2.0 through the New Organization (2.0) Transformation
•
ful collaboration for anyone, anytime, anywhere and from any device in the web 2.0 environment. Compared to Web 2.0 technologies of today which are user centered, the old Collaboration Technologies (CT, e.g. Groupware - GSS5) and Knowledge Management Systems (KMS) - task oriented, seem incredibly primitive in terms of interpersonal knowledge and socialization. These offer only limited and formal information on experts and explicit knowledge in terms of collaboration. They suffer from their lack of tools of self-expression, social interaction and visualization. These old technologies, such Intranet for example, are often passive with a static content and are generated by experts, administrators or professionals. Web 2.0 technologies are participatory and customizable with a dynamic content generated by users themselves. Old technologies are overly complex and rigid but Web 2.0 ones are flexible, pervasive and easy to use and to install. For example, anyone can create a blog in few minutes and be able to share his/her ideas with others. Launching a wiki for sharing editions is an easy task for a project team. Groupware, GDSS6 and KMS require significant investment usually only large companies can afford which is not the case with Web 2.0 technologies that are more accessible even to SMEs7. Technologies such as ERP8, SCM9, CRM10 and CAD11 have started providing tools (features) that facilitate and enable Collaboration 2.0 and KM 2.0 such as Wikis. Facilitation: In the Organization 2.0, facilitation techniques (Briggs et al., 2003) should evolve since collaboration practices and technologies have evolved too.
The Table 1 summarizes the key differences between Organization 1.0 and Organization 2.0 according to the key components of collaboration and therefore management seen above (see model proposed in Figure 1) and others related dimensions. Table 1 makes difference between Web 2.0 as a new technology, Enterprise 2.0 as new culture of technology usage, Collaboration 2.0 as new collaboration practices, KM 2.0 as a new generation of KM, and Management 2.0 as a new model of management. Other dimensions related to more holistic levels could be analyzed in the study of the Organization 2.0: organization’s values, business strategy and models, organizational structure and models, leadership, human resources management, performance management, information systems/IT implementation and management, etc (inspired from the Star Model, Galbraith, 2002). These dimensions could be treated with different perspectives: Social, managerial, technical, economic, legal, environmental, etc. Moreover the organization has undergone many changes through years. It has evolved over the two last centuries. Its characteristics have changed through the various economic ages (Galbreath, 2002). From the industrial age to the information age and after, from the knowledge age to the social age of today, the organization has not stopped changing. It is not the same nowadays (Uhl-Bien et al., 2007). In the last two decades especially ICST12 development (in society in general and in business in particular) has led to many changes in individual, group and organizational behaviors and practices (Siebdrat et al., 2009). Table 2 tries to summarize the evolution of the organization characteristics through these ages according to several aspects such as value creation, planning cycle, management structure, nature of production, key investments, etc.
7
Collaboration 2.0 through the New Organization (2.0) Transformation
All dimensions of analysis presented in this section deserve more in-depth theoretical and empirical verification in future research.
TOWARD AN OPTIMAL COLLABORATION 2.0 Ways to Integrate Web 2.0 Today’ organizations are likely to be jostled by the rapid development of Web 2.0 technologies. Three main ways to properly integrate them (Boughzala, 2009a): 1. Integrate Web 2.0 with the previous technology: Web 2.0 technologies do not replace but enrich and complete the old generation of collaboration and knowledge
technologies in terms of socialization (selfexpression, networking, interaction, sharing and collaboration) and ubiquity (connectivity, mobility and virtuality). Features to gain in collective effectiveness should to be proposed and integrated to the old generation. Integration needs to be guided (as services) with a content aggregation. Two actions have to be taken into consideration: Choosing the most appropriate technology in logic of a holistic integration and adopting a progressive deployment through a change management approach. 2. Streamlining the selection of Web 2.0 technologies and their usages: Sometimes Web 2.0 technologies bring confusing between private and professional spaces. Private use of these technologies influences necessarily the organizational productivity and perfor-
Table 2. Characteristics of the various economic ages (updated from Galbreath, 2002, cited in Torkia & Cassivi, 2008) (Note – italic police words were changed from the original table in Galbreath, 2002) Mechanical Age
Digital Age 1985+Beyond
1880-1985 Characteristic
Industrial Age
1955-2000 Information Age
1995+Beyond Knowledge Age
2003+Beyond Social Age
Basis for value creation
Products
Information
Knowledge
Networks
Strategic Planning Cycle
5 years
3 years
Continuous
Flexible and agile
Management Structure
Centralized
Decentralized
Virtual
Participatory
Key investments
Land & Machines
IS, IT and network/telecom infrastructures
Human resources and Knowledge tools
Social and Collaboration tools
Primary Strategic Resource
Raw materials
Information capital
Knowledge capital
Social capital
Nature of production
Mass production
Specialization
Mass Customization & personalization
On demand and open innovation
Economic output
Goods
Services
Experiences
Connections & partnerships
Marketing, Sales and Service
Uniformity (push)
Segmentation
1-to-1 relationships
Many-to-Many relationships
Pricing
Fixed
Flexible
Dynamic
Customized
Nature of competition
Distrust + Barriers to entry
Cooperation and Loose affiliations
Trust and Collaboration
Win-Win strategy & mass collaboration
Basis of market valuation
Book value
Revenue/earnings multiples
Value of intangible assets
Estimated value of potential customer capital
8
Collaboration 2.0 through the New Organization (2.0) Transformation
mance. Rules and policies of usage have to be clarified and specified in advance. It is therefore necessary to invent new original learning systems (adapted to the generation Y) and to implement more efficient monitoring techniques for supervising usage and controlling the “wild” tools deployment. To address this, three actions have to be taken into consideration: Studying and regulating usages according to collaboration structures and processes, making collaboration processes more transparent, and relying on champions and communication companions. 3. Studying without overestimating in advance their contributions to the organization: Web 2.0 technologies do not solve all the issues related to collaboration but could help to create a culture of sharing and job transversality, and to foster a dynamic of creativity among people. Indicators of technology adoption (usability, sociability, use frequency, duration…) have to be established and a usage monitoring is needed. Three actions have to be taken into consideration in this case: Reviewing the learning process, taking care to keep these social technologies “alive” and animated, and capitalizing on usages.
Ways to Integrate Generation Y On the other hand, today’s organizations are faced to a big challenge with the integration of the generation Y with other generations. Three main ways to properly integrate them (Dudezert et al., 2008, Boughzala, 2009a): 1. Remaking sense of collective work by moving from power relationship to seduction relationship: The employee “Generation Y” has a passionate relationship to work. (S)he is willing to invest his/her own time to learn but methods of rewarding as for the “rational” employee are totally inadequate
for him/her. It is necessary to have with him/ her a seduction oriented relationship rather than power oriented one. To address this, four actions have to be taken into consideration: Clarifying and communicating on business strategy of the organization, talking to the imagination (storytelling, metaphors…) and the emotional (recognition) of these new recruits, using the techniques of facilitation, companionship and coaching, and inventing a new balance between work and private life (flexible organization of working time, interesting facilities, etc). 2. Redesigning common work modes by moving from hierarchical organization to self-organization driven: The employee “Generation Y” uses technologies in his/her daily life, (s)he has developed the idea that social networking and self-organizing are the standard modes of working. There is a reconsideration of hierarchical relationships and task-oriented organization. The traditional management methods are thus to review. There is a need to anticipate changes to be implemented in the modes of supervising and daily management. Two actions have to be taken into consideration: Inventing new systems of performance assessment (collaboration maturity assessment, collaboration technology usage assessment…), and supervising self-organizing and open collaboration (virtual project management, technology usage assistance, empowerment and accountability). 3. Overcoming preconceived patterns of organization by changing the mental schema of managers: The employee “Generation Y” is different, not having known the socio professional world without internet. (S)he is a big user of technology and able to work remotely/virtually. (S)he did not need to be in collocation to work effectively, share knowledge and co-innovate. (S)he uses collaboration technologies, social networks
9
Collaboration 2.0 through the New Organization (2.0) Transformation
and online communities for that. His/her collaboration network does not end at the organization’s borders. (S)he is ready to share with anyone in a win-win logical. Work modes have to evolve in order to adapt to such networking. There is thus a need to understand his/her habits and way of thinking. Three actions have to be taken into consideration in this case: To propose him/her the forefront technology for his/her mobility, to provide a suitable formal framework for remote working, and to establish new indicators of individual and collective performance.
•
IMPLICATIONS Implications to Companies The emergence of Organization 2.0 model, due to these Collaboration/KM 2.0 practices, will affect companies on the following but not limited dimensions: •
10
Social dimension: Socialization is the most important mode of knowledge creation in the Organization 2.0. Social networks, hubs, online communities and virtual world collaborations are the main important instruments in which organizations should invest to manage their knowledge and enhance their creativity and innovation. This leads to answer several questions such as: How to manage/control effectively these new organizational forms? Which means and strategies to adopt? Etc. In addition, generation Y is taking over. These individuals are familiar with collaboration 2.0; But how to integrate this generation in current traditional organizations? How to manage their behavior through the use of technologies? How to solve problems related to generation gaps? Etc.
•
Managerial dimension: In the Organization 2.0, several modes of management should change. Specifically, recruiting methods, training and tutoring, monitoring and revaluating performance, career development and change management must change. Not only are the technologies changing, but also the attitudes/ behaviors of employees, work methods and skills, distribution of teams, etc. So, what will be the impact on organizational performance? Which profile should the manager of tomorrow have? For that profile, some companies like Google try to hire the leaders of MMORPG13’ Guilds (very suitable for collaboration 2.0); which kind of skills could be transferred from virtual to real life? Several companies such Dell, Microsoft, Accenture, are using serious games to train this new generation, but how designing good games to ensure effectiveness of training? Etc. Also, Y employees do not feel identified with any particular organization in the long term. So which means to retain them? Which type facilities should companies provide them? They confuse the private and professional use of technology. How then to allocate costs? How to evaluate collaboration maturity and performance? Etc. Economic dimension: Organization 2.0 model could affect business models since products and services are also changing. Similarly, inter-organizational relationships could also evolve. Through the Organization 2.0, customer/supplier and partners relationships are not the same. The investment in terms of acquisition of technologies may be less but much more in terms of data security, information privacy and confidentiality; so how to take a competitive advantage from these technologies? How to measure ROI? Etc.
Collaboration 2.0 through the New Organization (2.0) Transformation
•
•
Technological dimension: The technologies should be more adequate for connecting people, network emergence, mass collaboration and open innovation. Compared to the previous generation of technologies they have to offer much more possibilities in terms of monitoring, mobility, ubiquity and virtuality. Several questions related to technologies arise in this case: How to select the best technologies? How to ensure their integrity, interoperability and scalability? How to adapt training? How will other communication technologies, such as PDAs14, GPS15 and Cell phones, integrate Web 2.0 technologies? What security problems need to be taken in to account? Etc. Legal and ethical dimensions: In the Organization 2.0, some legal problems could be associated with information leakage, especially when people mix the private sphere with their professional activities. This could be revealing of strategic business information. This leads to answer several questions such as: How to control the flow of information? Should this be specified in the work contracts? Generation Y is used to work remotely. How contracts should take this into account? Etc. In this new organization, personal information is extracted through ICT16 sometimes without informing the user may pose ethical problem in terms of trust and Information Privacy; but how to make this transparent? Etc. Organization 2.0 involves much more informal and formal exchanges and knowledge sharing between people and partners. This raises the problem of Intellectual Propriety and Value Creation Sharing. The question is how to take into account this problem? Who owns the value that is created? How to manage this knowledge sharing which seems profitable for innovation but delicate to term? Etc.
•
•
Ecological dimension: With a focus on the interaction of people, identity, knowledge, and environmental factors as a complex adaptive system akin to a natural ecosystem, how to manage this within organizations and inter organizational networks? Etc. In the Organization 2.0, the use of technologies is intensive. This leads to less travels and associated costs; But is this really ecological? Is it not compensated by the deployment of the technological infrastructure and energy consumption? Etc. Cultural dimension: Culture has to be taken into account in Organization 2.0 studies as in the business models (provided products and services), the choice and design of collaboration tools, modes of management, motivation, incitement, generational gap, etc; But how this new organization integrate the culture of individuals? How to take advantage from culture diversity? How to build a culture of sharing that exceeds predominant individualism? Etc.
All these are important questions among others that are not yet answered.
Implications to Research From a research point of view, Collaboration 2.0/KM 2.0 and wider Organization 2.0 will lead to several interesting research questions for researchers. Besides issues and challenges such as mastering the scope of 2.0 domain and giving concrete answers to companies to take advantage of this new practices and organizational model that researchers face. Research interested in this may investigate the following issues: •
Theory (conceptual frameworks, models, methods, etc); Collaboration/KM/ Organization 2.0 presents an area of new theoretical interest. Maybe some theories
11
Collaboration 2.0 through the New Organization (2.0) Transformation
• •
(such as Social Presence theory (Short et al., 1976; Gunawardena, 1995), Media Richness theory (Daft & Lengel, 1986), Media synchronicity theory (Dennis & Kenny, 1998), etc) have to be adapted/reviewed and others to be proposed. Experimentation (field experiments, simulations, etc); Observation (usage, best practices, field studies, etc).
The Collaboration/KM/Organization 2.0 research could: •
•
•
•
•
Be pluri-, inter- and trans disciplinary covering Management Science, Information Systems, Computer and Information Science, Sociology, Behavior Science, Education, etc; Use several methods/methodologies: Qualitative and quantitative analysis, grounded theory, design science, etc. Be tackled from different dimensions: Social (behaviouristic), managerial (organizational learning), economic, technological (techno-centric), ethical (intellectual propriety), ecological (ecosystem), etc. Be related to different epistemological perspectives: Critical, Logical, Positivist or Interpretivist. Open to many future avenues in Management Science (Business strategy, organizational models, etc) Information Systems (usages) and Computer Engineering (new technologies).
Implications to Technology Designers Collaboration 2.0 and Organization 2.0 model requires significantly different technologies. Provided technologies are not defined by the richness of their features or the complexity of processes but by their ability to capture interpersonal knowledge
12
and implicit connections between people, data and systems. These technologies enable mass collaboration and promote the emergence of communities and social networks to enhance open participative innovation. They are indifferent to organizational identities and organization’s borders, structures and cultures. From a technology design point of view, Collaboration/KM/Organization 2.0 will be based on areas such as Social, Mobile, Ubiquitous, Grid, Cloud Computing, Ambient Technology, Virtual Reality, Computing, haptic technologies, 3D Social Virtual Worlds (Hendaoui et al., 2008), Green Technologies, etc. In the future, it will benefit more from Ontology Techniques, Semantic Web, Agent-based Intelligent Engines, etc. Someone’s speak already about Enterprise 3.0 which refers to the use of web 3.0 (semantic web) in the context of the intended enterprise (cross organizational collaboration).
CONCLUSION AND PERSPECTIVES It is our strong believe that the Organization 2.0 is not related to a passing 2.0 fashion (buzz word) but a real future organizational transformation. The use of SVW, 3D Internet and Internet of Things will grow. Organization 2.0 will certainly benefit from this technological evolution and vice versa. With the notion of Smart World (Ma et al., 2005) both real and virtual worlds become twin worlds (hybridization of real and virtual worlds). Perhaps in ten years we all live in a smart world and use smart devices. Every object around us will have an identity and controlled from anywhere. Not only people but also objects can communicate with each other and with people. This concept of Smart World will in turn increasingly shape up, and is not possible without effective and efficient organizations. Maybe we will speak about “Smart Organization” in the x.0 age with the generation Z (2000-). It goes without saying that all this evolution will have direct and profound impacts on
Collaboration 2.0 through the New Organization (2.0) Transformation
other related domains such e-business, marketing, finance, e-government, health care, etc. In this chapter, we tried to introduce and define the concept of Organization 2.0 as the novel model of organization for the new Web age caused by new collaboration practices related to a new generation of employees. It is true that this model can leverage the collective intelligence in sharing and co-creating knowledge, building social capital and fostering innovation, but it also presents several risks associated with the use of Web 2.0 technologies and also with characteristics of Generation Y. Indeed, the poorly framed use of Web 2.0 technologies could be cons-productive and a source of abuse: Lack of accuracy and unbiasness of content, waste of working time, misuse, information overload, overflowing, security and privacy, etc. Also, generation Y could be source of problems. Less monitored, it could contribute to anarchy, loss of power for managers, information leakage, isolation, generational conflicts, development of their only own knowledge, etc. Consequently and finally, the integration of generation Web 2.0 technologies led to improved collaboration practices and therefore innovation under conditions. On the other hand, the integration of Generation Y led to a major organizational change with all the risks that it may cause. There is a need among others of: Tailoring information systems, reinventing the traditional KM (KM 2.0, see Boughzala & Limayem, 2010), adapting performance assessment systems, taking into consideration the cultural diversity at the managerial and technological levels, and making innovation a primary concern of the organization.
REFERENCES Anderson, P. (2007). What is Web 2.0? Ideas, technologies and implications for education. JISC Technology and Standards Watch. Retrieved from http:// www. jisc. ac. uk/ media/ documents/ techwatch/ tsw0701b.pdf
Arina, T. (2008). The vision of the future Organization 2.0. Retrieved from http:// www. slideshare. net/infe/vision-of-the-future-organization-20presentation Bitner, M., Ostrom, A., Meuter, M., & Clancy, A. (2002). Implementing successful self-service technologies. Academy of Management, 16(4). Boughzala, I. (2007). Ingénierie de la collaboration: Théories, technologies et pratiques. Paris, France: Hermès. Boughzala, I. (2009a). Vers une Organisation 2.0 centrée sur l’intelligence collective et le capital social, Atelier de l’ANVIE: Manager la performance collaborative à l’heure du 2.0. Paris, 1 octobre 2009. Boughzala, I. (2009b). L’organisation 2.0 dans une société numérique en plein essor. Colloque international La recherche en sciences de gestion: défis et enjeux, 40ème anniversaire de l’ISG, 12 décembre 2009. Tunisie: Gammarth. Boughzala, I., & Limayem, M. (2010). The new generation of knowledge management for the Web 2.0 age: KM 2.0. In Lee, I. (Ed.), Encyclopedia of e-business development and management in the digital economy (pp. 1211–1220). Hershey, PA: IGI Global. doi:10.4018/978-1-61520-6117.ch122 Briggs, R. O., de Vreede, G. J., & Nunamaker, J. F. Jr. (2003). Collaboration engineering with ThinkLets to pursue sustained success with group support systems. Journal of Management Information Systems, 19(4), 31–64. Chesbrough, H., & Appleyard, M. (2007). Open innovation and strategy. California Management Review, 50(1), 57–76. Coleman, D., & Levine, S. (2008). Collaboration 2.0: Technology and best practices for successful collaboration in a Web 2.0 world. Happy About.
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de Vreede, G.-J., Briggs, R. O., & Massey, A. P. (2009, March). Collaboration engineering: Foundations and opportunities. Journal of the Association for Information Systems, 10(Special Issue), 121–137. Dennis, A., & Kinney, S. (1998). Testing media richness theory in the new media: The effects of cues, feedback, and task equivocality. Information Systems Research, 9(3), 256–274. doi:10.1287/ isre.9.3.256 Dodson, S. (2003, October 9). The Internet of things. The Guardian. Retrieved from http:// www.guardian.co.uk/technology/2003/oct/09/ shopping.newmedia Dodson, S. (2008 October 16). The net shapes up to get physical. The Guardian. Retrieved from http://www.guardian.co.uk/technology/2008/ oct/16/internet-of-things-ipv6 Dudezert, A., & Boughzala, I. (Eds.). (2008). Vers le KM 2.0: Quel Management des Connaissances imaginer pour faire face aux défis futurs? Collection Entreprendre Informatique, Vuibert, Mars 2008. Dudezert, A., Boughzala, I., & Mounoud, E. (2008, Octobre 17). Comment intégrer la génération Millennials à l’entreprise? Etats généraux du management workshop, Sénat/Paris, France. Forrester Consulting. (2006). Is Europe ready for the millennials? Innovate to meet the needs of the emerging generation. Retrieved February 25, 2009, from http://www.ffpress.net/Kunden/XER/ Downloads/XER87000/XER87000.pdf Galbraith, J. R. (2002). Organizing to deliver solutions. Special Issue, Organizational Dynamics. Retrieved from http://www.moderntimesworkplace.com/good_reading/GRLearn/Hybrid. Product.Customer.Org.pdf
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Galbreath, J. (2002). Success in the relationship age: Building quality relationship assets for market value creation. The TQM Magazine, 14(1), 8–24. doi:10.1108/09544780210413219 Gunawardena, C. N. (1995). Social presence theory and implications for interaction and collaborative learning in computer conferences. [Charlottesville, VA: AACE.]. International Journal of Educational Telecommunications, 1(2), 147–166. Hendaoui, A., Limayem, M., & Thompson, C. W. (2008). 3D social virtual worlds: Research issues and challenges. IEEE Internet Computing, 12(1), 88-92. ISSN 1088-7801/08 Kaplan, A., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. doi:10.1016/j.bushor.2009.09.003 Ma, J., Yang, L., Apduhan, B., Huang, R., Barolli, L., & Takizawa, M. (2005). Towards a smart world and ubiquitous intelligence: A walkthrough from smart things to smart hyperspaces and UbicKids. International Journal of Pervasive Computing and Communications, 1(1), 53–68. doi:10.1108/17427370580000113 Malone, T., Laubacher, R., & Dellarocas, Ch. (2009). Harnessing crowds: Mapping the genome of collective intelligence. MIT Center for Collective Intelligence, Working Paper No. 2009-001. McAfee, A. P. (2006). Enterprise 2.0: The dawn of emergent collaboration. Sloan Management Review, 47(3), 21–28. Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266. Nonaka, I. (1994). Dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. doi:10.1287/orsc.5.1.14
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O’Reilly, T. (2005), What is Web 2.0: Design patterns and business models for the next generation of software. O’Reilly Media. Retrieved from http://www.oreillynet.com/pub/a/oreilly/ tim/news/2005/09/30/what-is-web-20.html
Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18(4), 298–318. doi:10.1016/j.leaqua.2007.04.002
Polanyi, M. (1966). The tacit dimension. London, UK: Routledge & Kegan Paul Ltd.
Walsh, A., & Bourges-Sevenier, M. (2001). Core Web 3D. London, UK: Prentice-Hall. Print.
Shimazu, H., & Koike, S. (2007). KM2.0: Business knowledge sharing in the Web 2.0 age. NEC Technical Journal 2(2), 50-54. Retrieved March 8, 2009, from http:// www. nec. co. jp/ techrep/ en/ journal/ g07/n02/t070213.pdf
KEY TERMS AND DEFINITIONS
Short, J. A., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. New York, NY: J. Wiley & Sons. Siebdrat, F., Hoegl, M., & Ernst, H. (2009). How to manage virtual teams. Sloan Management Review, 50(4), 63–68. Smart, E. J., Cascio, J., & Paffendorf, J. (2007). Metaverse roadmap overview. Smith, J., & Duin, A. (1994). Collective intelligence in computer-based collaboration. Lawrence Erlbaum Associates Publishers. Spender, J.-C. (1996a). Competitive advantage from tacit knowledge? In Moingeon, B., & Edmonson, A. (Eds.), Organizational learning and competitive advantage (pp. 56–73). London, UK: Sage. Spender, J.-C. (1996b). Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, 17(Winter special issue), 45–62. Torkia, E., & Cassivi, L. (2008). E-collaboration: A dynamic enterprise model. In Kock, N. (Ed.), Encyclopedia of e-collaboration. Hershey, PA: Information Science Reference.
Collaboration 2.0: A new collaboration practices in the 2.0 era. This mass collaboration is open and emergent with an intensive use of Web 2.0 technologies, for anyone, anytime, anywhere and from any device, such as blogs, wikis, mashups, multimedia sharing, virtual worlds, etc. It refers to the technology and best practices for successful collaboration in the web 2.0 environment. Collective Intelligence: Refers to knowledge created from human interactions and interpersonal networking. Enterprise 2.0 or Enterprise Social Software: The use of Web 2.0, emergent social software platforms within companies, or between companies and their partners or customers. Generation Y: A new generation of younger, college- and university-educated workers born between 1980 and 2000 and grown up with the Internet, also known as Digital Natives or Millennials. KM 2.0: The new generation of KM allowing incorporated and pervasive KM for social and virtual organizations. Open Innovation: Is a new paradigm that assumes that firms can and should use external and internal ideas, and external and internal paths to market (Chesbrough & Appleyard, 2007). Organization 2.0: A social organization based on collective intelligence and social capital. It is the new conception of the organization or more the new generation of the organization’s model
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Collaboration 2.0 through the New Organization (2.0) Transformation
compared to the traditional one according to several organizational activities and dimensions. Social Capital: The set of resources embedded within the relationships among actors within a network. Socialization: Enables the conversion of tacit knowledge through direct interaction between individuals through join activities by observation, imitation, practice and networking. Web 2.0: The second generation of web development and design based on social software.
3
4
7 8 9 5 6
12 10 11
ENDNOTES 2 1
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Really Simple Syndication Impersonal knowledge consists of ideas and information made explicit in documents and files (explicit knowledge).
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16 14 15
Personal knowledge which is tacit and stored in the brains (tacit knowledge). Interpersonal knowledge which is communicated implicitly in the conversations and connections of people (implicit knowledge). Group Decision Systems Group Decision Support Systems Small and Medium Enterprise Enterprise Resource Planning Supply Chain Management Customer Relationship Management Computer-Aided Design Information and Communication Science and Technology Massively-Multiplayer Online Role-Playing Game Personal Digital Assistant Global Positioning System Information and Communication Technology
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Chapter 2
Exploring the Impact of Web 2.0 on Knowledge Management Thomas Bebensee Google Ireland Ltd., Ireland Remko Helms Utrecht University, The Netherlands Marco Spruit Utrecht University, The Netherlands
ABSTRACT Web 2.0 and Knowledge Management (KM) have a considerable overlap. It appears promising to apply Web 2.0 applications for supporting and improving sharing and creation of knowledge. Yet, little research examining the impact of Web 2.0 on KM has been conducted. This chapter presents research examining the suitability and impact of Web 2.0 applications on KM in organizations. Two extensive exploratory case studies were conducted involving 11 interviews with key personnel of two student-run organizations. It is demonstrated how Web 2.0 applications can be used for a number of KM practices mostly related to the areas of asset management and knowledge creation and innovation. Moreover, they suggest that among all the Web 2.0 principles, User-Generated Content and Unbounded Collaboration exert the biggest influence on creating and sharing of knowledge within organizations. The study contributes to the general understanding of how Web 2.0 and KM practices can be interlinked with each other.
INTRODUCTION Today, an increasing amount of organizations recognize the importance of their workforces’ knowledge as assets leveraging competitive advantage (Drucker, 1999). This development gave rise to the emergence of Knowledge Management (KM). The KM discipline describes how knowledge-intensive organizations can develop
a strategy and design an approach to manage the creation, sharing and application of knowledge in order to perform better and reach their overall strategic goals (Dalkir, 2005). After the dot-com crash in 2001, a new trend emerged on the Web that is often referred to as “Web 2.0” (O’Reilly, 2007). Although the name suggests a new release in a technical sense it is rather a new approach of how users and devel-
DOI: 10.4018/978-1-61350-195-5.ch002
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Exploring the Impact of Web 2.0 on Knowledge Management
opers face the Web. The key idea of Web 2.0 is putting the user at the center. It enables people to participate, collaborate and interact with each other. Web 2.0 has become a mass phenomenon. The social-networking site Facebook counts more than 400 million active users (Facebook, 2010), exceeding the population of USA, and the collaborative encyclopedia Wikipedia contains more than 15 million articles (Wikipedia, 2010) created by a collective of internet users. As Web 2.0 applications have brought about significant change to how we use the Internet nowadays, companies have begun adopting Web 2.0 applications such as wikis and social networking for leveraging and improving their core processes often referred to as “Enterprise 2.0” (Chui, Miller, & Roberts, 2009). McAfee states “Enterprise 2.0 tools have the potential to usher in a new era” (McAfee, 2006). As more than half of the 2,800 executives surveyed 2007 by McKinsey indicate that they are satisfied with their companies’ return on investment in Web 2.0 technologies, adopting Web 2.0 applications also seems to be interesting from an economic point of view. One of KM’s key aspects is also concerned with fostering interaction and collaboration, commonly referred to as “Socialization” (Nonaka, 1994). According to Levy (2009) KM and Web 2.0 are considerably close to each other. Therefore, it seems interesting to apply Web 2.0 principles to KM. Could this potentially lead to a new era of KM, a “Knowledge Management 2.0” that changes our understanding of it in a similar way as Web 2.0 changed our understanding of the Web? A literature research revealed a number of publications describing the implications of Web 2.0 on KM (cf. Hustad & Teigland, 2008; Levy, 2009). However, none of them has systematically studied the impact of Web 2.0 applications on KM. This is where this research joins in. By conducting two extensive exploratory case studies in organizations that use Web 2.0 applications for KM, we would like to shed light on the following research question:
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How can organizations use Web 2.0 applications for managing knowledge and which impact can they have on organizational KM? The research contributes to the general understanding of how Web 2.0 applications can be used to support or enable KM. The results are captured in a framework of Web 2.0 applications, the KM 2.0 Spectrum, and an impact model, the KM 2.0 Impact Model. The KM 2.0 Spectrum can be used as an orientation by organizations that are interested in bolstering up their KM practices by adopting Web 2.0 applications. It provides an overview of the KM aspects that may benefit from Web 2.0 applications. They are provided with suggestions and insights into which Web 2.0 applications can be used for KM. From a scientific point of view, the research contributes to the general understanding of Web 2.0 by proposing a model that relates different aspects of Web 2.0 with each.
BACKGROUND This section introduces the main concepts related to the research question: KM and Web 2.0. Furthermore, related literature on Web 2.0 in the context of KM is summarized and discussed. Finally, we introduce some literature concerning the impact of technology on organizations that we use as a basis for the impact model that will be introduced later on.
KNOWLEDGE MANAGEMENT In today’s economy increasingly more companies base their competitive advantage on what they know, how efficiently they use what they know and how quickly new knowledge can be acquired and used (Davenport & Prusak, 1998). These developments have led to emergence of the KM discipline that can be defined as follows:
Exploring the Impact of Web 2.0 on Knowledge Management
Knowledge management is the effective learning process associated with exploring, exploitation and sharing of human knowledge that use the appropriate technology and cultural environments to enhance an organization’s intellectual capital and performance. (Jashapara 2004)
tion. Tacit knowledge, in contrast, encompasses experiences, insights, and intuition. It is difficult to formalize and share this kind of knowledge.
Although its name may suggest something else, KM is not so much about managing knowledge but rather about managing knowledge-related processes. Knowledge management is more than information or document management. Additionally, it is not only focused on technology but also involved with cultural aspects. A general goal of KM is “to leverage knowledge to the organization’s advantage” (Nichols, 2000 cited by Dalkir, 2005, p. 4). KM programs aim at retaining knowledge in organizations when people retire (DeLong, 2004) and manage those processes effectively that help the organization to create and share knowledge. Scholars distinguish between two types of knowledge: explicit and tacit knowledge (Nonaka, 1994; Polanyi, 1966). Explicit knowledge can be expressed in numbers and words. It can be easily formalized and shared within an organiza-
There are numerous models that describe the major steps in the capturing, creation, codification, sharing, accessing, application and reuse of knowledge within and between organizations (Dalkir, 2005, p. 25). Based on the KM cycles of Bukowitz and Williams (1999), McElroy (1999), Meyer and Zack (1996) and Wiig (1993) and her experience in the KM field Dalkir (2005) proposes an integrated KM cycle that is shown in Figure 1. After knowledge has been captured from internal or external knowledge sources (previously unknown knowledge or know-how) and/or has been created, it has to be assessed according to the relevancy for the organization. Subsequently, knowledge is shared within the organization. Before it can be used by people it has to be contextualized in order to correspond to their needs. As people make use of the knowledge, the KM cycle will be restarted and people may contribute
Knowledge Management Processes and Practices
Figure 1. An integrated KM cycle (Dalkir, 2004, p. 43)
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Exploring the Impact of Web 2.0 on Knowledge Management
new insights and signal if the knowledge is not applicable anymore and needs to be updated. There are a number of KM practices related to the major KM processes. Binney (2001) came up with a framework that brings together various KM theories, tools and techniques discussed in literature. Binney refers to his framework as the KM Spectrum and it is depicted in Figure 2. Many of the KM practices that Binney refers to are rather technical. One might even argue that some of them, especially the ones on the left hand side of the spectrum, are more data analysis or information management applications. One of Binney’s own observations is that there is a tendency in the spectrum that reaches from a technologist viewpoint to a organizational theorist viewpoint. This goes along with a focus on explicit knowledge on the left hand side and more tacit knowledge on the right hand side. As pointed out in the definition of KM that we referred to earlier, KM is about both technology and culture. It is important to that technology should merely be a mean and not a goal in itself. In the context of KM, technology should support different KM practices in order to help an organization achieve its ultimate goal. As Binney’s KM spectrum provides an extensive overview of possible KM practices, we
will use it as a starting point for examining the KM functions of the case organizations and then determine in which way Web 2.0 applications can be used for facilitating these practices.
Web 2.0 A glance at Google’s search history shows an increasing interest for the term “Web 2.0” since its emergence in the early 2000s. This shows the term’s popularity but what does it actually stand for? Musser and O’Reilly introduce it as “a set of economic, social, and technology trends that collectively form the basis for the next generation of the Internet” (Musser & O’Reilly, 2006). However, some scholars argue that Web 2.0 is merely a meaningless marketing buzzword (Brodkin, 2007). It seems necessary to further illuminate it and its context in order to come up with a clearer definition of the concept. In 2004, the term gained popularity when O’Reilly Media and MediaLive initiated the first Web 2.0 conference (O’Reilly, 2007). O’Reilly and others (Hoegg, Meckel, Stanoevska-Slabeva, & Martignoni, 2006; McAfee, 2006; Vossen & Hagemann, 2007) came up with a number of general principles describing the properties of Web 2.0. Knol, Spruit and Scheper (2008)
Figure 2. Spectrum of KM applications (Binney, 2001)
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Exploring the Impact of Web 2.0 on Knowledge Management
compared the principles proposed by different authors and proposed a generic set of Web 2.0 principles (they refer to them as Social Computing Principles). They further point out that those generic principles are either technology-oriented or socially-oriented. The four technology-oriented principles are intuitive usability, enabling services, lightweight models and open platform. The five socially-oriented principles are user-generated content, network effects, collective intelligence, unbounded collaboration and leverage the long tail. The phenomenon of Web 2.0, i.e. what you can see about it, can be mainly related to the socially-oriented principles that are enabled by a set of Web 2.0 Technologies. Therefore, we propose the following definitions based on the Web 2.0 principles: Web 2.0 is the reorientation of the Web that promotes unbounded interaction, collaboration and participation of people. It is characterized by the emergence of a large amount of content generated by a collective of Internet users. It harnesses networking effects and leverages the long tail. Web 2.0 Technologies are technologies that transform the Web into a platform spanning all connected devices. They enable the creation of web-services and applications, constructed from lightweight models, and can be used intuitively.
Web 2.0 Applications The Internet is a very dynamic place where nearly every day new services and applications appear and others disappear. As things change so quickly, we will refer to generic types of services and applications rather than specific ones in the following. A general difficulty that we encountered while reviewing literature like Chui et al. (2009) and Andersen (2007) is finding a good scope of looking at these services and applications. Chui et al. list a number of “Web 2.0 technologies” which encompass both web-services (e.g. social
networking, wikis) but also function sub-aspects of them (e.g. commenting, tagging, polling etc.). Andersen speaks about “Web 2.0 services and applications” and describes it main characteristics. For the sake of simplicity, we will refer to these applications, services and technologies solely as “Web 2.0 applications” in the following. Table 1 lists a number of Web 2.0 applications that we derived from Andersen (2007) and Chui et al. (2009) and some examples of these applications.
Towards the Web 2.0 Layer Model In order to determine the importance of the socially-oriented Web 2.0 principles for each type of Web 2.0 application, we associated them with each other. The result of this matching is shown in Table 2. In Figure 3 the Web 2.0 Layer Model is shown. This model combines the three principal aspects of Web 2.0 with each other by depicting them in different layers. The technology-oriented Web 2.0 principles represent the fundament of Web 2.0 and therefore are depicted in the bottom. Based on these principles a number of Web 2.0 applications, as depicted in the middle layer of the model, have emerged. The socially-oriented Web 2.0 principles are related to social behavior that is enabled by Web 2.0 applications. Different colors are used to make clear which socially-oriented Web 2.0 principles describe the characteristics of each Web 2.0 application.
Towards an Impact Model of Knowledge Management 2.0 This section explains how we determined the impact of Web 2.0 applications on KM practices in case studies in two student-run organizations. In addition, it introduces the KM 2.0 Spectrum, an overview of Web 2.0 applications for KM, and the KM 2.0 Impact Model that is based on the findings from the two case studies.
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Exploring the Impact of Web 2.0 on Knowledge Management
Table 1. List of generic Web 2.0 applications Chui et al.
Andersen
Generic Web 2.0 application
Examples
Wikis
Wikis
Wiki
www.wikimedia.org www.twiki.org
Shared workspaces
Collaborating Replicate office-style software
Shared workspace
www.google.com/docs
Blogs
Blogs
Blogging
www.blogspot.com www.wordpress.com
Tagging social bookmarking
Tagging and social bookmarking
Social bookmarking
www.digg.com del.icio.us
Social networking
Social Networking
Social networking
www.facebook.com www.orkut.com www.myspace.com www.twitter.com
Podcasts Videocasts
Multimedia sharing Audio blogging and podcasting
Media sharing
www.youtube.com www.picassa.com www.flickr.com
Assessing the Impact of Technology on Organizations By applying Giddens (1976, 1979, 1984) theory of structuration to the specific context of technology in organizations, Orlikowski (1992) presents a theoretical model that conceptualizes the interaction between technology and organizations. In contrast to previous works that tried to conceptualize this relation, she introduces two important notions; the duality of technology, i.e. technology is not only shaped by humans but also shapes humans’ actions, and the interpretive flexibility of technology, i.e. the outcome of applying technology depends on the actors and the social-historical context it is applied to. DeSanctis and Poole (1994) further developed Structuration Theory to provide a set of concepts to examine technology induced change, which they call Adaptive Structuration Theory (AST). AST extends Structuration Theory for technological impact by considering the mutual influence of technology and social processes. They propose a model that summarizes the major constructs and propositions of AST and apply it to analyze the impact of group decision support systems
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on small group’s decision making processes but “the concepts and relations posited [there] could be applied to other advanced technologies and other organizational contexts” (DeSanctis & Poole, 1994). After exploring which Web 2.0 applications are used for KM (sub-research question 5) and formalizing the findings by mapping them to Binney’s (2001) KM spectrum, we used some of DeSanctis and Poole’s (1994) propositions and constructs to design our research, which is expressed by the questions of the case study protocols. These questions are used to derive some factors describing the potential impact of Web 2.0 applications on organizational KM practices.
Determining Impact Factors AST proposes that the use of advanced information technologies has two types of impacts on organizations. First, it has an impact on process outcomes and second, it leads to the creation of new social structures, i.e. rules and resources, within in the organization. In the case studies we determined how using Web 2.0 applications impacted process outcomes
Exploring the Impact of Web 2.0 on Knowledge Management
Table 2. Web 2.0 applications and principles (reasons indicated if associated) 1 – Unbounded Collaboration
2 – Collective Intelligence
3 – UserGenerated Content
4 – Network Effects
Wiki
Time and location not important for contributions
Snippets from many contributors
Content from users
Many contributors necessary to produce high quality
Social Bookmarking
Time and location of people is not important
Generates intelligence from users’ contributions
Users share bookmarks
Many contributors necessary to benefit from automatic suggestions etc.
Shared Workspace
Collaboration independent from time and space possible
Used for generating content by user
Blogging
Linking and commenting on each other’s posts independently from time and space
Enables every user to publish
People may only write a blog if others do as well and the blog is read by many
Media Sharing
Time and location not important
Enables every user to publish
People may only share media content if others do as well and the content is viewed by many
Social Networking
Interaction independent from time and space
User may contribute and share content
Many users necessary to make it work
5 – Leverage the Long Tail
Each post may add a micro value for people
Figure 3. Web 2.0 Layer Model
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Exploring the Impact of Web 2.0 on Knowledge Management
in the context of KM. The different aspects of KM are captured by Binney’s (2001) KM spectrum that we used for analyzing each case organization’s KM function. In addition, we identified new social structures that have emerged as a consequence of using Web 2.0 applications for a specific KM aspect.
Process Outcomes According to DeSanctis and Poole (1994) it is difficult to make “clear-cut predictions about how advanced information technology structures will be appropriated, or what the ultimate outcomes of that appropriation will be”. They assume that the expected outcomes are more likely to be found under ideal circumstances. Although it cannot be expect that ideal outcomes are found for adopting Web 2.0 application in KM, we think that interviews with key personnel can give a good indication of how these applications impact certain process outcomes. As AST proposes to look at the process outcomes (1) efficiency, (2), quality and (3) commitment, we adopted these and investigated for each aspect of the KM spectrum that is facilitated by Web 2.0 applications whether there is an increase in efficiency, an improvement of quality and/or an increased commitment towards the KM aspect.
New Social Structures DeSanctis and Poole (1994) define structuration as “the act of bringing the rules and resources from an advanced information technology or other structural source into action”. In the context of this research structuration takes place when people use Web 2.0 applications for specific aspects of KM (as summarized in Binney’s (2001) KM spectrum). It could be assumed, for instance, that the appropriation of Web 2.0 applications reduces the number of physical meetings and leads to new ways of coming together to share information and ideas.
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For each KM aspect that is facilitated by Web 2.0 applications we determined if new social structures had emerged. For instance, this could be new types of behaviors (rules), or new resources that can be used for the respective aspect of KM. Table 3 sums up the potential impacts that we look at for each practice of KM that we identified in the case organizations.
CASE STUDIES In order to answer the research question, case studies were conducted in two of Germany’s largest student-run organizations: AIESEC and MARKET TEAM. The case studies involved a number of semi-structured interviews with key personnel, a study of internal documents and a review of the used information systems. Case studies have be become a common research instrument used in social sciences (Yin, 2008) but also in information systems research (Benbasat, Goldstein, & Mead, 1987; Darke, Shanks, & Broadbent, 1998). As pointed out by Dul and Hak (2008, p. 4), case study research (CSR) generally involves only one single instance or sometimes a small number of instances. CSR is a research method that is applicable in situations where a number of variables are to be observed in a real life context and where this observation cannot simply be limited to an analysis of data
Table 3. List of potential impact factors of using Web 2.0 applications for different KM aspects Impact
Description
Efficiency
In which way has efficiency of the respective KM practice increased?
Quality
In which way has the quality of the respective KM practice’s outcome improved?
Commitment
In which way have people become more committed towards the KM practice?
New social structures
Which new social structures (rules and/or resources) have emerged?
Exploring the Impact of Web 2.0 on Knowledge Management
points (Yin, 2008, p. 18). It can involve both qualitative and quantitative evidence and is especially applicable to real-life situations that are too complex for survey and experimental research (Yin, 2008, p. 19). A recent study published by Pew Research Institute shows that the largest group of people (30%) using the Internet, in fact, consists of people born between 1977 and 1990 (Jones & Fox, 2009). In a 2009 article on Web 2.0’s implications on KM, Levy (2009) proposes to use people in this age as pioneers of Web 2.0 in organizations to leverage KM practices since “the younger generation finds the changes natural and or probably even waiting for the Web 2.0 tools to be available in the enterprise.“ (Levy, 2009) Obviously, the generation of today’s students is the most active group of Internet users and thus most familiar with the new technologies of Web 2.0. We therefore think that student-run organizations are an interesting subject for researching the implications of Web 2.0 on KM practices.
Case 1: AIESEC Germany AIESEC has over 45,000 members globally, whereof more than 2,500 are from 47 local chapters (LC) in Germany. The organization aims at developing tomorrow’s socially responsible leaders by running an integrated leadership development program and coordinating internships at its partner companies around the world. Although not explicitly formulated, AIESEC’s general KM strategy is to codify critical knowledge
to make it accessible to members. The strategy corresponds to a codification strategy (Hansen, Nohria and Tierney 1999). This strategy is necessary due to the high personnel turnover of the organization (e.g. AIESEC changes its complete management team every year).
KM Practices We use Binney’s (2001) KM spectrum as a checklist in order to map which aspects of KM are used by AIESEC. The key practices of AIESEC’s KM are shown in Figure 4.
Web 2.0 Applications In 2007, AIESEC decided to focus its strategy on fostering an organizational culture, where all members actively contribute to achieving the organization’s goals. For KM this would mean that members on all levels actively contribute knowledge assets for instance by sharing knowledge. As the KM infrastructure, mainly based on Lotus Domino, was not designed to facilitate knowledge sharing bottom-up, the national executive board at that time formulated an explicit information management strategy that encompassed the migration from the Lotus Domino system to a global web platform: MyAIESEC. A screenshot of the web platform page is shown in Figure 5. On the national level there are more than 400 wiki pages covering all functional areas. These wiki pages contain content that was formerly stored in the Lotus Domino based knowledge base
Figure 4. KM spectrum with AIESEC’s key KM practices
25
Exploring the Impact of Web 2.0 on Knowledge Management
Figure 5. Web portal page of AIESEC Germany
(manuals, process documentation, forms and other documents). Since then the organization has adopted a number of Web 2.0 applications to improve collaboration and knowledge sharing between its members. The upper part of Figure 6 provides an overview of different KM aspects in AIESEC Germany and the bottom part shows Web 2.0 applications used for supporting these aspects. MyAIESEC, AIESEC’s global web platform, contains a wiki module in which every user can create wiki pages. Information on MyAIESEC is searchable through an advanced search function based on tags and elaborated filters. Wikis are used for storing information such as manuals, contain process documentations and are used for collaborative idea generation (e.g. virtual brainstorming sessions). Even though wikis should enable everybody to contribute content or enrich other people’s contributions, only a limited number of members have actually been doing so and
26
most of them are active nationally. Since there were some severe problems with the usability of the platform after its introduction, an interviewee suggested that the problem might be related to that. AIESEC recently started using Google Apps, a bundle of collaborative web-applications. Its word processing module and its spreadsheets module are mainly used for documentation (e.g. minutes) and idea generation (e.g. brainstorming). The presentation module is used for virtual trainings and a module that allows form creation is used for creating surveys amongst members. In addition, for improving interaction and information exchange between the members a webmail application and a built-in instant messaging client that is identical with Google’s consumer product Gmail is used. According to an interviewee the acceptance of Google Apps was significantly facilitated by its intuitive interface and the fact that users already knew the applications from personal use.
Exploring the Impact of Web 2.0 on Knowledge Management
Figure 6. KM and Web 2.0 applications used for KM by AIESEC Germany
In order to streamline their marketing material creation, which needs to be customized for each chapter, AIESEC uses Brandkore, a webbased marketing automation tool. Consequently, members no longer need to be familiar with using complicated graphic suites. To facilitate development and learning of its members AIESEC uses a number of e-learning applications such as the platform WizIQ and Teamviewer in combination with web-controlled telephone conferencing tools such as Meetgreen. The organization is currently evaluating the use of web-based video conferencing tools such as Netviewer that allow multiple users to see and interact with each other. Although some communication channels such as Facebook and Twitter are mainly used for communication with external stakeholders, members have started using them for internal communications and collaboration amongst each other as well.
Impact of Web 2.0 Applications on KM The following tables summarize the findings regarding the impact of Web 2.0 applications on these aspects of KM. The impact assessment is based on the AST model.
As we can see in Table 4 there is no clear answer to the question if wikis have increased efficiency of knowledge repositories and content management. However, Erik’s negation is more attributable to the fact that people do not properly make use of the naming and tagging function that the system offers. Most respondents agree that there is an increase of knowledge quality triggered by the use of wikis. However, even with wiki systems the problem of redundancies remains. Instead of making use of links people tend to copy concepts and other knowledge assets to local versions of wikis where they become updated quite quickly (according to Peter S. and Erik S.). According to Michael it is also not clear if there is a commitment gain as people do not actively use the possibility of changing and contributing content even though they would be able to. Michael attributes this to the missing sharing culture. According to Richard people in one region (a geographical sub-unit of AIESEC) people used wikis to create a portal page that facilitates cooperation and knowledge exchange between different chapters. Before that there was no regional exchange platform in place. As Table 5 suggest, social networking sites have increased efficiency of communication within AIESEC. The respondents also propose that social networking and blogging has increased transparency within the organization. However,
27
Exploring the Impact of Web 2.0 on Knowledge Management
Table 4. Impact of wikis on AIESEC’s knowledge repositories and content management Interviewee
Web 2.0 Application
Efficiency gain
Quality Gain
Commitment gain
New structures
Richard
Wikis
People find knowledge more easily thanks to better search function
Knowledge is more up-to-date since more people (mostly on the national level) change it
-
Regional portal site created by region
Peter
Wikis
-
Yes, knowledge quality has increased over the past years
People more committed to share knowledge between local chapters
-
Michael
Wikis
-
Has not increased since the number people that contribute to wiki pages (that contain codified knowledge) has not significantly increased in comparison with the number of contributors to the previous Lotus Notes based knowledge base
Although it is possible to change pages, most members don’t use this ← possible reason: mindset did not change
-
Erik
Wikis
No, because people don’t use tags and title of wikis consistently finding information is more difficult
Yes, more codified knowledge is available However, still many redundancies as people copy instead of link content
-
-
they have also raised the problem that internal communication often takes place in public channels. In this way internal information could leak out of the organization. On the other hand, Peter notes that the current national executive board does not necessary see this as a deviation from the intended use since it might also shed a positive light on the organization if authentic internal communication in an open channel helps making the organization more transparent to people outside of it (e.g. people that are interested in joining it or partners). The respondents listed in Table 6 agree with each other that shared workspaces have contributed to an efficiency gain in collaboration and coordination of virtual teams in AIESEC. Richard notes that the availability of Google Apps has led to the emergence of user-generated resources, such as tracking tools that can be shared between different people. Since AIESEC has only recently started using Web 2.0 applications such as wikis and Google Presentation for virtual education, it was not yet possible to determine their impact. 28
Case 2: Market Team Market Team (MT), solely operating in Germany, aims at providing students insights into the business world by organizing events like workshops, trainings and symposia with companies. The organization has around 1,000 members in 23 chapters (Market Team, 2010). KM focuses on supporting day-to-day operations of the organization, which mainly consist of running various projects on both the local and the national level. Most KM practices are focused on codification of knowledge by creating handbooks for the organization’s key functions and documenting experiences with projects. Although there is no formally expressed KM strategy the generic strategy corresponds to a codification strategy (Hansen et al. 1999). Most KM initiatives take place on the local level. There is little knowledge sharing between different chapters. At the time of examination the organization ran an initiative for improving knowledge sharing between local chapters to build on synergy effect, i.e. re-use knowledge in different parts of the organization.
Exploring the Impact of Web 2.0 on Knowledge Management
Table 5. Impact of Web 2.0 applications on communities within AIESEC Interviewee
Web 2.0 application
Efficiency gain
Quality Gain
Commitment gain
New structures
Ken
Social networking sites, Blogs
Better communication
-
-
More transparency through communication between the national board and the local chapters Members have more information about events in other chapters People interact more with each other and ask for help from others more easily
Richard
Social networking sites, Blogs
More communication
-
-
More transparency through communication between the national board and the local chapters Internal communication in public channels
Peter
Social networking sites, media sharing services
-
-
-
Internal communication in public channels. However, this could be intended to increase external transparency.
People taking a role in a local or the national board generally have a term of one year. The fact that not all terms start at the same time ensures some retention of knowledge. On the national level this is formalized as the national board and the national advisory board have semi-overlapping terms, i.e. they start staggered by six months.
Knowledge Management Practices Binney’s (2001) KM spectrum is used as a checklist in order to map which KM practices are carried out by MT. The outcome of the analysis is shown in Figure 7.
Web 2.0 Applications MT uses a web-based intranet portal that contains a number of modules that allow members to access organization wide information. It contains a forum for announcements, a customer relationship management module, a directory of all members, a database containing some general facts about each past project and a data pool and a helpdesk module. Since the current platform has been developed for more than 10 years and is mainly designed for unilateral communication from national to local level, the organization is currently evaluating how it can be replaced by a more interactive platform leveraging Web 2.0 applications such as wikis and social networking.
Figure 7. KM spectrum with MARKET TEAMS’s key KM practices
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Exploring the Impact of Web 2.0 on Knowledge Management
Table 6. Impact of shared workspaces on virtual teams and collaboration in AIESEC Interviewee
Web 2.0 applications
Efficiency gain
Quality Gain
Commitment gain
New structures
Ken
Shared workspaces
Yes, content can be more easily shared with each other and distributed in the organization.
-
-
-
Peter
Shared workspaces
More efficient collaboration
-
-
Possibly less communication via email; instead coordination and collaboration via Google Spreadsheets
Richard
Shared workspaces
-
-
-
New tracking tools based on spreadsheets
Hannes
Shared workspaces
More efficient coordination, especially for virtual teams.
-
-
-
There is already a number of Web 2.0 applications used for KM on different levels of the organization as local chapters operate quite independently from the national level. Figure 8 provides an overview of the different KM practices in MT and the bottom part shows Web 2.0 applications used for supporting these aspects. Some chapters use wiki platforms based on MediaWiki for facilitating project management. In general, information and experience reports
from previous projects and manuals how to run a project are retrieved from the national webplatform and the local platform is used mainly for facilitating communication and collaboration between the members of project teams. In addition, they may guide project teams through the process of running a project. Besides physical meetings, communication mainly takes place through emails but also through StudiVZ, a large German social network-
Table 7. Impact of Wikis on its knowledge repositories, content management and document management within MARKET TEAM Interviewee
Web 2.0 Application
Ann-Christin
Wikis (Ilmenau chapter)
-
Before introducing a wiki in Ilmenau there was no knowledge repository. As people have started codifying knowledge and using it as a reference the quality has increased.
Only some people use them actively.
People use wiki page as a simple inventory management system
Frank
Wikis
-
In chapters where wikis are actively used (e.g. Münster), there are better project documentations More sustainable knowledge retention about past experiences
In most chapters wikis are not used actively. However, there are chapters where people actively use them
-
Anim
Wikis
-
In chapters where wikis are actively used more documentation than before; in this way there is an increase of the quality of codified knowledge
There is increased commitment for documenting
People are collaborating virtually with each other what they didn’t do before
30
Efficiency gain
Quality Gain
Commitment gain
New structures
Exploring the Impact of Web 2.0 on Knowledge Management
Figure 8. KM and Web 2.0 applications used for KM by MARKET TEAM
Impact of Web 2.0 Applications on KM
ing platform, and Facebook. These channels are therefore the main means of exchanging ideas and innovation. Skill development and training solely takes place in physical meetings and apart from providing manuals and explicit information on the national web platform, no specific web technology is used for this aspect of KM. Following the general trend, members have started using free Web 2.0 tools for collaborating and sharing files with each other. Dropbox is mainly used for sharing and storing documents online. Google Docs and Spreadsheets and Mindmeister, an online mind map tool, are used for collaboration and idea generation. These tools were not specifically introduced by the organization, but just appeared to be useful and very often already known by members from personal use.
The following tables summarize the findings regarding the impact of Web 2.0 applications on these aspects of KM. The impact assessment is based on the AST model. As the answers from the respondents in Table 7 suggest, wikis apparently lead to an increase of quality of codified knowledge in chapters where wikis are actively used. However, a main problem in many chapters is that only few people use them. According to Frank G. there are only a few chapters where wikis are used by a substantial number of people. As he supposes that in many chapters the critical mass of people using the application to make it attractive is not reached, a national wiki platform has been recently launched. The future will show if activity level will be higher on that platform.
Table 8. Impact of Dropbox on collaboration within MT Interviewee
Web 2.0 application
Efficiency gain
Quality Gain
Commitment gain
New structures
Christine
Dropbox
Yes, more efficient than for instance email as files are updated automatically on all computers
-
-
More collaboration between people
Anim
Dropbox
Yes, as files are synchronized automatically on the computer of all people using it
Yes, there’s more documentation than before
As it’s very easy to use the application, people just use it
-
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Exploring the Impact of Web 2.0 on Knowledge Management
Ann-Christin N. explains that in her chapter the wiki platform is also used as a simple inventory management system. As MT runs many projects, chapters have a considerable amount of materials that they have to store. As an ad-hoc approach to inventory management, members of a project team created a wiki page in which they update the amount of materials available. Both respondents in Table 8 agree that the use of Dropbox as media sharing tool has increased efficiency of collaboration. Anim thinks that there is a general increase of commitment in documenting and sharing files with each other. (See Table 9) According to both interviewees social networking has increased the efficiency of communication. Christine points out that social networking has especially also lead to more communication between different chapters.
earlier, the KM 2.0 Spectrum and a list of impacts of Web 2.0 on KM with three experts both from academia and practice. Two of the experts are consultants in the field of social media and Web 2.0 at Deloitte and Logica and one of them is an associate professor at Stockholm School of Economics and researches the impact of social media on knowledge work in multinational companies. The protocol for conducting the validation was based on the guidelines by Audenhove (2007). The interviews revealed some suggestions for correcting some smaller inconsistencies and presenting the results. The suggestions are already incorporated into the respective models presented in this text. Both consultants generally agreed with the impacts that we identified and confirmed that Web 2.0 applications can be used in the way presented in the KM 2.0 spectrum. We found out that a key impediment of using social networking in companies is the potential of knowledge leak to the external environment. According to one of the experts this is especially critical for organizations handling sensitive customer data, e.g. banks and care providers.
DISCUSSION We used the findings from the two case studies to construct a framework of Web 2.0 applications that can be used for different KM practices. As it follows the structure of Binney’s (2001) KM Spectrum we refer to it as “KM 2.0 Spectrum”. Furthermore, the case studies enabled us to identify a number of potential impacts of adopting Web 2.0 applications for KM that are summarized in the KM 2.0 Impact Model. In order to ensure the correctness, completeness and consistency, we presented and discussed the Web 2.0 Layer Model that was introduced
KM 2.0 Spectrum Based on the findings from the case studies, we created a mapping between each type of Web 2.0 application and the KM practices it can be used for. This mapping is shown in Table 10. Table 10 shows that wikis can be used for a number of different aspects of KM. They may be used as asset management tools as means of stor-
Table 9. Impact of social networking on communities and networking within MT Interviewee
Web 2.0 application
Efficiency gain
Quality Gain
Commitment gain
New structures
Frank
Social networking
Yes, as it can be used very easily
-
-
-
Christine
Social networking
Yes, communication on social networks tends to be faster than e.g. email.
-
More communication across the boundaries of chapters
Replacement of email; People use social networks to stay updated about other chapters
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Exploring the Impact of Web 2.0 on Knowledge Management
Table 10. Mapping of Web 2.0 applications with KM practices Web 2.0 Application Wikis
Media sharing
KM Practice Content management
KM Spectrum Element Asset management
AIESEC, MT
Document management
MT
Learning
Developmental
AIESEC, MT
Collaboration
Innovation and creation
AIESEC, MT
Knowledge repositories
Asset management
AIESEC, MT
Virtual teams
AIESEC, MT Innovation and creation
Communities Communities
Innovation and creation
AIESEC, MT AIESEC
Knowledge repository
Asset management
AIESEC, MT
Collaboration
Innovation and creation
AIESEC
Virtual teams Blogging
MT AIESEC, MT
Networking Shared workspaces
AIESEC, MT
Knowledge repository
Document management
Social networking
Source
AIESEC
Training
Developmental
AIESEC
Communities
Innovation and creation
AIESEC
ing knowledge and containing codified knowledge. As they contain codified knowledge they may also be used as a tool for learning or more specifically as a reference in the learning process of individuals as the AIESEC case suggests. Wikis also play a role as a tool for innovation and creation as they allow individuals to collaborate with each other. In both cases wikis have been used by people to come up with their own resources that facilitated their work practices (in the AIESEC case a portal page for different chapters and in the MT wikis have been used for a simple inventory management). As wikis can be used so flexibly in organizations they appear to be the “Swiss army knife” of Web 2.0 applications; being used for purposes that are not covered by other applications. Media sharing applications including video sharing services such as Youtube or Google Video but also online storage and sharing tools such as Dropbox play two important roles in the context for KM. First, they can be used for simply storing documents and media files and making them easily
accessible by a large number of people. Second, they facilitate innovation and creation as people can collaborate online without boundaries and create new content. A third type of application that spans the asset management and the innovation and creation elements of the KM Spectrum is social networking. Some well known examples are Facebook, MySpace, and Twitter. From an asset management perspective a micro-blogging functionality, i.e. the possibility to post small messages that are shown to one’s peers, can be leveraged as a kind of knowledge directory as people can use to locate specific knowledge assets by simply asking their peers. This can be a valuable complement to existing knowledge repositories as a key challenge has always been to find relevant knowledge assets easily. Social networking also plays a role for innovation and creation as it allows people to communicate with each other across departmental or even organizational boundaries. People may increase their awareness of activities in other organizational units and therefore improve net-
33
Exploring the Impact of Web 2.0 on Knowledge Management
working and collaboration with people they would otherwise not have been in touch with. Shared workspace applications such as Google Docs and Mindmeister play a role for both “developmental KM” and “innovation and creation”. They may be used for virtual education purposes, such as online training sessions as demonstrated in the AIESEC case. In this way training sessions are not limited to physical meetings but can easily be conducted remotely as participants can complement voice interaction, which has been possible for a long time through telephone or voice-over-IP, by visual interaction using blackboards, mind mapping and online presentations. Shared workspaces also facilitate innovation and creation as people can collaborate with each other online although they might be at different places and work on documents at different times. These applications allow virtual teams to collaborate with each other in new ways as the AIESEC case suggests. As blogging allows people to easily publish experiences and opinions they may foster innovation and creation as they may represent a new generation of discussion forum. Discussion does not take place in threads as in traditional online forums but people may discuss with each other by commenting on blog entries and referring to other’s blog entries in their own blog. The mapping that is shown in Table 10 is used for extending Binney’s (2001) KM spectrum to come up with the KM 2.0 Spectrum. This frameFigure 9. KM 2.0 Spectrum
34
work shows which applications can be used for different elements of the KM spectrum and the practices it encompasses. It is shown in Figure 9. Although there do not seem to be Web 2.0 applications associated with the spectrum elements “transactional KM”, “analytical KM” and “process-oriented KM” the AIESEC case demonstrates that Web 2.0 technologies may enhance KM practices associated to these spectrum elements (e.g. process support tools based on Web 2.0 technology). Hideo and Shinichi (2007) demonstrate how analytical KM may benefit from social networking data to create knowledge. Further research might reveal more examples in these spectrum elements. Some applications in Figure 9 are associated to a number of KM spectrum elements (e.g. wikis and social networking). This demonstrates that the boundaries between the different spectrum elements are fuzzy. The association of the different Web 2.0 applications should therefore only be seen as a rough orientation.
Impact Model of KM 2.0 We consolidated the findings from the two case studies and created a list of possible impacts from using Web 2.0 applications for KM. By having a look at each of the impacts and the Web 2.0 application that is related to the impact, we identified the socially-oriented Web 2.0 principles that reflect
Exploring the Impact of Web 2.0 on Knowledge Management
best the characteristics of the respective application that have most likely triggered the impact. In this way it is possible to discuss the impact of Web 2.0 on KM practices on a higher level, i.e. independently from the application level. The impact table together with the associated sociallyoriented Web 2.0 principles is shown in Table 11. The first impact is mainly triggered by the “unbounded collaboration” characteristic of media sharing applications as applications such as Dropbox simplify sharing of documents. The second impact benefits from the fact that people may use wikis and media sharing applications to contribute the content they consider relevant (user-generated content). Quality is ensured when a group of people contributes its knowledge and is engaged in continuously improving the shared knowledge (i.e. collective intelligence).
As wikis allow people to work together in creating codified knowledge independently asynchronously and from different places (i.e. unbounded collaboration) the efficiency of knowledge creation (impact 3a) may be increased. The same holds for social networking sites such as Twitter or Facebook (impact 3b) where people can post and react to micro-contributions independently from each other. Social networking in addition relies on the long tail as people may post micro-messages that they would otherwise not have expressed or just in an informal way (like during a coffee break) where there contribution would not have been captured. On the other hand unbounded collaboration and reaching the long tail in social networks may also lead to an increase leakage of knowledge (impact 4) as people can easily share organization internal knowledge with external peers.
Table 11. Impact of Web 2.0 applications on different KM practices #
KM practice
Web 2.0 applications
Impact
Source
1
Document management
Media sharing
Increased efficiency of document and media sharing
Christine (MT), Anim (MT)
2
Knowledge repositories, Document management
Wikis, Media sharing
Increased quality of codified knowledge
Peter (AIESEC), Richard (AIESEC), Michael* (AIESEC), Erik* (AIESEC), Frank (MT), Anim (MT), Ann-Christin (MT)
3
Communities
Social networking, Media sharing
More efficient creation and sharing of codified knowledge
Richard (AIESEC), Erik* (AIESEC)
Increased knowledge leakage
Richard (AIESEC), Peter (AIESEC)
Social networking
More efficient communication
Ken (AIESEC), Richard (AIESEC), Christine (MT), Frank (MT)
6
Social networking, Blogging
More transparency within the organization
Richard (AIESEC), Ken (AIESEC)
7
Social networking
More communication across organizational units
Ken (AIESEC)
4 5
Communities
8
Collaboration, Virtual Teams
Shared workspaces, Media sharing
More efficient collaboration
Ken (AIESEC) Peter (AIESEC), Hannes (AIESEC), Christine (MT)
9
Virtual Teams
Shared workspaces, Media sharing, Social Networking
More efficient coordination
Ken (AIESEC), Peter (AIESEC), Hannes (AIESEC)
10
Collaboration
Wikis, Shared workspaces
Emergence of user-generated structures
Ann-Christin (MT), Peter (AIESEC)
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Exploring the Impact of Web 2.0 on Knowledge Management
As people may generate and share the content they wish (user-generated content) social networking applications and blogs may lead to an increase of transparency within an organization (impact 6). The unbounded collaboration characteristic of social networking applications such as Facebook may trigger an increase in communication efficiency (impact 5) as people communicate with each other without boundaries. Sending messages, sharing files and instant messaging is all possible in one single application. This may also lead to an increase of communication across departmental boundaries (impact 7). Shared workspaces like Google Docs and media sharing applications such as Dropbox allows people to collaborate without boundaries and may lead to an increase in collaboration (impact 8). This is also the reason why these applications and social networking sites may increase coordination efficiency (impact 9), especially in virtual teams. As users can create their own content they may use applications such as wikis and shared workspaces for creating their own structures (impact 10) such as tracking sheets (as mentioned in the AIESEC case), simple resource planning (as seen in the MT case). The findings suggest that the principle “network effects” does not play a major role for the
impacts that Web 2.0 application have on KM practices of the two organizations. However, as the Web 2.0 Layer Model suggests network effects are important for most Web 2.0 applications (especially wikis, social networking and blogging) to work properly. Only if there is a critical mass of people using the application it increases it chance to becomebe successful. Therefore, it should be seen as a key enabler to those applications. The impacts in Table 11 can be associated with the different steps of the KM cycle (Figure 1). The associations are shown in Table 12. As impact 1 deals with the sharing of documents and media, we associate it with the “knowledge sharing” step. Impact 2 is associated with “knowledge capture and creation” as it deals with the quality of codified knowledge. Impact 3a concerns the creation and is therefore associated with the “knowledge capture and creation” step. As impact 3b deals with sharing of knowledge, we associate it with “knowledge sharing and dissemination”. As a side-effect of impact 3b, impact 4 is also associated with “knowledge sharing and dissemination”. As more transparency (impact 6) in an organization may lead to the discovery of new knowledge sources that would otherwise not have been discovered by people, it is associated with “Knowledge capture and creation”. As a
Table 12. Impacts of Web 2.0 on different steps of the KM cycle # 1
Impact Increased efficiency of document and media sharing
Principles 1
KM cycle step Knowledge sharing and dissemination
2
Increased quality of codified knowledge
3a
More efficient creation of codified knowledge
1
3b
More efficient sharing of codified knowledge
1,5
4
Increased knowledge leakage
6
More transparency within the organization
3
Knowledge capture and creation
1
Knowledge capture and creation Knowledge sharing and dissemination
1
Knowledge capture and creation
5
More efficient communication
7
More communication across organizational units
8
More efficient collaboration
2, 3
9
More efficient coordination
1
10
Emergence of user-generated structures
3
36
Knowledge capture and creation Knowledge sharing and dissemination
Exploring the Impact of Web 2.0 on Knowledge Management
more efficient communication (impact 5) and more communication across organization units (impact 7) may increase both knowledge creation and sharing, we associate it with “knowledge capture and creation” and “knowledge sharing and dissemination”. More efficient collaboration (impact 8) and coordination (impact 9) may lead to the emergence of user-generated structures (impact 10) and eventfully may improve “knowledge capture and creation”. Based on Table 12 an impact model is created in which the socially-oriented Web 2.0 principles are related with their impact to the different stages and processes of the KM cycle. The impact model is shown in Figure 10. By looking at Figure 10 one might assume that Web 2.0 solely impacts “knowledge capture and creation” and “knowledge sharing and dissemination”. Apparently, those KM cycle steps are mostly impacted by Web 2.0 applications. How-
ever, we think that especially “knowledge acquisition” should be impacted by Web 2.0 application as it is related to learning which can be faciliated by Web 2.0 applications as the AIESEC case showed. But, since AIESEC’s virtual education practices have only recently started, it was not yet possible to determine the impact of Web 2.0 application on them. Some research in this area was conducted by Kane and Fichman (2009) who demonstrate how wikis can be used for teaching and Andersen (2007) who examines Web 2.0’s implication for education. We expect that especially the principle “unbounded collaboration” has an impact on “knowledge acquisition and application”. For instance, the availability of powerful tools for long-distance learning may enable organizations to reduce costs by conducting training sessions online instead of having to meet.
Figure 10. KM 2.0 impact model
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Exploring the Impact of Web 2.0 on Knowledge Management
CONCLUSION The findings from the research suggest that Web 2.0 applications may have a positive impact on KM as they may increase efficiency, quality and commitment of certain KM aspects but, coming back to the question that we raised in the introduction, do they actually usher in a new era of KM, a “Knowledge Management 2.0”? Pointing to the limitation that we made early when we introduced KM, we do not believe that just introducing technology brings a change to an organization. This limitation also applies to introducing Web 2.0 applications in an organization as became apparent in both case organizations where interviewees pointed out that for instance the participation rate in wikis introduced by management tended to be very low. From a Technology Acceptance perspective (Davis, 1989) this problem may occur because people do not perceive wikis as useful or they perceive them as to difficult to use. On the other hand, when employees took the initiative and started using the application “Dropbox” bottom-up, it quickly spread out and eventually led to increased efficiency of collaboration. Apparently, this application did not suffer from low usefulness and/or ease-to-use. So what can we learn from this? The difference between these two situations indicates that the users of a technology are better in determining if they consider it useful and easy-to-use than those who implement technology on behalf of management. Taking on this idea, we believe that if Web 2.0 applications are used in this way, they have the potential of having a significant impact on organizational practices. This is an extension of the “user-generated content” idea towards “userinitiated application selection”. Interestingly, one of our validation-experts told us that Yammer, an intra-organizational microblogging platform, is being adopted by more and
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more organizations. Yammer is based on the idea that if they like it, employees just start using it within their organization. If management of their organization is also enthusiastic, they can upgrade the network to a corporate account and would gain access to the posted content and customize the application according their needs. In this light, we see KM’s role in fostering these user-initiated developments by providing the necessary means and incentives. KM 2.0 is not about enforcing new programs and tools from top-down. KM 2.0 is about listening to the people and encouraging bottom-up adoption of applications and encouraging user-participation.
FUTURE RESEARCH DIRECTIONS The findings in this research are based on two case studies. In order to increase external validity of study, the research should be extended by conducting case studies in different types of organizations. Hence it would be interesting to have a look at other types of non-profit and for-profit organizations. As both of the case organization had quite similar KM practices, it should be looked at organizations that cover different aspects of the KM spectrum. These case studies should also encompass an in-depth analysis of situational factors that influence the impact of Web 2.0 application on KM. The outcomes would help organizations understand which levers they have to move in order to benefit from Web 2.0. Eventually, the findings from the case study research should be used to conduct some quantitative research in order to derive some general conclusion about the impact of Web 2.0 on KM. The identified impacts could be used to design a survey to be sent to people in charge of KM in a larger number of organizations.
Exploring the Impact of Web 2.0 on Knowledge Management
REFERENCES Andersen, P. (2007). What is Web 2.0? Ideas, technologies and implications for education. JISC.
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Brodkin, J. (2007). Web 2.0: Buzzword, or Internet revolution? Network World. Retrieved December 5, 2009, from http://www.networkworld.com/ news/2007/012407-web-20.html Bughin, J., Chui, M., & Johnson, B. (2008). The next step in open innovation. The McKinsey Quarterly, 4, 112–122. Bukowitz, W. R., & Williams, R. L. (1999). The knowledge management fieldbook. Financial Times Prentice Hall. Chui, M., Miller, A., & Roberts, R. P. (2009). Six ways to make Web 2.0 work. The McKinsey Quarterly, (February): 1–7. Dalkir, K. (2005). Knowledge management in theory and practice. Butterworth-Heinemann. Darke, P., Shanks, G., & Broadbent, M. (1998). Successfully completing case study research: Combining rigour, relevance and pragmatism. Information Systems Journal, 8, 273–289. doi:10.1046/j.1365-2575.1998.00040.x
DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121–147. doi:10.1287/orsc.5.2.121 Drucker, P. (1999). Knowledge worker productivity: The biggest challenge. California Management Review, 41(2), 79–94. Dul, J., & Hak, T. (2008). Case study methodology in business research. Butterworth-Heinemann. Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550. Facebook. (2010). Statistics. Facebook. Retrieved June 21, 2010, from http://www.facebook.com/ press/info.php?statistics Giddens, A. (1976). New rules of sociological method: A positive critique of interpretative sociologies. London, UK: Hutchinson. Giddens, A. (1979). Central problems in social theory: Action, structure, and contradiction in social analysis. Berkeley, CA: University of California Press.
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Giddens, A. (1984). The constitution of society. Berkeley, CA: University of California Press. Google. (2010). About Google Scholar. Retrieved June 18, 2010, from http://scholar.google.com/ intl/en/scholar/about.html Hansen, M. T., Nohria, N. I., & Tierney, T. (1999). What’s your strategy for managing knowledge? Harvard Business Review, (March-April): 106–116. Hideo, S., & Shinichi, K. (2007). KM 2.0: Business knowledge sharing in the Web 2.0 age. NEC Technical Journal, 2(2), 50–54. Hoegg, R., Meckel, M., Stanoevska-Slabeva, K., & Martignoni, R. (2006). Overview of business models for Web 2.0 communities. Proceedings of GeNeMe, 2006, 23–37. Hume, C., & Hume, M. (2008). The strategic role of knowledge management in nonprofit organisations. International Journal of Nonprofit and Voluntary Sector Marketing, 13(2), 129–140.. doi:10.1002/nvsm.316 Hustad, E., & Teigland, R. (2008). Implementing social networking media and Web 2.0 in multinationals: Implications for knowledge management. In Proceedings of 9th European Conference on Knowledge Management (pp. 323-332). Jones, S., & Fox, S. (2009). Generational differences in online activities. Pew Internet & American Life Project. Retrieved October 21, 2009, from http://www.pewinternet.org/Reports/2009/Generations-Online-in-2009/Generational-Differencesin-Online-Activities.aspx?r=1 Kane, G. C., & Fichman, R. G. (2009). The shoemaker’s children: Using Wikis for Information Systems teaching, research, and publication. Management Information Systems Quarterly, 33(1), 1–17.
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Knol, P., Spruit, M., & Scheper, W. (2008). Web 2.0 revealed - Business model innovation through social computing. Proceedings of the Seventh AIS SIGeBIZ Workshop on E-business (WeB 2008). Lettieri, E., Borga, F., & Savoldelli, A. (2004). Knowledge management in non-profit organizations. Journal of Knowledge Management, 8(6), 16–30. doi:10.1108/13673270410567602 Levy, M. (2009). WEB 2.0 implications on knowledge management. Journal of Knowledge Management, 13(1), 120–134. doi:10.1108/13673270910931215 Market Team. (2010). Market Team e.V. - Die fachübergreifende Studenteninitiative. Retrieved March 19, 2010, from http://www.market-team. de/national/ McAfee, A. P. (2006). Enterprise 2.0: The dawn of emergent collaboration. MIT Sloan Management Review, 47(3), 21–28. McElroy, M. (1999). The knowledge life cycle. In ICM Conference on KM, Miami, FL, April. Meyer, M., & Zack, M. (1996). The design and implementation of information products. Sloan Management Review, 37(3), 43–59. Musser, T., & O’Reilly, T. (2006). Web 2.0 principles and best practices (Electronic version). O’Reilly Radar. Retrieved from http://radar. oreilly.com/research/web2-report.html Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. doi:10.1287/orsc.5.1.14 Nonaka, I., & Konno, N. (1998). The concept of Ba: Building a foundation for knowledge creation. California Management Review, 40(3), 40–54. O’Reilly, T. (2007). What is Web 2.0: Design patterns and business models for the next generation of software. Communications & Strategies, 65, 17–37.
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Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398–427. doi:10.1287/orsc.3.3.398 Polanyi, M. (1966). The tacit dimension. London, UK: Routledge & Kegan Paul. Scherp, A., Schwagereit, F., & Ireson, N. (2009). Web 2.0 and traditional knowledge management processes. In 1st Workshop on Knowledge Services & Mashups (KSM2009) at 5th Conference. Tredinnick, L. (2006). Web 2.0 and business: A pointer to the intranets of the future? Business Information Review, 23(4), 228–234. doi:10.1177/0266382106072239 Vossen, G., & Hagemann, S. (2007). Unleashing Web 2.0: From concepts to creativity (Vol. 2007). Boston, MA: Elsevier Morgan-Kaufmann. Wiig, K. M. (1993). Knowledge management foundations. Arlington, TX: Schema Press. Wikipedia. (2010). Wikipedia, the free encyclopedia. Retrieved June 21, 2010, from http:// en.wikipedia.org/wiki/Wikipedia#cite_note-4 Yin, R. K. (1994). Case study research. Thousand Oaks, CA: Sage. Yin, R. K. (2008). Case study research: Design and methods (4th ed.). Thousand Oaks, CA: Sage.
ADDITIONAL READING Ankolekar, A., Krötzsch, M., Tran, T., & Vrandecic, D. (2008). The two cultures: Mashing up Web 2.0 and the Semantic Web. Web Semantics: Science. Services and Agents on the World Wide Web, 6(1), 70–75..doi:10.1016/j.websem.2007.11.005
Baltatzis, G., Ormrod, D. G., & Grainger, N. (2008). Social Networking Tools for Internal Communication in Large Organizations: Benefits and Barriers. In Proceedings of 19th Australasian Conference on Information Systems Social Networking Tools in Organizations 3-5 Dec 2008, Christchurch (pp. 76-86). Benslimane, D., Schahram, D., & Sheth, A. (2008). Services Mashups: The New Generation of Web Applic. IEEE Internet Computing, 12(5), 13–15. doi:10.1109/MIC.2008.110 Borga, F., Lettieri, E., & Savoldelli, A. (2002). Knowledge Management for the Non-Profit Sector: methodologies and findings. In Third European Conference on Knowledge Management (pp. 79-93). Bughin, J. R. (2007). How companies can make the most of user-generated content. The McKinsey Quarterly, (August 2007). Chang, Y. J., Wang, F. T., Chuang, Y. C., & Tsai, S. K. (2007). Action Science Approach to Experimenting Nonprofit Web 2.0 Services for Employment of Individuals with Mental Impairments. In Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology-Workshops (pp. 288–291). Fages, R., & Sanguesa, R. (2007). Good practice exchange from a Web 2.0 point of view. European Journal of ePractice, 1, 1-21. Hackler, D., & Saxton, G. D. (2007). The Strategic Use of Information Technology by Nonprofit Organizations: Increasing Capacity and Untapped Potential. Public Administration Review, 67(3), 474–487. doi:10.1111/j.1540-6210.2007.00730.x Hurley, T. A., & Green, C. W. (2005b). Knowledge management and the nonprofit industry: A within and between approach. Journal of Knowledge Management Practice, 6(1).
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Lee, M. R., & Lan, Y. (2007). From Web 2.0 to Conversational Knowledge Management: Towards Collaborative Intelligence. Journal of Entrepreneurship, 2(2), 47–62. Levy, M., & Hadar, I. (2010). Teaching MBA Students the Use of Web2.0: The Knowledge Management Perspective. Journal of Information Systems Education, 21(1), 55–67. Panke, S., & Gaiser, B. (2009). “With My Head Up in the Clouds’’: Using Social Tagging to Organize Knowledge. Journal of Business and Technical Communication, 23(3), 318–349. doi:10.1177/1050651909333275 Paroutis, S., & Al Saleh, A. (2009). Determinants of knowledge sharing using Web 2.0 technologies. Journal of Knowledge Management, 13(4), 52–63. doi:10.1108/13673270910971824 Renshaw, S., & Krishnaswamy, G. (2009). Critiquing the Knowledge Management Strategies of Non-profit Organizations in Australia. World Academy of Science, Engineering and Technology(49), 456-464. Waters, R. D., Burnett, E., Lamm, A., & Lucas, J. (2009). Engaging stakeholders through social networking: How nonprofit organizations are using Facebook. Public Relations Review, 35(2), 102–106. doi:10.1016/j.pubrev.2009.01.006
KEY TERMS AND DEFINITIONS Collective Intelligence: Describes the presumption that a large collective (of users) can develop more than a small number of experts (Knol et al., 2008). O’Reilly (2007) notes that one key enabler of the Web has been the use of hyperlinks that indicate which documents are interlinked with each other. By analyzing hyperlinks a considerable amount of intelligence can be created. O’Reilly indicates that in the Web 2.0 era hyperlinks have
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been complemented by additional mechanisms that analyze the behavior of users. One prominent example is an automatic suggestion system as that of Amazon.com. Knowledge Management: The effective learning process associated with exploring, exploitation and sharing of human knowledge that use the appropriate technology and cultural environments to enhance an organization’s intellectual capital and performance. (Jashapara 2004) Leverage the Long Tail: A concept that allows for reaching out to the huge number of users and customers that represent a niche market. Thanks to approaches such as customer self-service and automatic data management in the Web 2.0 era, it becomes possible to leverage these markets. O’Reilly (2007) notes that successful Web 2.0 companies base a great deal of their businesses on the long tail of customers. This indicates a major change in understanding of e-business models. Network Effects: Apply to services that get better the more users use them. Since the Web 2.0 is characterized by user-generated content, it greatly benefits from network effects. O’Reilly (2005) notes that successful Web 2.0 companies heavily depend on their ability to harness networking effects from user contributions. He also argues that real Web 2.0 companies and their services do not rely on advertising. Instead, their popularity stems from viral marketing - that is one user recommends the products to another and so forth. Unbounded Collaboration: Indicates that users in the Web 2.0 world can collaborate with each other without boundaries in terms of time and location (Knol et al., 2008). In addition, Knol et al. note, users have an active role in the development of Web 2.0 applications by providing feedback or even delivering the content that would have traditionally been delivered by experts. One prominent example of such as collaboration would be social-tagging approaches (folksonomies) that let users assign tags to content resulting in a categorization that strongly reflects the users’ needs.
Exploring the Impact of Web 2.0 on Knowledge Management
User-Generated Content: One of the principal characteristics of Web 2.0. It breaks with the traditional way of publishing where spreading content was limited to professionals. In a Web 2.0 world, instead, users are enabled to create content and share it with each other. Consequently, large amounts of content are generated and available on the Internet.
Web 2.0: The reorientation of the Web that promotes unbounded interaction, collaboration and participation of people. It is characterized by the emergence of a large amount of content generated by a collective of Internet users. It harnesses networking effects and leverages the long tail.
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Chapter 3
Moving Wikis Behind the Firewall:
Intrapedias and Work-Wikis Lynne P. Cooper California Institute of Technology, USA Mark B. Rober California Institute of Technology, USA
ABSTRACT The use of wikis behind the firewall in corporations presents significant opportunities as well as challenges for improving knowledge capture and work processes. This chapter identifies fundamental characteristics of wikis and how these change between public and corporate wikis, and between wikis intended for knowledge capture (intrapedias) and those supporting work processes. A case study describing two organizational wikis illustrates the power of the individual in instigating knowledge capture and the ability of wiki technology to rapidly and easily support individuals in their work efforts. The case study also exposes how adopting wikis can challenge deeply engrained cultural beliefs. As wikis become more prevalent behind the firewall, organizations may need to shift to new ways of thinking about knowledge sharing, the role of the individual versus the collective, and governance. Conversely, characteristics of wikis may need to be adjusted to deal with the realities of knowledge use within organizations.
INTRODUCTION Corporations have started using wikis, defined as “sets of dynamically created web pages with content contributed directly by users in a web browser” (Yates, Wagner & Majchrzak, 2010), to support both internal and customer-centric business processes (Wagner & Majchrzak, 2006ab).
Behind the firewalls (BTF) that protect corporate intranets, wikis are used in purposeful environments, in a significantly different manner than that faced by public systems such as Wikipedia. While there is a large body of research examining the Wikipedia phenomenon, wiki research BTF is in an early stage (c.f., Holtblatt, Damianos & Weiss, 2009; Wagner & Majchrzak, 2006ab).
DOI: 10.4018/978-1-61350-195-5.ch003
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Moving Wikis Behind the Firewall
As corporations continue to invest in wikis – both in the technology platforms and in content development, there are open questions as to what factors contribute to successful use and how what is known about public wikis informs BTF use. Early research indicates that organizations are seeing many advantages, but also that defining features of public wikis (e.g., community authorship, open access) change in response to corporate needs (Wagner & Majchrzak, 2006b). The goal of this chapter is to examine in-depth specific corporate wikis: to understand the characteristics that define them, the processes that shape them, and how adoption of wikis may in turn affect changes in the organization. The chapter starts with a review of relevant literature on wikis. It then presents a case study of the implementation and use of BTF wikis developed in a U.S. national research laboratory. By contrasting these wikis with each other and with public wikis, we identify key characteristics and how they differ based on public versus private access and intended use. This is followed by a discussion of cultural and governance implications in the transition to wiki-based systems and ends with a presentation of research and practical implications for BTF wiki use.
Background Wikis are now routinely used to capture and share knowledge in the general public, as exemplified by Wikipedia. Wikipedia has been studied extensively as a volunteer, community-based resource for knowledge sharing. Research has shown that contributors are motivated by a sense of community, the desire to build reputation, and a need to correct errors (Anthony, et al., 2007). Wikipedia content is “crowd sourced” (Kittur, et al., 2007) so the quality and accuracy of content depends on the quality of the crowd, i.e., the active involvement of a community of users willing to contribute original material, identify and correct errors, expunge embedded advertising
or self-promotion, and cross-reference related material (Denning, et al., 2005). Content derived from different sources, ideologies, contexts, and experiences can find a home within the wiki, regardless of the credentials or capability of the contributor. The process of integrating these materials adds value by reconciling or highlighting inconsistencies and creating a richer, deeper, and broader representation. Through community scrutiny and peer review, errors can be identified and fixed, gaps can be filled, connections to related concepts established, and deviations from topic pruned. This iterative collective action enables convergence on a representation that satisfies the intellectual needs of the community relative to the specific topic. The wiki exists and evolves via the efforts of its collective membership drawn from the community of interest. Both the collective members and the overall community of interest are continuously evolving, with members moving in and out of both the collective and the community from which it is drawn (Ciffolilli, 2003; Yates, Wagner & Majchrzak, 2010). The “wiki way” (Leuf & Cunningham, 2001) assumes that the vast majority of participants will abide by rules and norms, that content-based conflicts can be resolved collectively, and that malicious or deviant behavior will be a rare exception. Wikis therefore rely on community governance. Article quality can therefore vary significantly depending on the community size, knowledge, and willingness to contribute. Because responsibility for the quality of the content is distributed across an amorphous community of contributors, users of Wikipedia must exercise caution when applying the knowledge (Young, 2006). There is no guarantee of accuracy, timeliness, or completeness (Kramer et al., 2008). Still, Wikipedia is widely used as a source of knowledge throughout the world, contains millions of articles (Ortega & Gonzalez-Barahona, 2007) and continues to grow.
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Moving Wikis Behind the Firewall
As knowledge capture and sharing efforts using wikis have become an integral part of the general public’s Web 2.0 experience, wikis are surfacing behind company firewalls to support areas such as e-learning, project management, scheduling, ad hoc collaboration, customer relationship management (Ben-Chaim, et al., 2009; Wagner & Majchrzak, 2006a; Majchrzak, Wagner & Yates, 2006; Moskaliuk & Kimmerle, 2009; Yates et al., 2009), as informal communications tools (e.g., to capture meeting minutes, c.f., Blaschke & Stein, 2008), and as a means to coordinate design and development teams (Ben-Chaim, et al., 2010). Used in this way, “work-wikis” can be viewed as yet another information and communication technology (ICT) available to aid organizations in collaborating and coordinating work. Applications more directly analogous to Wikipedia (e.g., Holblatt, Damianos & Weiss, 2009) are also beginning to emerge. These applications, which we call “intrapedias,” are wiki-based knowledge resources, accessible behind organizational firewalls via intranets, that enable the collective capture, refinement, and sharing of knowledge relevant to the organization in article format. Intrapedias result from the application of new wiki technology to the classic problem of how to capture and share organizational knowledge. Articles contributed to an intrapedia document knowledge that is highly localized and relevant to the organization while also providing easy-to-use mechanisms for keeping that knowledge up to date. Intrapedias are therefore, by definition, knowledge management systems (KMS) and are likely to exhibit many of the characteristics and challenges faced by KMS using earlier technologies. KMS have been used successfully in organizations to codify and share best practices, create knowledge networks, support organizational learning, develop knowledge directories, and facilitate innovation (Alavi & Leidner, 2001; Holsapple & Joshi, 2000; Massey, Montoya-Weiss, & O’Driscoll, 2002). KMS, however, face many challenges including motivating personnel to
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share their knowledge, keeping captured knowledge current, and providing effective delivery mechanisms (Majchrzak, Chellapa, & Cooper, 2005). Additional challenges exist in applying knowledge for a class of work activities referred to as emergent knowledge processes (EKP) such as new product development, organization design, and strategic planning. EKPs are “organizational activity patterns that exhibit three characteristics in combination: an emergent process of deliberations with no best structure or sequence; requirements for knowledge that are complex (both general and situational), distributed across people, and evolving dynamically; and an actor set that is unpredictable in terms of job roles or prior knowledge” (Markus, Majchrzak & Gasser, 2002: 179). To fully support EKPs, knowledge needs to be purposefully integrated into the flow of work in the organization. Behind the firewall (BTF) on corporate intranets, wikis are used in a purposeful environment, in a significantly different manner than by public systems such as Wikipedia. While there is a large body of research examining the Wikipedia phenomenon, wiki research BTF is in an early stage (c.f., Holtblatt, Damianos & Weiss, 2009). This chapter investigates these differences in general and relative to two categories of use, intrapedias and work-wikis, and addresses the questions: How does wiki use impact organizations? And how does organizational use impact wikis?
Case Study This section describes the creation and operation of two BTF corporate wikis developed at the Jet Propulsion Laboratory (JPL), a national research laboratory whose mission of planetary exploration is to “do what no one has done before” under sponsorship from the US National Aeronautics and Space Administration (NASA). The core work of JPL is organized into projects, and includes missions throughout the solar system.
Moving Wikis Behind the Firewall
Like many other organizations, JPL is facing significant knowledge losses as experienced personnel reach retirement age. JPL has deep organizational knowledge in many different areas, gained over the course of decades, and vulnerable to loss due to retirement and long gaps between uses. The nature of the work performed is multidisciplinary and requires the coordinated, integrated efforts of many people, often with unique skills and knowledge. The Laboratory, therefore, has a wealth of un-captured knowledge residing in its employees, and a compelling need to deploy that knowledge effectively and efficiently across a broad spectrum of activities. Many efforts have attempted to capture and preserve this unique and valuable knowledge over the years with varying degrees of success. The introduction of wikis presents an opportunity to enhance knowledge capture efforts and mitigate the potential “brain drain” (DeLong & Mann, 2003; DeLong, 2004). The next sections describe the implementation and operation of two JPL wikis that address the issues of knowledge capture and work coordination. These cases are descriptive, intended to provide insight into difficult to observe processes (Yin, 1994). The authors present the material as personal stories based on their experiences as participant observers (Jorgensen, 1989), in the spirit of workplace ethnography (Zickar & Carter, 2010). The roles of each of the authors relative to the cases are described in Table 1. Table 1. Roles of the authors in the case study Author/ Role
JPL Wired
STMC Wiki
M. Rober
Member of original working group; currently serves as champion and advisor to other contributors
Advisor, shaper
L. Cooper
Audience for JPL Wired “road show” Contributor of articles
Author and primary user
THE CASE OF JPL WIRED JPL Wired is an intrapedia that uses wiki technology to dynamically capture information for JPL personnel to share with each other. In the words of the second author: JPL Wired is analogous to JPL’s own version of Wikipedia. It’s basically our attempt to take all the great information that currently resides on people’s computers, in their file cabinets, or even in their heads and put it “in the cloud” so everyone can have access to it. It is not officially configuration controlled (aside from edit history) and therefore is not a replacement for JPL’s official document repositories. Rather, it complements those repositories by providing context for the information found there and then links to the official documentation. We envision that a user will search Wired first to get an overview of the subject, then they are provided links to the various official information resources on lab that relate to the subject. They will also find information on who the best JPL points of contact are, and links to applicable external resources (e.g. useful websites or books). Because it’s a wiki, in theory, it is never obsolete. If a user reads information that is out of date (e.g. a listed point of contact has since left JPL), it takes seconds to update the article. Each time the same article is edited by a different JPL employee, the more the article begins to converge on a true representation of the subject matter from a JPL point of view. In this manner, there is significant value added by placing even well understood scientific and engineering principles into a local context and interpreting the information through a JPL lens in a way that is pertinent to JPL’s core business (i.e. nuts and bolts are available from the local hardware store but JPL always uses specialized nuts and bolts for putting things together to send to space for performance and quality considerations).
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Moving Wikis Behind the Firewall
THE GENESIS OF JPL WIRED JPL Wired came into being to satisfy a compelling need identified by a cohort of new engineers at JPL. This group, frustrated by limited job-relevant training and a lack of information, approached management about possible on-line solutions. Management tasked an informal working group, which included several of the new engineers, to find ways to address these problems. The working group eventually came to the conclusion that an internal form of Wikipedia could be established behind the firewall to help start the process of gathering all the powerful information that existed haphazardly across JPL. Because a platform to host the wiki was already available from JPL’s Office of the Chief Information Officer (OCIO), the website just needed to be organized and configured so people could start adding information. This freely available infrastructure allowed the grass-roots effort to flourish. From June to August 2009 the working group built the site, established the basic infrastructure, and created articles that explained what Wired was, what the ground rules were and instructions on how to add and edit content. They established recommended standards (based on Wikipedia) for article content and created templates to encourage the use of this standard, which consists of: an overview, hyperlinked table of contents, body, references, “see also,” useful links, and JPL points of contact. Beta testing of JPL Wired occurred from October to November 2009 and involved 40 test users. One result of the beta test was to make Wired clean, fast and simple for the end user. To access the site, a user simply types the word “wired” into their browsers. Users do not have to log in to view articles as long as they are behind the firewall. The homepage is also clean and simple and is intended to remind people of using Wikipedia or Google because that is primarily how you find information on Wired as well.
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The working group introduced JPL Wired via an email from upper management on 18 January 2010. The working group did a soft-rollout by giving presentations to engineering sections at the working level, as well as division managers and executive leadership on lab. Through word of mouth, those initial presentations led to additional group meetings and demonstrations. This approach supported a deliberate and steady growth profile to allow for dynamic updates to the structure, documentation and articles of the wiki during the early months. The working group felt that growing too quickly initially wouldn’t allow time to adapt and make any changes to the wiki that might be needed to ensure long-term sustainability. JPL Wired grew steadily during the six-month period following launch, as shown in Figure 1, and continues to grow. Over half of JPL employees accessed the system and the number of articles grew to 477 during these first six months, as shown in Table 2. A core group of “Power Users” has emerged within Wired, analogous to those in Wikipedia (Kittur et al., 2007; Kittur, Pendleton & Kraut, 2009). These are employees that use Wired the most and make the most edits. Most of their edits are for format as opposed to technical content. This “shaping” behavior (Yates et al., 2010) helps maintain consistency from article to article and allows Wired to be read, written, edited, navigated, and used more easily by readers and editors alike. Newer employees (less than five years) have been contributors of particularly content-rich articles. These newer employees interview other Table 2. JPL Wire usage statistics from 18 Jan 2010 – 17 Jul 2010 Total page views
63,950
Unique visitors
2,837
Total articles
477
Page views/month
Over 16,000
Moving Wikis Behind the Firewall
Figure 1. Significant milestones and growth profile of JPL Wired
employees with more experience, capture that information in article format, and then publish it on JPL Wired. In this manner, the information in the experienced employee’s brain is indirectly transferred through mechanisms that are natural – and enjoyable – for these senior employees: ad hoc question & answer sessions. These senior employees contribute significantly to the wiki without ever having to touch a computer.
ORGANIZATIONAL ACCEPTANCE OF JPL WIRED JPL Wired used a bottom-up approach to knowledge management that resulted in top-down recognition and support. It is a grass roots effort that continues to succeed by the collective participation of many employees who are “working in the trenches”. However, lessons learned from past knowledge management efforts at JPL show that contribution rates may suffer if end users do not feel management values contributions to the wiki knowledge base. For this reason, management’s encouragement through actions such as verbal recognition, awards for outstanding articles, and including Wired contribution requirements on
yearly performance reviews have contributed to the success of the intrapedia. Early indications are that contribution requirements are particularly successful in motivating participation. One engineering division requires all engineers to contribute one article a year. After three months of this policy, the percentage participation is high and, more impressively, users go on to contribute additional articles beyond the required one. One area where JPL Wired has had limited success is promoting community authorship. The vast majority of articles are written by a single author; although more experienced users will routinely “shape” other articles. Exceptions to the norm of single authorship tend to be for general purpose articles such as favorite lunch spots or acronym lists. JPL Wired has benefitted from the transition of original members of the working group into “wiki champions” (Wagner & Majchrzak, 2006b). These champions promote JPL Wired across the Laboratory, organize “power user” meetings, assist new contributors, and routinely shape articles. The OCIO helps to defray the championing costs while allowing JPL Wired to maintain its grass roots feel.
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The Wired community expands significantly – and temporarily – during summers with the annual influx of co-op and summer hire students. To capitalize on this energetic, web-savvy population, several organizations across the Laboratory require students to contribute at least one Wired article based on their summer experiences. In addition to adding to the collective knowledge of the Laboratory, this approach provides the motivation for inter-generational knowledge transfer and increases the interactions between summer hires and more-senior personnel. As JPL Wired has matured over its first year of operation, the population of new users has shifted from early adopters to late adopters and followers (Grant, 1996). These users are less likely to be enamored with the technology and more with the benefits it could provide. During presentations throughout the organization, these employees consistently voiced a common set of questions: • • • •
•
Who do I contact to fix an error? Who determines that a topic should be included? Where is the official version of the article and how do you circulate drafts for review? How do I keep control of my content? (i.e., how do I prevent someone else from introducing errors into my article?) How do you prevent people from posting sensitive information (e.g., active proposals), putting in junk, doing something malicious, or sharing proprietary content outside the organization?
While these questions illustrate employee discomfort and lack of familiarity with wiki technology, they also provide insight into embedded cultural norms that are at odds with the “wiki way” (Leuf & Cunningham, 2001), as discussed later in the chapter. JPL Wired came into existence because of a compelling individual need, shared among a cohort of workers, recognized by immediate manage-
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ment, and enabled by organizationally provided wiki infrastructure. It has grown as a grass-roots effort by word of mouth, targeted meetings, management policy, and executive endorsement. Unlike other knowledge management efforts, success did not hinge on having an executive level champion convincing organizational members to use the resource (e.g., Holsapple & Joshi, 2000) – but rather on continued motivation at the grass-roots level, facilitated by the availability of wiki technology as part of the organization’s IT infrastructure, and enabled by modest OCIO financial support for championing. The majority of articles on Wired are analogous to the informational articles found on Wikipedia. The Wired power users group, however, encourages wiki use beyond knowledge capture. JPL users have an option when they create a wiki for the use of a group to do it as a private wiki or to instantiate their wiki as part of Wired. These work-wikis instantiated on JPL Wired represent a significant departure from the intrapedia model, but offer distinct team and organizational benefits. The second part of this case study describes one such work-wiki created to support the detailed technical review of potential space missions.
THE CASE OF THE STMC REVIEW SITE The STMC Review Site is a work-wiki set up to coordinate the scientific, technical, management, and cost (STMC) review of a JPL portfolio of potential NASA missions. In the words of the first author: The STMC Review Site was born of urgent necessity. I received a last minute assignment to facilitate the STMC reviews for an extremely large portfolio of proposed space missions [number intentionally withheld]. While the high-level planning for this review had been underway for several months, I now had to translate those plans into action. The
Moving Wikis Behind the Firewall
review involved coordinating 200 reviewers, each assessing different subsets of proposals requiring different mixes of scientific and engineering expertise, concentrated into a highly condensed three-week period. My role was to make the review process simple, easy and painless for those 200 people, while ensuring that we met our stringent deadlines, kept costs to an absolute minimum, and produced high quality feedback. Because the proposals would be part of a NASA competition to select the next space mission, access to specific types of information had to be controlled. The review involved every major scientific, engineering, and business organization on Laboratory, several external interfaces, the formulation office that oversees the review process, and multiple independent project teams working on individual proposals. Information was flowing in all directions. Stepping into the process mid-stream, I first used standard desktop tools (primarily spreadsheets and email) to make sense of this complex and highly dynamic situation. The next challenge was to find efficient ways to ensure that the participants knew what they needed to do, with what, and by when. This involved getting – and keeping – all the participant organizations in synch, distributing information to many different categories of users based on their needs, and tracking what was happening at any given time. In the past, I would have considered creating a website, but there wasn’t time or budget and the content was going to require frequent rapid updates. I considered a private wiki, but did not want to add another layer of user management and access control into the process. I was familiar with JPL Wired, knew they were open to including work-wikis (even though I didn’t fully support that idea at the time), and that the power users could provide help if needed. So, over the holiday weekend preceding the start of the review, I created the STMC Review wiki and hit the ground running.
THE GENESIS OF THE STMC REVIEW WIKI The STMC Review Wiki operated intensely for three weeks, and now resides as an artifact of an organizational event on JPL Wired. Its purpose was to facilitate the flow of knowledge for personnel participating in the STMC review. For the vast majority of review participants, the STMC Wiki functioned like any other website: it was a place to go to find information, navigate to web-based applications, and check for status and due dates. Access statistics show that over half of the review participants visited the wiki at some point during the review process. During the three weeks of operation, the wiki climbed into the Top 20 for JPL Wired and the Top 5 for most edit activity. Even when viewed simply as a website, several features of the wiki made it valuable during the review process. First, and most important, the same features that make it easy for multiple people to edit the site made it extremely easy for the single primary user to edit the site. WYSIWYG editing and article templates made it simple to create the initial structure, stub out areas for future development, update the content, and restructure as needed. While the wiki environment enabled rapid experimentation, the versioning and rollback made experimenting low risk. Second, the ability to embed actual spreadsheets so they were displayed on the wiki but kept their formatting so were still editable, enabled rapid easy use of personal work products within the wiki. For resources that relied on spreadsheet formatting functions to make the content more user-friendly, this saved a lot of time that would have otherwise been spent re-creating tables using the less-capable wiki formatting. Other wiki features provided smaller, but still tangible benefits such as setting “watches” for notification of page changes, being able to rapidly create and link “child” pages, and having access to page statistics to monitor traffic.
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THE STMC REVIEW WIKI IN THE CONTEXT OF THE WORK PROCESSES The use of the STMC wiki was constrained by the much larger context of the work processes and suite of other tools and resources used, as shown in Figure 2 and described in Table 3. The resources used to support the STMC Review included desktop applications, a dedicated area of the institutional document management system, the institutional system for collection and distribution of feedback, and the STMC Wiki, hosted on JPL Wired. The STMC Wiki filled three voids in the review process. First, the wiki was essential to synchronize reviewer assignments. One can think of these assignments as transactions that occurred on different baselines via multiple, asynchronous chan-
nels. Changes were sent via email, over the phone, or via modifications to whatever version of the spreadsheet the user had available. This process quickly grew unmanageable as the number of participants increased, emails crossed, mistakes were made in recording the transactions, and it became more challenging to trace the correct order for the transactions. With the wiki, management and individual reviewers could check official assignments against instructions received through other channels. Second, the wiki provided a centralized location for help resources. While valuable in directing users to resources for self-help, the wiki also made help resources available on demand for the help providers. In addition, if interaction with a user led to changes to help content, these changes could be implemented quickly. Finally, the wiki provided a place where new users could come up
Figure 2. Processes and resources provide the overall context for the review
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Table 3. Process descriptions and IT tool use for the STMC review Work Process
Activities
Performed by
IT Tools Used
Review the Proposal
Read Proposal Provide Feedback Process Feedback
Hierarchically structured review board with over 200 subject matter experts and management reviewers
Electronic Review Item Discrepancy System (internally developed web-based application)
Manage the Review Process
Identify and assign reviewers Create schedule Manage cost and schedule Communicate with executive management Communicate with external partners
Upper level management
eMail
Facilitate the Review
Coordinate participation Distribute documents Control roles and access privileges Provide help function for process and tool Track status
Review Facilitator
STMC Wiki eMail Document Management System
to speed. The chronological listing of announcements, assignment tables, schedules, due dates, and review instructions provided the context to understand the review process and the individual’s role within that process. All three of these voids could have been filled equally well by a regular website. Wiki technology, even if not fully exploited however, resulted in a resource that had a significant impact on the review process. In the next section we explore the longer-term contributions of the STMC wiki.
WORK-WIKI AS ARTIFACT The STMC Review lasted for limited time, during which it was critical for operations and highly active. It will, however, remain associated with JPL Wired as an artifact. The question then remains, what is the value of an artifact in an organizational intrapedia? There are at least two ways in which the STMC wiki helps the organization. First, the artifact may aid in the transfer of best practices. The STMC wiki was the first created to coordinate a STMC review. It evolved during the course of the STMC review because the wiki itself and much of its
content were invented on-the-fly as the review progressed. By the end of the review, the STMC wiki captured key features and knowledge relevant to conducting a review of this magnitude and complexity. Subsequent reviews have incorporated wikis modeled after the STMC review wiki. The second potential benefit is as a catalyst for process improvement. This first edition of the STMC review wiki emerged during the process to fill specific, unmet needs without disrupting the process. The open question, therefore, is what would an STMC wiki look like if its design could be used to intentionally change the process? Because changes in the tools are likely to result in changes to the process (Leavitt, 1965; Lyytinen, & Newman, 2006), one needs to consider the integration of the two in any design activity. The specific question inspired by the wiki technology then is how to incorporate community action into the joint modification of tool and process. This concept of a wiki artifact, however, deviates from the overarching wiki goal of keeping content current. Although the artifact no longer changes, it is not obsolete. To handle the paradox of a non-changing, but not obsolete wiki article, JPL Wired is considering modifying the article header to indicate it is an artifact, adding a sum-
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mary of how the article was used and during what time periods, and linking to information about the eventual outcome of the review process.
DISCUSSION Public vs. BTF Wikis In describing the application of general wiki technology internal to organizations, Wagner & Majchrzak (2006b) report, “corporate wikis differ from public wikis such as Wikipedia because they are smaller, have fewer contributors who are non-volunteers, are created to support organizational activities… and have to maintain propriety of intellectual property” (p.2). As summarized in Table 4, these and other differences exist between public and corporate wikis, and between different types of corporate wikis. Public wikis operate under a general set of assumptions. First, everything on the wiki is freely available to anyone. Given the broadness of topics, there are no boundaries so potential membership is the human race, and the wiki exists
for the public good. Second, they assume that collaboratively derived content is better than any individual effort because expertise is distributed and multiple perspectives are valuable. There is no guarantee, however, for the goodness of the content, so users must exercise caution when applying knowledge gained through the wiki. Third, the community can successfully integrate the content and consensus can be reached on how to represent controversial topics. The environment is set up to recover from rather than prevent malicious activities. Finally, participation is purely voluntary. Members participate because they want to, and for many, sharing is its own reward. Corporate wikis, however, exist to benefit the organization. The costs associated with operating a wiki are borne by the organization, which expects value from the wiki in return. If the wiki contains knowledge that provides a competitive advantage, the organization tightly controls access to ensure that the value remains in the company. Second, the scope of the wiki is limited to the interests of the organization and its employees. Therefore, there is a smaller number of articles and a smaller population of potential contributors
Table 4. Comparison of public wikis, intrapedias, and work wikis Characteristic
Public
Corporate-Intrapedia
Corporate Work-Wiki
Community of Interest
General public
Organization members
Organization members involved in the specific work process
Content ownership
Public property
Company proprietary
Company proprietary, possibly limited to members involved in work process
Creation/Editing
Self-selected
Self-selected, but also influenced by organization structure and extant communities of practice
Self-selected, but influenced by work group membership and expectations
Governance
Emergent, socially-based, community enforced
Community and organizationally enforced
Organizationally and work-group enforced
Hosting environment
Cloud, with no financial obligation to participants
Organization provides financial resources, physical, and software environment
Potential Topics
Anything
Limited to the broad interests of the organization
Tightly focused on the needs of the work group
Content Quality
Current, actively being updated Caveat Emptor
Value despite having no current activity Implied warranty as to accuracy
Required to be accurate and up-todate
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and users. The level of expertise of these users, however, can be expected to be much higher than the general public because the employees are paid to develop this expertise. Additionally, with a limited focus, the articles can be specific to the organization creating a higher information density than if the subject matter were diluted to suit a larger target audience. Third, while many users may participate voluntarily, the organization may mandate some level of participation. Parts of the organization may feel compelled to participate to preserve their reputation and ensure that content representing their domain is accurate. The wiki community is a subset of the organizational community and actions taken on the wiki can result in real-world organizational consequences. Unlike the public wiki, the organization can impose harsh penalties for violating norms as well as reward top contributors. Fourth, while public wikis operate on the principle of caveat emptor (“buyer beware”), corporate wikis may be perceived as having an implied warranty. The organization, by allowing the wiki to exist, implicitly accepts responsibility for how the content of the wiki is used by its employees.
INTRAPEDIAS VS. WORK-WIKIS This case study presented experiences implementing two types of wikis behind the firewall of a single organization. Despite having different purposes, the wikis shared several characteristics. First, and most contrary to public wikis, is the sense that for each article, there is a de facto owner for the content and hence others are reluctant to contribute. While prior research on knowledge management systems has found many reasons why people are unwilling to contribute such as a perceived potential to harm one’s reputation or loss of intellectual capital (Bock, Zmud & Kim, 2005; McDermott & O’Dell, 2001; Tsai, 2002), unwillingness to participate via wiki could also be rooted in the fear of impinging on someone else’s
territory. Users may recognize a natural authority associated with the content and have to overcome some threshold (e.g., of goodness, quality, uniqueness) before feeling that their contributions would be appropriate. Creating or contributing to a wiki article can be viewed as “speaking up” organizationally, and therefore be influenced by perceptions of psychological safety (Detert & Edmondson, 2006). Individuals are more likely to speak up when they feel that their inputs will be respected and valued, and that there are no negative consequences for doing so, even if they are wrong. Perceptions of psychological safety relative to wiki contributions therefore may be based on an individual’s self-assessment of his or her personal knowledge relative to others in the organization. While individuals contributing to a public wiki may compare their knowledge to that of the general public and feel confident that they can add value to the wiki, those in organizations may be evaluating their knowledge as compared to recognized, organizationally sanctioned experts, and consider themselves lacking. Patterns of participation in JPL Wired are consistent with this concept. Most articles are individual or team-generated, with subsequent edits by the originators and shaping by Power Users (e.g., per Yates, Wagner, & Majchrzak, 2010). Exceptions tend to be articles where no one would be perceived as having specialized knowledge, such as the article on “Where to Eat Lunch.” The successful operation of the STMC workwiki depended in large part on community members not making edits themselves. For content such as due dates, reviewer assignments, or status, discrepancies had many potential causes. Knowing what fix to make required access to knowledge beyond what most users had. Users of these two wikis may have applied an appropriateness heuristic when deciding if and how to contribute. Unlike with Wikipedia, whose reliability is often questioned (Lih, 2004) and whose founder has publicly stated should not
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be used for academic purposes (Young, 2006), users of these two BTF wikis expect the content to be reliable. Therefore contributions may have been limited by the contributors’ confidence that additional content they could provide was also reliable. Both the STMC work-wiki and the JPL Wired intrapedia challenge the concept of obsolescence in wikis. While the literature highlights metrics such as number of edits, rates of editing, and number of visitors as measures of goodness (Blaschke & Stein, 2008; Voss, 2005) these measures are based on the assumption that activity equals value. In Wikipedia, inactive articles are considered obsolete and freshness is valued. Using traditional measures, the STMC wiki could be evaluated as: exceedingly fresh (based on numbers and rates of edits), poor (just a single editor), and facing imminent obsolescence (significant drop in traffic after the STMC review ended). Intrapedia articles on JPL Wired may become stale, but again that does not imply obsolescence. JPL has seen, for example, many technology areas ebb and flow over time. Just because there is no activity now on an article, does not mean that the next flurry of activity is not just around the corner. For example, an article on JPL Wired states that JPL tested its first airbag system in 1966, but didn’t use the technology until the 1997 Mars Pathfinder Landing (Rivellini, 2004). One could imagine that in the intervening 30 years, there were long stretches of time when technology development was dormant. If there had been a wiki for using airbag technology to land on other planets, the wiki would still have been “current” but not fresh, dormant but not obsolete, and definitely of continuing potential value to the organization during those decades. As described by Kane and colleagues (2009), Wikipedia communities evolve over time with members leaving, joining, or changing types of participation. Corporate intrapedias are likely to experience the same changes as employees come and go, but also as business needs shift.
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Both JPL Wired and the STMC Review wiki succeeded in short amounts of time. This initial success, however, is tempered with the understanding that usage depends on organizational prodding such as management-levied requirements to submit articles to JPL Wired, reminder emails, or the review facilitator directing new reviewers to access the STMC Review wiki. Neither resource reached the point of being the de facto way users seek information; reasons to visit needed to be created by the organization. The long-term success of JPL Wired and future artifact wikis is in the hands of the general population of employees. In the next section we discuss how the transition to wiki-based systems may require organizational paradigm shifts and how moving behind the firewall may require adjustments to the public wiki paradigm.
PARADIGM SHIFTS AND ADJUSTMENTS While the reception to JPL Wired has been overwhelmingly positive, employees have consistently raised issues indicative of fundamentally different underlying assumptions about the way the world, the web, and the organization work. Addressing these legitimate concerns means recognizing the nature of the paradigm shifts required to move wikis behind the firewall, especially for intrapedias. While the majority of shifts are to the wiki paradigm, there are also some adjustments in the wiki paradigm needed to fully exploit wikis behind the firewall. A fundamental tenet of wikis is that content is published and then the community responds by reviewing the material, making corrections, adding new content, or changing the structure, which we characterize as “publish-then-review.” At JPL, however, work generally goes through a rigorous peer review process before being published to make products as accurate, complete, and comprehensive as possible. “Review-then-publish” is
Moving Wikis Behind the Firewall
deeply engrained in the engineering and science cultures. The concept of publishing something that others can see that may have errors, gaps or inconsistencies in it goes against the culture. When the organization is responsible for a spacecraft hurling its way through space 300 million miles away, errors are not acceptable. One obvious challenge then to the use of wikis is shifting from a “review-then-publish” to a “publish-then-review” paradigm for some wiki-appropriate subset of organizational knowledge. To make this shift, organizations need to understand the real risks associated with sharing information that may not be correct enough. Closely related to the review/publish issue is the shift from individual to collective ownership. Employees are comfortable with someone owning a document and therefore controlling all changes to it. Personnel in the JPL Wired meetings expressed extreme discomfort with the idea of changing someone else’s work. In one staff meeting presentation of JPL Wired, the staff members of the organization found several errors in a new JPL Wired article. No one, even the more web-savvy staff members, considered editing the wiki article themselves. Instead, every error was stated as a “need for the responsible person to fix.” After the meeting, the email traffic generated to fix the problems far exceeded the effort that would have been required for someone from the staff meeting to edit the article directly. In fact, several of the emails contained drafts of paragraphs for the originator to post. There’s no doubt that in situations such as these, using the collective editing capabilities of the wiki would be more efficient. However, the question remains whether it would be more effective. Specifically, the error resulted in a dialogue between different subject matter experts and the author of the wiki article, only part of which was captured in the eventual change to the wiki content. The net result was active learning from different perspectives due to the interaction. While wiki platforms provide discussion options that could support a similar
learning experience, email is a much more widely used approach. The acceptability of collective ownership may depend on how one defines the community. Collective ownership at the organizational level is appropriate when the article is addressing possible lunch locations, but much less so when addressing how to drive a rover on Mars. A much narrower population of JPL employees, those that actually drive rovers on Mars, are the natural community for the rover driver wiki. All rover drivers are expected to contribute relevant information to the wiki, as appropriate, to aid each other in operating these complex robots. It is highly unlikely that others outside the team would be in a position to make a valuable contribution to the wiki. Collective ownership is a defining characteristic for public wikis. Individual ownership is the default mode for organizational knowledge, at least at JPL. To reconcile these two different paradigms may require inventing a third, constrained collective ownership, where the constraints are tied to the locus of knowledge relative to a given subject. Within this constrained environment, personnel are expected to contribute. Outside of it, personnel self-limit their participation based on self-assessed appropriateness. Contributing to a wiki places one’s work into an environment where it can be modified by anyone in the community. Contrary to traditional individual ownership, collective ownership carries with it an on-going commitment to the content. Publishing a document is static – once published, it is not going to change. Wikis are dynamic, and not only can they be changed, there’s no guarantee these changes will improve the material. Therefore, in moving from static to dynamic publishing, the author has to expend effort not just to get her article right – but to keep it right. Moving to a wiki environment gives employees tremendous flexibility in deciding what articles to write and what subjects to cover. The potential exists to create a lot of valuable content – but also a lot of junk. Younger generations of workers are
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comfortable with searching, sifting, and surfing to get to the valuable nuggets; they have the tools to do so. Therefore, even though there may be a lot of junk on the wiki, powerful search tools means that the general user will never have to see it, unless specifically looking for it. This philosophy is part of the motivation for including work-wikis on JPL Wired. While younger generations are comfortable in the “cloud,” older generations have much stronger ties to actual hardware. The baby-boomer generation came of age in an environment where computer memory was precious and had to be carefully managed, where search engines were rudimentary, and where you never introduced extraneous material into your system or database for fear of degrading performance. The stronger one’s ties are to the physical hardware, the more challenging it is to move from a paradigm where knowledge is structured to be efficient, to one where inefficiencies are overcome by strong search capabilities. The close relationship of the user to the hardware (vs. the cloud) also exists at the organizational level when it comes to paying for the wiki. In moving from public to corporate wiki, the cost of use stops being “free.” The organization has to pay for servers, software licenses, memory, power – all costs that are relatively invisible for public wikis. Further, because the organization pays for wiki hosting, the operational costs cover all content, including clutter. Therefore, it is in the organization’s best interest to tightly focus wikis on content that is valuable to the organization. Organizational liability for the wiki extends beyond hardware and software to the content itself. In moving behind the firewall, the wiki content changes from caveat emptor to some level of implied warranty. With concentrated expertise, organizations cannot rely on the law of large numbers to ensure that the majority of
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critical information is covered – the quality of a given article may depend entirely on whether the right one or two people are engaged in writing it. Instead, the organization may need to actively take responsibility for ensuring that posted content is accurate. For example, if an employee acts in good faith based on a piece of information published in the wiki, and that incorrect information results in a failure, who is at fault? Public wikis rely on the community to detect and correct errors. Operating under an assumption that people will not intentionally try to damage the wiki, public wikis focus on being able to recover from errors rather than prevent them. Corporate wikis, however, face circumstances where there may be significant costs associated with errors, e.g., not protecting proprietary information. Corporate wikis therefore may need to find ways to aid users and prevent them from accidentally doing something inappropriate. Some form of organizational stewardship is necessary in organizations unwilling to accept the risks inherent in using information captured in wikis. In summary, using wikis behind the corporate firewall may require changes in the way organizations think and operate, and adjustments to concepts considered fundamental to public wikis. Behind the firewall, collectives are constrained, organizations bear the costs associated with hosting the wiki, content is presumed to be reliable which leads to organizational liability for the use of that content, and contributors must overcome the discomfort of publishing before reviewing and expend effort maintaining the accuracy of what they do publish. In return, the organization and its employees benefit from new approaches to capturing and sharing knowledge. How to best capitalize on the benefits of wikis while avoiding potential problems is an area of both academic and practical importance, as discussed in the next section.
Moving Wikis Behind the Firewall
FUTURE RESEARCH DIRECTIONS Wikis are moving behind corporate firewalls well ahead of the research that could help make these moves more efficient and effective. Based on our experiences implementing two inter-related corporate wikis in a single organization, we present the following recommendations for future research and practice. Our results, however, are based on two experiences in a single organization with systems that are still early in their lifecycle, and therefore the results may be limited in their generalizability to other domains and types of organizations. The results allude to the influence of organizational culture. One area for future research then is how do different types of organizational and social culture impact corporate wiki use? This chapter proposes a set of dimensions that can be used to characterize wikis (see Table 4). Future research can test the completeness and importance of these dimensions. Specifically, are there other dimensions? Which dimensions are most important in different organizational contexts? What characteristics are most important if the primary concern is content reliability; maximizing participation? Given that organizations pay for their wiki services, how can they measure their return on investment? More generally, how can they measure the success of their organizational wikis? Activity metrics such as number of edits or size of the community used on public wikis may not be sufficient for corporate wikis. For example, in a public wiki, the level of activity (number of contributors, frequency of edits) is an important metric, with more activity indicating a higher measure of goodness. For corporate wikis, activity is important, but lack of activity is not necessarily bad. Articles could be dormant rather than stale. Future research into appropriate metrics would be beneficial to practice, and provide a mechanism for researchers to quantitatively compare wikis.
Intrapedias and work-wikis clearly represent a codified form of organizational memory. Future research could examine how the ability to dynamically “revise” these memories impact creation, structure, governance, and application of organizational memory. Finally, this chapter provides insights into several emerging issues for IT governance. The introduction of wiki applications extends the dichotomy of IT versus business applications used in hybrid governance approaches (e.g., Gallagher & Worrell, 2008; Sambamurthy & Zmud, 1999) to include knowledge providers from throughout the organization. Wikipedia provides an example of how governance mechanisms such as super users or featured articles evolve over time in a public setting. In an organizational setting, intrapedias and work-wikis may also stress governance models due to new requirements for stakeholder involvement, content reliability, and platform maintenance. Research is needed to address multiple governance issues relative to the use of intrapedias and work-wikis behind the company firewall. For example, as the organization grows more dependent on knowledge captured in wikis, how will the responsibilities for increased stewardship be distributed throughout the organization? As employees move in and out of the organization, who is responsible for the knowledge content they leave behind? In the JPL examples, there are both individual and organizational responsibilities for maintaining the quality of content and consistency of presentation. To what extent does content contributed by individual employees become the responsibility of their managers? How will the organization reward contributors? What mechanisms need to be in place to discourage harmful behavior? While public wikis rely on community governance and behind-the-scenes administrators to maintain order, corporate wikis reside within an organizational environment complete with exist-
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ing roles, responsibilities, cultural and behavioral norms, and accounting standards. Changes in governance approaches as well as adjustments to wiki characteristics will be needed to enable wikis to function effectively behind the firewall. Research is needed to understand the nature of these changes and their larger impact within the organization.
CONCLUSION The use of wikis behind the firewall in corporations presents significant opportunities as well as challenges for improving knowledge capture and work processes. This chapter identified fundamental characteristics of wikis and how these change between public and corporate wikis, and between wikis intended for knowledge capture (intrapedias) versus supporting work processes. A case study describing two organizational wikis illustrated the power of the individual in instigating knowledge capture and the ability of wiki technology to rapidly and easily support individuals in their work efforts. The case study also exposes how adopting wikis challenged several deeply engrained cultural beliefs. As wikis become more prevalent behind the firewall, organizations may need to shift to new ways of thinking about knowledge sharing, the role of the individual versus the collective, and governance. Conversely, characteristics of wikis may need to be adjusted to deal with the realities of knowledge use within organizations.
ACKNOWLEDGMENT This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
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REFERENCES Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. Management Information Systems Quarterly, 25(1), 105–136. doi:10.2307/3250961 Anthony, D., Smith, S. W., & Williamson, T. (2007). The quality of open source production: Zealots and good Samaritans in the case of Wikipedia. Dartmouth Computer Science Technical Report TR2007-606, September 2007. Ben-Chaim, Y., Farchi, E., & Raz, O. (2009). An effective method for keeping design artifacts upto-date. In Proceedings of the Fourth Workshop on Wikis for Software Engineering 2009, ICSE, (pp. 1-6). Ben-Chaim, Y., Levy, M., Hadar, I., Farchi, E., & Bronshtein, A. (2010). Engaging stakeholders in globally distributed software development processes. In MCIS 2010 Proceedings. Paper 14. Blaschke, S., & Stein, K. (2008). Methods and measures for the analysis of corporate wikis. In Proceedings of the 58th Annual Conference of the International Communication Association (ICA), May 22-26, Montréal, Canada. Bock, G.-W., Zmud, R. W., & Kim, Y.-G. (2005). Behavioral intention formation in knowledge sharing: Examining the roles of extrinsic motivators, social-psychological forces and organizational climate. Management Information Systems Quarterly, 29(1), 87–111. Ciffolilli, A. (2003). Phantom authority, selfselective recruitment and retention of members in virtual communities: The case of Wikipedia. First Monday, 8(12). Retrieved June 4, 2010, from http://firstmonday.org/htbin/cgiwrap/bin/ ojs/index.php/fm/article/view/1108/1028
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Denning, P., Horning, J., Parnas, D., & Weinstein, L. (2005). Wikipedia risks. Communications of the ACM, 48(12), 152. doi:10.1145/1101779.1101804 Detert, J. R., & Edmondson, A. C. (2006). Everyday failures in organizational learning: Explaining the high threshold for speaking up at work. Harvard Business School Working Paper, 06-024. Gallagher, K. P., & Worrell, J. L. (2008). Organizing IT to promote agility. Information Technology Management, 9, 71–88. doi:10.1007/s10799007-0027-5 Grant, R. M. (1996). Prospering in dynamically competitive environments: Organizational capabilities as knowledge integration. Organization Science, 7(4), 375–387. doi:10.1287/orsc.7.4.375 Holsapple, C. W., & Joshi, K. D. (2000). An investigation of factors that influence the management of knowledge in organizations. The Journal of Strategic Information Systems, 9, 235–261. doi:10.1016/S0963-8687(00)00046-9 Holtblatt, L. J., Damianos, L. E., & Weiss, D. (2009). Factors impeding wiki use in the enterprise: A case study. Mitre Corporation Report: 09-3961. Jorgensen, D. L. (1989). Participant observation: A methodology for human studies. Newbury Park, CA: Sage. Kane, G. C., Majchrzak, A., Johnson, J., & Chenisern, G. L. (2009). A longitudinal model of perspective making and perspective taking within fluid online collectives. Paper presented at Thirtieth International Conference on Information Systems, Phoenix, AZ, 2009. Kittur, A., Chi, E., Pendleton, B. A., Suh, B., & Mytkowicz, T. (2007). Power of the few vs. wisdom of the crowd: Wikipedia and the rise of the bourgeoisie. In Proceedings of the 25th Annual ACM Conference on Human Factors in Computing Systems (CHI 2007), April-May 2007.
Kittur, A., Pendleton, B., & Kraut, R. E. (2009). Herding the cats: The influence of groups in coordinating peer production. Paper presented at WikiSym ’09, October 25-27, 2009, Orlando, FL. Kramer, M., Gregorowicz, A., & Iyer, B. (2008). Wiki trust metrics based on phrasal analysis. Paper presented at WikiSym 2008, September 8-10, 2008, Porto, Portugal. Leavitt, H. J. (1965). Applied organization change in industry: Structural, technical and human approaches. In Cooper, W. (Ed.), New perspectives in organizational research (pp. 55–71). Chichester, UK: Wiley. Leuf, B., & Cunningham, W. (2001). The wiki way. Quick collaboration on the Web. Boston, MA: Addison-Wesley Longman Publishing Co., Inc. Lih, A. (2004). Wikipedia as participatory journalism: Reliable sources? Metrics for evaluating collaborative media as a news resource. Paper presented at 5th International Symposium on Online Journalism, April 16-17, 2004, University of Texas at Austin. Lyytinen, K., & Newman, M. (2006). Punctuated equilibrium, process models and information system development and change: Towards a socio-technical process analysis. Sprouts: Working Papers on Information Systems, 6(1). Retrieved from http://sprouts.aisnet.org/6-1 Majchrzak, A., Chellappa, R., & Cooper, L. (2005). Personalizing knowledge delivery services: A conceptual framework. In Desouza, K. C. (Ed.), New frontiers in knowledge management (pp. 51–75). Palgrave McMillan, UK. Majchrzak, A., Wagner, C., & Yates, D. (2006). Corporate wiki users: Results of a survey. In. Proceedings of the International Symposium on Wikis, 2006, 99–104. doi:10.1145/1149453.1149472
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Markus, M. L., Majchrzak, A., & Gasser, L. (2002). A design theory for systems that support emergent knowledge processes. Management Information Systems Quarterly, 26(3), 179–212.
Wagner, C., & Majchrzak, A. (2006a). Enabling customer-centricity using wikis and the wiki way. Journal of Management Information Systems, 23(3), 17–44. doi:10.2753/MIS0742-1222230302
Massey, A. P., Montoya-Weiss, M. M., & O’Driscoll, T. M. (2002). Knowledge management in pursuit of performance: Insights from Nortel Networks. Management Information Systems Quarterly, 26(3), 269–289. doi:10.2307/4132333
Wagner, C., & Majchrzak, A. (2006b). The wiki in your company: Lessons for collaborative knowledge management. A report for the Society for Information Management Advanced Practices Council. SIM, October 2006.
McDermott, R., & O’Dell, C. (2001). Overcoming cultural barriers to sharing knowledge. Journal of Knowledge Management, 5(1), 76–85. doi:10.1108/13673270110384428
Yates, D., Wagner, C., & Majchrzak, A. (2010). Factors affecting shapers of organizational wikis. Journal of the American Society for Information Science and Technology, 61(3), 543–554. doi:. doi:10.1002/asi.21266
Moskaliuk, J., & Kimmerle, J. (2009). Using wikis for organizational learning: Functional and psycho-social principles. Development and Learning in Organizations, 23(4), 21–24. doi:10.1108/14777280910970756 Ortega, F., & Gonzalez-Barahona, J. M. (2007). Quantitative analysis of the Wikipedia community of users. Paper presented at WikiSym 2007, Montreal, Canada. Rivellini, T. (2004). The challenges of landing on Mars. Paper presented at the 2004 U. S. Frontiers of Engineering Symposium, National Academy of Engineering, September 8-11, 2004. Sambamurthy, V., & Zumd, R. W. (1999). Arrangements for information technology governance: A theory of multiple contingencies. Management Information Systems Quarterly, 23(2), 261–290. doi:10.2307/249754 Tsai, W. (2002). Social structure of coopetition within a multiunit organization: Coordination, competition, and intraorganizational knowledge sharing. Organization Science, 13(2), 179–190. doi:10.1287/orsc.13.2.179.536 Voss, J. (2005). Measuring Wikipedia. Paper presented at International Conference of the International Society for Scientometrics and Informetrics, 10th, Stockholm (Sweden), 24-28 July 2005.
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Yin, R. K. (1994). Case study research: Design and methods (2nd ed.). Newbury Park, CA: Sage. Young, J. R. (2006). Wikipedia founder discourages academic use of his creation. Retrieved March 14, 2010, from http://chronicle.com/blogPost/ Wikipedia-Founder-Discourages/2305 Zickar, M. J., & Carter, N. T. (2010). Reconnecting with the spirit of workplace ethnography: A historical review. Organizational Research Methods, 13(2), 304–319. doi:10.1177/1094428109338070
ADDITIONAL READING IT Governance Institute. Board Briefing on IT Governance, 2nd Edition. Rolling Meadows, IL; www.itgi.org. Raghupathi, W. (2007). Corporate governance of IT: A framework for development. Communications of the ACM, 50(8), 94–99. doi:10.1145/1278201.1278212 Reagle, J. M., Jr. (2007). Do as I do: Authorial leadership in Wikipedia. Paper presented at WikiSym ’07, October 21-23, 2007, Montreal, Quebec, Canada.
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Schwartz, A. & Hirschheim, R. (2003). An extended platform logic perspective of IT governance: Managing perceptions and activities of IT. Strategic information Systems, 12, 129-166. Wade, M., & Hulland, J. (2004). The resourcebased view and information systems research: Review, extension, and suggestions for future research. Management Information Systems Quarterly, 28(1), 107–142. Weill, P., Subramani, M., & Broadbent, M. (2002). Building IT infrastructure for strategic agility. MIT Sloan Management Review, Fall 2002, 57-65.
KEY TERMS AND DEFINITIONS Authority: The bestowed or inherent right to make changes to a wiki. Behind the Firewall: Residing on a corporate intranet, with access limited to those internal to the corporation. Collective Membership: The self-selected set of participants who make changes to the form or content of a wiki. Community Governance: The formation and stewardship of the formal and informal structures, rules and procedures that guide the activities of the wiki by the collective membership.
Community of Interest: The set of people interested in a given topic. Corporate Wiki: Wiki-based knowledge resources, accessible behind organizational firewalls via intranets. Governance: Application of management, policies, processes and decision-rights for a given area of responsibility (adapted from Wikipedia/ governance). Hosting Environment: The physical and software resources used to host the wiki. Implied Warranty: Expectation by users that wiki content is assumed to be reliable, irrespective of whether the provider has expressly promised reliability, unless expressly disclaimed by provider. Intrapedia: Corporate wiki that enables the collective capture, refinement, and sharing of knowledge relevant to the organization in article format. Responsibility: The bestowed or inherent obligation to contribute to or maintain the quality of a wiki. Wiki: Sets of dynamically created web pages with content contributed directly by users in a web browser (Yates, Wagner & Majchrzak, 2010). Work-Wiki: Corporate wiki that enables coordination of work activities or otherwise supports the accomplishment of work in an organization.
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Chapter 4
Social Networks and Knowledge Management:
An Explorative Study in Library Systems Bhojaraju Gunjal University of Mysore, India Panorea Gaitanou Ionian University, Greece Sarah Yasin YBP Library Services, USA
ABSTRACT This chapter gives a brief introduction to Knowledge Management (KM) and its components, emphasizing the role Social Networks (SNs) can play on KM. The authors will delineate the benefits of collaboration between the concept of Social Networking and the process of KM. With the advent of Web 2.0 technologies, it is a natural evolutionary outcome that SNs have driven the advancement of KM, and conversely KM has driven the advancement of SNs. In certain instances, SNs and KM have a symbiotic relationship whereby one cannot exist without the other. Moreover, an impact analysis will be performed to show that while SNs are an outcome of KM, both require each other in order to succeed where Social Software fits. This chapter is particularly intended to cater to the needs of librarians in a corporate environment and to show the impact and benefits of SNs and KM in the information world.
INTRODUCTION Knowledge Management (KM) is the process of gathering, managing and sharing stakeholders’ knowledge capital within an organization. It promotes a collaborative and integrated approach to knowledge creation, capture, organizational access
and use (and re-use) of an enterprise’s knowledge assets. KM is not only about Knowledge Technology; rather it is a facilitator for achieving strategic business objectives (Gunjal, 2005). In addition, knowledge sharing in an organization enhances existing organizational business processes, introduces more efficient and effective business
DOI: 10.4018/978-1-61350-195-5.ch004
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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processes and removes redundant processes (Gunjal, 2005). Based on actual experiences of the leading global KM case-studies, the components of KM can be categorized into three components - People, Processes and Technology (seeFigure 1). •
•
•
People: The biggest challenge in KM is to ensure participation by employees in knowledge sharing, collaboration and reuse, to achieve business goals. Processes: These include standard processes for knowledge-contribution, content management (accepting content, maintaining quality, keeping content updated, deleting or archiving obsolete content, document/information retrieval, membership in communities of practice, implementation projects based on knowledge-reuse, methodology and standard formats to document best-practices and case studies, etc. Technology: KM technology solutions are facilitators for achieving strategic business objectives. KM provides functionality to support knowledge-sharing, collaboration, workflow, and document-management across an enterprise (Gunjal, 2005).
Social Networking plays an important role in enabling the KM process, which is mainly seen with the advent of Web 2.0 technology. Social Media are tools that provide users with knowledge on a local and global scale. The incorporation of Social Software in organizations not only benefits users, but also benefits the organizations themselves as well as other organizations it may collaborate with. When implemented efficiently, SNs have a great potential for building brands and capital, especially in a market considered to be sluggish in growth. Moreover, most organizations make use of Web X.0 technology in their KM approaches to enable their employees with knowledge sharing processes. This technology enhances KM usage and evaluation. Thus, the authors focus on this particular relation between SNs and KM to study the possible implications of SNs to KM. The rest of this chapter is structured as follows: the next sections outline the basic features of SN services. To continue, authors will provide an overview of the most important integrated SNs, underlining the basic scope they serve. While discussing SN services, the authors will concentrate on virtual environments as an important part of SN, where Second Life is presented as a case study.
Figure 1. Components of KM
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Next, the chapter will aim to analyze the impact of SNs to KM, emphasizing the particular role of SN services to the Library world. Finally, the chapter will draw some remarkable conclusions, regarding all the aforementioned issues.
Some of the main features of SNs are related to several factors, such as the relationships that are created within them, the network shape, etc. (Papailiou et al., 2007). In particular, the aforementioned factors can influence networks development and structure as follows:
SOCIAL NETWORKS: AN OVERVIEW
•
The idea behind social networking sites is not new. Since the early dates of internet, there was a plethora of SNs which users could join, exchange ideas and thoughts, participate in chat rooms and forums, discuss anything they desired, make friends, etc. An important difference between social networking sites and earlier forms of manyto-many conversations, such as chat rooms and blogs, is that social networking sites are based mainly on social relationships and connections, rather than on a shared interest (OfCom, 2008). The term “Social Network” was first used by J. A. Barnes in 1951, and can be defined as “a specific set of linkages among a defined set of actors, with the additional property that the characteristics of these linkages as a whole may be used to interpret the social behavior of the actors included” (Seufert et al., 1999). SN users seek connections based on culture, business, or general knowledge (the reference query). Becoming part of a SN is similar wherever one goes: there is a starting point at which users are requested to create a profile in order to place themselves within the architecture of an interface (OfCom, 2008). Depending on the richness of the architecture of the KM behind the SNs, the information users provide to the interface can be as static or as dynamic as the platform may allow. An example of such richness is when users create profiles which list their interests and each of the entries listed as free text can be searched. KM is also a process to make such information even more discoverable by using codices for those words which are often misspelled.
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•
When referring to relationships within SNs, we should acknowledge that these can be either formal-professional (focusing mainly on creating business relationships) or informal (among friends). In addition, relationships among users within networks can be categorized according to contents (e.g. services provided) or form (duration). The shape of a SN can be also considered of great importance. For instance, “open” networks help participants to have access to a wide range of information. Furthermore, users have the chance to participate to various communities and get to know several other users with common interests. On the contrary, “private” networks don’t provide enough chances for users to expand their social and professional networks and participate in various social activities and events, but offer a feeling of enhanced security and privacy.
Social Networking Services SNs are an important part of Social Software, but Social Software also include blogs, wikis, social bookmarking services, Instant Messaging Services (ΙΜ), micro-blogging services (like Τwitter) etc. Nevertheless, all these services aim to create SNs. In detail, some basic features of the architecture of SNs can be presented in Table 1. By presenting the above, it is clearly indicated how social networking sites can support knowledge sharing. The phenomenal rise of people connecting, creating and distributing user generated content through social networking sites
Social Networks and Knowledge Management
Table 1. Web 2.0 tools Web 2.0 tools
Description
Profiles
SNs allow people to create a free and rich representation of their own identity containing text, images and sound clips (Coenen et al., 2006), where personal information (such as education) and contact information can be presented.
Connections (friends)
These connections can be persons, groups or organizations that users are related to either friendly or professionally.
Groups
SNs allow people to form their own groups and freely join new groups as they realize they fit in. This characteristic, meaning the ability to create a network from the scratch, is one of the most important features that highlight the basic difference between social software and traditional communication software (Malone, 2009).
E-mail
An internal messaging system, quite similar to an e-mail system, is also provided through these networks, thus the sender doesn’t need to know the receiver’s e-mail, while messages are forwarded directly to the user’s external e-mail account.
Instant Messaging (IM)
This specific technology has greatly reduced the cost of communication and has made computer-mediated communication much richer (Coenen et al., 2006).
Scrapbooks (walls) and comments functionality
Through these functionalities identity feedback can be given and enhanced when social interactive features are provided.
Personalized toolbars
Personalized toolbars that can be configured by each user, according to his preferences, to provide quick access to programs.
Search function
This allows users to search or be searched by some sort of criteria, while at the same time offering people to maintain a degree of anonymity.
RSS (Really Simple Syndication)
RSS is a technology that is used by millions of web users around the world to keep track of their favorite websites. RSS allows automatic delivery of relevant content as it is published or updated either via a blog or within the news or media areas of a site. This technology is a new model for keeping employees, customers and business partners up to date. It pushes relevant information to them via subscription rather than relying on their ability to find the information.
Blogs and blogging
A blog (or weblog) is a web 2.0 application that offers periodic entries called posts on a dynamic webpage. Blogs changed the game of KM because with their creation came an entire shift in users’ approach to knowledge. Now both authors and users interact on these webpages and deliver an entirely new flavor of content (Martin-Niemi, 2009).
Social bookmarking services
As we encounter more information than ever was presented to a single user since the renaissance, one of the challenges of our day is remembering the information we see. Bookmarking programs help with the recall of this information. The beauty of social bookmarking services is that users can retrieve their bookmarks from anywhere they are connected to the internet (not just the one laptop/PC/iPhone they used to store the page to begin with). Users can also manage their bookmarks with folksonomies which tag the sites that interest them with identifying terms of their own choice which are meaningful on the indivisualized level (Millen et al., 2006).
Wikis
From a Hawaiian word that indicates the concept of quickness, a wiki is a website that allows users to change its content instantaneously and does not require the executive decision of a webmaster in order for new content to be uploaded. Wikis are a great example of the shift from the static Web 1.0 world to the dynamic Web 2.0 world. Wikis offer rapid collaboration within business networks and can be used to create multiple workspaces with page hierarchies and page linking for projects or topics (Harris-Jones, 2005). In 2006, Mahchrzak et al. conducted a survey in which 168 corporate wiki users were interviewed and present a list of a plethora of work activities that wikis can support within organizations. These include the following: software development, e-learning, project management, technical support, marketing and customer relationship management, resource management, R&D, etc. (Majchrzak, A et al., 2006). Finally, there are several benefits for organizations that use these collaborative technologies, because wikis can make work easier, improve processes that enhance an organization’s image and reputation.
Tagging, folksonomies, and tag clouds
Social tagging is a way to get relatively reliable content classification out of a large number of people (Avram, 2006). Folksonomies are search terms offered by users themselves. Websites that offer users to tag items using terms of their own choice can also diplay these tags as clouds which offer the most frequently used terms in larger and darker fonts than others. This is particularly useful to the librarian who seeks to know more about her end-users.
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has led to predictions about the potential of social networking to transform organizations. To be more specific, several people believe that SNs will become the new operating system for businesses. The future will show how things will finally evolve.
Integrated Social Networking Tools According to Boyd and Ellison, SN applications are actually web-based services that allow individuals to construct a public or semi-public profile within a bounded system, articulate a list of other users with whom they share a connection, and finally view and traverse their list of connections and those made by others within the system (Boyd & Ellison, 2007). Nowadays social networking services are proliferating much wider and faster, creating a unique problem for managing our social web presence. A lot of individuals need to be online to a great variety of groups, and it’s very difficult to remember all of the SNs they belong to and manage them separately. For example, a person needs to be active on Facebook to socialize, on Twitter so that he can write briefly his thoughts, on LinkedIn and Mendeley so as to communicate with partners around world. Also, he may have his own blog, where he shares more analytically his thoughts and ideas about specific issues. It is also very difficult for friends, coworkers or partners to find someone easily when he uses various social media since they don’t know which one to look for him on. These are basically the reasons for the development of several SN management tools which seem to offer significant solutions to the aforementioned issues. Web 2.0 technologies enable users to add and bookmark the desired content from the internet to their personalized websites without logging in to each site separately. These tools save time for users and enable collaboration in much faster way. Such examples are the following services can be see in Table 2.
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VIRTUAL ENVIRONMENTS AS PART OF SOCIAL NETWORKING: SECOND LIFE AS A CASE STUDY One of the primary concepts in KM literature is to identify key knowledge resources and to provide the appropriate mechanisms for creating, adopting and leveraging individually acquired knowledge for organizational benefit (Martin-Niemi, 2009). We believe that collaborative virtual environments can offer significant help towards this direction. A collaborative virtual environment can be defined as a software environment that creates a configurable universe, which emulates a number of serviceable aspects of physical reality, such as the concept of space, movable objects, navigation and communication between (representations of) humans (Tomek, 2001). One of the most widely known environments is Second Life (SL). Second Life, launched in 2003, is a 3D virtual world where users can socialize, connect and create using voice and text chat and in general can do whatever they choose to enhance their environment (Urban et al., 2007). Second Life offers a compelling synchronous experience for geographically disparate users to meet and interact. It’s a dynamic and interactive environment, where users have the feeling of immersion into a digital environment while at the same time the feeling of presence (by the sense of orientation and position in space) is enhanced. Users are represented by extremely customizable avatars that own a unique name and can resemble strong identities (Schmeil & Eppler, 2008). Real world corporations, universities, memory institutions, are expressing a great interest and have already established a virtual presence in Second Life. This presence and mainly the level of its success depend mainly on the network of relationships that will be created, instead of the traditional organizational connections within a business. Moreover, the basic characteristics that these virtual communities express are the informal type of network ties and the fact that no formal alliances or any kind of
Social Networks and Knowledge Management
Table 2. Integrated SN tools Integrated SN tools
Description
Xeesm
Xeesm is a social business application, helping people to be more approachable and reaching more people faster and more easily. It can be used as a social contact directory, which combines all online links to one (Xeesm).
Ping.fm
Ping.fm is a free social networking service that enables users to post to multiple SNs simultaneously (Ping. fm). Once one updates his account on Ping.fm, then the update is forwarded to all other social websites that are connected to Ping.fm. Consequently, this service can be proved very important to those users who need daily to manage various social media. Ping.fm groups services into three categories – status updates, blogs, and microblogs – and updates can be sent to each group separately (Berlin, 2009).
Socializer
Socializer allows users to easily submit a link to several social bookmarking systems. Thus, instead of having a link to each social bookmarking website, a single link to all of them is provided (Socializer).
Digsby
Digsby is a multiprotocol IM client that keeps all social media updated and allows collecting all e-mail, instant messaging, social networking and microblogging accounts under one roof. It’s really a very useful tool if someone wants to find a solution for social media overload (Digby).
TweetMeme
TweetMeme is the place to discover all the “hottest” links that users tweet on Twitter. One can retweet without going to twitter, by using one of over a million buttons on 10,000s of websites. It converts links to a short link before posting to SN services. These services can be used on different platforms such as – web, mobile, desktop, plugin and others (Tweetmeme).
Add This
Add This makes sharing easier for blogs, websites and flash. It’s one of the most multilingual sharing tools, as it is already translated in over 60 languages (Add this).
Add to Any
Add to Any is a tool quite similar to Add This, offering multiple possibilities to its users, sharing content, customizable and personalized options, etc. (Add to any).
Tweetdeck
Tweetdeck is a leading browser for real-time and social web, allowing users to connect with Twitter, Facebook, LinkedIn and MySpace (Tweetdeck).
ReBlog
Zemanta’s Reblog feature makes it easy to expand on conversational threads in the blogosphere-or to start our own. Users just identify the quotable text they want and add their own comments to it to create a new post on our blog (ReBlog).
Wefollow
Wefollow is a directory of Twitter users organized by interests (Wefollow).
control policies can exist (Martin-Niemi, 2009). This is one of the most important reasons that nowadays Second Life is under a lot of criticism. Moreover, a lot of residents (residents are called all the persons that participate in Second Life, either they own a land or not) are complaining of a plethora of problems and issues regarding their daily transactions within Second Life that actually spoil their virtual experiences. Some of them include the following: grid issues with logins, asset services, technical and maintenance issues that cause unfixable problems to organization’s structure, stability and communication problems, unsolved illegal issues etc. Consequently, a lot of people are re-evaluating their own personal investments in Second Life and meet a lot of difficulties to run their businesses and finally rely on Linden Lab’s (the firm that is responsible for
the development of Second Life) often unstable environment. Linden Lab’s vision was to make Second Life the world to achieve global virtualization. The potential for this growth should be continued at any cost and all provided services should be improved. Library organizations “jump into” virtual worlds like Second Life, mostly for marketing or educational purposes. As mentioned before, Second Life is a global community of creativity, collaboration, entertainment and interaction. Specifically, there are a lot of options for librarians-educators regarding learning-teaching in SL, as these multiple media platforms are unlike conventional environments. At the same time, these virtual worlds enhance social networking by providing orientation and instruction. In particular, Second Life offers new possibilities: 69
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•
• • •
•
The creation of new communities using web 2.0 applications (podcasting, video hosting, IM etc.). Participation in group projects around the world. Development of new partnerships and relationships among libraries. Provision of specific reference services and programs (such as book discussions, art exhibitions, skills practice, seminars, conferences etc.). Organizing events for fund raising.
Second Life makes us rethink library’s roles and strategies and provides a chance to collaborate and interact globally with users, share expertise, discuss issues and problems, and exchange ideas and new technological trends. Refer Second Life screen shot in Appendix 3 (Figure 7).
Impact of Social Networking on Knowledge Management The impact of Social Networking on KM can be seen with a broad look at all the components of KM. All these components - People, Process and Technology along with content - are greatly influenced by Social Networking. Social Νetworking itself is the process whereby technology allows people to collaborate, and so does KM. (see Figure 2) The nature of KM lends itself to collaboration, and because of this any type of collaborative software also enhances KM (Jones, 2001). The sharing of data though a SN is a prime example of such collaboration. Internet technology and KM go hand in hand. When there is a change in internet technology (Web X.0) it directly impacts KM (KM X.0) generations and its services. Where any entity of people is able to connect to another entity of people via the internet, KM is a natural evolutionary result of the development of such connectivity. Because of the collaborative nature of the internet, it follows that generational enhancements will involve the Management of
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Knowledge. As people willingly post minutia to online platforms, users suffer from Information Overload, thus sophisticated models of KM are required to filter the information that is meaningful. The trend of micro blogging may fade someday socially, but it thrives in the current climate because of the Attention Deficit many users have when using the internet. The Law of Least Effort applies to any entity using software applications: users will employ as few methods as possible when retrieving information (Gunjal & Buck, 2007). Rather than cull through lengthy documents online, users prefer to locate that small gem that pertains to their search. As long as search time is valuable to users, KM will be just as valuable as the process by which such information is streamlined. Users who tag items using social networking software do so for the benefit of information retrieval of selected items, where in KM 1.0 a webmaster or administrator would decide how users found items. KM 2.0 allows more people to lend a hand in enriching the functionality of the software and has in essence democratized information by putting this power in the users’ hands. Providing such power to users is also a driving force behind social networking: it appeals to users because of the shared sense of ownership it engenders. For interfaces that rely on Social Networking to bolster KM, organizations must create motivation for its users to contribute to the collaborative efforts of its users. This is a major shift for users whose ideas of possession of knowledge are not aligned with the new climate of collaboration and sharing. For instance, some users of Shelfari don’t go so far as to enter data about books they read because they feel they are providing free knowledge to Amazon, an organization that profits from such bibliographic data. Users with this mindset value the network of users more than the posterity of knowledge and the organization that supports the KM that delivers the functionality of the SN itself.
Social Networks and Knowledge Management
Figure 2. Impact of SNs on KM
It is clear from the proliferation of SN applications that KM is necessary to wrangle them into order. Social Networking applications can be organized like Russian nesting dolls – smaller applications nesting within larger ones. For example, Wefollow is a directory that compliments Twitter. Anyone who uses Yahoo Mail can also access his chat network from the email application, and from there use various plug-ins that go with chatting. Google sponsors the social networking site Orkut, which allows users within their own networks to photo share, video share, write on public scrapbooks and exchange emails. Hariharan argues that the way to overcome this challenge is to give credit to contributors and implement other systems of praise (Hariharan, 2002). We need to make SNs engaging to users; otherwise we will lose a piece of the KM triangle (seeFigure 1). Boyd stated that, “Until recently, most of the KM efforts were focused on the creation of central knowledge repositories, topdown approach where knowledge was seen as a separate entity” (Boyd, 2005). Social software
takes a dramatically different approach by connecting people to other people with the expertise they need at the moment.
KNOWLEDGE MANAGEMENT AND SOCIAL NETWORKING IN ORGANIZATIONS Organizations have profited from KM tools that enhance Social Networking – this is done with Facebook, Orkut, and LinkedIn to name a few. When people come together to meet others in their same professional field, or in interdisciplinary fields, businesses benefit because they can judge the value of a potential new hire based on the professionalism of their references. Using this type of social software actually enhances KM within an organization because it offers relevant data to be absorbed by their own processes. Organizations also benefit from creating their own SNs in order to mine data about their markets. While Twitter is primarily a venue for friends to
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communicate amongst themselves, businesses can follow their customers to see what they are tweeting about. The library whose “fans” tweet about other interests can take that information and expand their collection and services to accommodate their users’ demand. Twitter is not just a platform for organizations to beat their own drums; when used to its greatest potential, organizations can enhance their own popularity and processes by accommodating the needs of their stakeholders. Social Networking clearly requires KM in order to function. Without KM, tags and classifications that users apply to their own posts and changes wouldn’t tie to anything. Users might not find each other if KM wasn’t set up to make user data discoverable. Likewise, in cases where Social Networking behooves organizations, SN is as much a part of their processes as are the idea of processes themselves. However, certain organizations do not benefit from Social Networking. For example, the Department of Motor Vehicles as an authoritative function of society, ought not to post a blog where users can band together to complain about the organization, nor should they open their sites so that dynamic content can be manipulated by dissatisfied customers. But for those organizations which benefit from Social Networking, without Social Media and the tools that attend it, KM could easily have become a parasitic process, leading users in circles or even to nowhere. Businesses rely on knowing their customers. SNs allow business to peek into their clients’ needs to enhance the products they offer, based on what they learn from the KM they build.
WHAT KNOWLEDGE MANAGEMENT AND SOCIAL NETWORKING MEAN FOR LIBRARY ORGANIZATIONS We have delineated above different components involved within the KM process in the enterprise world. Within KM arena, the workflow consists
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of various steps from knowledge creation to its use/re-use. The same workflow also applies to corporate libraries managing their collections and providing services to their patrons. Knowledge refers to the KM arena and Document Management System (DMS) refers to the library field. Documents may consist of either hardcopy or softcopy in the form of WebPages, Records, etc. In general, these are the workflow aspects of KM that libraries follow to manage their knowledge/collections for the use of their clientele. These steps involve various components such as – People, Process and Technology to manage the Content. The complementary SN acts as a catalyst to boost the usage of resources in a much easier and better way than by utilizing the benefits of KM alone. (see Figure 3) Workflow in KM/DMS lifecycle involves the following steps: •
•
•
•
•
•
Creation: consists of the process involved in generating the knowledge or the content. E.g.: an author creates content. Acquisition: consists of the process involved in acquiring or capturing the generated knowledge or the content. E.g.: capturing the document through scanning. Classification: consists of the process involved in segregating the knowledge or the content for ease of retrieval. Taxonomy plays an important role here for defining the structure of folders/documents. Storage: consists of the process involved in storing the content on various media. E.g.: hard disk, tape drive, intranet web pages, other media. Search/Access: consists of the process involved in providing accessibility to the content. Security of the information can be dealt with here. Search also helps in getting access to the required information or content. E.g.: read, contribute, edit, delete. Use/Re-Use: consists of the process involved in using available knowledge/
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Figure 3. Workflow in KM/DMS life cycle and impact of SNs
content to fulfill the desired requirements. Knowledge/content in documents can be used/re-used in various forms. E.g.: re-use of a document with a template for different projects. In recent years, KM has overlapped the library world as the requirements of users have drastically changed. This change has forced library professionals to inculcate the components of KM in their practice. These components play an important role in achieving the desired goal. In a similar way, library patrons are more oriented to content found within a SN. Hence, the impact of SN is inevitable on libraries that make use of SN technology to provide better services. To cope with this changing demand from users, library software provides options for various SN elements. The user interface has been enriched with these SN aspects and enables users to interact with content and SN attributes. These libraries have started to change their user interface to enrich the content and SN aspects (Gunjal et al., 2008).
A. Washington Research Library Consortium (WRLC) ◦⊦ Visual search results showing concept mapping ◦⊦ Unique icons for different document types like – book, serial, sound record, etc. ◦⊦ Sort results option ◦⊦ Narrow results by various options. (SeeFigure 4) B. Victoria University (VU), Melbourne ◦⊦ Library Search Interface – Libraries started integrating new technologies and web 2.0 features in their library tools to enable the users to provide user friendly features. ◦⊦ The new library Catalogue Search Interface is powered by commercial software i.e. Encore, Innovative Interfaces, Inc. (Encore). ◦⊦ Third party tools are used to integrate the book cover images, tags, etc in search results to provide better User Interface (UI). (SeeFigure 5). 73
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Figure 4. Visual search results in ALADIN Discovery in WRLC
Implications of SN on Users and Content in Libraries Social Networking acts as an enabler for the usage of content and the development of knowledge in today’s world. With the advancement of technology, users access content on the web extensively through SN. People use social media in communicative and collaborative ways. Applications such as Wikis, Blogs, Forums and RSS feeds are used to keep abreast with the latest happenings in users’ fields. (see Figure 6) People in an electronic social network or in an offline social network connect with their peers within communities that are defined by similar interests. In an electronic setting, they use these various social media to cater to their needs. This helps to transform content and information into knowledge, and to share an increase of knowledge through networks by using various platforms that
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employ Social Networking, Social Bookmarking, Research Networking, etc. Here are a few examples: •
•
•
Social Networking: to connect with friends related to work, business, professional of similar groups. For Ex: Facebook, LinkedIn, Orkut, YouTube, Picasa, etc. Social Bookmarking: to bookmark of the favorite content on the web and refer it for future use. For Ex: Delicious, Digg, Technorati, Connotea, StumbleUpon, Diigo, etc. Research Networking: to connect with people of similar interests in their domain of knowledge. This mostly used extensively in academic world by professionals. For Ex: ResearchGate, Mendeley, Academia, etc.
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The content of KM 1.0 was prominent over the internet but now with KM 2.0 the user him/ herself has become part of the content itself. Each Social network gives a huge amount of knowledge (made up of the various implications of content) to other users over the network. For example: Twitter, Facebook, Instant messaging and other SN applications create a dynamic among the users whereby the users themselves enrich their shared knowledge.
Challenges Faced by Library Professionals Libraries that manage information through Web 2.0 applications can also provide knowledge. With the changing needs of users, libraries have enhanced their function as Knowledge Centers, so it is natural that libraries would embrace Web 2.0 functions because of their ability to enhance knowledge sharing.
Libraries have always been Knowledge Centers, even though the term didn’t become popularized until this millennium. A library is not just a storage space for books and information: it’s a centralized entity that helps its users discover resources and collaborate within and outside of their own communities and organizations. Beyond responding to reference questions, Librarians coordinate events and exhibits to enrich users and engender Knowledge. An important role of the Librarian is to provide a platform for collaboration between parties who require an expansion of their own knowledge. It has been argued that ancient libraries were not Knowledge Centers because of their exclusivity, but definitions of organizations change with social mores, and future scholars may look back at what we have dubbed the “Digital Age of Information” and scoff at our myopic definitions of organizations that blatantly exclude the poorer classes and those people living in remote locations without internet connectivity.
Figure 5. Search results in VU Library
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Figure 6. Impact of social networks on users and content in libraries
For the purposes of our analysis, we must limit the communities and organizations we speak of to those who are accessing the Knowledge Centers and using the processes of KM we are exploring. It follows that because libraries are now and always have been Knowledge Centers, the modern Library would capitalize on the advances of KM because of their collaborative nature. We do not argue that Libraries ought to adopt a bleedingedge acceptance of new technologies (KM is not terribly new as technology goes), but the entire premise of KM is one that fits the scope of every Library. Information should be organized in a way that is discoverable in a relevant manner. While libraries are Knowledge Centers it’s important to make the distinction that KM is a practice, not an organization. Libraries utilize KM for the advancement of their own organization and are the best stewards of KM because of their relationship with people, culture, technology and content. It is the Reference Interview experts (i.e. Librarians) who
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can best develop the benefits of the symbiosis of KM and social networking. Librarians are by their very nature observers of search behavior. Social Networking and the usage statistics tools of KM are invaluable to Librarians. Using the functionality of any Web X.0, Librarians can learn about the user group they serve and enhance the collaborative services they provide. It is not the role of librarians to integrate resources together to deliver them to individual end-users: instead they facilitate user’s ability to access whatever resources they or their group (organization or community) requires. In this way librarians mirror the function of the KM process in that the work they do is a process, not a product. An example of a SN within the library is the body of library users themselves. Using a hybrid of both print and electronic survey applications, Librarians can determine useful programs to offer to the users. If a community wants to learn about tax preparation in the month of February, a Librarian
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can measure the need based on interest they gather using Social Networking applications. Granted, not all the users of a Library are plugged into the Internet, but Librarians combine Human and Artificial Intelligence by providing paper surveys or taking quick verbal polls to gather data from all subsets of a SN. Along with providing a speaker or organizing a learning workshop, Librarians can create a space on their website with a pathfinder and FAQs on tax preparation to help members of the community according to their needs. Downloadable Audio Books and eBooks are making their way into public library collections as suppliers strike deals with state governments to provide their platforms to the public. The users of these products must access them using the internet, so Librarians’ range of communicating can be limited to an online environment (with the odd exception of the user who must enter the brick and mortar library to access the internet – and even then any assistance they might receive from a Librarian is limited to pointing him to an empty PC corral. The rest of the assistance is executed online). Librarians usually have an online chat feature for reference help, and these features accept troubleshooting queries which generally point users back to the platforms themselves. A well created eBook platform ought to have a sophisticated KM process built inside to support its users. Librarians also wear the hat of Marketing for their own organization: blogging, micro blogging, and setting up blog interviews with popular bloggers are just some of the new venues for Librarians to enhance their Knowledge Centers and reach their communities. This information can be sent to mobile devices as well, thus expanding an otherwise limited scope of advertising. Most Academic Libraries and many public libraries have created Facebook pages. They use this platform to reach a broad number of users to announce the programs they hold and to drum up involvement among the community. Where KM is the process of managing knowledge, Librarians
are stewards of this process and have been since their inception. We do not argue, though, that KM and Librarian are interchangeable terms and we rue the day that an organization re-names KM 2.0 “Librarian 2.0” as it would decry the obsolescence of the role of Librarian, but such a role can never become obsolete. Human Intelligence will always trump Artificial Intelligence, and that is why we will always have Librarians. As long as there are Librarians interceding on behalf of end-users, James Cameron’s SkyNet will never be a threat to humanity.
BENEFITS OF SOCIAL NETWORKING ON KNOWLEDGE MANAGEMENT As already mentioned, Social Networking enhances KM. Many companies communicate internally using wikis to post information to forums, so that employees can exchange ideas informally (Mel Oxford, 2010). This ease of use and informal online environment increases productivity, because people are not intimidated by the formality of “the big meeting.” Again, this is a vast difference from KM 1.0 when content was still largely authoritative and grandiose. Most organizations benefit through the implementation of SNs for the Resource Management. For example, LinkedIn, Facebook, and MySpace are extensively used for staffing by many companies. When a Human Resources unit narrows down their resume choices and performs the usual criminal and character background check, the final character check is done by examining candidate’s social networking profiles to see the sundry array of personal and professional connections she has made (and to screen candidates by looking for red flags such as incendiary photos from nonprofessional springtime vacations). Other SNs include Orkut, Plaxo, Ning, Xing, and Ecademy. Scholars believe we are approaching an epoch where research can be streamlined and
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delivered swiftly enough to change the practice of many fields. Some research networks are ResearchGATE, Mendeley, Nature Network, and Methodspace. A subset of SNs for the research community includes publication sites like BibSonomy, CiteULike, ArnetMiner, and SSRN. Both scholars and general users of the internet may use social bookmarking software, such as Delicious, Digg, Technorati, Connotea, StumbleUpon, Diigo, etc. to promote and tag items relevant to their organizations. Another form of Social Networking for both scholars and general users is Document Sharing. Document and File Sharing is the champion of KM and can be seen in such software as Slideshare, Scribd, Docstoc, and Google Docs. Anyone needing a wiki can use Wikidot or Pbworks. Social Networking in the form of Blogs is beneficial to commerce, education, and leisure. Some major blog platforms are Blogger, LiveJournal, Wordpress and Blogster. Those users who prefer to digest information in smaller portions utilize micro blogging applications like Twitter, Plurk, and Tumblr. These blogs (macro and micro) can point to other Social Networking arenas for posting and sharing photos (Picasa, Flickr), Videos (YouTube, Vimeo), Travel (WAYN, TripIt), Movies (Flixster), Music (Last.fm, Pandora), Names (Naymz, Spezify), and anyone who posts comments on the web can manage them using Disqus. Another Social Networking triumph born out of the particulars of KM are the sites that connect people who read books: Shelfari, LibraryThing, GoodReads. Shelfari is actually a child of Amazon. com and uses the data that users freely post to garner bibliographic data about specific editions of books. Users post information, which then belongs to Amazon, so the company in essence draws from the kindness of strangers rather than pay employees a salary to research and find books. The interesting phenomenon with Shelfari is that the data is seen with skepticism, because there is no Quality Control on what people are posting about their books, and here we have exposed
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the weaknesses of KM 2.0. While KM 1.0 was authoritative and rigid, KM 2.0 is democratic and open, but the tradeoff is the authenticity of information. Wikipedia is the starting point for many people doing research. It is a fact that Wikipedia (a champion of KM 2.0 and social interaction) is not an authoritative source of information. Even though sources are cited, there is no single entity policing the bibliographies. Only users with discriminating eyes look for the authoritativeness of Wikipedia entries, which is another reason that we need Librarians to monitor the KM process. As KM 2.0 flourishes, the need for Human Intelligence to temper the quality of data increases.
DISADVANTAGES OF SOCIAL NETWORKS ON KNOWLEDGE MANAGEMENT With the help of SN tools such as Blogs, Wikis, Facebook, LinkedIn etc., there is a chance of leakage of Company information to the World. People tend to suffer from logorrhea online especially when they are engaged by a SN, which offers addictive stimulation to the mind. This is also a caveat for the youngster about to apply to college: review your Myspace page! Even though junior excels at Math and is a Varsity member of the Lacrosse team, those pictures of him funneling beer in his cousin’s kitchen could sway the Admissions Office in a negative way. Another grave disadvantage of SNs on KM is when it is abused in the workplace. People, once they become addicted to these Social Media, can invest their time in using various applications while they are on the clock (e.g. Chat, Farmville, Games on Facebook, Orkut, etc.). This indirectly reduces the productivity of the organization and many companies have blocked such sites from their intranet, so that their employees don’t waste their days on them. SNs also need to be monitored to audit their efficiency and veracity. A renegade user
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of a SN could potentially smear a great number of other users using the technology provided to him by the very KM that allows him to access the SN itself.
CONCLUSION KM is an organizational approach that is not easily implemented. On one hand, knowledge sharing activities depend on the voluntary participation of employees, where a culture of sharing plays a prominent role (Broadbent, 1998). The implementation of KM requires a holistic and multidisciplinary approach, whereby process management is understood in light of the dimensions of an organization’s working knowledge. On the other hand, KM should encapsulate the evolution of logical management practices, which are purposefully enforced, as it presents a major shift in focus regarding the development and use (and re-use) of knowledge, where its use increases the effectiveness of any organization in achieving goals and objectives while supporting its mission (Broadbent, 1998). SNs could provide a useful compliment to existing central knowledge repositories, as they open wide opportunities for collaboration and interaction. Social Software is rapidly evolving; new features are being thought of and made available almost every day. Probably the most interesting trend is the participation of users in the development of new features and the speed of developers trying to bring in new applications. The huge number of available tools and features and the rapid pace of innovation in the field bring the advantage of a wide choice, adapted to the users’ needs and continually evolving to serve them better. This kind of flexible and rapidly evolving tools in the hands of innovative users will be probably one of the major sources of competitive advantage in the new Knowledge Economy. While KM 2.0 clearly enriches user’s experiences of an organization, there remains the
need to monitor such communities within the organization in order to prevent user mutiny of a website, which is the central point of a company’s reputation. KM 1.0 was authoritative and static, but even in the dynamic world of KM 2.0 some of that hard-line authority must remain in order to check the behavior of a SN and its power over the knowledge that is presented. Implementation of appropriate SN applications within the KM process can benefit the organization to a large extent. They can surely change the culture of knowledge sharing among the communities by building social aspects.
REFERENCES Avram, G. (2006). At the crossroads of knowledge management with social software electronic. Journal of Knowledge Management, 4(1), 1–10. Berlin, E. (2009). Use Ping.fm to reach all your online profiles at once. Retrieved from http://www. salon.com/technology/the_gigaom_network/ web_life/index.html?section=web_life&blog=/ tech/giga_om/web_life/2009/03/31/use_pingfm_to_reach_all_your_online_profiles_at_once Boyd, D. (2005). The significance of social software. Retrieved from http://www.futurelab.net/ blogs/marketing-strategy-innovation/ 2005/ 05/ the_ significance_ of_ social_sof.html Boyd, D., & Ellison, N. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1). Retrieved from http://jcmc.indiana.edu/vol13/ issue1/boyd.ellison.html. doi:10.1111/j.10836101.2007.00393.x Broadbent, M. (1998). The phenomenon of knowledge management: What does it mean to the information profession? Information Outlook, 2(5), 23-36. Retrieved from http://www.unlibrarynairobi.org/PDFs/PhenKM.doc
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Coenen, T., et al. (2006). Knowledge sharing over social networking systems: Architecture, usage patterns and their application. Paper presented at the OTM 2006 Workshops, On the Move to Meaningful Internet Systems, (pp. 189-198). Gunjal, B. (2005). Knowledge management: Why do we need it for corporates? Malaysian Journal of Library & Information Science, 10(2), 37–50. Gunjal, B., et al. (2008). Australian digital libraries: An overview. In Proceedings of WCECS 2008’s International Conference on Education and Information Technology (ICEIT’08), San Francisco, USA, 22-24 October, 2008. Gunjal, B., & Buck, S. (2007). Ontologies in portal design. In Tatnall, A. (Ed.), Encyclopaedia of portal technology and applications (pp. 653–657). Hershey, PA: Information Science Reference. Hariharan, A. (2002). Knowledge management: A strategic tool. Journal of Knowledge Management Practice, December. Retrieved from http://www. tlainc.com/articl46.htm Harris-Jones, C. (2005). Knowledge management past and future. Retrieved from http:// www.kmworld.com/Articles/Editorial/Feature/ Knowledge-management%E2%80%94Past-andfuture-9596.aspx Jones, P. M. (2001). Collaborative knowledge management, social networks, and organizational learning. In Proceedings of HCI International 2001: Ninth International Conference on Human-Computer Interaction. Retrieved from http://humansystems.arc.nasa.gov/publications/ collab_know_paper.pdf Majchrzak, A., et al. (2006). Corporate wiki users: Results of a survey. In WikiSym’06: Proceedings of the International Symposium on Symposium on Wikis, (pp. 99-104).
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Malone, N. (2009). The role of social software in knowledge management. Retrieved from http://www.nicholausmalone.com/wp-content/ uploads/2009/03/nmalone_emerging.pdf Martin-Niemi, F. (2009). Knowledge sharing in virtual communities: Reframing organization for knowledge management research in cyberspace. Ottago School of Business Postgraduate Colloquium. Millen, D. R., et al. (2006). Dogear: Social bookmarking in the enterprise. CHI 2006 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, (pp. 111-120). Quebec, Canada. OfCom. (2008). Social networking: A quantitative and qualitative research report into attitudes, behaviours and use. OfCom. Retrieved from http:// www. ofcom. org.uk /advice /media_literacy/ medlitpub/medlitpubrss/socialnetworking Oxford, M. (2010). Web 2.0 key to collaboration and agility says United Planet. Realwire. Retrieved from http://www.realwire.com/release_detail.asp?ReleaseID=17153 Papailiou, N., et al. (2007). Social networks for knowledge management in management consulting firms. Proceedings of the 4th Conference Professional Knowledge Management Experiences and Visions, GITO-Verlag, (pp. 21-30). Retrieved from http://www.imu.iccs.gr/Papers/ C81-Papailiou+Apostolou+Mentzas.pdf Schmeil, A., & Eppler, M. (2008). Collaboration patterns for knowledge sharing and integration in Second Life: A classification of virtual 3D group interaction scripts. In K. Tochtermann & H. Maurer (Eds.), Proceedings of the Eighth International Conference on Knowledge Management Iknow. Seufert, A. (1999). Towards knowledge networking. Journal of Knowledge Management, 3(3), 180–190. doi:10.1108/13673279910288608
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Tomek, I. (2001). Knowledge management and collaborative virtual environments. Journal of Universal Computer Science, 7(6). Urban, R., et al. (2007). A Second Life for your museum: 3D multi-user virtual environments and museum. In J. Trant & D. Bearman (Eds.), Museums and the Web 2007: Proceedings. Toronto, Canada: Archives & Museum Informatics. Retrieved from http:// www. archimuse. com/ mw2007/ papers/ urban/urban.html
KEY TERMS AND DEFINITIONS Bottom-Up Network: Network enabled by web 2.0 technology where users provide the content and form the shape of the discoverability of said content. Knowledge Management (KM): Strategy or process, which enables knowledge sharing through collaboration in an organization in achieving a business goal. Law of Least Effort: The phenomenon where users of an application expel the least amount of time and energy as possible when seeking information.
Monarchy Model of Information Politics: Essence of Web 1.0 technology where webmasters held the only control over content. Social Media: or Social Software: Application that supports Knowledge Management activities to enhance or enable the exchanging of ideas or information within a Social Network. Social Networks (SNs): Groups of people linked together by similar interests in a business or leisure pursuit or combination of both. This connection is as ancient as hunter-gatherer tribes or as modern as a yahoo group. Software applications enable and enhance these networks, but are not needed (e.g. a meeting of people where most members are computer illiterate constitutes a Social Network). Taxonomy: The classification of concepts within an organization to enhance the retrieval of information. Virtual Environments: Artificial simulations of real or imaginary places where people learn about a particular topic (e.g. skydiving) or each other (e.g. World of Warcraft).
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APPENDIX 1: LINKS USED • • • • • • • • • • • •
Add this. Available at http://www.addthis.com/ Add to any. Available at http://www.addtoany.com/ Digsby. Available at www.digsby.com Encore, Innovative Interfaces, Inc. Available at http://www.encoreforlibraries.com/main.html Ping.fm. Available at http://ping.fm/ ReBlog. Available at http://reblog.zemanta.com Second Life. Available at http://www.secondlife.com Socializer. Available at http://ekstreme.com/socializer/ Tweetdeck. Available at http://www.tweetdeck.com/beta/ Tweetmeme. Available at http://tweetmeme.com Wefollow. Available at http://wefollow.com/ Xeesm. Available at http://www.xeesm.com/
APPENDIX 2: LIST OF FEW SN TOOLS AND SERVICES Social Networks, Tools and Services
Examples
Social Networks
LinkedIn, Facebook, MySpace, Orkut, Plaxo, Ning, xing, Viadeo, Ecademy, Myspace
KM Networks
KM4Dev, IT Toolbox, TED
Research Networks
ResearchGATE, Mendeley, Nature Network, Methodspace. LinkedIn, Academia.edu
Blogs
Blogger, LiveJournal, Wordpress
Publications
BibSonomy, ArnetMiner, SSRN
Bookmarks
BibSonomy, Delicious, Digg, Technorati, Connotea, StumbleUpon, Diigo, Technorati, CiteUlike, Zotero
Share and bookmark tools
Add This, Add to Any, Ping.fm, XeeSM
Bookshelf
Shelfari, LibraryThing, GoodReads
Video
YouTube, Vimeo
Photo
Picasa, Flickr
Document Share
Slideshare, Scribd
File Sharing
Docstoc, Google Docs
Wikis
Wikidot, PBWorks
Travel
WAYN, TripIt
People Search
Naymz, Spezify
Manage Comments on web
Disqus
RSS
Bloglines, Google Reader
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APPENDIX 3: SCREENSHOT FROM SECOND LIFE
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Chapter 5
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management Edward T. Chen University of Massachusetts, USA
ABSTRACT Effective information systems have become necessary for organizations to be successful and stay competitive. With the proper adoption of new strategies and Web 2.0 technologies, information and knowledge generated from these Web 2.0 technologies will continue to enable organizations to adapt quicker and give them additional advantages across the global business landscape. Knowledge workers need better tools to allow them to effectively manage the growing amount of information and knowledge. Social networking is one of the IT solutions to this problem. This chapter discusses the Internet phenomenon known as Web 2.0. It explores Internet use, Internet users, and the continuous improvements being made to the Internet. The purpose of this chapter is to explain the impact that social networking has on the modern enterprise; particularly, when it comes to collaboration and knowledge sharing. The growth trajectory of Web 2.0 software such as social networking, blogs, tags, RSS feeds, wikis, YouTube videos, and widgets are presented, and each component is outlined in detail. Each application is also applied to a practical business setting. The benefits and challenges of each application are discussed, and examples of organizations that are implementing Web 2.0 strategies are presented. Some limitations and concerns of Web 2.0 are discussed. The chapter concludes with an examination of the implications of Web 2.0 on companies and their business and marketing strategies.
INTRODUCTION Today’s knowledge management (KM) systems focus on centralized sets of repositories, organized around established business processes. The current knowledge management systems are expensive to
implement and the long-term commitment of the major resources of their deployment, maintenance, and daily operation can be seen as a huge burden. Consequently, even customized solutions end up going unused, with the knowledge workers running these custom KM solutions not having
DOI: 10.4018/978-1-61350-195-5.ch005
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management
the information technology (IT) tools to provide support for their responsibilities. Based on these underutilized KM systems, the continuing evolution of Web 2.0 is providing a new KM solution, a collaboration based solution (Harris & Rea, 2009; Levy, 2009). Social networking technologies provide immediate solutions to the large investments for the deployment, maintenance, and daily operations for today’s KM systems (Burrus, 2010; Diehl, Grabill, Hart-Davidson, & Iyer, 2008). It is time for organizations to start looking at tomorrow’s knowledge management solution and realize this new solution is a more efficient and effective model for today’s enterprise knowledge management systems. Each time a new system is implemented; large investments into systems that have promised automation and seamless integration to share knowledge across the organization rarely become a reality (Fitzgerald, 2008; Parise, 2009; Strehlke, 2010). To understand the most fundamental aspects of knowledge management, one must first understand the process of knowledge acquisition, the use of intellectual property and the use of non-material assets. It is the knowledge within the organization that is the basis of an organization’s development and allows them to find solutions to business problems. The knowledge management system becomes an essential tool for all the organizations actions, with the goal being that decisions can be made quicker and are justified and strengthened by the knowledge within the system itself. Using these systems to have knowledge about clients, similar to a customer resource management system also increases the level of success in providing them with the best solutions. In proving solutions to clients, the knowledge that is captured also allows the knowledge system to help drive innovation. The learning organizational culture is a requirement for the constant changes in business processes and management practices that are driven by staying focused on the KM system and continuing to improve that knowledgebase
(Kreitzberg, 2009). Web 2.0 social networking (SN) technologies provide organizations with a set of tools to facilitate the knowledge acquisition, transformation, and sharing. Employees using SN to interact with other coworkers and teams will create an environment where information is exchanged with ease. SN eventually promotes a learning organizational culture that engages these people, connects information, and establishes strong relationships. The knowledge management system should help maintain continuous innovations that lead to the creation of new goods and/or services and establish new business processes (Pascu, Osimo, Turlea, Ulbrich, Punie, & Burgelman, 2008). Knowledge management is a solution that requires organizational, human and technological resources to provide the assets for the system (King, 2007). Choosing not to focus on any of these aspects will many times lead to failure of the system. It is the values of the organization which is the general problem in the realm of knowledge. And more accurately it is the human component that will determine the level of success of knowledge management systems (Kreitzberg, 2009). Building trust across the organization so everyone trusts the KM and the solutions it will provide. Trust in the people that help create the organization is important and a lack of it is one of the biggest reasons of failure from human aspect of knowledge management. Once organization implements Web 2.0 and SN tools, talent and expertise can be retained through portal, networking and relationship building. The purpose of this chapter is to explain the impact that social networking has on the modern enterprise; particularly, when it comes to collaboration and knowledge sharing. The growth trajectory of Web 2.0 software such as social networking, blogs, tags, RSS feeds, wikis, YouTube videos and widgets are presented and each component is outlined in detail. Each application is also applied to a practical business setting. The benefits and
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challenges of each application are discussed and examples of organizations that are implementing Web 2.0 strategies are presented. Some limitations and concerns of Web 2.0 are discussed. The paper concludes with an examination of the implications of Web 2.0 on companies and their business and marketing strategies.
WEB 2.0 Web 2.0 is defined in many ways by a variety of different sources. The term Web 2.0 describes the transformation of websites from silo information sources to interlinked computing platforms (O’Reilly, 2005). Traditionally, websites presented static information that was rarely updated. Companies and organizations published information on the web and users consumed what was offered. There was no ability to interact with others on the web. However, the emergence of Web 2.0 has transformed the way the web is used, managed and developed. Web 2.0 allows for a richer user experience. It embodies interactive functionalities such as social networking, blogs, tags, RSS feeds, wikis, YouTube videos and widgets. These applications enable users to become active participants in the web. They are no longer forced to passively consume the information available. They can contribute to and improve content on websites such as Wikipedia in real time. They can develop social networks with other users through platforms such as MySpace, Facebook and LinkedIn. They can share life events through YouTube and they can publish their own content on blogs. Web 2.0 allows users to share information, opinions, and thoughts through blogs. It enables users to improve free source software and redistribute it for free. According to Tim O’Reilly, founder and CEO of Sebastopol-based O’Reilly Media, the company that coined the phrase Web 2.0, “the heart of Web2.0 is the community – building collective
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intelligence from the mass of people that you can reach and interact and hear from – like customers which make this community” (O’Reilly, 2005). In addition to transforming the user experience, Web 2.0 is forcing companies to consider how they can take advantage of this groundswell of technological advancement (Burrus, 2010). Forrester Research reports that 29 percent of the U.S. population watches user generated videos on the web. Twenty-five percent read blogs, visit social networking websites such as Facebook and MySpace, and read reviews and ratings on line at least once a month. People are spending more of their time on-line than watching TV, reading newspapers, and listening to the radio. People ages 16-24 years old consume the least amount of television. Eighty three percent spend their time on-line playing games, downloading music, using instant messenger (IM), participating in social networks, and inhibiting virtual worlds. They are increasingly on the move. Ninety five percent of them own mobile phones (Bernoff & Li, 2008; Webb, 2007). Moreover, wireless hand held devices like Blackberry’s and personal digital computers (PDA) enable people to log on to the Internet from remote locations anywhere in the world at any time. Figure 1 outlines the components of Web 2.0. It is built on the cornerstone concept of the web as a platform where the user controls the data. The core competencies transform software packages into services, a participative architecture, costeffective scalability, interchangeable data sources and data transformations, software above the level of a single device, and the harnessing collective intelligence. On the periphery, Web 2.0 focuses providing rich user experiences where open source functionalities require trust and decentralization. Tagging is emphasized in place of taxonomy and user participation and contributions are promoted in place of traditional web publishing (O’Reilly, 2005).
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management
THE TECHNOLOGY BEHIND WEB 2.0 The foundation of Web 2.0 is based on a group of existing coding technologies called Asynchronous JavaScript and XML (AJAX). It allows interactive user capabilities and it enables web applications to operate with increased speed and efficiency. With AJAX, users requests occur instantaneously, eliminating the delay time incurred with clicking through to multiple web pages. One example of an AJAX application is Google Earth. This application lets the user virtually tour the world, zoom in, swoop from outer space to street level and get detailed descriptions of monuments and landmarks instantaneously. All interaction happens within a single page. AJAX represents a new way to use the existing technologies that are supported by all major browsers. It works by collectively using JavaScript, XML,
HTML and CSS. AJAX enables web pages to respond to a user’s action without reprocessing or reloading the web page. This is accomplished because AJAX allows JavaScript to communicate directly with the server and trade data without reloading the page. AJAX uses asynchronous data transfer between the browser and the web server allowing web pages to request small amounts of information from the server instead of whole pages. This occurs behind the scenes and is not visible to the user. It increases a web page’s interactivity, speed, functionality, and usability. Traditionally, every time a user clicked on a web page, it prompted a request to a web server. The request had to be processed before the web server presented the desired page on the user’s web browser. The user was required to wait for the page to process and load resulting in a delay each time the user made a request.
Figure 1. Web 2.0 meme map (Source: O’Reilly, 2005)
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Blogs A blog, also known as a web-log, is defined as an online journal. It can contain commentary, photos, videos, and links to other websites. Blogs provide a platform for online dialogue. Therefore, the concept of online journal is an inaccurate representation of a blog. It functions more like an online conversation than a journal. Effective blogs are updated regularly, often daily, and generally allow readers to post comments. Anyone can create a blog. They can be as personal as on line diaries and as generic as corporate product updates. Companies are beginning to recognize the business and marketing benefits of blogging (Taylor, 2008). Some companies have internal blogs allowing employees to communicate, share ideas, and provide feedback with each other. Others are becoming aware of the opportunities presented by blogs. They allow organizations to connect with customers and constituents. It gives them an ability to uncover their personalities and it allows them to connect with customers in a more personal way. Dell is an example of a company that is embracing social networking as part of its strategic business operations. In 2005, Dell noticed a blog called “Dell lies, Dell sucks,” that criticized the company for its deficient customer service. It was posted by a customer who purchased a new computer through Dell’s online distribution channel. When the newly purchased computer failed to operate properly, customer service representatives at Dell refused to accommodate the customer with in-home technological support. They insisted that the customer repack the computer and send the entire set-up back to Dell for repairs. The enraged customer developed the blog titled “Dell lies, Dell sucks” to document his experience. He often referred to the company as Dell Hell throughout the blog. The blog was so sneering, that it caught the attention of Dell’s founder, Michael Dell, who decided to develop a Blog Resolution Team. The
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team’s main objective was to search for blogs that involved dissatisfied Dell customers and proactively reach out to them to offer technical support and customer service. In addition to the Blog Resolution Team, Dell implemented a customer-facing blog called Direct2Dell. Dell used the blog to actively engage and communicate with its customers. In fact, many Dell customers reach out and communicate with each other through Direct2Dell solving technical problems among themselves (Bernoff & Li, 2008). With the emergence of Web 2.0, Dell believes in providing as much transparency as possible to its customers. It wants them to be the first to know about recalls and defective equipment and it wants its customers to be actively engaged with the company. When the company needed to recall one of its laptops due to faulty wiring, it communicated directly with customers on Direct2Dell before the media announced the problem. It created a post called “The Flaming Laptop” to catch the attention of customers. Dell believes that this proactive approach to building customer support will also build customer loyalty (Bernoff & Li, 2008). Civic organizations are also using blogs to connect with their citizens. The city manager of Des Moines, IA, Jeff Pomeranz developed a blog when he noticed that attendance was down at the monthly town meeting. According to Pomeraz, his incentive for blogging was to communicate with his residents in a less formal way. He understood that residents had very busy schedules and believed that opening the lines of communication in a more convenient, informal way would engage more people to take an active role both online and off line (Jackson, 2008). Many town leaders also feel that blogging makes them more approachable and accessible. Scott Neal, city manager for Eden Prarie, MN, noted that since he started a city blog, he is able to interact with citizens on a more intimate level. Citizens that regularly read his blog feel like they know him and are more comfortable striking
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management
up a conversation or raising an important issue. Residents even feel comfortable approaching him in the grocery store. The mayor of Roundlake, IL started a blog to help build a sense of community in his city. He uses the blog to promote local events and believes that more citizens are actively participating in city events since he started his blog. Before his blog, 100 citizens attended the Christmas tree lighting. After his blog was initiated, over 500 people attend the Christmas tree lighting (Jackson, 2008). Most town and city officials want blog to be a platform for open dialogue with their citizens (Cardon, et al., 2008). Similar to the insights realized by businesses, civic organizations and towns are realizing the shift in how citizens are spending their time. They are realizing that in order to keep citizens engaged; they need to interact with them in the space that is flexible, informal and convenient.
Widgets Widgets are basically small pieces of programming code embedded in an image file. They are programmed to react to a user’s command such as a mouse click. Computer desktop icons are examples of widgets. Users click on the desktop icon sending commands to the computer to perform a specific function like open a word processing software or log onto the Internet. Websites are becoming more user-friendly all the time. Many websites are increasing their use of widgets to simplify and enhance the user experience. Buttons, drop-down menus, and other elements located on a web page that are controlled by the user to perform a function are also considered widgets. Examples include stock tickers, media player buttons, web browser controls, email function controls, social-networking sites that enable information sharing, RSS feed icons, interactive graphs, charts, and other statistical media. In the context of Web 2.0, widgets are small web applications that look similar to web ads and
they can be added to any web site. For example, if a user had a friend participating in a fundraising walk, the user could add the friend’s fundraising widget to his or her blog. In theory, this would increase the visibility of the widget. By increasing the visibility and reach of the widget, the user enables his/her friend increase the number of donations. Visitors could click on the fundraiser’s widget and go directly to the donation site.
Tags and Social Bookmarking Tags and social bookmarking are essentially the same thing. Tags are used to sort and classify information. A tag is a key-word attached to a piece of information such as a picture, blog, or video clip. The tag helps classify the piece of information. Tags are used in a variety of ways. Items can be tagged for personal use. Individual users can tag pieces of information or websites in a way that is meaningful to them so that they can find the information again. However, tags are also used to locate content tagged by others, to target Internet searches and advertising, and to connect people of common interests. The concept of tagging reinforces the fact that the web is no longer a storehouse for static content with passive users. It is now used to connect users from disparate locations with common interests. The benefits of personal tagging are generated by the value that is created when connections take place. Similarly, there are many benefits associated with tagging web pages. Tags are visible to the user and they can be copied and duplicated on other web sites, increasing their reach and frequency. Before tagging, keywords were decided by the webmaster of an organization when he or she made web pages. The webmaster had to be painstakingly thorough in identifying keywords so that search engines would identify them and display the website in search results. If the webmaster made a page about knitting and forgot to include “knitting” as a keyword, the page might not appear in search results even though it was
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one hundred percent relevant. With tagging, the keywords, which are a form of metadata, are determined more democratically. Users are now able to tag pages. All of the tags get aggregated for others to use. Some tagging is useless, but much of it is very effective. However, in the aggregate, tagging is often as good as or better than the old command structure where web masters had to individually identify key words with every page (Carmagnola, et al., 2008). Websites like Del.ic.ious (Delicious) are social bookmarking websites. Social bookmarking websites allow users to store links to their favorite websites on the Internet instead of on a specific computer. This allows access the bookmarks from any computer and it allows the user to add and access bookmarks from anywhere. Delicious uses tags to organize and remember a user’s bookmarks. It can also be used to share interesting links among friends or to discover links bookmarked by users with similar interests. Delicious can also be used like a search engine. It can be used for research, collaboration, wish lists, recipe sharing, podcasting and more. Many companies are beginning to realize the benefits of social bookmarking (Parise, Guinan, Iyer, Cuomo, & Donaldson, 2009). They are using sites like Delicious to gain competitive advantage. A company based out of New York City called Wiredset is using Delicious to illustrate the impact, in real time, of a record label’s marketing activity. It developed a service for record labels that assimilates online data including sales at Amazon.com Inc., the number of blog posts, and number of tags on Delicious. It can track entertainment releases on social networking sites such as MySpace and determine the amount of interest generated from the release. It can also determine the impact of an MTV video on Amazon record sales. As a test, Wiredset is tracking the tags of a London based band called Bloc Party. It will track the web based interest generated from the band’s new album to determine the influential online players.
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Other companies are using Delicious to open the lines of communication with their customers. They are using it as a mechanism to stay in touch and form relationships. The marketing agency MarCom: Interactive holds seminars on marketing strategies and communications activities. It creates resource web pages with tags to blogs, Web sites, and research presented in conjunction with its seminars. After the seminar is over, MarCom: Interactive and its customers can add more links, keeping the discussion alive. Both companies are examples of how businesses are taking advantage of the interactive components of Web 2.0 to communicate directly with their customers and gain an edge on their competitors.
Real Simple Syndication (RSS) Feeds Real Simple Syndication (RSS) is an Internet technology that allows users to receive custom content from websites. With RSS, users do not have to visit their favorite blogs and websites on a daily basis to get current information. News and updates can be delivered directly to the user, often delivered directly into their email box. Users must subscribe to a RSS news feeder. However, once a user has joined, they can select to receive updates to any of their favorite content sources. RSS readers are also available. They collect, organize and display all of the user’s selected RSS feeds in one convenient location (Gaspar, 2007). Some companies are beginning to adopt RSS feeds as part of their Internet marketing strategies (Cooke & Buckley, 2008). They simply add an RSS icon to their websites. Customers, who select the icon, will receive immediate updates from the company. The RSS feature is especially beneficial as a marketing tool for companies that have blogs. It is a way for companies to immediately update their customers anytime a blog is updated. The system is automated so there is no need to manage and update customer distribution lists. Moreover, the RSS functionality allows the organization to
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management
track which feeds have a high subscriber rate and which do not. This allows them to tailor their content to meet the interests of their customers (McCluskey & Korobow, 2009).
Wikis and Open Source Wikis allow Internet users to publish information in a collaborative manner on the Internet. They offer a simple editing and publishing interface that can be used and understood easily. Wikis work by employing open source software that allows any user to contribute content. They present an easy to use, free platform for collaborative website management and updating. Wikipedia, the free online encyclopedia that anyone can edit, is an example of a wiki (Lending, 2010; Prasarnphanich & Wagner, 2009; Wang, 2009). Wikis allow an open author system. This means any user can add, delete or edit content that is published within a wiki. The main feature that distinguishes a wiki from a traditional website is the ability of a wiki user to easily edit all aspects of a website. This is also one of its major advantages. The author does not have to have web coding or website management knowledge in order to contribute. This allows authors with a variety of backgrounds and levels of expertise to contribute, add and edit information, adding a level of expertise that otherwise could not be achieved. Authors can also link to other websites adding richness and interoperability (Lending, 2010; Posey, Lowry, Roberts & Ellis, 2010; Raman, 2006). There are many benefits to wikis. Some companies are using wikis as internal collaborative tools to share knowledge and information within the organization. The Claremont University Consortium, a conglomerate of seven colleges, implemented the use of wikis for its emergency preparedness operations. This enabled them to develop a set of standard operating procedures for the seven colleges that were accessible on line. Each time the standards were updated, the
changes were immediately available to all. This eliminated the delays associated with production and the costs associated with printing new manuals every time updates were needed. It also allowed the consortium to update their procedures more frequently. While critics point out the occasional inaccuracy or mistake, champions point to wikis as a prime example of individual initiative, peer review and error correction, and mass collaboration (Dearstyne, 2007; Posey, Lowry, Roberts & Ellis, 2010; Raman, 2006). Similar to wikis, open source software allows anyone to edit and improve the source code behind open source software. After the open source software is updated, it is redistributed for use. This open format facilitates collaborative intelligence and enables users with the technical skills and ability to make adjustments to software as they find roadblocks in their everyday use. Open source software packages usually make money by selling technological support programs that help average users when they have difficulty (Wang, 2009).
YouTube YouTube is owned by Google. It is a website that hosts user generated videos and it has become the internationally accepted web video platform. Anyone can post a video to YouTube and everyone can watch them. The YouTube phenomenon is attracting 20 million visitors every month who watch 100 million video clips a day. Moreover, there are 65,000 new videos posted every day. Users include everyone from teenagers looking to post their skateboarding video, to major corporations, political candidates, and human rights activists. In some cases, videos captured in real time on digital cameras or cell phones can add authenticity to a situation or event like traditional media sources cannot. For example, the South Asian tsunami in 2004 and the London underground bombings in 2005 were captured first by amateurs and posted on YouTube (Jones, 2006; Kessler, 2007; Naim, 2007).
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YouTube also allows companies to participate in viral marketing campaigns. By posting a video on YouTube, companies can show their personalities and connect directly with their target customers. For example, MassGeneral Hospital for Children is developing a YouTube program as part of its marketing campaign. Through a market research study, it learned that its target audience spent a lot of time researching pediatric health conditions on the Internet. As a result, MassGeneral Hospital for Children felt that it needed more vehicles to attract users to its website. In addition to implementing a search engine optimization plan, MassGeneral Hospital for Children decided that it needed a way to get users that might not otherwise visit the site, to the MassGeneral Hospital for Children website. By posting videos on current children’s health topics, and tagging them appropriately, MassGeneral Hospital for Children hopes to position itself as a resource for parents and other healthcare consumers. In addition, it hopes that this campaign will increase its visibility and top of the mind awareness with its target audience. YouTube will be the vehicle that connects users to the MassGeneral Hospital for Children website. Once the parent receives the health information they are looking for, the hope is that they might look around the website. In the long run, MassGeneral Hospital for Children hopes it can develop a relationship with its target audience through YouTube with the ultimate goal of attracting new patients. One of the benefits of YouTube campaigns is their low cost. There is no need to incur the cost of fancy production companies. Some of the most effective YouTube videos were developed out of grassroots efforts. In the case of MassGeneral Hospital for Children, it purchased the necessary video equipment and lighting and is planning to produce its YouTube campaign in-house. The hospital’s webmaster will act as the videographer, the media relations officer will do the interview-
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ing and the physician will be the clinical expert. The videos will be approximately three minutes long and will cover a variety of pertinent pediatric health topics. Organizations that implement YouTube campaigns can increase their effectiveness by offering a variety of digital formats and making use of tags. For example, files can be saved as.flv,.avi, and. mov. They can also be saved in two different size formats and each can be tagged with a variety of unique tags. Essentially, this allows one video to be posted six times increasing its visibility and reach. Another effective technique to increasing traffic is to tag a video with key words that are similar to well established videos that generate a lot of views. YouTube makes suggestions to users about videos they might find interesting. By implementing the similar tag approach, organizations can increase the likelihood that their video gets suggested.
DRAWBACKS OF WEB 2.0 There is no disputing the fact that Web 2.0 is revolutionizing the way users interact with the web. As a result, users are becoming more sophisticated. They expect rich user experiences and know how to actively participate with the Web 2.0 technologies. Therefore, organizations need to be cognizant of this phenomenon and adjust their interactive on line marketing strategies to meet the advanced needs of consumers (Burrus, 2010; Cooke & Buckley, 2008). If they fail to recognize this transformation, they risk being overtaken by their competitors. However, as the web continues to improve, the concerns about security, accuracy, and information management continue to grow. In the on line banking world, executives are concerned about malware. Malware is malicious software that targets on line banking transactions and steals account numbers and
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management
funds from customers. At the beginning of 2007, anti-malware vendors detected about a quarter of a million incidents worldwide (Orr, 2008). Information is also becoming more challenging to manage. There are concerns about the legitimacy and accuracy of information on wikis. Participation in wikis requires a level of trust and respect. Since wikis are not monitored by any one governing force, there is always a chance that inaccurate information could be posted. Malicious authors could add information that is untrue. In a business setting, it is important for organizations to establish policies to determine who can access systems and change information. They also need a way to track who changes information, if appropriate (Dearstyne, 2007). Companies that blog need to pay particular attention to the content that they are generating. Business blogs take a lot of time and effort if they done correctly. Companies need to be sure that they are crafting appropriate messages and that they are effectively reaching their target audiences. Moreover, organizations need to be sure that they have the right person writing their blog. After all, the blog is their face to the world. A blogger without the appropriate skills could embarrass the organization and even harm customer relationships (Taylor, 2008). Blogging can be time consuming if it is not done effectively. There are several components that make a blog successful. In a business setting, blogs need to provide the reader with relevant information and a rich experience. Blogs must be updated regularly, even daily if possible. The person responsible for blogging within an organization should make it part of their daily routine and only publish coherent, well conceived content. Messages should have a focus and follow the best practices of traditional writing by answering the questions who, what, where, when and why. Blogs should pose questions to encourage dialogue and link to other blogs to facilitate interactivity and enrich the conversation (Maulana & Eckhardt,
2007). Most importantly, bloggers need to bring something interesting to the conversation to keep readers continuously engaged. Without employing sound blogging techniques, organizations might do more harm to their businesses and reputations. In addition to effective blogging techniques, organizations have to be aware of the fact that a blog can open them up for attack. For example, Wal-Mart started a social networking application to communicate with college students on Facebook. The application became a magnet for anti-Wal-Mart comments and discussion (Bernoff & Li, 2008).
SOCIAL NETWORKING Social networking (SN) builds web-based communities. SN software gives web users the ability to create profiles that foster interaction between groups of people based on interests and expertise. Typical SN applications include blogs, wikis, bookmarking/tagging, RSS feeds, and mashups. A mashup is a web page or application that combines data or functionality from two or more external sources to create a new service (Dearstyne, 2007). The result is typically a new and distinct Web service that was not originally provided by either source. Hence, SN software includes majority of the Web 2.0 technologies. Figure 2 indicates the connections of a typical SN. First made available on consumer-oriented sites such as MySpace, Facebook, LinkedIn, and Twitter, SN is beginning to find a place in the enterprise (Lamont, 2009b). Many business executives question whether SN is effective or desirable within a corporate setting (Mills, Chen, Lee & Rao, 2009). However, now that many SN products are scalable to the enterprise and address security and other concerns, it is becoming more common for companies to incorporate SN into established business processes. SN complements traditional working practices by creating opportunities for extending sales,
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Figure 2. Social networking: Connecting information, people, and websites (Source: Ektron, Inc., Nashua, New Hampshire, USA)
marketing, recruitment, research, and technical support. SNs can be leveraged as a customer relationship management tool for companies selling products and services. Using SN, these companies have been able to drive traffic to their own online sites while encouraging their consumers and clients to have discussions on how to improve or change products or services. As SN applications become integral to an organization’s activities, they achieve legitimacy and value that puts at the same level as enterprise applications (Lamont, 2009b; Wilson, 2009). The need to create, acquire, store, organize, search, filter and visualize information for business purposes will only increase in coming years. Therefore, despite initial trepidation, enterprises; especially those with highly skilled employees working in remote locations, are coming to the realization that SN tools can help build a corporate culture in which knowledge is quickly located and shared (Gibson, 2009; Lamont, 2009b).
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SOCIAL NETWORKING AND KNOWLEDGE MANAGEMENT Knowledge Management (KM) is a set of tools and processes companies use to create, track and share intellectual assets. The first wave of KM involved digitizing and tracking documents using tools like content management systems. It quickly became clear that it was too hard to share those documents, so companies adopted collaboration tools. “Document-centric collaboration by itself isn’t enough. You need to have something peopleoriented right alongside it,” said Oliver Young, an analyst at Forrester Research (Gibson, 2009). Organizations are already actively leveraging the power of social networks to find new business opportunities, but SN tools show clear potential for improving collaboration and knowledge sharing within organizations. With social networks, companies are extending KM to make it easier to connect employees and information (Fitzgerald,
Web 2.0 Social Networking Technologies and Strategies for Knowledge Management
2008; Parise, 2009; Wilson, 2009). SN can be effectively used for finding expertise quickly and easily, particularly for people working remotely who feel part of the broader community with the use of SN (Cardon, et al., 2009; Maulana & Eckhardt, 2007). Since businesses operate globally, social networks can make it easier to keep in touch with contacts around the world. Additionally, employees are typically familiar with SN since they use them outside of work (Fitzgerald, 2008; Lamont, 2009b). The following section of this chapter addresses the business advantages of SN in many perspectives. Existing business tools for knowledge sharing and collaboration primarily consist of email, work productivity desktop applications and portals. These tools are very structured and rigid in their set up and interaction, and do not provide a free-form medium for users to leave their impressions and opinions behind in the way that SN applications do. Bookmarking/tagging and other SN tools help bring order to the abundance of information that employees have to sift through (Conry-Murray, 2009; Gupta & Carpenter, 2009). SN helps people find and connect to co-workers through user profiles, expert search, and social graphs—visual maps of an employee’s connections with co-workers. This makes it easier to stay in touch with a greater number of people than would be possible with one-to-one interactions. SN also helps workers find content and people relevant to their work, share information easily, and offer insights to each other on a continuous basis. For instance, experienced senior staff members can offer insights to junior staff members in small doses and in a casual style (Conry-Murray, 2009; Lamont, 2009a). Many organizations are still divisionally segmented. SN can bridge groups so they can see what is going on outside their own area. For instance, an employee whom reads blogs outside of his/her own business group can understand the bigger picture of what is happening in the organization (Conry-Murray, 2009; Lamont, 2009b).
If used properly, SN lets firms accelerate business by bringing faster response time to all facets of the business. In order to support growth, firms need ways of expediting innovation and SN tools supports the agility needed in today’s economy (Lamont, 2009b; Pascu, et al., 2008). SN tools bring people from different locations or business functions to participate in solving problems or creating innovation. Rapidly sharing ideas and complementary skills can help firms reduce development time (Lamont, 2009b). The theory here is that good ideas get validated and bad ideas get discarded more quickly, which leads to faster product development (Conry-Murray, 2009; Fitzgerald, 2008). SN tools have made it possible to tap into the decision-making capabilities of the collective on a greater scale than ever before by opening discussions to a greater sample of resources, with greater disparity of areas of knowledge (Longbottom & Bamforth, 2008; Iandoli, 2009). A growing number of applications have shown that a large enough group of diverse, independent and reasonably informed people might outperform and get to an end result that reflects a complete truth more effectively than a single expert or closed group (Bonabeau, 2009; Cardon, et al, 2009). For many problems that a company faces there can be a solution far outside of the traditional places that managers might search, within or outside the organization. Furthermore, decisions made at the head office may not fit local or field realities. The knowledge of those who have the necessary information from being in the field can be more effective than the use of top-down, template-based decisions. Collective intelligence accumulated via SN can help provide a diversity of viewpoints and input that can deter self-serving bias and belief perseverance, and can help combat pattern obsession and negative framing effects (Bonabeau, 2009). Most business people are familiar with SN sites like MySpace, Facebook, and LinkedIn, other online communities and SN tools. Since SN has
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become a part of these people’s lives outside of the office, they will be eager to use these tools; potentially leading to more business collaboration (Fitzgerald, 2008; Gibson, 2009). Social networks are also easy and intuitive. There is great business opportunity here since there is always demand among learners for easy-to-use tools that simplify processes and SN tools can be used to replace more complicated collaboration tools (Gibson, 2009). This ease of use epitomizes SN’s potential for companies that want to tap the knowledge of their workers (Fitzgerald, 2008). The foundation of SN is its social context. Sharing is encouraged, and the open, visible contributions and interactions reduce barriers to information flow. The personal nature and immediacy of SN can make interaction less impersonal and artificial than older bulletin board, mailing lists, and collaboration tools (Gupta & Carpenter, 2009). Adding a face and personality to the names of coworkers and business partners can go a long way toward supporting productive interaction (Lamont, 2009b). For instance, a SN application like Facebook could act as a virtual employee water cooler (Fitzgerald, 2008). Some individuals who might not otherwise interact as extensively with co-workers are actively participating. Formerly, people were forced to give up their knowledge, but with social networks, people willingly give up their knowledge (Gibson, 2009). SN exchanges are preserved, creating a record of previous conversations. Within a SN, employees search, view, bookmark/tag, rate, comment on, and edit information. In doing so, employees leave “digital fingerprints” on the content they access and these “digital fingerprints” provide insight into what is influencing the daily work of employees (Diehl, et al., 2008; Gupta & Carpenter, 2009). Capturing this valuable engagement data and making it actionable presents organizations with a clear opportunity to visualize and improve the way information is both consumed and contributed to by employees. These findings are important for businesses since they point to the nature of how
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people find and internalize information and more importantly how organizations can then make these traits part of their best practices (Gupta & Carpenter, 2009).
LIMITATIONS AND CONCERNS There are several limitations and concerns in bringing SN into the business environment. SN requires that firms turn over the technology experience to the end user. That is not normal, nor is it comfortable for companies, especially information technology (IT) departments (Burrus, 2010; Wilson, 2009). Also, SN applications often lack any explicit refereeing process that might provide some degree of quality assurance, which could lead to unwanted and undesirable outcomes (Bonabeau, 2009). Communities of interest could drown out any voice of reason leaving the majority view essentially unchallenged (Longbottom & Bamforth, 2008). Further control concerns include unpredictability, unassigned liability, and data leakage from staff gossiping freely in an open environment. Consequently, one of the biggest issues with respect to control is whether to include outsiders in the process (Bonabeau, 2009; Wilson, 2009). Companies have reservations about SN privacy and security, and rightfully so. SN opens up new avenues for the introduction of malware and phishing scams practiced by cyber-crooks. Also, businesses should be wary of potential about open access to the company servers as a result of lax and outdated attitudes toward passwords (Fitzgerald, 2008; Orr, 2008; Wilson, 2009). The assumption that an unmediated open group of resources will always come to a better conclusion than a single expert or closed group is dangerous. Companies can collect information from myriad sources and then perform some sort of averaging. In this case, the whole is equal to the sum of its parts, but the key is to maintain the right balance between diversity and expertise. Certain
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problems are more appropriately addressed by a diversity-based approach than others, but no amount of diversity will help if the group is completely ignorant of the issues (Bonabeau, 2009). Therefore, firms need to decide which people to involve in group decisions and whether or not each participant should be given an equal voice. Even an application like Wikipedia, which might look simple on the surface, relies on a complex hierarchy of carefully selected editors (Bonabeau, 2009; Longbottom & Bamforth, 2008). Companies have generally been convinced of the value of connectivity and sharing information, but SN communities sometimes lack focus. Personal SN sites such as MySpace, Facebook, and Twitter, have been given a bad rap and are often seen as vehicles for sophomoric selfaggrandizement (Conry-Murray, 2009). This has led some to argue that SN interaction in the business environment is a nonproductive use of time. It also raises policy questions around moderating employee behavior and the use of network bandwidth (Lamont, 2009a; Wilson, 2009). Also, introducing SN into the enterprise presents a learning curve for workers whom are not familiar with SN and are used to communicating in specific ways. Firms not fully convinced of the business value of SN stand to waste significant time with employees needing training (Fitzgerald, 2008). Use of SN as business tools lacks a reliable formula for measuring return on investment (ROI). When these tools are used to connect with customers and partners, there are usually ways to calculate a payback, but when companies provide them to employees, they’re often going on gut instinct that SN will be good for business (Conry-Murray, 2009). It is hard to come up with a reliable yardstick to measure the cost of the tool versus cost savings due to time saved or new opportunities created (Gibson, 2009). There is no real way to know how solutions will fit in a firm’s
environment until they have been implemented and used by employees and customers (McCluskey & Korobow, 2009; Wilson, 2009).
DISCUSSION AND SUGGESTION With thousands of active user groups already contributing to social networks, companies have been cautious when adopting SN technologies. SN is here to stay so it is important for businesses to find a practical way to adapt to it and work with these SN sites (Wilson, 2009). Following are some suggestions for firms when considering in rolling out SN applications.
Create Community As a collaborative tool for KM, SN must be embraced by all employees and should inspire the frequent sharing of valuable knowledge. What motivates people to participate in a collective undertaking can vary widely so organizations must provide a continuous flow of new, enthusiastic participants to keep engagement high, or they need to provide incentives to sustain people’s motivation over time (Bonabeau, 2009; Maulana & Eckhardt, 2007). Rewards and recognition are not necessarily monetary in nature. Instead, a community of practice (CoP) should be formed around a recognized identity that all members can relate to and feel part of. For a CoP to be successful, the community must become part of the practice itself. Community members must be able to easily see a direct benefit from being a member of the CoP and the community must take on a sufficient level of importance to its members. Otherwise, it becomes easy for them to lose interest in contributing. The “what’s in it for me” factor is lost and the pressure of day-to-day business outweighs any reasons to
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contribute (Posey, Lowry, Roberts & Ellis, 2010). Members of communities rely on other members for assistance with work-related issues, problemsolving and professional support. They need to know that they can trust their colleagues if they are to share openly and they must also feel that they are treated with appropriate respect (Posey, Lowry, Roberts & Ellis, 2010).
Do Not Let Fear Strangle Growth Many organizations are wary of giving a voice to employees because they do not know what they will say. Businesses also worry that employees will overdo the social aspects of these applications. This may tempt organizations to police employeegenerated content, either through monitoring or pre-approving contributions. However, it is important to resist that temptation, as it will drastically affect employee participation. Employees need time to become comfortable with the idea of speaking up, sharing ideas, and participating in company-wide conversations. A SN project will likely wither before it has a chance to grow if people fear the thought police (Conry-Murray, 2009). Remember that a CoP is voluntary, so any attempt to control a SN is likely to destroy it (Zhang & Daugherty, 2009).
Resist Exclusivity Business units or teams may want to build gated communities, but that approach defeats the purpose of a social network. The value of SN is in broadening the number of individuals who are generating or evaluating solutions (Bonabeau, 2009). A company may want to tap into people or groups that it has not traditionally included when collecting and evaluating ideas. For instance, it might want to reach across business functional barriers or even groups outside of the company (Conry-Murray, 2009; Bonabeau, 2009).
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Standard Code of Conduct When people are allowed to contribute to decisions, the likelihood that some will misbehave increases with group size. An implicit code of conduct like e-mail protocol helps govern people’s behavior (Bonabeau, 2009). The development of standards would also help to establish SN more firmly in the corporate world (Lamont, 2009b; Posey, Lowry, Roberts & Ellis, 2010). This is not to be confused with policing. As mentioned earlier, policing an enterprise SN will kill it.
Select the Right SN Technology SN technology should be as simple, effective, and transparent as possible and applied as needed in order to support key community functions and effective group development. An important element with choosing technology for a SN is to be very clear from the start on exactly how the technology will best serve the community. Even though a particular platform is either popular or easily available at a given point in time, it may not necessarily be the best solution for all communities (Posey, Lowry, Roberts & Ellis, 2010). Search underpins the value of a SN so insufficient indexing and searching capabilities will make social applications less useful. The point of SN in business is to let people provide input into the relevancy of content and people, so make sure SN has a search engine that allows for usergenerated feedback such as tags and content-rating systems (Conry-Murray, 2009).
Measuring Business Value SN helps organizations achieve internal goals. In 2008, the popular consumer electronics store known as Best Buy successfully used an internal social network site (ISNS), BlueShirt Nation, to achieve its HR goal of increasing participation in
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the company’s 401(k) plan. Through BlueShirt Nation, Best Buys HR department launched a contest inviting employees to create online videos about what 401(k) plans mean to them. By the time the contest ended employee participation had jumped 47%. Additionally, an ISNS assists in keeping employees engaged. In 2007, Nissan successfully launched an ISNS, N-Square, to connect 50,000 of the company’s 180,000 employees. N-Square was launched to provide employees with a way to avoid bureaucratic communication channels; create new partnerships and engage employees. The launch was tied to Nissan’s overall business strategy that called for talent retention. First, N-Square increased efficiency by providing a direct channel to connect employees with others that can provide expertise so that they can do a better job. N-Square makes it quick and easy for employees to communicate. Second, N-Square improved job engagement by making employees feel more connect to their jobs. In the end, Job engagement combined with easy access to mentors contributes to employee happiness and retention. As mentioned earlier, it is almost impossible to calculate the ROI of a SN. Instead, firms should try to measure the success of a SN in other ways. A key indicator of the value of SN is engagement - whether the application has stimulated and maintained the active participation of people in a meaningful way (Bonabeau, 2009). In this case, it is important to consider qualitative value. For instance, if system A has 3,000 users and system B has 60,000, but the 3,000 on system A are all doing clinical research and using it daily, clearly the more valuable system is A. Another way to measure a SN is the number of other applications that can be linked to it in ways that enhance productivity. For instance, a system that’s highly integrated into other systems is indicative of high value. Finally, firms should relate SN to process improvements rather than time-savings or efficiency gains. For instance, the use of a wiki might cut down the number of help desk requests (Conry-Murray, 2009).
CONCLUSION SN continues to expand across businesses and enterprises. Social network software could have a more far-reaching organizational impact than technologies adopted in the 1990s. Vendors including IBM, Microsoft, Adobe, Novell and Oracle are adding SN tools to their products. Similarly, vendors such as Jive and Ektron have gotten into the act by offering SN toolboxes with their core products, and Yammer, a tool that works much like Twitter but is intended for business use, includes a SN component that gives employees personal pages. The bottom line is that SN tools are helping businesses streamline the processes of researching projects, forming teams, and sharing knowledge. The personal nature, familiarity, and ease of use of SN attract executives and employees to improve their collaboration and relationship. Clearly, the future of collaboration and knowledge sharing can be enhanced by SN tools. We are seeing the beginnings of a new era of how information and knowledge will be discovered, created, distributed, and utilized inside organizations. In order for companies to stay ahead of the curve and, more importantly ahead of their competitors, companies and organizations need to seriously determine how they can implement effective marketing strategies that incorporate Web 2.0 capabilities. They need to interact in a more personal way and create favorable user experiences by proactively reaching out and connecting with their customers. Web 2.0 has introduced a new level of technological sophistication. RSS feeds enable companies to stay engaged with customers by delivering updates to them directly, without requiring them to visit the company’s website. YouTube marketing strategies offer companies the ability to showcase their personalities provide and offerings in a way that can be more authentic. It also provides a platform for viral marketing campaigns.
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Companies that fail to think outside of the box, and that fail to think about the opportunities presented by Web 2.0 strategies, will be at risk of being surpassed by their competitors. Web 2.0 is revolutionizing the Internet and the way users interact with the Internet. It will continue to have a very powerful effect. Adoption or lack of adoption will eventually be the difference between the companies that succeed and those that do not.
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Dearstyne, B. (2007). Blogs, mashups & wikis: Oh, my! Information Management Journal, 41(4), 25–31. Diehl, A., Grabill, J. T., Hart-Davidson, W., & Iyer, V. (2008). Grassroots: Supporting the knowledge work of everyday life. Technical Communication Quarterly, 17(4), 413–434. doi:10.1080/10572250802324937 Fitzgerald, M. (2008). Why social computing aids KM (pp. 1-5). CIO. Retrieved April 15, 2009, from http:/ /www. cio.com /article /395113 /Why_ Social_ Computing_ Aids_ Knowledge_ Management_ Gaspar, M. (2005). RSS: A new way to keep in touch. International Trade Forum, 4, 27. Gibson, S. (2009). Web 2.0 tools gain enterprise acceptance. eWeek, 26(7), 16-18. Gupta, P., & Carpenter, H. (2009). Enterprise wide SN. Business Intelligence, 12(3), 26–29. Harris, A. L., & Rea, A. (2009). Web 2.0 and virtual world technologies: A growing impact on IS education. Journal of Information Systems Education, 20(2), 137–144. Iandoli, L. (2009). Internet-based decision support systems: Leveraging mass collaboration to address complex problems. Journal of Information Technology Case and Application Research, 11(4), 1–10. Jackson, N. (2008). Blog city. American City and County, 123(1), 30–33. Jones, M. (2006). Will news find a home on YouTube? Nieman Reports, 60(4), 52–54. Kessler, C. (2007). Where were you when YouTube was born? Journal of Brand Management, 14(3), 207–210. doi:10.1057/palgrave.bm.2550069
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King, W. (2007). IT strategy and innovation: Recent innovations in knowledge management. Information Systems Management, 24(1), 91–93. doi:10.1080/10580530601082004 Kreitzberg, A. P. (2009). Building a Web 2.0-friendly culture: Success on the Web is about people, not technology. People and Strategy, 32(2), 40–45. Lamont, J. (2009a). KM past and future: Solutions for a changing world. KM World, 18(1), 6–7. Lamont, J. (2009b). Social networking gets down to business. KM World, 18(6), 10–13. Lending, D. (2010). Using a Wiki to collaborate on a study guide. Journal of Information Systems Education, 21(1), 5–13. Levy, M. (2009).Web2.0implicationsonknowledge management. Journal of Knowledge Management, 13(1), 120–134. doi:10.1108/13673270910931215 Longbottom, C., & Bamforth, R. (2008). Social networking in the public sector. Knowledge Management Review, 11(5), 30–33. Maulana, A. E., & Eckhardt, G. M. (2007). Just friends, good acquaintances or soul mates? An exploration of website connectedness. Qualitative Market Research, 10(3), 227–242. doi:10.1108/13522750710754281 McCluskey, T., & Korobow, A. (2009). Leveraging networks and social software for mission success. Public Management, 38(2), 66–70. Mills, A., Chen, R., Lee, J., & Rao, H. R. (2009). Web 2.0 emergency applications: How useful can Twitter be for emergency response? Journal of Information Privacy & Security, 5(3), 3–26. Naim, M. (2007). The YouTube effect. Foreign Policy, 158, 103–104. O’Reilly, T. (2005). What is Web 2.0? Design patterns and business models for the next generation of software. Retrieved March 11, 2009, from http:// oreilly.com/web2/archive/what-is-web-20.html
Orr, B. (2008). Security 2.0: Not just a new kettle of phish. American Bankers Association. ABA Banking Journal, 100(2), 54–55. Parise, S. (2009). Social media networks: What do they mean for knowledge management? Journal of Information Technology Case and Application Research, 11(2), 1–11. Parise, S., Guinan, P. J., Iyer, B., Cuomo, D. L., & Donaldson, B. (2009). Harnessing unstructured knowledge: The business value of social bookmarking at Mitre. Journal of Information Technology Case and Application Research, 11(2), 51–71. Pascu, C., Osimo, D., Turlea, G., Ulbrich, M., Punie, Y., & Burgelman, J. (2008). Social computing: Implications for the EU innovation landscape. Foresight: The Journal of Futures Studies. Strategic Thinking and Policy, 10(1), 37–52. doi:10.1108/14636680810856017 Posey, C., Lowry, P. B., Roberts, T. L., & Ellis, S. (2010). Proposing the online community self-disclosure model: The case of working professionals in France and the UK who use online communities. European Journal of Information Systems, 19(2), 181–195. doi:10.1057/ejis.2010.15 Prasarnphanich, P., & Wagner, C. (2009). The role of wiki technology and altruism in collaborative knowledge creation. Journal of Computer Information Systems, 49(4), 33–41. Raman, M. (2006). Wiki technology as a free collaborative tool within an organizational setting. Information Systems Management, 23(4), 59–66. doi:10.1201/1078.10580530/46352.23.4 .20060901/95114.8 Strehlke, C. (2010). Social network sites: A starting point for career development practitioners. Journal of Employment Counseling, 47(1), 38–48. Taylor, S. (2008). Blog on! A review of two consultants’ online musings on marketing. Of Counsel, 27(4), 3-4.
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Wang, J. F. (2009). Building social networking sites (SNS) on open source platforms. Business Review (Federal Reserve Bank of Philadelphia), 13(2), 32–40. Webb, G. (2007). A new future for brand marketing. British Journal of Administrative Management, 13–15. Wilson, J. (2009). Social networking: The business case. Engineering & Technology, 4(10), 54–56. doi:10.1049/et.2009.1010 Zhang, J., & Daugherty, T. (2009). Third-person effect and social networking: Implications for online marketing and word-of-mouth communication. American Journal of Business, 24(2), 53–63. doi:10.1108/19355181200900011
KEY TERMS AND DEFINITIONS Collaboration: Knowledge workers work together either face-to-face or virtually to solve business problems. Knowledge Management (KM): KM comprises a range of strategies and practices used in an organization to identify, capture, represent, and transfer knowledge across the organization to achieve organizational goals.
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Real Simple Syndication (RSS): Real Simple Syndication (RSS) is an Internet technology that allows users to receive custom content from websites. Social Networking: A web-based service allows members of the web site to create a personal profile to interact with other users through sharing ideas, common interests, events, and activities. Tag: A tag is a key-word attached to a piece of information such as a picture, blog, or video clip. The tag helps classify the piece of information. Virtual Organization: An organization allows workers to live and work anywhere in the world. Employees use Internet-based infrastructure to communicate, collaborate, and conduct organizational functions. Web 2.0: The term Web 2.0 represent Internetbased applications that supports collaboration, social networking, blog, wiki, RSS, mashups, and a number of media sharing tools. Widgets: Widgets are basically small pieces of programming code embedded in an image file. They are programmed to react to a user’s command such as a mouse click. Wikis: Wikis allow Internet users to publish information in a collaborative manner on the Internet. They offer a simple editing and publishing interface that can be used and understood easily.
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Chapter 6
Competence Management over Social Networks Through Dynamic Taxonomies Giuseppe Berio University of South Brittany, France Antonio Di Leva Università di Torino, Italy Mounira Harzallah University of Nantes, France Giovanni Maria Sacco Università di Torino, Italy
ABSTRACT The exploitation and integration of social network information in a competence reference model (CRAI, Competence, Resource, Aspect, Individual) are discussed. The Social-CRAI model, which extends CRAI to social networks, provides an effective solution to this problem and is discussed in detail. Finally, dynamic taxonomies, a model supporting explorative conceptual search, are introduced and their use in the context of the Social-CRAI model for exploring retrieved information available in social networks is discussed. A real-world example is provided.
INTRODUCTION The current focus of organizations is on gathering, planning, representing and exploiting competencies of employees and other collaborating/ concurrent organizations. As explained in the last Cedar Crestone report (CedarCrestone, 2010),
organizations with individual competence management (i.e. the management of competences of any employee) have better than average sales growth; those outperforming organizations have been supported by Human Resource software systems (HR systems) with integrated and unified functionalities and are even able to exploit social
DOI: 10.4018/978-1-61350-195-5.ch006
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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networks; more importantly, their best practices in talent management have been fundamentally driven by individual competence management. In the context of web 2.0, social networks are becoming a basic mechanism for advertising and sharing information about competencies of people, roles (in the sense of roles played by people and organizations within one organization) and organizations. For instance, social networks such as LinkedIn are becoming more and more important in forging networks of professionals for deal-making, collaboration, and, most importantly in this present context, for recruiting. On the one hand, companies can use information from social networks to speed up recruitment/collaboration and, conversely, persons can use the same information to get more job opportunities. On the other hand, companies can advertise their interests about specific required competencies and persons may even want to focus on these competencies when looking at learning opportunities and curricula. Therefore, in social networks several types of information about competencies may be found. However, these information need to be carefully identified and assessed before moving further because A. Any self qualitative or quantitative evaluation of own proper competencies may be wrong; B. Any self definition of a competence may differ significantly from definitions provided by other actors in the same or other contexts. Otherwise, there is a risk of making wrong decisions concerning recruitment of people and collaboration with people or organizations. Since late ‘90, we have proposed a competence reference model (Harzallah & Vernadat, 2002; Berio & Harzallah, 2006) and a competence management process model (Berio & Harzallah, 2005; Berio, Harzallah & Sacco, 2007): the former provides a precise definition for the concept of competence, acquired and required
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by an organization, and comprises concepts that are required for managing theses competencies; the latter provides the definition of four macroenterprise processes (i.e. required competence identification for planning and identifying what an organization is looking for, competence assessment for understanding the current status of individual competencies within the organization, competence acquisition – and retention - for acquiring missing required competencies - – and retaining currently available required competencies - and, finally, competence knowledge usage for exploiting in specific manner any knowledge about competencies and supporting the previous three processes) that defining what management of competencies is. The competence reference process model supports two management styles: •
•
Competence identification first i.e. the enterprise is able to define and to plan its required competencies (mostly usable when competencies are mostly known or envisioned in advance); Competence assessment first i.e. the enterprise discovers its competences, possibly not required in short-term but becoming required in long-term, based on assessment, (mostly usable when competencies are not known a priori or with very qualified employees undertaking actions and making decisions autonomously toward the fulfillment of given enterprise objectives).
Both styles are valuable in specific situations and probably can be mixed. This robust baseline, both the competence reference model and the competence management process reference model, is fully in line the findings cited in (CedarCrestone, 2010). The baseline indeed supports the development unified and integrated functionalities for HR systems by providing a complete implementation framework. Additionally, the framework comprises modern technologies compliant with the Semantic Web,
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such as ontologies (Guarino, 1995; Gruber, 1993) and dynamic taxonomies (Sacco, 2000). Moreover, other than the development of new HR systems, the two models of the baseline can also be used for the alignment of existing HR systems. The benefits of using and implementing the two models cited above are closely related to the availability of codified, precise and shared competencies for within the organization and also for its external environment; this leads organizations to outperform on: •
•
•
Competence identification – introducing well defined and precise definition for required competencies, planned by the organization; Competence acquisition – ◦⊦ Trainings: unnecessary training is eliminated and better prediction of required training, increased usage of contracted vendor training programs, employee perceptions of the “relevancy” of purposeful training, clear development plans and career development support; ◦⊦ Improved retention rates of talented employees as employees are better able to develop their own employability, improving and partially automating the search for good candidates even because competencies are precisely defined and can also be shared outside the organization; ◦⊦ Improved employee commitment as they perceive their importance to the organization; ◦⊦ Evaluating automatically gaps between acquired and required competencies; Competence assessment – Dramatic improvement of the employee competence assessment process based on information
•
extracted from available activity reports and other documents by using (business) rules or navigations through dynamic taxonomies; Competence knowledge usage – Ensures people are adding the most value because they are in the right place at the right time.
The paper provides the reader with conservative extensions of the competence reference model for dealing with information conveyed through social networks such as experiences, jobs, and links to other persons. These extensions especially focus on the competence assessment and acquisition processes because social networks should be explored for selecting potentially competent individuals (within and outside the organization), then associated information (published in profiles) and links to those individuals should be used systematically (by some software) for extracting competencies. The process reference model that we have proposed so far remains unchanged and therefore will be not discussed deeper in this paper. The extensions to the competence reference model are especially required for accommodating competence assessment and scoring of individuals as well as more including organizations as competence holders for taking into account that even organizations can advertise information related to competences within social networks. The paper is also focusing on how to explore social networks and retrieved information (even transitively) for selecting potentially competent individuals.
BACKGROUND The competence reference model (Competence, Resource, Aspect, Individual - CRAI) has been developed since 2000 throughout several applications and publications. Hereinafter, we provide the reader with the fifth main features of the model
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as well as with some of additional features. We also provide a short positioning of the CRAI model with respect to recent proposals dealing with competence models. The first central feature of the model is the following definition of a competence: a competence is the effect of combining and enabling operational use of its competence resources (or c-resources for short) being c-resources some specific well-defined and simple abilities, skills, knowledge etc. of individuals according to three conceptual categories, knowledge, know-how, and behaviors, in a given context to achieve an objective or fulfill a specified mission. Within the definition there two important points that should be emphasized: first, a competence is based on simple, precisely defined abilities, skills, knowledge etc. (ASKe in the remainder) of individuals (named c-resources or resources of the competence), second the individual should be able to combine and effectively used these ASKe for achieving an objective or being successful for a specific mission or task. Therefore, the simple ASKe are mostly organization independent and may also be assessed independently; a competence is mostly organization specific and should only be assessed within the organization. Why there is the need of distinguishing carefully between competencies and simpler ASKe. Saying “He’s competent on Oracle” does not make sense but saying “He’s able to restore an Oracle database status after a failure” makes sense. The second may participate to the definition of the former, within a specific organization where, implicitly, saying that “He’s competent on Oracle DBMS” means that “He’s able to restore an Oracle database status after a failure”. However, within the organization is also required that “He knows the organization specific Oracle DBMS environment” or that “He’s able, within a short period of time, to fully understand and operate on any organization specific Oracle DBMS environment”. In this sense, some specific ASKe are required to use other specific ASKe as well. The competence “He’s competent on Oracle”
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within one organization brings all those ASKe as well. Finally, the concept of competence can sometimes be “transitive”. For instance, we want to say that “He’s competent on -To move composed objects-” may also mean that “He’s competent on -To dismount composed objects-”. In CRAI, it can be stated that a competence is transitive (in one specific enterprise): in the case above, for instance, one competence is transitive through one enterprise activity “To move composed objects” to one another enterprise activity “To dismount composed objects”; i.e. that is the same as saying that the task “To move composed objects” requires to accomplish the task “To dismount composed objects” and therefore competencies required for the latter are also required for the former. The second central feature is that competences hold by one individual are not stated but derived from ASKe associated to that individual. This is consistent with the previous discussion because you can assess specific simple ASKe of individuals but competencies are defined by the organization for its own specific tasks, missions, objectives etc. One individual holding all ASKe defining one given competence also holds that competence. CRAI therefore provides a clear distinction between required and acquired competencies as well. The third central feature is the clear link between competencies and the enterprise context where these competencies must be used. Specifically, in CRAI there is a specific link between simple ASKe and missions, tasks, objectives and other aspects of the enterprise that require these ASKe. In few words, there is a link between the specific represented ASKe and the enterprise model (Vernadat, 1996) representing the enterprise (processes, activities, tangibles and intangible resources – including competences -, information objects, products, services, missions, objectives etc.). The enterprise is therefore able to trace, and further to assess, the link between what should be done and which competencies are required for accomplish the task. As shown in (Harzallah, Berio & Vernadat, 2006), the enterprise model often
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takes the form of a multifaceted taxonomy i.e. multiple interrelated classifications of enterprise artifacts (such as organization structure, processes, resources, products, objectives etc.). The fourth central feature is the distinction between competencies and ASKe and other kinds of information that can be useful for selecting among several candidates when running the competence acquisition process. Information such as age, required salary, geographic zones and so on are interesting information but they are not belonging to individual competencies. The fifth central feature is the link between any document or report used to assess some ASKe of individuals and the ASKe represented according to the model. This can be done, for instance, according to some i) explicit rules and therefore can be eventually automated or ii) focused navigations throughout documents and reports. Some additional interesting features can also be mentioned such as scoring of ASKe and competencies and the definition of “cumulative competence” for dealing with individuals that should be interchangeable or when mass-work is required. It can be therefore represented that “5 individuals should be competent on Oracle”. All these features above have been concretely represented by using a UML class diagram (Unified Modeling Language, 2010). However, CRAI is not only a diagrammatic artifact but, as said in the Introduction, it provides an accompanying implementation framework for actually implementing very open HR systems. An earlier version of the framework was based on database technology by supporting automated transformations of the CRAI model in database schema. The current framework is based on the one side, on ontologies (Guarino, 1995; Gruber, 1993) and, on the other side, on dynamic taxonomies (Sacco, 2000). Ontologies assure that represented information can be shared between people and between software applications. At the same time, ontologies assure that some reasoning capabilities are available and rules can be defined for easily building automated
functionalities. As for generating database schema, it is also possible to automatically generating ontologies from the CRAI model (Spaccapietra et al., 2004; Upadhyaya & Kumar, 2005). However, ontologies and databases, are not the best technologies for exploring information, especially if this information is textual and poorly standardized. This however can be done easily with dynamic taxonomies as explained later. CRAI (including the accompanying implementation framework) has been extensively compared and takes into account several other proposals for representing competences and effectively managing them. These include, among others, Lucia & Lepsinger, 1999, Marreli, 1998, Hiermann W & Hôfferer M., 2003, Laukkanen & Helin, 2005, and Colucci et al., 2003, as well as the papers listed as additional readings. A recent survey (Sampson & Fytros, 2008) concerning the concept of competence points out that a unique definition of competence is still missing and the authors propose a definition of competence: however, authors provide an “additional” definition for “competence” that is close the definition provided by CRAI. Various papers e.g. (Sitthisak, Gilbert, Davis & Gobbi, 2007; Cicortas & Iordan, 2007; Sampson & Fytros, 2008) provide detailed analysis on how two prominent initiatives HR-XML1 (Consortium HR-XML, 2010) and IMS RDCEO (IMS Reusable Definition of Educational Objective) (IMS, 2010) are not enough for building complex functionalities supporting competence management because lack of formalization and expressiveness; indeed, HR-XML and RDCEO, are essentially useful for, possibly limited, competence data interchange across various software systems. Those existing analysis reveal that RDCEO provides a flexible definition of competence using unstructured textual definitions that is (1) not precise enough for well representing competences and (2) of limited use for data interchange. Additionally, RDCEO and HR-XML lack of information on both context and relationships among competencies: however,
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in HR-XML competencies can be composed of other competencies. RDCEO does not provide any proficiency level while HR-XML provides a limited support for that. Looking to other recent proposals for representing competences by using formal models such as in (De Coi, Herder, Koesling, Lofi, Olmedilla, Papapetrou & Siberski, 2007; Caetano, Pombinho & Tribolet, 2007) we can say that the definition of competence found in CRAI is more precise and articulated: for instance, CRAI provides a clear distinction between “elementary competence” and c-resource because the former is “organization dependent” while the latter is clearly “organization independent”. CRAI provides a deeper and more precise definition of competence than the model in (Sitthisak, Gilbert, Davis & Gobbi, 2007); indeed, in CRAI, relationships between competencies are not stated but are derived on the base of their definitions and the explicitly represented “transitivity” (first features). In (Tarassov, Sandkuhl & Henoch, 2006), authors describe a very limited usage of (is-a) taxonomies and it seems that their definition of competence is fundamentally a whole description of general characteristics, educational history and job history of one individual. Therefore, the notion of competence per se may be not really found in the proposed model because several distinct histories may lead to same competencies as well.
THE SOCIAL-CRAI MODEL Social networks can be perceived as platforms where individuals and organizations present themselves and create links with other individuals and organizations. The original CRAI model, discussed above, was developed in a more classical setting; however, the original model is based on universal principles making it customizable and extensible.
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In the context of social networks is necessary to carefully distinguish between declared and collected data about individuals and organizations. Declared data are provided by or associated to individuals (for instance CV and activity reports) while collected data are specifically collected (performed) by the enterprise (for instance interview reports and test results). The difference between the two data classes concerns belief. Additionally, clearer shared criteria (or rules) used to assess c-resources over those collected and declared data are mandatory: this allows precisely understanding how the enterprise willing to use declared and collected data for competence assessment and acquisition. Very specific criteria may apply within social networks: some criteria may be based, for instance, on links to promoters or other individuals and their opinions, provided that promoters/individuals are eventually scored according to their “average” credibility. Therefore, remarkable extensions to CRAI are: •
•
Rawdata is further specialized in DeclaredData and CollectedData as defined above; AssessmentResource provides resources required for collecting data for further evaluation or assessment of specific cresources. These resources can be interaction driven meaning that they guide direct interactions toward individuals or can be data driven meaning that they support evaluation and assessment for specific cresources based on data (declared or collected) associated to individuals; interaction driven resources can be for instance interview templates and guidelines and test questions while data driven resources can be (mining) rules used for inferring c-resources. An example of rule is: “if an individual has participated as programmer to X projects based on Java, and X>s then this individual /knows Java/ at /acquired level L(X)/”. Data-driven resources can
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also be navigations or inquiries for selecting interesting data (collected and/or declared) such as: “selecting data containing – Java – Salary <30000 – Area = Milan”; Application is required to ensure the traceability/explanation of how assessment resources are used to both selecting interesting data (collected and/or declared) and then inferring c-resources concerning one individual (or organization); indeed, selection data are necessary whenever you can access different data, possibly in a conflicting way; for instance, if activity reports are available and a CV is also accessible through the social network, both can be used but may be some information in the CV prioritize the CV over activity reports (or vice-versa as well) for assessing competencies.
Finally, Competence Unit takes into account organizations as well: indeed, organizations as individuals hold and offer competencies; however, this extension is only descriptive in the sense that there is not an explicit relationship between competencies of individuals and competencies of organizations employing those individuals. Figure 1 shows the Social-CRAI model as a UML class diagram (i.e. mainly composed by classes (rectangles) for representing concepts and relationships (lines and arrows) linking concepts). Concepts belonging to the original CRAI model are Competence, C-resource, Aspect, Individual and Acquired. Specifically, classes C-resource and Aspect are the way in which CRAI provides both the description of c-resources and the definition of the enterprise model. Class C-resource categorizes three types of c-resources: the “known”
Figure 1. The Social-CRAI model (as a UML class diagram)
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resources, the “know-how” resources and the “behave” resources. Class Aspect is the root of a multiple taxonomies introducing the enterprise model artifacts (possibly decomposed), on which one c-resource is based. Moreover, the relationship “DM” on the class Aspect is used to realize the “transitiveness” of a competence according to the first feature of CRAI.
DYNAMIC TAXONOMIES Dynamic taxonomies are a general knowledge management model for complex, heterogeneous information bases (Sacco, 2000; Sacco & Tzitzikas, 2009). It has been applied to very diverse areas, including electronic commerce, multimedia databases and medical guidelines e diagnosis. Dynamic taxonomies are a holistic model, in which data modeling and human computer interaction issues have the same importance. This represents a dramatic departure from most research on Semantic Web, which focuses on expressivity and sophisticated reasoning capabilities but is geared toward programmatic access and requires mediator agents for user interaction. Our approach is, instead, user-centric because it supports direct and transparent user interaction by using a simple model that is easily understood by users, and that is at the same time sufficiently powerful to support effective exploratory access. The intension of a dynamic taxonomy is a taxonomy, i.e., a concept hierarchy going from the most general to the most specific concepts. Multiple inheritance is supported but rarely required. A dynamic taxonomy does not require any other relationships in addition to subsumptions (e.g. IS-A, PART-OF relationships): B≤A, read as B is subsumed by A, implies that the set of items classified under B is always a (possibly improper) subset of the items classified under A. In the extension, items can be freely classified under several concepts at any level of abstraction (i.e. at any level in the conceptual tree). This mul-
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tidimensional classification is a departure from the monodimensional classification scheme used in conventional taxonomies. We claim that a multidimensional classification is an essential requisite to model common real-life situations. First, an item is very rarely classified under a single concept. One reason is that items very often deal with different concepts: for example the current paper can be classified under “human resource management”, “competence management”, “social networks”, “dynamic taxonomies”, etc. Second, items usually can be classified from different perspectives (or facets; e.g. Time, Location, etc.), each of which can be described by an independent taxonomy. Since concepts are defined by instances rather than by properties, a concept C is just a label that identifies all the items classified under C. Because of the subsumption relationship between a concept and its descendants, the items classified under C (items(C)) are all those items in the deep extension of C, i.e. the set of items identified by C includes all the items directly classified under C union all the items directly classified under any of C’s descendants. There are two important consequences of this approach. First, since concepts identify sets of items, logical operations on concepts can be performed by the corresponding set operations on their deep extension and the user is able to restrict the information base by combining concepts through the normal logical operations (and, or, not). Second, dynamic taxonomies can find all the concepts related to a given concept C, which represent the conceptual summary of C. Concept relationships other than subsumptions are inferred through the extension only, according to the following extensional inference rule: two concepts A and B are related iff there is at least one item d in the infobase which is classified at the same time under A (or under one of A’s descendants) and under B (or under one of B’s descendants). For example, we can infer a (unnamed) relationship between Raphael and Rome, if an item that is classified under Raphael and Rome exists in
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the infobase. At the same time, since Rome is a descendant of Italy, also a relationship between Raphael and Italy can be inferred. The extensional inference rule can be extended to cover the relationship between a given concept C and a concept expressed by an arbitrary subset S of the universe: C is related to S if there is at least one item d in S which is also in items(C). Hence, the extensional inference rule can produce conceptual summaries not only for base concepts, but also for any logical combination of concepts. In addition, access through dynamic taxonomies can be easily combined with other retrieval methods because dynamic taxonomies can summarize sets of items produced by other retrieval methods (database queries, text retrieval queries, etc.). Dynamic taxonomies can be used to explore the infobase in several ways. Usually, the user is initially presented with a tree representation of the initial taxonomy for the entire infobase (the universe). Each concept label has also a count of all the items classified under it (i.e. the cardinality of items(C) for all C’s). The initial user focus F is the universe. In the simplest case, the user can then select a concept C in the taxonomy and zoom over it. The zoom operation changes the current state in two ways. First, concept C is used to refine the current focus F, which becomes F∩items(C). Items not in the focus are discarded. Second, the tree representation of the taxonomy is modified in order to summarize the new focus. All the concepts related to F are retained and the count for each retained concept C’ is updated to reflect the number of items in the focus F that are classified under C’. Concepts not related to F are either discarded from the taxonomy or shown as non-selectable (e.g. grayed). The reduced taxonomy is a conceptual summary of the set of items identified by F, exactly in the same way as the original taxonomy was a conceptual summary of the universe. The term dynamic taxonomy is used to stress the fact that the taxonomy adapts to the current user focus.
The retrieval process can then be seen as an iterative thinning of the information base: the user selects a focus, which restricts (thins out) the information base by discarding all the items not in the current focus. Only the concepts used to classify the items in the focus (and their ancestors) are retained. These concepts, which summarize the current focus, are those and only those concepts that can be used for further refinements. From the human computer interaction point of view, the user is effectively guided to reach his goal, by a clear and consistent listing of all possible alternatives (guided search). Most importantly, the same overall structure is used at each stage, and this prevents user disorientation.
Example Figures 2 to 6 show how the zoom operation works. Figure 2 shows a dynamic taxonomy: the upper half represents the intension with circles representing concepts; the lower half is the extension, and items are represented by rectangles. Arcs going down represent subsumptions; arcs going up represent classifications. In order to compute all the concepts related to H, we first find, in Figure 3, all the items classified under H (i.e., the deep extension of H, items(H)) by following all the arcs incident to H (and, in general, its descendants): items(H)={ b, c, d }. All the items not in the deep extension of H (Figure 4) are removed from the extension. In Figure 5, the set of all the concepts under which the items in items(H) are classified, B(H), is found by following all the arcs leaving each element in the set: B(H)={ F, G, H, I }. The inclusion constraint implied by subsumption states that if C’ is a descendant of C in the taxonomy, items(C’) ⊆ items(C). Equivalently, an item classified under C’ is also classified under C. Hence, the set of concepts related to H is given by B(H) union all the ancestors of all the concepts in B(H), i.e. the set of all concepts related to H is {F, G, H, I, B, C, A}. Finally, in Figure 6, all the concepts not related to H are
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Figure 2. A dynamic taxonomy: the intension is above, the extension below. Arrows going down denote subsumptions, going up classification
Figure 3. Focusing on concept H: finding all the items classified under H
Figure 4. All the items not classified under H are removed
removed from the intension, thus producing a reduced taxonomy that fully describes all and only the items in the current focus. A visual interaction example is provided in the following.
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Figure 5. All the concepts under which the items in the focus are classified (and, because of subsumptions, their ancestors) are related to H.
Figure 6. The reduced taxonomy: all concepts not related to the current focus are pruned
Benefits of Dynamic Taxonomies As explained before, there is the need to identify potentially interesting individuals and organizations before proceeding to a more complete competence assessment. Within the Social-CRAI model, the proposed framework uses dynamic taxonomies for identifying potentially interesting individuals and organizations. User access to the diverse types of information required by competence management is often implemented by different technologies, including information retrieval and structured databases (usually, relational databases) managed through relational queries. The use of different access paradigms makes interaction more difficult for user, and the construction and maintenance of competence management applications costly
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and complex. Most importantly, paradigms for exact retrieval are not appropriate in this context, because users do not know exactly what they are looking for and need to explore the infobase in order to find persons that best fit different requirements. Exploratory search models such as dynamic taxonomies should be used instead. Here, we discuss the advantages of dynamic taxonomies with respect to traditional techniques. Major areas include human factors and effectiveness of interaction, convergence of exploratory patterns, schema and system design and application maintenance. Dynamic taxonomies require a very light theoretical background: namely, the concept of a taxonomic organization and the zoom operation, which seems to be very quickly understood by end-users. Usability tests on a corpus of art images (Yee et al., 2003) show a significantly better recall than access through text retrieval and, perhaps more importantly, the feeling that one has actually considered all the alternatives in reaching a result. Although there currently is no extensive human factor experimentation, the widespread adoption of dynamic taxonomy systems by all major e-commerce portals gives empirical evidence that benefits in interaction are so significant as to warrant the expensive restructuring of wellestablished portals. Benefits include: •
•
•
•
A simple and familiar interface (the only new operation is the Zoom, which is easily understood); Transparent, user-centric interaction: users are in charge and easily understand the consequences of their actions; The user is effectively guided to reach his goal: at each stage he has a complete list of all related concepts (i.e. a complete taxonomic summary of his current focus); Completely symmetric interaction: if A and B are related, the user will find B if he zooms on A, and A if he zooms on B (many systems are asymmetric);
•
Easy integration with other retrieval methods, such as text retrieval.
According to Yee et al. (2003), users feel that interaction is faster with respect to traditional search methods. Sacco (2006) shows that this is not just a psychological feeling, as the convergence of exploratory patterns is extremely fast in dynamic taxonomies: under reasonable assumptions, three zoom operations on terminal concepts are sufficient to reduce an information base of up to ten million items, described by a compact taxonomy with 1,000 concepts, to an average 10 items. Dynamic taxonomies cleanly separate the process of classifying items from the use of the classification information in the browsing system, and considerably simplify the design of the conceptual taxonomy. First, dynamic taxonomies actually perform concept association mining. This simplifies taxonomy creation and maintenance since concept associations, which are often quite dynamic in time, need not be forecasted and accounted for in schema design. At the same time, the user is presented with associations the schema designer might not even be aware of. In traditional approaches, only the relationships explicitly described in the conceptual schema will be available to the user for browsing and retrieval, so that all of them must be anticipated: a very difficult if not helpless task, especially in competence management applications. In summary, the schema required is a minimalist one that only accounts for subsumptions. The simplifying effect of the extensional inference rule carries over to schema evolution and maintenance, because changes occurring in the extension are immediately reflected in the dynamic schema. Second, since dynamic taxonomies synthesize compound concepts, these need usually not be represented explicitly. Sacco (Sacco, 2000; Sacco & Tzitzikas, 2009) developed a number of guidelines that produce taxonomies that are compact and easily understood by users. Some of these guidelines are similar to the faceted
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classification scheme by Ranganathan, at least in its basic form: the taxonomy is organized as a set of independent, “orthogonal” subtaxonomies (facets or perspectives) to be used to describe data. As an example, a compound concept such as IT in Northern Italy need not be accounted for, because it can be synthesized from its component concepts: Sector>IT and Location>Northern Italy. Thus, one of the main causes of complexity in the design of comprehensive taxonomies is avoided: by synthesizing concepts, we avoid the exponential growth due to the description of all the possible concept combinations, and the resulting taxonomy is significantly more compact and easier to understand. In addition to minimizing the concepts in the taxonomy, breaking compound concepts into their base components allows the user to easily correlate concepts and explore such correlations. In the example, the user focusing on Sector>IT will immediately find all the relevant Locations related to Information Technology (which include Northern Italy). If compound concepts are used, correlation requires the manual inspection of labels. In addition, the excellent convergence of dynamic taxonomies allows the designer to define taxonomies that are much simpler and smaller than traditional ones. Concepts are not terms that documents must contain, but just labels that denote a set of abstract items/resources. This distinction is extremely important in separating the way items are classified and allows to dispense with well-known problems such as polysemy, to deal with any type of items (text, video, etc.), and finally to easily support multilingual access to information, a feature that is extremely important for transnational applications. In fact, concepts as defined in dynamic taxonomies are language-independent: changing the language simply requires changing the concept labels. Dynamic taxonomies support personalization and push strategies. In both cases, they can be implemented by using boolean expressions on the concepts in the taxonomy. In the case of personalization, such an expression defines a
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user profile and can be automatically added to user queries. This will be considered as the initial context or focus, instead of the universe: when the initial reduced taxonomy is presented, only the concepts under which there are items satisfying the current profile are preserved. This same user profile (or multiple versions of it) can be used to implement push strategies, since it provides an accurate statement of interests. In this way, the system acts in a proactive way and informs the user whenever new relevant material is available. This is an important feature in competence management, where searches for specific competencies can span relatively long periods of time. We contend that dynamic taxonomies organized by facets provide the ideal middle ground between the conflicting issues of adaptability, structuring and abstract reasoning. As we have shown above, even simple dynamic taxonomies allow a significant speedup in exploring the information base and locating information. Such a lightweight semantic structuring supports abstraction and avoids ambiguities. The taxonomic structure allows to explore potential competencies (but also locations, or salary ranges) at different level of abstraction, and easily accommodates specific semantic dimensions such as length of connection paths to a candidate, endorsements, etc. Most importantly, dynamic taxonomies can be seamlessly integrated with text retrieval, tag clouds and geographic maps (Sacco & Tzitzikas, 2009), allowing considerable freedom in the definition of the taxonomy but also different visualization and search strategies. Access to unstructured curriculum texts via information retrieval or tag clouds combined with dynamic taxonomies allows the practical implementation of competence management systems. Solutions based on access to unstructured text only do not provide the abstraction capabilities required by competence applications. At the other end, solutions based on ontologies, though inherently providing abstraction capabilities, require that all information be described by the ontology, which is unrealistic except for very
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limited domains. Finally, neither approach supports exploration, which is a fundamental feature for effective competence management. Sacco (Sacco, 2008) presents extensions to dynamic taxonomies that support statistical data mining capabilities and trend analysis. Although these extensions are not discussed here, they can be used to support strategic competence analysis and planning and are extremely relevant for a number of important applications. For instance, they simplify worker orientation by showing which competencies are currently significantly “hot” in certain geographic areas, or which competencies are significantly associated to higher salaries. Statistical trend analysis allows to plan public or private education offerings in response to shifts in demand.
A COMPLETE EXAMPLE The following example shows a full interaction searching for IT candidates on a real competence infobase. We show how the integration of information retrieval capabilities solves practical problems, and how different interactions and
interfaces can be used. The reader is referred to (Sacco & Tzitzikas, 2009) for a thorough discussion of interaction issues. In Figure 7, the highest levels of the taxonomy for the application are shown. On the upper right side, a text box allows full-text search on the infobase in an integrated way. We open the “Last work sector” concept, and select the “Information technology/internet” concept. In the current simple interface, clicking on a concept AND’s it immediately with the current focus, initially the universe. Figure 8 shows the result, in which the “Salary” concept is expanded. We now enter a full-text query for “java”. Figure 9 shows that only 134 candidates out of the 2953 in IT are retained. In a brittle ontology-based approach, a “java” concept would be required in the ontology. This considerably adds to the complexity of the ontology, both from the design and the navigation point of view. On the other hand, if the concept is not defined, it does not “exists” and is therefore not selectable. Here instead, we combine information retrieval with dynamic taxonomies in a natural way, with the benefit of a much simpler conceptual structure and extremely quick adaptation to new competencies. Note that only two interactions were sufficient
Figure 7. The initial infobase
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Figure 8. Zooming IT/Internet as last work
Figure 9. Preparing to search for java on full-text
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Figure 10. Preparing to zoom on a range of salaries
to reduce 60,000 candidates to 134. In Figure 10, we switched to the advanced interface, which allows to select the OR of several concepts for inclusion in the current focus. Here, we are selecting the 80 candidates in the salary range 15-40,000 euro.
CONCLUSION The chapter provides insights on competence management and on one specific competence model that has been developed since 2000 and currently extended in order to account for information conveyed throughout and by social networks. The proposed extensions (forming Social-CRAI model) allow building (or aligning) automated competence management systems that exploit social networks information for competence assessment and competence acquisition processes. However, the deployment of the Social-CRAI model requires the solution of a number of technical and conceptual challenges. First, producing accurate and reliable competence information is not so easy and assessment resources (interac-
tive or based on data extraction) should be carefully designed and relevant technologies should be identified. However, we have shown that dynamic taxonomies can be helpful for identifying potentially interesting candidates before going deeper in any competence assessment or acquisition process. From this point of view, the progressive conceptual refinement provided by dynamic taxonomies plays a very important role in making such a selection as fast and as natural as possible. Tag clouds and their integration in the accompanying implementation framework provide exploration capabilities on unstructured documents, and consequently decrease the complexity of the dynamic taxonomy. Second, acquisition processes cannot be only based on competences but additional criteria and technologies are required. Social-CRAI carefully distinguishes between competence related information and other types of information (such as salary). In the accompanying implementation framework, the integration of geographic maps with the dynamic taxonomy provides selections and summaries by geographic areas, which are extremely important capabilities in web-based
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recruiting. However, Social-CRAI does not provide all the elements for making final decisions and running competence acquisition processes (e.g. who should be recruited/trained but also acquisition through “day by day work experience or learning by doing”). The integration of these elements with Social-CRAI remains an open and challenging research topic.
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Lucia, A. D., & Lepsinger, R. (1999). The art and science of competency: Pinpointing critical success factors in organizations, (hardcover edition). Marreli, A. F. (1998). An introduction to competency analysis and modeling. Improvement, 37(5), 8–17. doi:10.1002/pfi.4140370505 Sacco, G. M. (2000). Dynamic taxonomies: A model for large information bases. IEEE Transactions on Knowledge and Data Engineering, 12(2), 468–479. doi:10.1109/69.846296 Sacco, G. M. (2006). Analysis and validation of information access through mono, multidimensional and dynamic taxonomies. FQAS 2006, 7th International Conference on Flexible Query Answering Systems, Springer LNAI 4027.
Tarassov, V., Sandkuhl, K., & Henoch, B. (2006). Using ontologies for representation of individual and enterprise competence models. International Conference on Research, Innovation and Vision for the Future, (pp. 206–213). Unified Modeling Language. (2010). Superstructure, version 2.1.2. Retrieved from www.omg.org Upadhyaya, S. R., & Kumar, P. S. (2005). ERONTO: A tool for extracting ontologies from extended E/R diagrams. In Proceedings of 20th ACM Symposium on Applied Computing (SAC, DTTA Track), Santa Fe, New Mexico. Vernadat, F. B. (1996). Enterprise modelling and integration - Principles and applications. Chapman and Hall.
Sacco, G. M. (2008). DT-miner: Data mining for the people. 2nd Int. Workshop on Dynamic Taxonomies and Faceted Search (pp. 387-391). IEEE Press.
Yee, K.-P., et al. (2003). Faceted metadata for image search and browsing. Proc. CHI 2003.
Sacco, G. M., & Tzitzikas, Y. (Eds.). (2009). Dynamic taxonomies and faceted search – Theory, practice and experience, information retrieval series (Vol. 25). Springer.
ADDITIONAL READING
Sampson, D., & Fytros, D. (2008). Competence models in technology-enhanced competencebased learning. In H. H. Adelsberger, Kinshuk, J. M. Pawlowski & D. Sampson (Eds.), Handbook on Information Technologies for education and training, (pp. 155-174). Sitthisak, O., Gilbert, L., Davis, H. C., & Gobbi, M. (2007). Adapting health care competencies to a formal competency model. Seventh IEEE International Conference on Advanced Learning Technologies (ICALT 2007). Spaccapietra, S., Parent, C., Vangenot, C., & Cullot, N. (2004). On using conceptual modeling for ontologies. WISE Workshops.
Becerra, I. (2000). The role of artificial intelligence technologies in the implementation of people-finder knowledge management systems. In: Proceedings of the Bringing Knowledge to Business Processes Workshop, AAAI Spring Symposium Series. Stanford, USA. Biesalski, E. (2003). Knowledge management and e-human resource management. In Proceedings of FGWM 2003: Workshop on Knowledge and Experience Management, Karlsruhe, October 6 - 8, 2003. Garro, A., & Palopoli, L. (2003). An XML MultiAgent System for e-Learning and Skill Management. In Agent Technologies, Infrastructures, Tools, and Applications for E-Services, LNAI 2592. SpringerVerlag. doi:10.1007/3-540-36559-1_21 Levy-Leboyer, C. (1996). Evaluation du personnel: quelles methodes choisir?Paris, France: Les Editions d’Organisation.
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Ley, T., & Albert, D. (2003). Identifying employee competencies in dynamic work domains: methodological considerations and a case. Journal of Universal Computer Science, 9(12), 1500–1518. Lindgren, R., Stenmark, D., & Ljungberg, J. (2003). Rethinking competence systems for knowledge-based organisations. European Journal of Information Systems, 12(1), 18–29. doi:10.1057/palgrave.ejis.3000442 McDonald, D. W., & Ackerman, M. S. (2000). Expertise Recommender: a Flexible Recommendation System and Architecture. CSCW 2000, Proceeding of the ACM 2000 Conference on Computer Supported Cooperative Work, Philadelphia, USA; 231-240. Sure, Y., Maedche, A., & Staab, S. (2000). Leveraging Corporate Skill Knowledge: From ProPer to OntoProPer. In Proceedings of the Third International Conference on Practical Aspects of Knowledge Management, Basel, Switzerland Vasconcelos, J. B., Kimble, C., & Rocha, A. (2003). Ontologies and the Dynamics of Organisational Environments. An example of a Group Memory System for the Management of Group Competencies. The 3rd International Conference on Knowledge Management, Graz, Austria.
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KEY TERMS AND DEFINITIONS Competence: The effect of combining and enabling operational use of c-resources (i.e. knowledge, know-how, and behaviors) in a given context to achieve an objective or fulfill a specified mission. Competence Management: The way organizations manage the competences of the corporation, the groups and the individuals. Its primary objective is to define, and continuously maintain competencies, according to the objectives of the corporation. C-Resource: A simple ability, knowledge, skill etc. (categorized as knowledge, know-how or behavior in CRAI) that contributes to a competence. Dynamic Taxonomy Search: An integrated visual environment for retrieval and guided exploration, based on a multidimensional taxonomy. Ontology: an explicit specification of a shared conceptualization.
ENDNOTE 1
It seems that in the latest versions (3.0 and 3.1) the definition of competence (named competency) has been changed to the IEEE Reusable Competency Definition; however, the status of the change is “provisional” so that it is unclear if this is finally accepted or still discussed. In this paper, therefore, we refer mainly to older versions.
Section 2
Business Implications of KM 2.0
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Chapter 7
Knowledge Sharing in the Age of Web 2.0: A Social Capital Perspective François Deltour LEMNA Research Center, France Loïc Plé LEMNA Research Center, France Caroline Sargis Roussel LEMNA Research Center, France
ABSTRACT Web 2.0 tools are more and more prevalent in organizational life, and this chapter identifies their multiple influences on knowledge sharing practices, as well as the main challenges of the social turn in knowledge sharing. Indeed, it is argued that social capital, a key concept from social sciences that recognizes the benefits practice derived from connections between people, also plays a role in the context of renewed knowledge sharing practices (i.e. based on Web 2.0 technologies). Therefore, this chapter provides an analysis of the influence of social capital in leveraging knowledge sharing in a Web 2.0 context. Finally, using secondary data, this research details a specific case to illustrate how employees can benefit from new forms of knowledge sharing that rely on interactive tools and their social capital.
INTRODUCTION Knowledge Management (KM) has become of paramount importance for most companies as they progress from the industrial to the informational age. Growing interest in KM resulted from both the conceptualization of knowledge as a source DOI: 10.4018/978-1-61350-195-5.ch007
of competitive advantage and the evolution of information systems during the 1990s. Accordingly, KM has progressed through several development phases, overcome several barriers, and arrived at using Web 2.0 tools that reflect the evolution of Information and Communication Technologies (ICT). Knowledge management encompasses several processes, including knowledge creation, diffusion, and integration, though knowledge
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sharing appears particularly relevant and critical to strategic aspects of business life such as project management, innovation or new product development. In a context of technological evolution, knowledge sharing also confronts several challenges: The tricky part isn’t creating web sites to bridge distance and time zones, though they help, but finding ways to motivate proud, skilled professionals to share expertise and to cooperate to advance the frontiers of knowledge for the benefit of the shareholders and society (Wessel, 2005). That is, knowledge sharing is a matter of both technological tools and human interactions. Thus, the notion of social capital has emerged as a promising concept to understand knowledge sharing practices. This chapter aims to understand how social capital influences knowledge sharing in a Web 2.0 context and to analyze interactions between social capital and Web 2.0 tools as means to leverage knowledge sharing. Accordingly, the first part of this chapter is dedicated to defining and gaining an understanding of knowledge sharing 2.0 (i.e. knowledge sharing in a Web 2.0 environment). Then, we define social capital and propose that it could be useful as a means to understand knowledge sharing practices based on Web 2.0 tools. Finally, we illustrate our findings with the experience of a French firm, Schlumberger. Thus we derive main issues, managerial implications, and direction for further research from our findings.
RENEWING KNOWLEDGE SHARING THROUGH WEB 2.0 TOOLS The Stakes of Knowledge Sharing Knowledge distribution across space and time is crucial to ensure the value and development of firms’ activities. Such a distribution of knowledge
is possible through knowledge sharing within companies, defined as the idea that: Knowledge, no matter how intangible or fuzzy, is capable of being disseminated, transferred, diffused, shared and distributed within and between organization, communities of practices and departments (Kalling & Styhre, 2003, p.57).
The Importance of Knowledge Sharing The results from OECD surveys in Canada, Denmark, and Germany show that the primary goal and motivation for implementing knowledge management practices is to facilitate knowledge sharing. For example, 91% of German companies claimed to use knowledge management because they expected to speed up and improve their knowledge transfer. Other benefits included avoiding the same mistakes and preventing the reinvention of the wheel (OECD [2004]). Knowledge sharing largely depends on the intrinsic characteristics of the focal knowledge, such as its level of codifiability, degree of dispersion, contextualization, and accuracy. Codifiable knowledge may be explicit or tacit, though tacit knowledge is more than difficult to transfer. More explicit knowledge is easier for people to share or diffuse. By its very nature, knowledge is distributed across the organization, so knowledge sharing must overcome scattering and knowledge managers must develop tools to share knowledge in an efficient manner. Despite its benefits, knowledge sharing is often one of the most difficult steps to achieve in knowledge management, due to its stickiness (Szulanski, 1996, 2000) or given its embeddedness within individuals or contexts. The role of information systems as means to overcome the difficulties in achieving knowledge sharing is evident (e.g. MIS Quarterly, Special Issue on Information Technologies and Knowledge Management, vol. 29, n°2, 2005). Many organizations have implemented ICT to
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provide technical support for knowledge sharing (Davenport & Prusak, 1998). Yet the use of ICT in knowledge sharing remains controversial because such support may not be obvious, and even might be counterproductive (McDermott, 1999; Kaiser et al., 2009). In particular, ICT can neither convince nor oblige employees to share their knowledge or decrease their reluctance to do so. Another controversy is rooted in users’ assessment of knowledge sharing systems. Despite their popular diffusion among companies, users often express their dissatisfaction with such tools compared with other management tools, such as the ones related to customer relationship management (Rigby & Bilodeau, 2007). For example, with the first generation of technological tools, users could access huge databases, gather data, and develop their knowledge, but they could not directly or collaboratively interact in a knowledge sharing process. Stated otherwise, Web 1.0 was about publishing, not participating.
Technological Evolutions and New Expectations The shift from Web 1.0 to new collaborative tools based on Web 2.0 technologies has been significant (see O’Reilly, 2007). Web 2.0 can be defined as web that facilitates interactive information sharing, interoperability, user-centered design, and collaboration on the World Wide Web. A Web 2.0 site allows its users to interact with each other as contributors to the website’s content, in contrast to websites where users are limited to the passive viewing of information that is provided to them. Examples of Web 2.0 include web-based communities, hosted services, web applications, social-networking sites, videosharing sites, wikis, blogs and folksonomies (Web 2.0, 2010).
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We extend this list to include semantic widgets, tags, RSS flows, etc. Thus, Web 2.0 represents the business revolution in the computer industry caused by the move to the internet as platform, and an attempt to understand the rules for success on that new platform. Chief among those rules is this: Build applications that harness network effects to get better the more people use them (Musser and O’Reilly, 2006, quoted byLevy 2009, p.121). Web 2.0 is centered on users and allows them to participate directly and actively. These tools thus offer more decentralization, more transparency, and a global orientation toward social dimensions: Users add value through their collaboration. Because the tools are more flexible, easier to use, and more user-friendly, they might help reconcile knowledge users with available tools for sharing knowledge. The people using these tools also have changed; for example, so-called Generation Y workers grew up with the Internet. Therefore, knowledge sharing tools need to offer personalization and more dynamic approaches to appeal to these young workers. The management of knowledge sharing in turn entails the management of both knowledge per se and the context of knowledge (which refers to the concept of Ba from Nonaka et al., 1996), as characterized by the social network. Web 2.0 tools are useful for sharing explicit knowledge through collaborative technologies such as wikis, blogs, intranets, and so on. Moreover, they aid tacit knowledge sharing by supporting group work, communities of practice, or face-to-face collaborative work (Table 1). Web 2.0 tools seem to provide useful support in diffusing and sharing knowledge, though some contingencies demand questioning, in that the objective is not to eliminate former knowledge sharing tools but rather to improve their function-
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Table 1. Benefits of knowledge sharing 2.0 tools: A user’s perspective Increased speed of access to knowledge
68%
Reduced communication costs
54%
Increased speed of access to internal experts
43%
Decreased travel costs
40%
Increased employee satisfaction
35%
Reduced operational costs
32%
Source: Bughin et al. (2009)
alities through the use of technological progress, exemplified by Web 2.0. The degree of maturity of knowledge sharing practices also may be key, because knowledge sharing depends on organizational variables such as the implementation process, the nature of work, previous experience with KM, and the organizational culture. Finally, the issue of how to assimilate knowledge based on Web 2.0 tools remains unresolved. Organizations must be aware of the buzz effect and carefully manage both mimetic phenomena and the change invoked by these new tools.
The Mutation of Knowledge Sharing: Towards Knowledge Sharing 2.0 The aforementioned features of Web 2.0 tools have led to several mutations in knowledge sharing practices, as listed in Table 2 and discussed next.
Table 2. The shift from knowledge sharing 1.0 to knowledge sharing 2.0 1. Change in the scope of knowledge sharing 2. Evolution of the knowledge manager role 3. Modification in knowledge structures 4. Modification of knowledge validity and accuracy 5. Evolution of the nature of knowledge sharing 6. Change in the role and perception of knowledge sharing tools 7. Modification of the temporality of knowledge projects
1. The scope of knowledge sharing is changing. Originally, knowledge sharing practices were implemented in a top-down approach. The use of Web 2.0 tools has changed this approach; they favor not only a bottom-up process but also transversal and interdisciplinary communication, including the emergence of collective forums, the development of communities of practice. People who use Web 2.0 tools in their daily lives can capitalize on this knowledge and transfer it to professional spheres. 2. The role of the knowledge manager is evolving, from content manager to community or connection manager. A community manager facilitates links between people and creates the community of knowledge workers. The knowledge manager also trains people in the use of knowledge sharing tools. Then, it is legitimate to wonder who leads a knowledge sharing 2.0 initiative: stakeholders, the CEO, knowledge managers, or users? 3. In modified knowledge structures, the useful life of knowledge is shorter and may even be superficial. Its organization is not hierarchical and appears independent from the company’s organizational chart. Web 2.0 tools should help to open knowledge sharing to different services and functions and emphasize collective knowledge. 4. Whereas previously a knowledge manager ensured the validity, accuracy and update of knowledge databases, Web 2.0 allows the knowledge shared within a community to be validated directly by users. Therefore, this process is managed directly by the users of the knowledge. 5. The nature of knowledge sharing is changing. Whereas first-generation knowledge sharing projects aimed to formalize knowledge and make it available to the largest number of users through databases, knowledge sharing 2.0 organizes around communities, driven by a common interest. Networking is as im-
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portant as content management. New waves of knowledge sharing focus on users, not on their processes or activities. 6. New roles and perceptions have emerged for knowledge sharing tools, whose usage is more important than the technology. The Web 2.0 tools are more user-friendly and allow for greater participation and interaction. That is, the objective is not just to increment a database but to create social links. Weblogging is fun, partly because it is not technical challenging and partly because the process invigorates people (Kaiser et al., 2009, p.123).
7. The new temporality of knowledge sharing projects means that the long process of implementation and huge investments that marked previous efforts related to knowledge sharing have been replaced by Web 2.0 tools that speed up the process and offer a cheaper technical solution. Therefore, the arrival of Web 2.0 tools represents an important milestone in the evolution of knowledge sharing practices. It marks the shift from a logic of content management to a logic of networking management (Bessard, 2010). However, major risks also emerge with these tools, which are more user-friendly, easier to use, and more familiar, such that they could elide the goal of knowledge sharing practices. Knowledge sharing in a Web 2.0 context thus must ensure a sufficient level of quality control with regard to knowledge accuracy and reliability. Actually, the content is often generated by the most enthusiastic users, not the most experienced. Therefore, knowledge communities require careful usage and automatic regulation, though most rules and norms are produced by the users themselves. It can be difficult to find the right balance between the technological and social perspectives of knowledge sharing, and
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knowledge sharing might suffer from too much trust in technical tools (McDermott, 1999). In this scenario, social relations become increasingly important for knowledge sharing issues. Boughzala (2008) notes that knowledge communities represent key resources for modern companies, and that such communities are supported mainly by social capital through its structural, relational and cognitive dimensions. In addition, the motivation to share knowledge is a critical factor for the successful implementation of ICTs in knowledge sharing (Ardichvili et al., 2003; Kaiser et al., 2009). Such motivation could depend on the features of the people engaged in the activities (e.g., age, culture, social status), on their sense of belonging to a community, or on potential enhancement of their reputation among peers. We propose that Web 2.0 tools, no matter how useful they may seem for knowledge sharing on their own, need to be supported and reinforced by social capital.
RETHINKING KNOWLEDGE SHARING 2.0 IN TERMS OF SOCIAL CAPITAL Social Capital Theory, a Focus on Social Networks in Organizations The concept of social capital has been well developed and widely mobilized. Historically, anthropologists used it to study the nuclear family, individuals in social communities, or collective action. It also is popular among sociologists and economists. Four illustrations of social capital in social sciences: a. On the wholesale diamond market of New York, strong social ties permit high levels of trust among merchants, making expensive security measures unnecessary.
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b. Korean students’ activism and clandestine “study circles” in the 1980s reflected their hometown or church ties, which created an extra layer of trust. c. The increased feeling of security among parents in Jerusalem, compared with those in any U.S. city, is a consequence of the social norm that people watch out for one another’s children. d. A complex system of reciprocity and obligations among merchants in the Kahn El Khalili market in Cairo is based on proprietorship and family stability. (Coleman [1988]). Organizational behavior and business contexts also have become significant fields of study focused on social capital. Batt (2008) summarizes its emergence as an important theoretical framework in management: Bourdieu (1986) explored the concept of social capital in discussing social interactions, while Granovetter (1985) identified the role of social capital within embedded social networks. However, it was the work of Coleman (1990) and Putnam (1995) who are most responsible for the renewed interest in social capital as a means to moderate the behavior of individuals within society and exchange transactions (Batt, 2008, p.487). Management literature also has started to apply this concept to achieve several different purposes. For example, social capital is associated with existing management topics, such as value delivery (Adler & Kwon 2002), firm performance (Batjargal, 2003), entrepreneurial network growth (Liao & Welsch, 2003), or intellectual capital and learning (Nahapiet & Ghoshal, 1998). Social capital can support innovative activity at an organizational level (Kaasa, 2009) or influence strategic choice (Houghton et al., 2009), and contribute to buyer performance at the individual level (Lawson et al., 2008). Accordingly, it is regarded more and more as a requisite precondition of ef-
fective organizational behavior, such that it “acts as the fluid that enables the knowledge-intensive organization” (Kianto & Waajakoski, 2010, p.5).
Defining Social Capital Adler and Kwon (2002) review social capital literature and find no single, widely accepted definition. They consider it: The goodwill available to individuals or groups. Its source lies in the structure and content of the actor’s social relations. Its effects flow from the information, influence and solidarity it makes available to the actor (Adler & Kwon, 2002, p.23). Nahapiet and Ghoshal (1998) define social capital as: The sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit (Nahapiet & Ghoshal, 1998, p.243). Therefore, social capital includes both the network and the outcomes it generates. Kianto and Waajakoski (2010, p.6) indicate that “social capital deals with how whom we know benefits what we do,” such that they distinguish social capital from other forms of capital because it requires maintenance (interpersonal connections can deteriorate), does not depreciate with use (but rather is often strengthened by use), is a jointly owned resource, and offers consequences that can be analyzed as either positive or negative.
Three Dimensions of Social Capital Nahapiet and Ghoshal (1998) provided a key step forward in the empirical study of social capital when they conceptualized it as a multidimensional construct with three distinct and complementary dimensions: structural, cognitive, and relational.
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They thus offer a conclusive operationalization of the concept and demonstrate its relevance in understanding knowledge sharing.
facilitates individual and collective actions and common understanding of proper actions and collective goals (Yang and Farn, 2009, p.211).
•
We adopt this multidimensional construct when further studying the relations between social capital and knowledge sharing.
The structural dimension refers to connections between actors, their links, their network, and the density and hierarchical nature of that structure.
Structural social capital can be conceptualized as the overall pattern of relationships among social actors (Yang & Farn, 2009, p.211).
•
The relational dimension describes the types of relationships among people, which can be characterized by trust or respect, that is expected behaviors.
Relational dimension is associated with building trust; developing norms for interaction; setting expectations and obligations of its members; and creating a distinctive identity of the community with which members associate (Sherif et al., 2006, p.797).
•
Finally, the cognitive dimension refers to resources such as shared representation and interpretation, and a common language among people. Interactions facilitate the development of a common sensemaking (with a shared language for example), which prompts Yang and Farn (2009) to define cognitive social capital:
Cognitive social capital is the common understanding among social actors through shared language and narratives. It is embodied in attributes such as shared vision or shared value that
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Social Capital and the Challenges of Knowledge Sharing 2.0 Knowledge sharing and social capital have much in common, beginning with their reliance on people’s ties, people’s motivations, and community thinking. Several empirical investigations consider the influence of social capital on knowledge sharing (for a review, see Chow and Chan, 2008). With rare exceptions, proof of the positive relationship between social capital and knowledge sharing relies on qualitative or quantitative methods, in multiple contexts such as managerial work (Chow & Chan, 2008) or virtual communities (Chiu et al., 2006). Cabrera and Cabrera (2005) also explain how the three dimensions of social capital help leverage knowledge sharing. They hold that: The structural and cognitive dimensions of social capital determine whether or not individuals have the opportunity to share their knowledge with others. The opportunity to share is increased when individuals spend more time together, not only because increased interaction leads to more frequent communication, but also because communication is more effective due to the fact that these interactions also result in a shared language and codes,” whereas the relational dimension of social capital “influences whether or not individuals have the motivation to share what they know with each others. Although the opportunity to share may exist, an individual may not be willing to share (Cabrera and Cabrera, 2005, p.722).
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Yet social capital also may be “a doubleedged sword, which can both facilitate and hinder knowledge sharing within a group” (Yang & Farn, 2009, p.216). For example, phenomena such as inertia in highly cohesive relations or corruption and in-group favoritism can decrease creativity and innovation (Kianto & Waajakoski, 2010). Several studies highlight that social capital may risk support for organizational routines, which inhibits knowledge creation (Edelman et al., 2004; Leonard-Barton, 1995). Most research suggests, however, that the advantages outweigh the disadvantages. Because Web 2.0 tools favor online interactive relationships and help renew knowledge practices, we explore the interplay between social capital and knowledge sharing 2.0. That is, the connections between “offline” social capital and “online” social networks appear obvious but actually require precise analysis. For example, social capital may help reduce cultural distance through its cognitive dimension, such that it can overcome a major barrier to online knowledge sharing within or outside companies. Thus, tools alone can’t help, but they must be exploited in a social context that can enable online behaviors.
The offline and online practices meld, as they are enacted by the same person. We propose to specifically analyze the role of social capital in knowledge sharing 2.0 through the lenses of the three dimensions of social capital: social, relational, and cognitive (Table 3). As Table 3 shows, social capital constitutes a lever for a more efficient knowledge sharing, even as the Web 2.0 tools foster each dimension of social capital to increase the influence in terms of knowledge access. Complementarily, the dimensions of social capital influence the renewal of knowledge sharing practices allowed by Web 2.0 tools. To study this influence, we now draw on the seven-step process used in the first part of this chapter to analyze the shift from knowledge sharing 1.0 to knowledge sharing 2.0 (see Table 2). 1. A change in the scope of knowledge sharing leads not only to bottom-up processes but also transversal communication. Such nonhierarchical knowledge sharing practices receive support from the structural dimension of social capital, which allows for multiple connections within and outside the
Table 3. Social capital dimensions, knowledge sharing, and knowledge sharing 2.0 Social perspective
Social perspective of knowledge sharing
Social perspective of knowledge sharing 2.0
Social capital
Social capital and the process of knowledge sharing
Social capital and the process of knowledge sharing using Web 2.0 tools
Structural dimension
Structural dimension of social capital describes the frequency of connections between people
€€Structural dimension grants opportunities to access knowledge
Web 2.0 tools provide more opportunities for connection and allow a greater influence of the structural dimension on knowledge sharing
Relational dimension
Relational dimension of social capital refers to the kind of link developed between people
€€Relational dimension creates a favorable environment to access knowledge
Web 2.0 tools enhance the favorable environment with richer links and allow a greater influence of the relational dimension on knowledge sharing
Cognitive dimension
Cognitive dimension of social capital is based on common representations shared by people
€€Cognitive dimension sustains social proximity to access knowledge
Web 2.0 tools support social proximity with a quicker actualization of representations and allow a greater influence of the cognitive dimension on knowledge sharing
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organization and overcome its internal and external borders. Kaiser et al. (2009) also note the issue of reciprocity, a key concern of the relational dimension of social capital: Webloggers who are more active, in terms of number of written posts and comments, are more likely to get significant assistance and support. To put it differently, one can assert [that] a high degree of reciprocity […] leads to the emergence of subgroups or clusters around specific knowledge topics and practices in the blogosphere (Kaiser et al.,2009, p.124).
2. The evolution of the role of the knowledge manager means a shift toward the emergence of a community manager. In this context, the knowledge manager uses social capital to support the effective existence of the community and mobilize the social capital of other members to enlarge or strengthen the community. The frequency of interactions among members (structural dimension) and the content and quality of those interactions (relational dimension) are key concerns for this new function. Social capital is also relevant for building a community identity (cognitive dimension). 3. Modifications in knowledge structures suggest the more diffuse circulation of information, such that Web 2.0 tools skip traditional flows of information. The structural dimension of social capital (i.e., connections with whom) can be mobilized to create new paths of information and knowledge. 4. Modifications of knowledge validity and accuracy imply self-validation by knowledge owners and users, not by database managers. This validation requires easy access to the appropriate users of the concerned knowledge. Social capital can help the community
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identify and reach the appropriate person much faster and with more efficacy than many formal or data computing tools. 5. The nature of knowledge sharing, which has moved from formalizing knowledge to the socialization of knowledge, means that accessing people is just as important as accessing databases. Social capital, an asset held by people or the group, encourages this shift, in which case the cognitive dimension is a pertinent issue, because it helps maintain weak links between people who share the same representations and values. These weak links can be mobilized online, thanks to social networking tools for example. 6. New arising perceptions of knowledge sharing tools imply that usage and interactions are more important than technology. Thus, when the technology becomes less visible and constraining for interactions, the social capital of technology users can be solicited and reused easily and naturally online. 7. Shorter knowledge sharing processes and faster time dimensions demand the accurate mobilization of resources at just the right moment, without delay. To avoid failures related to the non-involvement of the appropriate person or the failure to use proper knowledge, the three dimensions of social capital can dictate the correct conduct for knowledge sharing projects with Web 2.0 tools. That is, favoring connections gains time. These elements illustrate the idea that social capital is critical for renewing knowledge sharing practices through Web 2.0. We also note that Web 2.0 tools affect people’s social capital—whether related to organizational life or now—by facilitating and enlarging the opportunities for interactions (Ellison et al. 2007). Therefore, it seems that both social capital and Web 2.0 tools aid in the implementation of the effective appropriation of
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knowledge sharing systems by users and lead to more efficient knowledge sharing, as we illustrate with the following case.
SCHLUMBERGER: ENHANCING KNOWLEDGE SHARING 2.0 WITH SOCIAL Capital... and Vice Versa Schlumberger defines itself as: The world’s leading oilfield services company supplying technology, information solutions and integrated project management that optimize reservoir performance for customers working in the oil and gas industry (Schlumberger, 2010b). Its activity comprises two segments: Schlumberger Oilfield Services (petroleum-related) and Western Geco (world’s largest seismic company). As of March 2010, approximately 83,000 people of over 140 nationalities shared out between 80 countries worked for Schlumberger. At an operational level, the business is managed through 33 GeoMarket regions, grouped into four geographic areas (North America; Latin America; Europe, CIS & Africa; and Middle East & Asia), with activity shared between Products Centers and Research Centers. Similar to many firms, Schlumberger puts knowledge management at the heart of its strategy, such that it represents a major component of the firm’s culture. For example, Schlumberger won its fourth MAKE (Most Admired Knowledge Enterprises) Award in 2009, in the twelfth iteration of the award.
The Importance of Knowledge Sharing at Schlumberger From its very beginning, knowledge has been a core component of Schlumberger’s business: the two Schlumberger brothers who founded the firm
in 1926 “invented wireline logging as a technique for obtaining downhole data in oil and gas wells” (Schlumberger, 2010b). This focus has remained constant and strongly influenced the firm’s strategy and organization over the years. Despite sluggish economic conditions, its R&D investments in oilfield activities in 2009 reached $802 million. However, the launch of Schlumberger’s KM strategy in 1998 also initiated a huge reorganization of the firm, spanning from 1996 to 2000. Back then, Schlumberger reorganized in order to develop a knowledge sharing culture among employees, wherever they worked in the world, and in the firm (i.e., geographically and/or functionally). This reorganization aimed to improve customer satisfaction and business performance through shared, integrated knowledge among employees in their daily jobs. Prior to that period, Oilfield Services “operated largely as a series of semiautonomous, regional organizations in over 100 locations” (Schlumberger, 2004). Training and technological support were centralized and provided by an operational center in Houston, Texas, which used to slow communications and knowledge sharing. It also hindered the management and motivation of the firm’s geographically dispersed technical professionals. As a consequence, knowledge was not always available where and when it was needed, which impeded the firm’s global performance and reduced customer satisfaction. By restructuring the organization to create the GeoMarkets, the company replaced notions of separate locations (i.e. regions, countries, or even districts) and implemented a customer-focused organization, such that it replaced “product lines” with “customer segments” (Guillaume, 2001). These changes deeply altered employees’ working environment by making it easier for them to share and access knowledge (Guillaume, 2001). The restructuring also aligned Schlumberger’s organization with its KM strategy, as illustrated by the company’s internal definition of KM that has driven its KM strategy since 1998:
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Develop and deploy processes and technology to improve organizational performance and reduce costs for Schlumberger and its customers by enabling individuals to capture, share and apply their overall knowledge—in real time (Guillaume, 2001).
Early Adoption of Knowledge Sharing 2.0 Practices at Schlumberger
In 2002, Louis-Pierre Guillaume (the KM Business Manager at Schlumberger) even represented this strong relationship between knowledge sharing and the firm’s performance as: Power = Knowledgeshared, capturing the meaning of Schlumberger’s motto relative to KM: “Apply everywhere what you learn anywhere.” To reach these goals, Schlumberger set up, in late 1998, two new Web 2.0 complementary knowledge sharing tools (though this timing occurred five years before the first use of the expression, according to Web 2.0, 2010). From the beginning, both tools, called Eureka and InTouch, have primarily relied on direct social interactions among employees.
Initially launched at the end of the 1990s, Eureka aims to link more than 5,200 technical experts in virtual, transversal technical communities for Oilfield Services (Guillaume, 2001). The communities can include people who work in any GeoMarket, Product Center or Research Center, though some feature more focused interactive subgroups. Eureka’s overall philosophy, “Networking for Technical Excellence and Business Success” (Ferchaud, 2001), reflects its main goals and thus the resulting technical and organizational choices (Table 4). Table 4 highlights three noticeable features of Eureka. First, people are free to register with a community; it is not compulsory, and registration does not depend on experience, education, or title. They can access the Eureka Web site, participate in discussions, or merely observe online activities. To encourage interactions, Henry Edmundson,
Eureka: Virtual, Transversal, and Evolving Technical Online Communities
Table 4. Main goals and solutions for Eureka Main Goals
Resulting Technical and Organizational Solutions
• Increase the links between technical experts to improve business performance: €€€€€• Create virtual and transversal technical communities €€€€€• Increase personal motivation (through empowerment and teamwork) €€€€€• Improve knowledge sharing dynamics (thanks to networking, community creation, and storage of knowledge) • Find transversal solutions across multiple segments or services • Enable a long-term reflection on technology and operations to answer clients and R&D needs
• One Webspace per community: €€€€€• The charter and objectives of the community €€€€€• A shared calendar of events €€€€€• A bulletin board for discussion €€€€€• Files to download and interesting hyperlinks €€€€€• Leaders’ photos €€€€€• Recent additions: blogs, networking profile tools, and video sharing functionalities (technical and social videos) • Freedom of registration • Self-governing communities (elected leader) • Flexibility
Source: Adapted from Guillaume and Gibert (2003); Awad (2007); Andreev et al. (2010); Bessard (2010)
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who was in charge of creating and directing the technical communities, allowed users to post information about themselves. Given that the employees’ personnel files are locked by human resources on a secure Web site, he let them create their own online vitae. This has been an enormous success. As Edmundson explains, “It was the first time employees had been given a chance to stand up and say ‘this is who I am’” (Wessel, 2005). It worked so well that the whole company has embraced this practice. Second, the members of each community or subgroup democratically elect their leader (or leaders, depending on the size of the community), who manages and animates it for a year. Leaders cannot be elected more than twice and must “be backed by at least one other community member and by his or her manager, who [consents] to let the subordinate devote a chunk of time to the endeavor” (Wessel, 2005). According to Andrew Gould, Schlumberger’s current Chief Executive, this self-governing feature is crucial to Eureka’s success, because “technical professionals often are motivated by peer review and peer esteem.” Thus, elections by the community “ensure the integrity of peer judgment” and reinforce employees’ motivation and pride. John Afilaka and the Rock-Characterization Community Name: John Afilaka Function: Geological engineer, Schlumberger business development manager in Nigeria. September 2004: John runs for the leadership of the 1000-member rock-characterization community, which aimed to determine what might be in an underground reservoir. He campaigns “to increase technical professionals’influence on top management’s R&D priorities and to forge better links among various communities.” After winning, John
spent 15–20% of his time organizing and managing the community (e.g., setting up an annual conference, intermittent workshops, subgroup coordination). He proudly claims that his community “helped shape the research agenda of a new carbonate research facility in Saudi Arabia.” (Adapted from Wessel [2005]) Third, Eureka’s communities are flexible: they evolve, some new emerge, some disappear, while others merge. Edmundson (2001, p.21) describes them as “organic” and mentions: In one month, Mathematics appeared and now has 69 members. Nuclear separated from Physics, to be a community in its own right.” What’s more, “these changes occur democratically at the will of members (Edmundson, 2001, p.21). Eureka thus has been a tremendous success for Schlumberger. From October 2000 to the beginning of 2010 (Guillaume, 2001; APQC, 2010), the number of participants rose dramatically from 4,375 (68 leaders) to 25,000 (339 leaders), and the number of communities rose from 17 (no subcommunities) to 27 (127 subcommunities). Yet, its cost is relatively limited, since Schlumberger has spent about $1 million per year on it since its creation. According to Edmundson, “Compared with other knowledge initiatives, it’s a cheapie” (Wessel, 2005). Moreover, the Human Resources (HR) department of the firm also increasingly rely on Eureka (Awad, 2007), because it helps them track employees’ online activities and identify their participation in the communities (process), as well as the quantity and quality of their participation (frequency and content). The firm uses this knowledge to encourage certain employees to develop in specific ways and restructure some services and departments
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InTouch: Professional, Interactive Social Network Parallel to Eureka, Schlumberger developed another social and complementary knowledge management tool, called InTouch, which aims to diminish the waiting time between the emergence of an operational need or problem and a response from one of the firm’s technology centers (Table 5). Before InTouch, average delays ran from 2 to 16 weeks to get an answer to a technical question; 16 weeks to make engineering modifications; and 2 to 5 years to update archived material. Moreover, these processes relied on multiple data sources, which really complicated their consolidation (Guillaume, 2002). The long service gaps hindered operational performance, customer satisfaction, and knowledge sharing. Consequently, InTouch has been developed and nurtured to allow field engineers who encounter an operations problem and cannot find the answer in their local resources (e.g., manuals, CD-ROMs, local experts, the firm’s knowledge database) to contact dedicated engineers in technology centers. They can be contacted 24/7 (i.e. 24 hours a day, 7 days a week), as they literally “sleep with beepers and cell phones” (Susan Rosenbaum, Director of Knowledge Management; Schlumberger, 2010a). These InTouch engineers “have at least 5 years of field experience and are drawn from all the company’s product and domain segments” (Schlumberger, 2010a), so they can
provide help on diverse dimensions, such as improving a product or service or resolving technical problems. They also take charge of capturing and diffusing solutions, best practices, and conclusions from their interactions. Figure 1 depicts the whole InTouch process. This process has proven extremely reliable, encouraging the rapid acceptance of the tool. Thus, as of January 2010, InTouch was being used daily by 14,000 engineers on average, and knowledge sharing among the different divisions appeared in a minimum of 40,000 daily transactions. These transactions (as well those with Eureka) feed a huge knowledge database. An example of this would be the cataloguing of industry best practices. These are divided into three categories: “Good Idea,” “Local Best Practice” and “Schlumberger Best Practice.” After a thorough screening process, each practice is assigned a category, and information is provided for each entry: who performed the screening; the specifics of best practice; the breadth of its applicability; and systematic comments on its contents (Edmundson, 2001, pp.22-23). People can retrieve the information based on previous experiences very quickly and in an interactive way. Employees provide rich information about themselves, including their fields of interest and competences.
Table 5. Main goals and solutions for InTouch Main Goals • Improve the effectiveness, speed, and service quality improvements through operational support €€€€€• Activate an immediate solving-problem process €€€€€• Access with no delay to validated technical information about products and services €€€€€• Improve customer service • Capitalize immediately to share and reuse knowledge resulting from the InTouch social exchanges Source: Adapted from Guillaume and Gibert (2003)
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Resulting Technical and Organizational Solutions • Global network facilities (standard PC) • One unique portal to enter the technical resources knowledge base • More than 75 helpdesks, available 24/7 • One validated knowledge base • Interactive and distributed training • Constantly updated online materials
Knowledge Sharing in the Age of Web 2.0
Figure 1. An example of an entire InTouch process (adapted from Smith, 2004)
InTouch engineers use that information to identify people according to location, technical domain, level of expertise, and job type. This enables them to push pertinent information to a selected audience. If a piece of hardware needs a modification, for example, everyone who may be concerned by the change can be made aware of it (Schlumberger, 2010a).
•
Interplays between Social Capital and Knowledge Sharing 2.0 at Schlumberger
•
Despite their specificities, Eureka and InTouch share the same objectives of developing technical improvements, facilitating online interactive exchanges, and sharing best practices through Web 2.0 tools. They also affect knowledge sharing at Schlumberger in ways that reflect the shift from knowledge sharing 1.0 to knowledge sharing 2.0, which we analyzed in the first part of this chapter (see Table 2):
•
•
They have favored both a bottom-up process and transversal and interdisciplinary communication, and they have changed the information and knowledge structures (e.g., the very creation and structure of Eureka).
•
They changed the role of the firm’s knowledge manager to managing connections between people and training in the use of the tools (e.g. the case of John Afilaka). Shared knowledge is now directly validated by users, who sit at the heart of the whole knowledge management processes (e.g. Figure 1 that illustrates an InTouch process). The ease of use and the level of interaction of these technologies has favored their use, as shown by the dramatic growth in the use of both tools. The tools have changed the temporality of KM projects, saving time and money (discussed at the end of this section).
However, these tools alone would not have been sufficient to provoke such a shift; the Schlumberger example illustrates rather well that social capital and knowledge sharing 2.0 influence each other (see Table 3 in the second part of this chapter). The firm has relied on social capital to leverage this evolution, even as the online interactions between users influence the transformation of the three dimensions of social capital (Table 6): •
By aligning from the very start the conception and use of Web 2.0 tools with the structural dimension of social capital (i.e. 135
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Table 6. Mutual influence of social capital and Web 2.0 tools, resulting in an enhanced knowledge sharing process at Schlumberger Development and refinement of knowledge sharing thanks to Web 2.0 tools Social capital as a lever (enables and / or explains the need for the development of Web 2.0 tools)
Structural Dimension
Relational dimension
Cognitive dimension
• Internal reorganization (from products lines to segments, and from Regions / Countries / Districts to Geomarkets) and development of new tools due to the firm’s geographic dispersion • Slow communication between the operating regions • Very few “information and knowledge professionals” • Lack of direct connections between field and expert engineers → Delay between the moment a question is asked and an answer is provided • Centralization of training and technological support
• Reinforcement of the motivation of people to share their knowledge and reuse the one of others in their daily operations • Existence of a common interest between some employees (or groups of employees) in a body of knowledge • Need to develop reciprocity in the share practices
• Common technical culture across large communities of employees • Innovation-based culture • Knowledge management at the cornerstone of Schlumberger’s culture and success for 80 years
Time
Consequences for social capital (impact of Web 2.0 tools on social capital) • Easier access to people • Creation of 150 new positions (InTouch engineers, experts) offset by the suppression and restructuring of 200 positions of intermediate technical managers • Integration of knowledge sharing as a key competency on the employees’ performance appraisal form • Development of transversal relations within the firm • Election of communities’ leaders with multiple tasks (animation of the community, intermediary between managers and the community, etc.) • Growth in the number of exchanges/connections between experts and between field engineers and experts engineers • Identification, stimulation, and reward of desired behaviors in terms of knowledge production and sharing (e.g., delivery of a quarterly nonmonetary award to each of the geographic operating areas, chosen by the community and represented by a senior manager) • Acknowledgement of mutual competences between field and experts engineers • Increase in mutual confidence between field and experts engineers • Reinforcement of reciprocity through development of a compelling need to share problems, experiences, insights, templates, tools, and best practices • Better and faster learning that enables to develop shared frames of reference and languages (knowledge and discourses centered on the customer and on R&D) • Group/team spirit and identity of work communities • Development of a culture based on “solutions” and knowledge sharing
Sources: de Chizelle and Guillaume (2001), Guillaume (2001, 2002), Guillaume and Gibert (2003), Smith (2004), Martellozo (2009), Schlumberger (2004, 2010a).
•
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interacting actors, frequency of connection), Schlumberger enabled quicker and more transversal communications in a bottom-up process. This resulted in the multiplication of connections inside the organization, beyond geographical or functional boundaries, enabled and supported by the implementation of Web 2.0 tools. The quality of the knowledge built and shared by the users contributed to develop the relational dimension of social capital
•
(mutual trust, norms for interactions, etc.) which in turn materialized as enhanced content and higher quality of the interactions within the firm. The implementation and further development of the Web 2.0 tools, based on shared representations and language, relied thus on the cognitive dimension of social capital. This common language is also reinforced by more and more frequent interactions through Web 2.0 tools.
Knowledge Sharing in the Age of Web 2.0
Finally, the three dimensions of social capital limit the temporality of knowledge sharing, increasing the efficacy and efficiency of knowledge sharing processes and activities. For example, a net decrease in response delays has resulted from formal, diffuse knowledge at Schlumberger, including a 95% reduction of the time needed to answer technical requests and a 75% reduction of the time needed to update engineering changes. However, it is very important to note that, without an appropriate culture or aligned tools with the organization’s processes and objectives, the results would have been rather different. Beyond the multiple functions of the tools, these results show the importance of usage and the need to align it with organizational life, that is, the business processes of the firm as well as the social norms of the employees’ community, as expressed by the idea of social capital. This point is well summarized by this last quote from Susan Rosenbaum, Schlumberger’s Knowledge Management Director: It is critical not to think that the tools are the answer. And this is the key for all knowledge management. The people are in the center and the tools surround them as aids. If we come to rely only on online tools and forget the people and their connections and interactions, then the knowledge and information will die (in Andreev et al., 2010, p.11).
CONCLUSION Knowledge management by itself cannot originate value creation without being inserted into the firm’s practices. Among knowledge management processes, knowledge sharing is one of the most critical and challenging for value creation. Therefore, practitioners must be aware of the stakes related to knowledge sharing and take care of their sources of knowledge sharing, such as social interactions, especially in a Web 2.0
context that makes connections fast and easy. The Schlumberger case shows that new knowledge sharing practices oriented toward social interactions can succeed if the managerial environment is supportive and the appropriate tools are chosen and appropriated by users. This success also is based on innovative policies that prompt the firm to stress the benefits of knowledge sharing and adopt up-to-date technologies. For example, Schlumberger recently turned to wiki and video technology tools (N’Kaoua 2009; Bessard 2010). Its supportive managerial environment appears institutionalized in its organizational culture, which is significant when it comes to implementing innovative knowledge sharing practices. This chapter emphasizes the role of social capital. Managing relationships based on trust is the core process of knowledge management and of paramount importance for tacit knowledge sharing. Therefore, all three dimensions of social capital must be managed carefully to ensure effective knowledge sharing. In many cases, despite its importance, managers may not be able to take advantage of social capital to leverage 2.0 knowledge sharing practices, perhaps because of inadequate communication tools for the characteristics of knowledge they need or a lack of sufficient social networks outside the company (Anand et al., 2002). Web 2.0 might offer a viable solution. Several recommendations derived from our analysis also can help practitioners address this issue. First, we support the recommendation of Yang and Farn (2009): Managers need to foster the formation of an intensive social network among employees in order to promote tacit knowledge sharing within a workgroup (Yang and Farn, 2009, p.216). Moreover, managers should cultivate a sharing environment (i.e., develop relational social capital), such as by establishing regular group meetings. Practitioners also need to realize that knowledge management requires the assistance
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of people who can appropriate technological tools while also reducing knowledge complexity and managing knowledge sharing process. These employees might be named “interface integrators,” and their role should be clear within the company (Deltour & Sargis Roussel, 2007). Moreover, the balance of the three dimensions of social capital within the company is of paramount importance for practitioners, who cannot just rely on interactions between actors (structural dimension). They also must assess their common meanings and trust (cognitive and relational dimensions), because all three dimensions have a joint influence (Deltour & Sargis Roussel, 2010). Achieving effective knowledge sharing remains challenging for most companies which largely have focused on technical solutions and expert knowledge for decades. The KM perspective that has evolved in recent years suggests a more social vision of KM practices. Social capital theory defined through structural, relational, and cognitive dimensions in turn has emerged as a main theoretical framework to understand and improve KM practices. To enhance understanding of the role of social capital, future research should investigate rich empirical cases. As the Schlumberger case reveals, and as underlined by Schneckenberg (2010), conceptual improvements also might come from a bridge between social capital and organizational culture: The goal should be to create a proper work culture to foster the use of Web 2.0 for knowledge sharing.
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KEY TERMS AND DEFINITIONS Knowledge Sharing: The transfer, diffusion, and distribution of knowledge within and between organizations, communities of practices, and departments. Knowledge Sharing 2.0: Renewed practices of knowledge sharing supported by Web 2.0 tools. Social Capital: “The sum of the actual and potential resources embedded within, available through, and derived from the network of relationships possessed by an individual or social unit” (Nahapiet & Ghoshal, 1998, p. 243).
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Chapter 8
Strategic Knowledge Management System Framework for Supply Chain at an Intra-Organizational Level Cécile Gaumand Ecole Centrale Paris, France Alain Chapdaniel ACTIMUM, France Aurélie Dudezert Ecole Centrale Paris, France
ABSTRACT In the Web 2.0 and organization 2.0 era, implementing Knowledge Management Systems (KMS) in Supply Chain (SC) in companies should contribute to gain sustainable competitive advantage. Using a case-study in an Italian SME (BONFIGLIOLI), this chapter seeks to propose new processes and recommendations to design and operate an efficient KMS for a SC at an intra-organizational level. This case study shows in particular the role of IT as an artifact implying individuals in organizational knowledge creation. It also shows that implementing KMS in SC makes SC actors change their cognitive scheme and work practices and calls for a new role of middle management.
INTRODUCTION During last decade academic researches and practitioners placed Knowledge Management and Supply Chain Management as strategic key drivers for companies. DOI: 10.4018/978-1-61350-195-5.ch008
Knowledge Management sources from several theories that cover among other fields such as economic, strategic, artificial intelligence, organizational culture, social science or management fields without really becoming an independent theory. For instance many Knowledge Management practices are encompassed in the Resource-Based view (Penrose, 1959; Rumelt, 1984; Wernerfelt,
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Strategic Knowledge Management System Framework
1984; Conner & Prahalad, 1996) that considers knowledge as a scarce resource contributing to economic profits. As a result “such issues as skill acquisition, the management of knowledge and know-how, and learning become a fundamental strategic assets” (Teece & Pisano & Shuen, 1997, p.514). Nevertheless organizations have difficulties to identify and understand their knowledge in order to design an appropriate framework and processes management empowering all actors through the same global goal of performance (Grant, 1996). Knowledge Management is also considered as a complex process mobilizing tacit or non codified explicit know-how in daily activities that have to span traditional structures, culture and management forms (Grover & Davenport, 2001). Supply Chain is a transversal function which is a stake for companies which aim to consolidate their competitive edge. For several years Supply Chain optimization has mainly been oriented toward managing physical and financial flow of information. Operational Research and IT have contributed to the creation of tools and methods for managing demand, production, distribution and reverse logistics. As examples we can mention integrated tools such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Efficient Customer Response (ECR). Methods such as Lean Management, Supplies Synchronization, Late Product Differentiations have also improved Supply Chain. Technologies as Radio Frequency Information Device (RFID) provide with opportunities to accelerate informational and physical flows while improving reliability. Nevertheless more improvements are expected. Managing physical and financial flow of information is mandatory, but interpreting information all along the Supply Chain to focus actions on competitive advantage development brings a new way of optimization. In the Web 2.0 and Organization 2.0 era, Knowledge Management approaches such as that of WAL MART (Binot & Dudezert,
2008) have recently led scholars to focus on this type of improvements in Supply Chain (Lancini, 2007; Gunasekaran & Ngai, 2007). Most of researches deal with Supply Chain optimization at an inter-organizational level (Hult & Ali, 2003; 2006; Evrard & Spalanzani, 2009; Fabbe-Costes & Lancini, 2009). However there is also need to study intra-organizational level. This chapter based on a case-study in an Italian SME assesses to explore the impacts of a Knowledge Management System implementation in a Supply Chain Department. First we present the characteristics and aims of Knowledge Management System for Supply Chain. Second we present the methodology of research and the context of its application. Then we describe the case-study and the lessons learned from industrial and academic points of view. Finally we continue with discussing Supply Chain KMS characteristics, the role of IT as an artifact leading individuals to create organizational knowledge, the role of middle management which has to consider individual cognitive scheme changes and the emergence of new work practices.
BACKGROUND: DEFINING KNOWLEDGE MANAGEMENT SYSTEM FOR SUPPLY CHAIN Knowledge Management System Knowledge is when collaborators can interpret information linked to a specific context by adding in the expertise of their own experience. The works of Polanyi, Nanoka & Takeuchi regarding the knowledge nature (explicit/tacit), the hypertext cycles (internalization/externalization, individual/ collective) have highlighted that only an observation can help to understand tacit knowledge. Most research defines Knowledge Management as the generation, representation, storage, transfer, transformation, application, and protection of or-
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ganizational knowledge. Organizational memory, division of information and collaborative work are also closely related to Knowledge management (Schultze & Leidner, 2002). Knowledge Management Systems can take different organizational forms such as knowledge bases, knowledge formalization (marks, patents, customer contract …) or workspaces (Earl, 2001). Knowledge Management Systems are “information system classes dedicated to the organizational knowledge management (i.e. they are based on information technologies developed to support and improve the processes of creation, storage, research and identification, transfer and integration of knowledge).” (Alavi & Leidner, 2001). However implementation steps often do not take into account culture, power games, structural forms or management style (Span & Scarbrough, 1999; De Long & Fahey, 2000; Ipe, 2003). Their implementation should take into account all determinant elements to qualify and design the adequate Knowledge Management System for an organization (Dudezert & Lancini, 2006; Aviv & Ali, 2008). The knowledge nature of the organization, its operational objectives impacting processes and its business model have to be considered as well (Hansen & Ali, 1999; Earl, 2001; Dudezert & Lancini, 2006).
Supply Chain Characteristics The Council of Logistics Management defines logistics as a “part of the supply chain process that plans, implements, and controls the efficient, effective flow and storage of goods, services, and related information from the point of origin to the point of consumption in order to meet customers’ requirements.” This requires a global coordination of activities within and between companies including reverse logistics. Supply Chain Management is defined as “the management of upstream and downstream relationships with suppliers and customers to deliver superior
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customer value at less cost to the supply chain as a whole” (Christopher, 1998, p. 18). Supply Chain is a transversal function becoming a strong concern for any company seeking to reinforce its market position. “As such, SCM (Supply Chain Management) is concerned with improving both efficiency (i.e., cost reduction) and effectiveness (i.e., customer service) in a strategic context (i.e., creating customer value and satisfaction through integrated supply chain management) to obtain competitive advantage that ultimately brings profitability” (Mentzer & DeWitt & Kleeber & Min & Nix & Smith & Zacharia, 2001, p. 115). Supply Chain performance requires the implementation of a robust and evolutionary information system to answer the requirements of visibility, reactivity, simultaneity, and traceability while piloting flows of goods in real time. It uses most of the information stored in the information system (databases, management parameters, transactional messages, historical consumptions, forecasts, planning, simulations, flow information, and reporting …) and provides also information required for all functions at strategic, tactical and operational levels. Supply Chain uses several tools implemented for Knowledge Management such as computer-mediated communication (E-mail, Infoportals, Instant Messaging) without really focusing on knowledge transfer and renewal. They are used to exchange information resulting from all Supply Chain actions dealing with customers, internal processes and suppliers. Supply Chain also uses technologies based on the information-process model as ERP (Malhotra, 2000). Implementing and using ERP involves a standardization of the processes as well as an integration of these standard processes in the company (Reix, 2005). However implementing ERP is not only a technological exercise. It is also an organizational revolution. It outlines the premises of a collective learning (Akkermans & Van Helden, 2002; Wei & Ali, 2005) that have to be considered by managers.
Strategic Knowledge Management System Framework
Therefore SC mobilizes competences using huge variety of knowledge based on human characteristics (Fabbe-Costes, 2008) at an intraorganizational level. Crossing all the organization, SC develops not only technical but also organizational and relational knowledge. SC knowledge is also located at the interfaces of several functions of the organization. Thus knowledge in SC is depending on individual experience and knowhow developed during the realization of daily tasks in interaction with others all departments of the organization. Logisticians work also at inter-organizational (external partners interfaces) dealing with product/service life cycle. Therefore logisticians are in the middle of relations with internal departments of the firm and with suppliers and customers. This access to internal and external information through organizations provides them the capacity to confront their own knowledge with other actors. It places logisticians in the core of a process of knowledge integration that strongly contributes to the knowledge and competence renewal of the company (Charon-Fasan & Farastier, 2003). However logisticians are men of interfaces in charge of a mission of coordination integrating a global overview (Mathe & Tixier, 1981). Gammelgaard & Larson (2001) report that logisticians are seen as men of “coordination” and “situation” enables to adapt to “special” situations (Sheffi & Klaus, 1997). Meanwhile the learning mechanisms developed in such situations are difficult to be understood. First they mobilize numerous actors coming from different horizons who can twist the perceived reality of situations. Second urgency and uncertainty can inhibit reflexive capacity yielding to the non use of know-how, experiences needed to capitalize and integrate new knowledge in the “Habitus schemes” (Bourdieu, 1980). Moreover many logisticians are autodidact and still not focused on formalizing their knowledge. The hardness of work, the lack of recognition of operational functions, and low remunerations lead
many logisticians to frequently move from one company to another (Camman & Livolsi, 2007). Thus there is a need of managing logistician knowledge to maintain SC performance. The state of art highlights that SC knowledge is confronted with an evolutionary environment where technologies, social and managerial aspects are intertwined (Fabbe-Coste, 2000). Thus taking SC characteristics into account should help to target the objectives of the KMS for SC at an intra-organizational level.
Knowledge Management System for Supply Chain Most of KM practices in SC are structured around information management tools aiming on coordinating and storing the knowledge formalized within organizations (Oppong & Ali, 2005). These practices optimize Supply Chain. They also partially highlight SC characteristics (Spalanzani, 2003). Thus KMS for an intra-organizational SC should manage this tacit knowledge using adequate tools with an objective of improvement, integration and flexibility to reach the firm’s strategic goals. Taking into account the Supply Chain characteristics, objectives, and the key drivers identified by Fabbe-Costes (2007) we identify the following characteristics that should be developed by KMS for SC: •
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Integrate individuals in social networks to make them develop a vision of network with the aim of creating leaders and developing a culture of project, and risk taking; Develop know-how in terms of design, simulation, process reconfiguration, as well as performance management and measurements; Select internal standards suitable with information technologies and with inter-organizational standards;
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Identify and secure information flows circulation and choose flow support formats compatible with inter-organizational standards;
Figure 1 synthesizes the Supply Chain knowledge characteristics, aims and its KMS objectives. It illustrates also the links to be explored between each of them. The first objective consists on developing knowledge process. As highlighted in the previous part, it should focus on the tacit knowledge embedded in SC actors in interaction with all functions of the firm. Such knowledge is particularly tacit and almost deals with interface situations. Figure 1. Supply chain knowledge characteristics
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The matter is to understand how to transform this tacit knowledge in process knowledge capable of improving Supply Chain objectives (performance, agility and adaptability of Supply Chain at an intra- and inter-organizational level supported by IT supports). The second aim is to transform current cognitive schemas resulting from daily activities management and problems resolution often localized at a tacit, individual or collective level. Developing a culture of sharing or network should be an opportunity to understand and use knowledge of actions and situations. The matter is to understand how to change cognitive schemas for improving the SC objectives achievement.
Strategic Knowledge Management System Framework
According to literature and practices researches there is need for research on the process of KMS for SC implementation in organization. Such studies should take business-model, strategic, structural, and managerial aspects into account. This kind of research is complex because intertwined with several fields of firm theory.
CHOICE OF METHODOLOGY: ACTION-RESEARCH Our recommendations on KMS implementation in an intra-organizational SC are based on our Action-Research study conducted at an Italian SME (BONFIGLIOLI) during 3 years. Action-Research (Baskerville, 1999) is particularly adapted to examine organizational complexity in emerging research issues. The first step of Action-Research is introducing changes in an organization and observing their effects. This aim allows to precise the scientific problem and to build grounded theory. Action-Research methodology is especially used in such context because it aims at building grounded theory by experimenting organizational solutions on specific organizational issues. According to David (2000) this research method aims at considering the research field as an engineering place (use adequate management tools and models to master the change) and the empirical field as a source of grounded theories (understand how design and tools implementation impact organizations, and how they enrich the theoretical knowledge corpus in management sciences). David (2000) underlines that this research method is based on four principles: •
An understanding of the process activities of the system, associated with an investigation step leading the researcher to use his position to co-produce knowledge inside the system;
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A knowledge production sourcing from interactions with the field when designing and implementing procedure and management tools; An analysis spanning several theoretical levels requires the researcher to be acquired with organizations theory, management tools and technical aspects; The intervention is naturally normative.
Such cognitive process is articulated through three steps structuring the research process: intuitive, understanding and conclusive steps (Wacheux, 1997). They are integrated in the three phases of an Action-Research (Baskerville 1999): •
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Diagnosis: This phase implies an analysis of the organizational context in collaboration with actors of the firm Therapy and evaluation of knowledge created: the researcher introduces changes in the organization to study their impacts. The knowledge evaluation phase
This chapter is based on an Action-Research study conducted at an Italian firm (Bonfiglioli) which has one of the authors as Supply Chain Manager. Thus our “actor-researcher” position (Lallé, 2004) guided us in suggested solutions to optimize SC through Knowledge Management. Basically literature allowed identifying Supply Chain actors, characteristics and aims that have to be considered for implementing a dedicated Knowledge Management System. The following described Action-Research ambitions to expose the different tools we used. Iterations with literature were useful to appreciate our grounded results in order to give recommendations for practitioners and research. The following parts present the diagnosis and therapeutic phase to bring new lights on the intertwinement between actors, the Supply Chain Knowledge Management System and the tools we used. (See Figure 2).
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DIAGNOSIS PHASE Bonfiglioli Presentation Bonfiglioli, a family company became a multinational organization in less than 50 years. It has manufacturing sites and sales subsidiaries in more than 14 countries, with more than 2.600 employees. The culture of the group is embodied by the charisma and the visionary spirit of its founder, Clementino Bonfiglioli. Founded in 1956 Bonfiglioli focused its core activity on designing, manufacturing, and distributing motor gearboxes for industrial sector. The French subsidiary, Bonfiglioli Transmission (our experimentation perimeter) is present since 30 years and has adopted the family culture
of the group. The Supply Chain department, created in 2006, follows the company management methods based on the strong implication of sales functions in logistic activities. Today the Supply Chain department represents around 30 people across six functions: procurement, stock management, production, reception, picking and shipment. These functions were previously managed by the General Director. According to the organizational culture, sales forces gave instructions to logisticians to procure, receive, produce and ship products. The intertwinement of both sales and logistics generated certain agility in sales priorities management. Actually logisticians, who received instructions of sales department to answer customer request, have developed a capacity of understanding and
Figure 2. Supply chain knowledge characteristics and actors
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interpreting customer needs. This agility and adaptation capacity is therefore reinforced when managing daily uncertainties occurring within and outside logistics system (e.g. carrier or supplier delays, delivery or quality problems…). However this process does not provide enough autonomy and possibility of knowledge sharing and capitalization. The Bonfiglioli group strategy in 2008 was to move from delivering a product to propose a solution integrating several product lines and services. This strategy is based on following key drivers: 1. Reorganization in business units. 2. Investments in robotizing production and research and development on mecatronics. 3. Harmonization of structures, data, and management processes (e.g. implementation of ERP, CRM, ISO Group Certification) 4. Management of knowledge and talents allowing excellence achievement. Bonfiglioli Transmission was a major actor in the deployment of this strategy. The French subsidiary is the first to deploy the ERP and CRM and contribute also to the ISO group certification. The Bonfiglioli aims at better integrating demand management processes among factories and subsidiaries. The Bonfiglioli’s culture and the implementation of its strategic key drivers provide the field of our Action-Research. Meanwhile in order to implement a KMS, we have chosen to explore and characterize the present Bonfiglioli’s SC knowledge.
Supply Chain Existing Knowledge Capital In order to identify knowledge of SC we have first focused on logisticians to understand their knowledge characteristics. Second we have audited the SC processes.
Therefore we worked with logisticians to build the Knowledge Map of BONFIGLIOLI’s Supply Chain. On the basis of the AFNOR X50-600 standard as well as the literature on logistics, we carried out a pre-cartography of Supply Chain knowledge visually representing the technical, functional and human knowledge of logisticians. Then we realized 13 interviews of 1 to 3 hours with every individual over a period of one month to improve the Knowledge Map. During each interview, the pre-cartography was discussed and modified according to the knowledge acquired by interviewees during their experience (Figure 3). Thanks to these interviews and to the Knowledge Map, logisticians became progressively aware of the diversity of the logistic functions and knowledge they imply. Moreover we have noticed that the development of the Knowledge Map improved trust and mutual commitment of collaborators in the Supply Chain Department. Finally this first step of the diagnosis showed that the Sales Department deeply influenced Supply Chain Department. In order to better understand this point and its impact on knowledge development, we have chosen to analyze social networks of influence in the Supply Chain Department. For this purpose we used the MACTOR method (Godet, 2006). MACTOR (Method Actors, Objectives, Ratio of force) estimates ratios of power between actors. It positions actors in relation to strategic stakes and associated objectives to identify convergences and divergences with objectives and themselves. We have involved 14 actors from sales and logistics whose actions deeply impact the 2008 objectives in sales budget achievement, EBIT, ERP implementation, stock level, costs reduction, and delivery service level. By deploying this method we created a map of relations between actors. Based on their objectives, their projects in progress, their motivations, and their constraints, it specified the nature of the influence network of logistics functions. This work first confirmed the Sales department’s investigation in the processes management. Second it highlighted the negative
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Figure 3. Supply chain knowledge map
impact of conflicting goals of SC functions. Both sales investigation and conflicting goals generated conflicts almost situated at the interfaces between Supply Chain and other departments. Nevertheless this analysis provided with convergence links that helped us to build coherent work groups during our Action-Research.
Supply Chain Knowledge Maturity Second we worked to understand the specificities of BONFIGLIOLI’s Supply Chain Department. Thus we audited the Supply Chain Department of Bonfiglioli Transmission with the ASLOG Supply Chain methodology. A Supply Chain audit implements a process approach to start a continuous improvement plan. The ASLOG Supply Chain audit targets to stimulate development of companies in function of their capacities and stakes:
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customer service, delivery reliability, times, stock management or competitiveness. We have chosen the ASLOG methodology because it is recognized by logisticians and it is become a standard. We have addressed the 132 questions relating to all Supply Chain functions dealing with operational, tactical and strategic level. The audit results showed that 45% of criteria haven’t the minimum required for obtaining level 1. The ASLOG audit underlined that tactical and operational functions are self organized in respect to the sales culture. The basic logistics knowledge is absent at Supply Chain processes. As a result no forecasting, long term planning, production and delivery planning, product cycle management, MRP calculation, and supplier audit exist. This audit reveals the lack of Supply Chain integration in the strategy definition and the lack of Supply Chain performance mastering. Moreover the information system does
Strategic Knowledge Management System Framework
not use of ERP information because of the lack of codification and standardization in master data and processes. To complete this audit we analyzed the current quality documentation regarding the Supply Chain functions. The result pointed out the predominance of the sales department in Supply Chain functions. As an example the document “customer order management” explains how sales has to launch procurements via a “request of purchase,” or how they can decide to implement customer dedicated stock. This information was stored in the previous ERP in fields exclusively managed by sales. Following this diagnosis phase, the therapeutic phase aims at implementing solutions to test. These solutions are built by confronting the results of the diagnosis phase to previous results in the literature. As mentioned before, two development objectives are particularly suitable for SC KM: knowledge process development and cognitive schemas transformation. These objectives serve for developing a culture of networks, chains, project, risk, change and innovation. We describe hereafter the steps implemented at Bonfiglioli to achieve these two goals.
THERAPEUTIC PHASE Actions for Process Knowledge Development: Modeling, Simulating, Reconfiguring Processes for Mastering, Measuring Performance According to the Firm Objectives Our Research-Action is tied to the Bonfiglioli strategic key drivers. Our starting point was officially attached on the key driver consolidation of subsidiaries to allow a better integration and harmonization of the information system and processes management (SAP implementation, group certification, CRM). Therefore the ERP implementation became our first leitmotiv.
Generally first ERP implementation step consists of the formalization and adaptation of the ERP model to the firm business model. We started a training of Supply Chain actors to generate a formalization of Supply Chain business processes. To codify these processes we framed our action with the SCOR and ASLOG model. Few weeks later we proposed to the 70 end-users a design of Supply Chain processes, integrating the role played by sales function in the supply chain tasks. Despite comments were “I do not find my functions clearly”; “Where do we see that I am recording the sales orders?” with actors we further adapted this model according to the culture and current practices. One of the aims was to frame logistician’s ideas and actions in order to better codify their practices. They took the habit to position their action or problematic in accordance with this model. It facilitated the Supply Chain process knowledge formalization. We have taken the opportunity to train logisticians to Supply Chain concepts. We have organized exchange meetings twice a week during 6 months, opened to all the Bonfiglioli Transmission endusers (70 people). People were fond of them. We fixed topics around ERP modules and Bonfiglioli Supply Chain processes. We answered the main questions: “today I do that, tomorrow how will I do it with the ERP?” Questions without any answer, or whose answer was considered to be unsatisfactory, were submitted to the Businesses Process Owner (BPO). His mission was to clarify processes, to simulate and integrate them in the ERP. Then proposals were discussed with endusers, until an agreement was reached. In parallel the training helped logisticians to associate a more formalized and more effective technique to their grounded learning. Actors joined the work group to explain their know-how as well as to learn how to formalize them in the ERP. Thanks to this free context to share knowledge actors proposed a frame matrix to formalize the processes integrated and non-integrable in the ERP.
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In three months logisticians have formalized 18 processes and 74 procedures concerning all Supply Chain functions. Moreover we integrated 6 processes not identified during the business model construction, in the ERP. At this moment of the Action-Research we obtained positive results in term of developing knowledge for modeling, simulating, reconfiguring processes. We have balanced the Bonfiglioli processes specificities with the ERP process management standardization to stimulate knowledge exchange and to teach Supply Chain concepts. But actions have to be done for mastering, measuring the performance according to the firm’s objectives. Thus when the ERP went live, we embodied our action in the Total Quality Management (ISO Group certification) aim. Even if our KM approach was in relation with objectives of the organization, our results were not mature enough to measure our contribution to the firm performance. Nevertheless it is worth considering the 3 mains consequences of our action: Logisticians became more demanding on quality in the customer needs expression given by the sales department which is a condition for the SC processes improvement. Following our free meeting of exchange, spontaneous meeting for knowledge sharing and learning took place. This helped to solve dysfunctions in day to day tasks. But all dysfunctional points localized at interfaces (Sales/Supply Chain) systematically spawned conflicting situations. Logisticians also became more demanding for a better knowledge management system integrated with a better human resources management system (knowledge accessibility, rewards depending on knowledge development, time given to exchange and formalize knowledge …). Taking these points into account we decided to cope with change mentalities so as to render it compatible with the SC characteristics. In the following part we describe the actions phase of cognitive schemas change. To achieve this aim we have encouraged knowledge sharing and capi-
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talization of logisticians, who are in contact with other functions. We also changed the knowledge map and its uses in relation with key performance drivers.
Actions for Cognitive Schemas Transformation: Develop a Culture of Knowledge Sharing, Change Management, Innovation, and Performance Daily individual salutations were for us an opportunity to discuss with every logistician. These discussions helped us to strike the balance between individual declared motivations and firm’s goals or problems issued from a lack of knowledge. We daily encouraged spontaneous exchanges when a dysfunction occurred within the SC department. Logisticians felt free to take time to discuss and analyze problems with concerned logisticians, instead of solving it by themselves and blaming them. The role of SC manager was first to encourage this dynamic of exchange. Second it targeted to provide them an adequate help to capitalize the new knowledge creation. Most of this knowledge was codified in process knowledge sheet stored on IT network. Finally the SC manager had to communicate with other departments that did not understand the time spent by logisticians to solve definitively problems instead of realizing their operational tasks. In parallel, we tried to find the best context to create a network dealing with dysfunctions occurring at interfaces. Dysfunctions at interfaces increased the cleavage between sales and logisticians resulting from conflicting goals and the Bonfiglioli culture. Such a verbatim witnessed this pernicious schema from both sides: “they have the information from the other side but this is always the same story, they do whatever they want, so this is not my problem even if I know that we will have a customer claim.” To transform this type of cognitive schema slowing the KM dynamic, we ask top management to support our action.
Strategic Knowledge Management System Framework
Using the MACTOR analysis we involved 14 participants from production, quality, customer service, procurement and planning functions. Then we created an excel matrix (stored on an accessible network) to record dysfunctions, their origins, impacted processes, and consequences on customer service level, cost, efficiency and quality. For 4 weeks, 70 dysfunctions impacting production (66%), provisioning (13%) and customer service (10%) have been recorded and analyzed. An improvement plan embodied in Total Quality Management has been developed. The Chairman involved managers to follow it with objective of enriching the knowledge base of the new and updated processes. During this phase we showed logisticians use their new cognitive schemas developed thanks to the KM approach. They used their new capabilities to share and understand knowledge at interfaces with other departments. This new attitude yielded logisticians to create 5 additional processes and update 3 processes. Moreover they asked for 3 changed requests in order to embodied 3 processes in the ERP. Another action was to address the logisticians request concerning a better Knowledge System management. In fact the first knowledge maps were not used because of poor accessibility. They were more focused on individuals than on job descriptions that were obsolete and quoted as a reason of non motivation. Thus we updated all job descriptions describing main activities, missions and concrete goals linked to the firm key performance indicators. We also included dedicated knowledge radar for each activity in all job descriptions that allowed us to appreciate and improve the individual knowledge of logisticians in their tasks (see Figure 4).
Therefore we have programmed internal or external trainings. Moreover we have set individual goals linked with SC functions and firm’s goals. To help logisticians to understand performance intertwinement we created a Balanced Scorecard. It visually represents impacts of SC processes objectives on the Firm’s Key performance indicators. We organized a monthly Supply Chain process review to master logistics performance as well as KM approach. In six months several improvements have been realized, with a transversal approach bringing a better agility needed in a moving context. As an example we quote an emergency check process we implemented in the ERP for goods reception. All Supply Chain activities focused on the service level by receiving, planning, producing, picking and delivering in emergency all customer orders or planned production in late. To bring accessible information to the customer service the production and shipping planning file is stored on the server. Our actions contributed to increase the customer delivery rate of 3%, and the quality level perceived by customers of 4%. Knowledge logisticians are now convinced of their impact on the company performance. Annual individual evaluation reveals that the main barriers reside in the firm management and structure that change slowly. This situation is not very well accepted by knowledge workers who clearly explain that they appreciate the recognition of their performance but they ask for specific individual evaluation indicators based on their activities of knowledge creation. They therefore clearly expect to know what their individual contributions to sales, costs amount and customer satisfaction are. These new expectations as well as financial and training requirements are mentioned on individual evaluation document.
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Figure 4. Individual knowledge map evaluation
LESSONS LEARNED Lesson 1: KMS for Supply Chain Should Consider its Specificities in Order to be Articulated Around Two Objectives: Knowledge Process Development and Cognitive Schemas Transformation Taking SC specificities into account allow framing the KMS for CS. All along our action-research tools for IT, Management, Quality, Human Resources have been used with several actors. Figure 5 illustrates the links between the KMS for SC goals, tools and actors. Therefore our case study highlights that knowledge developed in Supply Chain at an intra-organizational level is almost tacit. Built on experience of individuals this tacit knowledge deals with actions often situated at interfaces that occurs conflicting or emergency situations unfavorable to knowledge capitalization. Our case fits into the Bourdieu’s work on the Theory of practice (Boudieu, 1980). He argues that knowledge coming from actions can take a conscious as well an
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unconscious faces built all among our life experience (the Habitus). Therefore we are all social agents. Basically in case of emergency our scheme interferes with rational actions that inhibit the use of the Habitus necessary for finding definitive solutions (Perrenoud, 1999). Moreover according to Argyris & Schön (2002) logisticians who have to face with conflicting situations generated “pernicious learning” which negatively reinforces their “espoused theories” as well “declared theories.” These kinds of situations that inhibit individual, collective and organizational learning are called learning in “single loop.” According to this assessment the aims of the KMS for SC should deal with process knowledge development and cognitive schemas transformations. This will let codify tacit knowledge daily necessary and transform the logistician learning dynamics in “double loop” (Argyris & Shön, 2002) useful for organizational knowledge. Nevertheless the second lesson learned highlights the need to find artifact to mobilize positively actors in this learning dynamics.
Strategic Knowledge Management System Framework
Figure 5. Knowledge management system for supply chain
Lesson 2: Find Artifacts Linking Actors and the Organization This case shows that ERP can be used as an artifact to change cognitive schemas as well as the process of knowledge development. The ERP provided the possibility to build a formal frame of rules and constraints to help actors to focus on knowledge identification and codification. Moreover this case shows that according to Giddens (1997) interactions between actors and the organization via the ERP have built a common sense building in order to improve the process knowledge to reach the Supply Chain goals. In this case-study ERP can be seen as a structuring tool useful for harmonizing business processes and developing
logistics skills. The KM approach facilitated the adoption of ERP by logisticians who were themselves improving ERP processes following the codification of their daily knowledge. As a result logisticians have initialized different ERP change requests in order to integrate the most important processes in the ERP. Global Quality approach (ISO certification, audits) was also used here as an artifact to positively change cognitive schemas and to improve process knowledge. Daily dysfunctional points were managed according to the problem-solving process. This Action-Research validates the position of Gray (2000) that is a detected failure or a mistake encourages knowledge sharing and creation in interactions with other functions of
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the firm. The stake of explanation, formalization and combination of knowledge that take place in specific, shared cultural environment in an intra-organizational context can be assimilated to the four Bâ types described in the SECI model (Nonaka & Takeuchi, 1995). Thus, we have seen that implementing a Knowledge Management System even if embodied in the compatibilities of the IT supports is tied to a stake of clarification, formalization and combination of knowledge in order to generate a knowledge externalization almost with sales teams. The Action-Research fits well to the recent “Reconciliation Theory” (Felin & Hesterly, 2007) which states that knowledge is the result of interactions between individuals and organization where artifacts are needed to stimulate knowledge. Nevertheless lesson 3 points out the need of transforming the traditional role of middle managers in order to motivate and guide actors in a KM approach.
Lesson 3: The New Role of Managers From a managerial point of view this case-study points out the difficulty to localize and understand the tacit knowledge daily deployed by actors. It shows that implementing a dedicated Knowledge Management System for Supply Chain borders more on a managerial caring than technological tools caring. Technological tools are here more seen as a way of integrate codified processes in the organizational memory. Therefore manager role should span the traditional way of managing by exploring other dimensions than those established by Taylor’s theory. The Bonfiglioli case-study shows the importance of understanding the influences of Bonfiglioli culture and the enterprise goals that are often contradictory. The creation of knowledge maps and influence maps allowed us to identify and manage the role of each logistician involved in the Knowledge Management System implementation phases.
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Interviews and meetings conducted during our Action-Research lead us to think that managers have to carry their efforts on more social and emotional aspect without losing sight the strategic performance (Karoui & Gürkan & Dudezert, 2010). “Understanding how knowledge flows (or more frequently does not flow) across these various boundaries within an organization can yield critical insight into where management should target efforts to promote collaboration that has strategic payback for the organization” (Cross & Parker & Prusak & Porgatti, 2001, p. 119). Managers who take employees social dimensions unconsciously used in actions (Bourdieu, 1972) should better understand knowledge creation, sharing, reusing, renewal and retention processes. It should help managers finding the best fit between knowledge and relationship properties and transversal business processes in an organization (Argote & Evily & Reagans, 2003). Moreover our case-study points out that Knowledge is almost sourcing from operational logisticians who often are autodidact and focus on action situations dealing with interface relations. Theses relations escape to traditional organizational charts and job descriptions. Thus manager should span traditional organizational boundaries and imagine new organizational structures to promote Knowledge Management System goals. Several new organizational forms as the hypertext organization or the middle-up-down model developed by Nonaka and Takeuchi (1997), the reversed pyramid (Mack, 1992) have been designed. They all highlight that such structures should disrupt the current managerial practices placing knowledge in the core of processes and decision making. “The upper management creates a vision, a dream, while the middle management develops more concrete concepts that the employees of the front of line can understand and implement. The Mid-level managers try to solve the contradiction between what the upper management hopes to create and what really exists in the real world” (Nonaka &
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Takeuchi 1997, p.145). Considering SC functions as network connected with processes design (plan, make, deliver, return and master) should help to span traditional structural barriers. The research-action confirms that introducing a KM approach creates a different set of needs required by owners of knowledge and knowledgeable individual. Reward, recognition, new job description have to be implemented to encourage Knowledge dynamic. Knowledge Management approaches have generated a new type of employees called the “knowledge worker” that is to be better identified and generalized in firms to find different way of motivation (Drucker, 1999). Thus managers should help firm to grow with knowledge creation, sharing, reuse and renewal in order to enter a circle of wisdom of knowledge striking the balance between human relationships and processes. Nevertheless this management has to be done in parallel with a management of performance according to the organizational goals.
Lesson 4: Further Works to Measure the Knowledge Management Contribution to Performance Are Needed By this Action-Research we demonstrate that Knowledge Management and Supply Chain are contributing to the firm competitive advantage in terms of value perceived by the customer. We have improved the customer delivery performance as well as the quality level. Supply Chain seems to have adapted existing methodologies (Balanced Scorecard) for cascading the firm strategy in specific Supply Chain goals. Further improvement ways seem to be located in the analysis and integration of human knowledge being mobilized all along the Supply Chain to comfort the firm competitiveness. In the same time Knowledge Management has emphasized the importance of the tacit character of knowledge in the competitive
advantage. Introduce Knowledge Management in Supply Chain should be a way of improving firm competitiveness. Our work is an additional example as one of Hult, David, and Slater (2004) who explain via a quantitative research, that merging Knowledge-based-view, organizational information processing and organizational learning perspective improve the Supply Chain performance by reducing the cycle time of the firm. We can also quote Wadhwa and Saxena (2005) who build a knowledge-based view of an inter-organizational supply chain that promotes knowledge sharing concepts and Decision Knowledge Sharing (DKS). This model “demonstrate better performance both in terms of the number of orders fulfilled and the overall costs reduction” (p.26). Nevertheless in 2004 a Supply Chain survey in collaboration with the Supply Chain Management Review points out the lack of Supply Chain integration in the development and measurement of the firm strategy. This is also the case in our research. Supply Chain remains a weakness especially when it is question of reconciling logistic strategy with strategy of company (CSC, 2004). For a short time few organisms (AFNOR, 2007) seek to align the firm strategy with Supply Chain key drivers and variables of action in order to better manage the 535 key performance indicators identified in 9 frame references (SCOR, ECR, WCL, CLASS A, EFQM, EVALOG, MIT2020, CCI, ASLOG). Jouenne clearly exposes the aim to build a “Supply Chain Meter” standard tool (Jouenne & CFPIM, 2007). This approach as well as our case-study adapts balanced scorecard according to Supply chain aims encouraging a “balanced management” (Brewer & Speh, 2000, p.91). In fact the Balanced Scorecard by combining financial, customer, internal processes and innovation, organizational learning perspectives gives a methodology to cascade firm strategic goal till the operational levels. It aims to help “managers to understand, at least implicitly, many inter-relationships” to take the best decisions. Ka-
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plan & Norton (2002), p.78-79, conclude on the fact that firms have to “learn how to make such explicit linkage between operations and finance.”
CONCLUSION AND FUTURE RESEARCH PATHS Academic literature and our research-action converge on the fact that Knowledge Management System for Supply Chain should be embodied in the strategy of the firm, its business processes, its management and its structure. Knowledge Management System spans the fact of deploying information system tools. Our case study demonstrates that it can structure and store explicit process knowledge which is daily used. Applying Knowledge Management in a transversal function demonstrates that propagation and adoption of such practices in others functions of the company is possible. Some recommendations have to be taken as representing current knowledge map in the firm, understanding the business processes and the firm strategy. Mapping the influence network is helpful to build efficient work groups in order to design and implement a KM approach. Therefore the role of middle management spans traditional management methods in order to help firm to grow with knowledge workers. Nevertheless Human Resources department should also have a role to support such approach. Further research should seek to understand what kind of Human Resources tools and processes should be implementing for managing knowledge workers. Moreover Supply Chain provides an opportunity to cascade the firm objectives on logistics functions and logisticians. This should help to bet-
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ter understand specific knowledge in organization to master efficiency and effectiveness. Introduce Knowledge management approach change the position of workers, who become Knowledge Worker contributing to the performance of the firm. This new position will generate new requests in terms of management recognition, and responsibilities. Then further research should explore possible models to align Knowledge Management system with human being in a specific firm, its structure, processes management and strategy without missing its main goals: develop process knowledge and transform cognitive schemas. Our research pointed out that the IT objectives should address issues resulting from our research-action. Other researches should also work on the informatics tools role in Knowledge Management. They should focus on consequences of such Knowledge Management Systems to address requests as how to give to workers more responsibilities and autonomy in mastering the knowledge performance. We have almost worked on an operational level, and at an intra-organizational level. Therefore further research has to deal with tactic and strategic levels. Such research can probably help to align all these dimensions (operational, tactic, and strategic). Our research-action sought to build an efficient Knowledge Management System for Supply Chain at an intra-organizational level. Further researches should promote this kind of research in other transversal functions at intra-organizational level, but also at an inter-organizational level. Such further researches should enrich grounded experiences and academic knowledge corpus in order to build knowledge management model for companies.
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KEY TERMS AND DEFINITIONS Action-Research: The principle is to introduce changes in the organization and to observe theirs effects. By doing so, the aim is to solve operational problem, and to enrich the scientific knowledge corpus on organizational problematic. Enterprise Resource Planning: A unique integrated IT system for the enterprise supporting all its different functions. Intra-Organizational: What’s going on inside the organization; the opposite, the extra-
organizational implies outside actors as suppliers, clients… Knowledge Management: It mainly concerns the generation, the representation, the storage, the transfer, the dissemination and the improvement of Knowledge. Knowledge Management System: A system (generally IT based, but not only) that enables the Knowledge Management. Supply Chain: All the parties implied in the satisfaction of a final client’s need. (Also called Business Network) Supply Chain Management: A set of approaches to satisfy the final client’s need, at a given level of service and at a lower cost, in respect of sustainable development.
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Chapter 9
Web 2.0 and Project Management:
Reviewing the Change Path and Discussing a Few Cases Antonio Carlos de Oliveira Barroso IPEN-CNEN/SP, Brazil Rita Izabel Ricciardi IPEN-CNEN/SP, Brazil Jair Anunciação de Azevedo Junior IPEN-CNEN/SP, Brazil
ABSTRACT The so called Web 2.0 has, in many ways, created the conditions for people to use the power of crowdsourcing. Many business areas and experts are taking advantage of this phenomenon, but what we see is just the beginning. As individuals we are being culturally transformed by Web 2.0 and are ready to use many of these new habits in our working practices. The boundaries between tools and applications we use to interact socially and to work are becoming fuzzier and paler. Management, in general, and specially knowledge and project management have a lot to gain by combining all of these possibilities. This chapter focuses on the synergy of Web 2.0 applications and services and project management needs. To some extent, a knowledge management lens is used to comment and to discuss the issues. Later it examines the Brazilian situation of current project management practices and discusses some cases of our own experience. Also, to gain insight on the path forward, helping levers and possible hampers are identified and discussed in the text. In general, our case study observations indicate that the use of these tools and platforms has become more than promising, because as people become familiar with them, they are usually converted to it. DOI: 10.4018/978-1-61350-195-5.ch009
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Web 2.0 and Project Management
INTRODUCTION This paper starts making introductory remarks on the affinity of web 2.0 resources and current project managers’ needs, emphasizing how webbased tools can help their work. Next, there is a review and a historical perspective of the relevant literature describing applications of such tools that can be related to project management. Subsequently, there is a Brazilian panorama of project management practices. It follows a description and subsequent discussion of some cases of our own experience, trying to relate the users’ perspective in terms of the conditions that helped them to adopt these tools and how they have helped their work. Furthermore, some cross-case inferences are conducted and a short longitudinal analysis is attempted. This work tries to connect and make sense out of four chunks of information that the authors have come across with. They are: •
•
•
•
there is only a small body of literature assessing or speculating about the usefulness or leveraging power of the web 2.0 components for project management; the results of a large survey, conducted by the Brazilian section of the Project Management Institute, have shown that on the one hand web-based project management software is used in less than 40% of cases, and on the other, the five abilities that are at the same time classified as most valuable and most lacking are those for which potentially the web 2.0 seems to be promising to leverage; most of the of core issues concerning on how the web 2.0 can deliver its promises involve questions concerning the realm of or related to knowledge management; the experience of the authors on using web 2.0 components as complementary tools for managing projects in a variety of settings and conditions.
A knowledge management lens was used to help us dissect the issues of culture and common “language,” or knowledge basis, that actually mediate the transfer and sharing of knowledge in a project setting. Our framework was geared to assess (a) the project teams’ culture and knowledge basis; (b) the potential gains they see today with the use of the web 2.0; (c) the gains actually perceived at the time that the cases occurred; and (d) how their uses of web 2.0 in project settings have evolved since then. Many new features of what is being called web 2.0 have spurred the imagination and creativity of application service providers. To frame its possibilities in a simple manner, we can just think of the demand growth if all the companies decide to outsource the hosting of all their web applications. As it was pointed out by Winans and Brown (2009), it is a fast growing business, and the easiness of scalability can be pointed out as a real lever. On the client’s side, there are some issues of mind frame and of corporate computing architecture that will have to be sorted out before a large migration of the applications can take place. Also on the vendor’s side, issues concerning the robustness and security of applications will have to be dealt with to assure smoothness in the clients’ transition. If one adds to cloud computing the affordability of larger bandwidth, mobility, virtual collaboration/meeting, work spaces, blogs, RSS, wikis, social bookmarking, social network platforms, with many of these services being able to handle multimedia, one grasps what is being collectively denoted as web 2.0. Hoffman (2009) commented on an information technology (IT) survey of the “Nine Hottest Skills for 2009,” which listed on 3rd and 7th places project management and web 2.0, respectively. His comments, from the IT perspective, list a couple of reasons regarding the possible synergy of web 2.0 and project management, summarized below. Concerning project management he points out that:
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…even though many companies are cutting back on IT projects, there’s still robust demand for project managers with solid track records. (Hoffman, 2009). As for web 2.0, he argues that: …while many companies are just starting to noodle with corporate implementations of social networking applications such as MySpace and Facebook, more and more companies are trying to reach their customers via the web,… (Hoffman, 2009). Looking from the project management point of view, Bannan (2007) commented on a series of occurrences that can be seen as emerging manifestations of a transformation wave leveraging the affinities between project management and the new aspects of web 2.0. The main points of her article are commented below. For instance, aspiring project managers are trained to tap into blogs and podcasts before they even leave the university. Also, a lot of hot veterans have learned to be “wired” to those things, as they are excellent means to keep updated with emerging project management techniques and advancements. In short, there is an invasion of young “pod people” in the Project Management arena and a significant rate of conversion of new users within the population of traditional Project Managers. Social networking is a population phenomenon since more than half of the people that access the web are enrolled in at least one kind of network. The point here is that to be known means to be referable to and, given the somewhat short life cycle of most projects, this can be a real asset for Project Managers. Although there are many advantages, there are a few catches, as well, especially what Bannan (2007) called the complacency factor:
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…people may simply be more likely to seek out and use blogs and social networks that support positions they are comfortable with and knowledgeable about. As a project manager, this can impede your learning curve and simply make your use of web 2.0 moot. (Bannan, 2007). In addition, because web-based blogs can be found and read by anyone, people should be careful about posting sensitive materials and promises that cannot be kept. A blog, like an e-mail or a written document, leaves a paper trail. But the bottom line is that project managers don’t have any excuses for limiting their blog use to reading about someone else’s project adventures or posting a rant about an uncooperative project sponsor. Perhaps the main challenge of project management is to create a nice atmosphere and common space accessible for everybody from everywhere, to promote the interaction, the participation and the proactive collaboration of the involved work team, which in a large project can involve a lot of people from different specialties, organizations and physical work places. The adoption of web 2.0 services and applications to project management gave origin to what is often called “Project Management 2.0,” which is producing changes of cultural and structural nature in the process of managing projects. One sees a new kind of workers’ behavior as people are bringing to the work arena their individual practices with web 2.0 “wonders.” In a slightly different way to look at the facts, Filev (2006) named this emergence “Social Project Management.” Emphasizing collaboration makes teams much more productive as information flow and knowledge sharing is facilitated among team members. The easier and more accessible social connections opportunities are inside of the organization, the higher the quality of interaction among people and the more intense the team collaboration will be.
Web 2.0 and Project Management
We have used Figure 1 to put into perspective what we have grasped from the literature review, as blended with our own experience. Each Web 2.0 component is described in terms of the attributes that matter for our analysis and its potential relevance for project management is summarized.
CULTURE, TECHNOLOGY AND THE POSSIBILITY OF COLLECTIVE REASONING AND KNOWLEDGE Some project types are very intense in information exchange needs and, at the same time, very fragmented in terms of stakeholders and intervening parts. As a consequence, delays and off target costs are common in these situations. For such category of projects, web-based applications can provide decision supporting, project management and knowledge management tools that enable
to pool, from the dispersed agents, meaningful information, knowledge and opinion in a near to real time fashion. If a project environment can provide information collection, knowledge links, cross fertilization of ideas and opinions from the different areas of expertise of people involved in the project, one has the right conditions for the emergence of the collective intelligence of people collaborating for a common target. The disposition for that is directly linked to the interaction potential of the group or community and its respective conditions. Individual intelligence requests certain conditions to flow in each one of us; collective intelligence should also request specific conditions to flow among the individuals. As Lévy (1997, 1999) suggests, those conditions could be given by the social, cultural and technological capital of a collectivity. In that sense, the interaction potential among individuals (social capital)
Figure 1. Relevance of Web 2.0 to project management
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would constitute one of the reference indexes to understand the form of propagation of the ideas through a communication infrastructure inside a community, and its consequent unfolding or not in intelligent collective actions. Given the right culture of project teams, the new generation technologies applied to project management, along with the right methodology can, in principle, enable project managers and leaders to tap into the synergetic collective intelligence of project teams.
WHATS IS IN THE WEB 2.0 TO HELP MANAGING PROJECTS? Traditionally a project manager acts as a proxy in all project-related communications. Except for small projects, this practice is bound to reduce manager productivity and therefore curtailing the efficiency of the rest of the project team. Web 2.0 tools emphasis on collaboration and many-tomany communication makes teams more productive and every willing member well informed. They are not only very helpful in managing distributed teams, but also enable restructuring of communication and work flow to take care of a lot of routine operations for the manager. In one of the first practical uses of web based tools, Rojas and Songer (1999), emphasized the fact that the success of architecture, engineering, and construction projects relies heavily on timely transfer of information among the multiple parts involved. They proposed a web-centric system that supports inspection, called ‘‘Field Inspection Reporting System’’ and for that they conducted a short business case comparing the traditional paper based inspection with the new web-centric version and reached a cost reduction of 20% and also a slightly better quality of the new process. O’Brien (2000) analyzed the early generation of web tools for project management, which he called project web sites. On one hand, he recog-
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nized the potential value of providing a centralized, commonly accessible, reliable means of transmitting and storing project information and as such, availing a level of access to project information that surpasses such traditional means of communication as telephone, fax, overnight mail, and e-mail and such traditional storage mechanisms as project binders. On the other, he pointed out that, despite some extravagant claims, in practice, “successful” examples were cases where those using the site were mostly members of a core group of (innovative) project team members, with pragmatist users participating only minimally. Sawyer (2001) reported that the 2001 Information Technology and e-Business Survey found that number of firms that have used a project website has risen to 62% from 46% in the previous year. Besides at least 80% of project site users say the websites are at least somewhat effective in improving the management of construction projects. Nitithamyong and Skibniewski (2004) have conducted a research at Purdue University on the identification of factors determining the success or failure of web-based construction project management systems. They stated that, for companies to successfully embrace PM-ASPs, factors such as technology, process, people, procurement, legal issues, and knowledge management must be considered. They believe there is a gap of a deeper discussion of what factors, technical and nontechnical, significantly affect the outcome of using of web-based PM tools. They have summarized the current business models of PM-ASPs and categorized the features of the commercial offerings using a comparison table to present the panorama. The potential benefits and barriers were discussed, using some of the ideas of O’Brien (2000). They ended up by concluding that PMASPs present significant benefits to the construction industry, but their successful implementation is still hindered by barriers, nontechnical ones for the most part.
Web 2.0 and Project Management
Knowledge Management Aspects Construction projects have deserved some special attention from knowledge management (KM researchers). As observed by Kamara et al. (2003), current practice for capturing project knowledge focuses mostly on people (i.e. the learning acquired by a project participant from his own experiences or from resources within his organization is reused when that person works on another project) and the use of post-project reviews within each participating organization. In a multi-organization project, the attempt to collect and to transfer usable knowledge experience has many limitations related to technical, human and business factors. A web-based prototype KM system for capture and reuse of knowledge during the project life cycle and after project implementation was developed by Udeaja et al. (2008). This solution focuses on the use of a web-based project management system, with a KM vision, that enables good coordination and improves collaborative work between members and different entities in the project team. System functional requirements were defined to satisfy the needs of project managers and project offices related to project knowledge as it was found by a previous research Tan et al. (2004). Interesting was the substantive suite of tests applied to evaluate the prototype performance.
Agility of Communications and Decisions For many years now it has been noted how critical communication is for the success of large construction projects (Thamhain & Wilemon, 1986). To state it more precisely, one can say that the issue here is accurate and fast sharing of information to produce better informed and faster decisions. Scott et al. (2008) highlighted observations from the Council on Tall Buildings and Urban Habitat since 1995 and pointed out some reasons for it, such as (a) the variety of forms and types of project information required at different stages
of a project and the wide range of professionals from many disciplines in the project team; (b) the dynamics of data changes and its shortening life cycle from creation, storing, manipulation, transmission, reformatting, application and revision; (c) the cost and time delay consequences of inappropriate or inaccurate data; and (d) the fact that construction development and operation cycle is highly dependent on the integrity and effectiveness of the information flowing between the client, design engineering, equipment manufacturing, contracting, and facilities management segments of the construction industry. Alshawi and Ingirige (2003) have already noted the web-enabled project management as an emerging paradigm in construction. They analyzed the significant challenges facing projects and the limitations of the current project management practices at that time and showed that most of the limitations could be coped with the right web-enabled applications. Next, they reviewed the influence of the internet and emerging business models on project management and the current stage of web-enabled project management software, also they made a short analysis of 5 project cases. They end up pointing out the main issues: security, culture, ownership of drawings, integration of databases and to what extent virtual meetings can substitute site/project meetings. Concerning the path ahead, the main conclusion was for the construction industry to equally consider technology, process, people and knowledge management in order to successfully embrace web-enabled project management tools. Chassiakos and Sakellaropoulos (2008) summed up well the underlying reasons, reproduced as follows: Construction is one of the most informationdependent industries, mainly due to its extended fragmentation. Construction projects are often complex and unique, involve a large number of activities, and require the employment of several human resources with various specializations.
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Thus, the amount of information generated and exchanged during the construction process is enormous even for small-sized projects. The distance between the construction company headquarters and construction sites augments the communication problem. (Chassiakos & Sakellaropoulos, 2008).
Conflict Management in Projects Conflict in project management is inevitable and is more usual when the project’s team group involves individuals from different backgrounds and orientations working together to complete a complex project scope. An important aspect is to build an appropriate environment among the project team to avoid conflicts. Anyway, conflicts mean entropy and consequent losses of efficiency and money. As Ford (2000), project managers can spend much time to try to solve conflicts: Up to 30% of a typical managers time is spent dealing with conflict (Thomas and Schmidt, 1976)…A more current study showed that 42% of a manager’s time is spent on reaching agreement with others when conflicts occur (Watson and Hoffman, 1996). (Ford, 2000). Causes of conflict can be related to differences in values, attitudes, needs, expectations, perceptions, resources, and personalities. Because of this, managers have to deal with a conflict in a variety of ways, depending on its causes and many techniques and resources can be used to accomplish predictable results. Speakman and Ryals (2010) collected, from the literature, many approaches to describe conflict types and presented a typology, using the antecedents or the nature of the conflict episode, as they say “interpersonal conflict” within the organization. Analyzing these approaches, they observe that most of the authors subdivided conflict into two types: relationship conflict and task conflict.
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In many cases task-oriented conflicts are originated by lack of timely information and poor communication among the involved peers. It can be argued that potentially web 2. 0 tools can reduce the number and importance of this category of conflicts. Relationship conflicts, which can stem from differences in values, attitudes, needs, expectations and so on, are often manifested in decision making and review meetings when people can become very emotional about somebody else’s positions and view points, that they were not familiar with and that may end up affecting their own points of view. Here also, it can be argued that web 2.0 tools, especially social networking and blogs can promote sociability and improve the emotional interrelation of the group making them more closely related in a spontaneous and friendly way.
THE BRAZILIAN PANORAMA OF PROJECT MANAGEMENT Every year, the Brazilian Project Management Institute (PMI) conducts a benchmarking study to profile current practices and observed trends of project management in Brazilian companies. PMI is represented in Brazil by 13 regional sections, also called chapters, and this study is the result of an integrated work of all these regional sections. The study tries to identify the alignment degree of the organizations to the best practices in project management as recognized by PMI. This assessment covers the following aspects: Organization’s Culture; Organization’s Structure; Project Portfolio Management; Project Management Office (PMO); Processes and Methodology; Professional Development; Tools; and Performance and Results. Some effort is dedicated to uncover the main problems, needs and critical success factors. The two last editions of the study (PMI, 2008 and 2009) enrolled 373 and 300 organization, respectively. A summary and comments on the main findings will be presented in the next couple of
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pages. In the presented tables, the term “selected” means those topics of the study results that were chosen due to their connection to the subject of our interest.
Profile of the Assessed/ Surveyed Organizations The surveyed sample was highly representative, covering the whole Country and almost all sectors of economy. Organizations of all sizes (large, medium and small) were surveyed. The net profit distributions of the surveyed organizations for the studies of 2008 and 2009 were respectively: 28% and 24% earnings over US$ 560,000,000; 11% (in 2008 and 2009) from US$ 278,000,000 to US$ 560,000,000; 14% and 15% from US$ 56,000,000 to US$ 278,000,000; 20% and 19% from US$ 5,600,000 to US$ 56,000,000; and 27% and 31% below US$ 5,600,000. As for the number of employees the distributions of 2008 and 2009 were respectively: 26% and 15% organizations with over 5,000 employees; 18% and 23% between 1,000 and 5,000 employees; 5% and 10% between 500 and 1,000 employees; 24% and 20% between 100 and 500 employees; and 27% and 32% below 100 employees.
Size of the Projects As it happens for the company sizes, the size of the projects is somewhat smaller and more representative in the 2009 sample. From Table 1, one can estimate that the cost of the average project came down from R$ 4.12 million to 3.5 million, which is a 15% reduction.
Survey Results Our attention was concentrated on the topics that could give insight into issues of web-based tools and knowledge management. It was noticeable that in several aspects the topics of communication,
Table 1. Size distribution of projects in terms of budget (PMI, 2008 and 2009) Average Project Budgets
Percentage of surveyed organizations 2008
2009
Above US$ 5,600,000
26%
20%
From US$ 560,000 to US$ 5,600,000
24%
23%
From US$ 56,000 to US$ 560,000
33%
39%
Below US$ 56,000
17%
18%
knowledge on PM, team working, capacity to integrate parts appear among the most important for the surveyed organizations. These findings are highlighted below. For Professional Development, Table 2 shows an extract of the abilities considered to be more important and Table 3 indicate those abilities in which the organizations feel they have greater deficiencies. As one can see, communication, knowledge on PM, ability to integrate parts, team working and conflict management are subjects that potentially can be leveraged by web 2.0 tools and are considered very important but also abilities in which they have proficiency gaps. For Processes and Methodology, communication was a highly ranked topic in the PM Methodology, as indicated by 51% of surveyed sample in 2008 and 68% in 2009; also integration was listed by 44% of surveyed sample in 2008 and 57% in 2009. For Performance and Results, communication problems have been pointed out as probably the most important cause of deficiencies. It has shown a frequency of 58% in 2008 and 76% in 2009 in the list of the most common problems in PM. Focusing on KM practices, it is worth noting that, in the assessed aspect PMO, there are two of the functions performed by the PMOs that are directly connected to KM and that have deserved increased attention by the companies, as we com-
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Table 2. Most important abilities in PM Brazilian organizations (PMI, 2008 and 2009) “Selected” PM Important Abilities
2008
2009
chosen by
rank
chosen by
rank
Communication
71%
2
nd
41%
2nd
Team working
67%
3th
18%
9th
Knowledge on PM
59%
7
th
33%
3rd
Conflict Management
59%
7th
15%
10th
Capacity to integrate parts
54%
8th
25%
6th
Table 3. Deficient abilities in PM Brazilian organizations (PMI, 2008 and 2009) “Selected” PM Deficient Abilities
2008 chosen by
rank
chosen by
rank
Communication
47%
st
1
50%
1st
Conflict Management
41%
2nd
36%
2nd
Knowledge on PM
38%
rd
3
34%
3rd
Ability to integrate parts
36%
4th
29%
4th
Team working
14%
12th
11%
12th
pare the results of the two last surveys on Table 4. The evolution is a good indicator that knowledge management is finally attracting the attention of project managers. In the assessed aspect of Processes and Methodology, it is a current practice to generate a few documents that could be considered inductive or enabling of KM practices. Concerning the generation of documents making explicit valuable knowledge to be reused, the results of the last surveys showed that a sensible number of organizations are doing it (Table 5). Another important point of the Study refers to IT tools and software. It is shown that most of the Brazilian organizations don’t use Web 2.0 tools for managing their projects. The most used PM software is MS Project in standalone version (not web-based), used by 62% in 2008 and 60% in 2009 of the organizations. A very slow progress was made concerning this aspect.
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2009
Table 4. PMO functions in Brazilian organizations “Selected” PMO Functions
Organizations practicing it in 2008
in 2009
To keep, manage and disseminate project related knowledge
44%
76%
Training in Project Management
41%
77%
Table 5. Documents included in PM methodology in Brazilian organizations “Selected” Documents Included in the PM Methodology
Organizations doing it in 2008
in 2009
Discussed and recorded lessons learned
44%
54%
Communication plan
44%
58%
Formal client satisfaction evaluation
30%
40%
Web 2.0 and Project Management
However, just to show that the managers acknowledge the importance of the Web 2.0 tools, 48% in 2008 and by 54% in 2009 indicated that “web-accessibility” is a fundamental functionality that PM Software should provide. Corroborating with this finding, the Studies showed that many organizations don’t use integration tools and a unique data base in their PM software (45% in 2008 and 35% in 2009) and they also recognize this causes difficulties for managing their projects.
is only when it puts it into motion, which means kinetic energy, that the actual work and results are accomplished. It is also interesting noting that is in supporting these needs, making knowledge available at the point of use, that information and communication systems may play a role. Following on a discussion presented by Davenport and Prusak (1998) about the value chain built from data, information and knowledge, Alavi and Leidner (2001) stressed that:
Final Thoughts on the Panorama
A significant implication of this view of knowledge is that for individuals to arrive at the same understanding of data or information, they must share a certain knowledge base. (Alavi and Leidner, 2001).
The Brazilian panorama showed that the Project Management is not yet an area of “excellence” in Brazil. The results of the presented study showed that there are issues in PM that were considered very important and prone with inefficiencies (communication, capacity to integrate parts, team working, conflict management, knowledge on KM). Besides, most of the organizations recognizing those gaps have also indicated that they affect the results of their performances. It is also striking that 58% in 2008 and 76% in 2009 of the organizations believe that communication problems have been one of the main causes of deficiencies.
SUMMARIZING THE FRAMEWORK FOR OUR ANALYSIS Knowledge assets, because of their special characteristics (difficult to imitate and socially complex), may produce long-term sustainable competitive advantage. However, as pointed out by Alavi and Leidner (2001), it is not so much the existing knowledge per se at any given time, but the firm’s ability to effectively apply the existing knowledge to create new knowledge and to take action that form the basis for achieving competitive advantage from knowledge-based assets. One can make an analogy with classical mechanics, where a system can have a lot of potential energy, but it
In the same article the authors come again to the essence of this argument, quoted here: The inextricable linkage of tacit and explicit knowledge suggests that only individuals with a requisite level of shared knowledge can truly exchange knowledge: if tacit knowledge is necessary to the understanding of explicit knowledge, then in order for Individual B to understand Individual A’s knowledge, there must be some overlap in their underlying knowledge bases (a shared knowledge space) (Ivan and Linger, 1999; Tuomi, 1999). However, it is precisely in applying technology to increase “weak ties” (i.e., informal and casual contacts among individuals) in organizations (Pickering and King, 1995), and thereby increase the breadth of knowledge sharing, that IT holds promise. Yet, absent a shared knowledge space, the real impact of IT on knowledge exchange is questionable. (Alavi & Leidner, 2001). These initial considerations lead us to make an assessment of how the shared knowledge base of the project teams of our cases were considered by them as enablers or hampers of knowledge exchanges during the course of the project. Culture has also been identified, by many authors as a major catalyst, or alternatively, a major hindrance
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to knowledge creation and sharing in organizations. Therefore, our interest on the effectiveness of web 2.0 tools to help managing projects has to take into account culture issues. Beyond his definition of culture, Schein (1999, 2009) stated that culture can also be observed in terms of its outcomes. Therefore, it can be characterized as manifested behavior patterns, or consistent patterns, observed in a group of individuals or an organization. Pragmatically people say “our culture is the way we do things around here,” which means culture define the way people consistently perform tasks, solve problems and treat colleagues and clients. One way of exploring cultures is to classify them into types. Organizational culture may be differentiated in many ways. Goffee and Jones (1996), for example, identified four types of organizational culture, which they created by using two dimensions. They have used the lens of sociology distinguishing two dimensions of human relations: sociability, a measure of friendliness among members of a community, and solidarity, a measure of a community’s ability to pursue shared objectives. Combining the classification according to these two dimensions, in a high-low scheme, it results in four types of business community: networked, mercenary, fragmented, and communal (Figure 2). The authors say that none of these cultures is “the best.” In fact, each one is appropriate for different business environments. To classify the culture, a questionnaire with seven closed questions for each dimension is suggested in the reference. We have found this approach adequate for our purposes, but have slightly adapted the questionnaire to better fit the questions to project teams. The content of the questionnaire that we have used is described in following. a. Potential usefulness: on the demand side, the Brazilian PMI study has indicate the five most important and also, to some extent,
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Figure 2. Two dimensions, four culture types (reproduced from Goffee and Jones, 1996)
lacking abilities. Our review of the literature and our experience indicate that web 2.0 components have a good potential to leverage such abilities. Therefore the first part of the questionnaire poll the opinion of the participants concerning which web 2.0 components can support/help the deployment of the abovementioned abilities, as the best of their knowledge today. b. Culture assessment: to appraise the importance of culture we have use fourteen questions as commented above and just one question to get an idea of the suitability of the common knowledge basis. c. Usefulness in the case: to check if the experience they have had in the case matches what they think today, the same set of questions (as in the first part of the questionnaire) is also asked concerning their experience in the case they have participated. d. Further use: finally to see if their use of web 2.0 in a project setting was just occasional or if it is evolving positively a set of three questions is asked to know what happens after the case project. In addition to the questionnaire, a couple of interviews and a review of the project manager notes taken during the course of the projects was
Web 2.0 and Project Management
undertaken to give substance to our qualitative analysis and get deeper insights from this triangulation (questionnaire – interviews – observations). There is a limited literature assessing the benefits of web 2.0 tools for project management and almost all of them fall within realm of the construction industry. Also all studies have taken place or have used data from OECD countries. Given the opportunity of our experience, real cases of applications in different industry sectors in a developing country, we felt it would be useful to do a case study analysis on the backdrop of the theoretical and practitioners’ viewpoints found in the existing literature. Case study research has many meanings, but according to Dul and Hak (2008, p. 4), one very distinct aspect from other research strategies is the fact that a case study basically is an inquiry of only one single instance (the case), or sometimes a small number of instances, of the object of study. Another important characteristic is that it copes with the distinctive situation in which there are more variables of interest than data points. We then have to resort to multiple sources of evidence, with findings being the result of convergence in a triangulating fashion. As pointed out by Yin (2003, pp. 5-7), case study methodology allows retaining the holistic and meaningful characteristics of real life events and were the best fitted option for our research concerned with contemporary events and focused on questions of what, how and why types. Most researchers think that case study can only be used for exploratory purposes, but the same author Yin (2003, p. 16) defends the possibility of using case studies for generalization. Many cases should be used for this purpose. In our work we have favored the use of multiple case research design, because the opinion samples were not large. Dul and Hak (2008, p. 5) went on to say that a “case study draws conclusions on the basis of a “qualitative” analysis (“visual inspection”) of scores from one single instance (single case study) or from a small number of instances (comparative
case study), whereas the survey draws conclusions on the basis of a quantitative (statistical) analysis of data from a population with a large number of instances. We have targeted a combination of description and exploratory explanations of suggested relations among the variables under study. The choice of the cases was guided by the representativeness of the research material in terms of our experience, diversity of settings and team size and project duration. The intention to undertake a cross case analysis to attempt some meta-explanatory comments lead us to use more than one instrument and we chose triangulation.
CASES OF OUR EXPERIENCE Three cases, dating from 2003 up to 2009, are described and analyzed in this section. The idea is to show how the use of web 2.0, in a complementary fashion to other project management tools, have coped with difficulties that would be hard to be dealt with otherwise. A short profile of projects’teams and the quantity of people who have answered the questionnaire is shown in Table 6. Although the projects were done in three different industry segments, the scope of the work felt in the same field of software system development and deployment. The composition of the involved people differ somewhat across the cases form a 100% TI team to a 39% share. To assess how this can influence the familiarity and proficiency with web tools, an introductory quesTable 6. Projects’ teams’ profile TI people
Other areas
Total
Polled
22
14
14
23
10
Ensurance Co.
22
Petroquisa
9
Vivo
10
8
18
13
Total
41
22
63
37
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Web 2.0 and Project Management
tion was included. Figure 3 shows these results, where all the respondents have declared advanced (78%) or at least intermediate familiarity with web tools. It is apparent that the composition might be an explanation for the above results. For all of the cases the same description pattern will be followed: (a) project summary with scope description, some short technical information, project size and period, number of participants, budget and time line; (b) Potential and practical uses of web 2.0; (c) Comments from project managers and team members. For item (b), we display and discuss the results of parts (a) and (c) of the questionnaire, as described in the section “Summarizing the Framework for our Analysis.” Two figures are presented there, the first is a frequency-column graph of five categories covering the web 2.0 components and five series covering the PMI issues and we have chosen to use frequency in absolute numbers instead of percentages. The second figure is used to compare potential and experienced usefulness, it is similar to the first, but since the project cases have used only blog and wiki, only four series were needed in the second graph. When discussing questionnaire results we have tried to maintain the same pattern to facilitate cross-case analysis. Project managers and team members’ comments were collected during interviews, mostly done by the
Figure 3. Prior Web knowledge of the participants
176
phone, and performed with some advance before the survey was sent to avoid short memory pseudo-consistency.
Implementation of Digital Document Management and Workflow Systems in a Telecommunication Company (Vivo) Vivo is the leader cell-phone company in Brazil since its creation in 2002, as a result of the joint venture between Portugal Telecom and Telefonica (Spain). The company covers more than 2,900 Brazilian municipal districts, it is the largest company of this sector in the country and also the largest group of cellular telephony of Southern Hemisphere. (www.vivo.com.br).
Project Summary It consisted of the Implementation of a Platform for Managing Corporate Documents in an Enterprise Document Management System (EDMS), for both technical and administrative documents. This corporate system was thought of as a scale up, in size and scope, of a previous system recently deployed at a branch of the company located in the state of Bahia. The project should provide team integration across different areas of the company
Web 2.0 and Project Management
(marketing, communications, engineering and IT) to generate and deliver on time products and services to end customers. Two project managers, one from Vivo and another from Xerox, plus 16 project team members and 32 technical consultants were involved in this project. The budget was around US$ 1 million and the timeline has run from 2003 to 2005. Figure 4 shows an overview of system architecture.
Potential and Practical Uses of Web 2.0 Ideally the respondents find web 2.0 tools very useful for addressing the five issues raised by the Brazilian PMI survey, as it is shown in Figure 5. Communication is the issue with the highest gain from web 2.0, and it is closely followed by conflict management, team working and knowledge in project management (with less than 10% frequency difference). Concerning the tools from a maximum possible of 65 hits, we observe that social networking (59 hits) and blog (58) were the most praised, followed by wiki (50); on the low end there is tagging (18) and RSS (5). It is worth noting that as a means to acquire knowledge in project management none of the tools were considered very valuable, except that of social networking (Figure 6).
Wiki has matched its expectation for communication and team working. It also performed well concerning conflict management, but has fallen 33% short of its expected number of hits regarding the capacity to integrate parts. Surprisingly it was thought to be of a superior performance when the question was of knowledge in project management. Blogs have matched their expected recognition as a way to acquire knowledge in project management and have presented a good performance to communication and team working, but have fallen 32% and 46% short of its expected number of hits, respectively, as a lever for conflict management and capacity to integrate parts. As we can see in Figure 13, this case was the one with the weakest initial project team common knowledge basis, as they have ranked it as very low (69%) and low (31%). During the project they have relied heavily on the wiki to build lessons learned, which was also a way to build their common knowledge basis. When asked specifically about the usefulness in the real case but not as they see it today for other projects, they pointed out that: (a) the scope of the project has caused the team to consist of people from different parts of Brazil with different working process backgrounds; and (b) they had a lot of catching up to do in order to have people “speaking the same language”
Figure 4. System architecture overview
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Web 2.0 and Project Management
Figure 5. Potential usefulness of web 2.0 components to address the Brazilian PMI issues (Vivo)
and they found wiki very handy for this purpose. Those comments are consistent with the fact that the most surprising performance item was exactly on the issue of knowledge in project management.
•
Comments on Web 2.0 Use
•
•
Project Managers’ Comments. •
Better perception of what people understood about the project, throughout discussion over blogs and forums.
•
Clear feedback process from team members and global vision of who was involved in each process*. Project risks could be better understood and shared*. Better perception and agility to cope with the impacts of tasks done by teams of different companies over the whole project thread*. Communications, in general, were more effective than when only done by e-mails.
Figure 6. Potential vs. observed usefulness of wikis and blogs at Vivo
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Web 2.0 and Project Management
Team Members’ Comments on Web 2.0 Use
Project Summary
•
A fast Implementation and deployment of all subsystems of MySAP R/3, for the eight months of the project implementation stage and the subsequent seven months of face-to-face support. ASAP methodology and “big-bang” model (all subsystems at same time) were used to meet the deadlines. The project’s objective was to allow Petroquisa to speed-up the incorporation of new and better practices to its business processes, ensure reliability of information and increase control and availability of information to a more efficient enterprise management. Two project managers, one of each company, plus 21 team members and 48 technical consultants were involved in this project, the budget was around US$ 500,000 and the timeline was from 2005 to 2006.
•
•
•
The improvement of the communication within the group was rated as the greatest benefit when using the Web 2.0. Improved collaboration between remote teams and more agile answers to questions posted helped the success of the project. More transparency caused problems to be more easily detected and increased the accountability of teams and managers. In some occasions, the extra visibility of the team performance was a scaring and perhaps counterproductive factor.
The comments are, for the most part, aligned with our previous conjectures and the results of the polling. The three comments from project managers marked with asterisks can be seen as a confirmation of the perceived benefits concerning the issues of conflict management and team working. As for the team members’ comments, one can see: first, a direct ratification of the benefits perceived for communication; second, a direct link with team working; and third, an association with conflict management.
Implementation of SAP: EnterpriseWide Resource Planning in a Large Petrochemical Industry Using ASAP Methodology The Project was implemented at Petroquisa, a subsidiary Petrobras S.A. that account for the chemistry and petrochemistry sectors. Petrobras is a corporation of open capital whose major shareholder is the Brazilian Government. It is the largest company of the country and 8th of the world in market value. (www.petroquisa.com.br and www.petrobras.com.br).
Potential and Practical Uses of Web 2.0 The drivers of project governance were defined by the methodology developed by SAP (ASAP methodology - Accelerate SAP), a roadmap of project phases was followed. Web 2.0 components were used mainly for creating process documentation and information spreading and validation. Wikis helped non collocated teams to consistently generate documentation. Besides e-mails alerts, notifications about new and edited documentation were posted on the website of the project. A weekly blog with fresh information of project and status report on its development was also used. As soon as the teams were finishing phase documentations, they were loaded into a repository whose structure is shown in Figure 7. Then comments were posted in the blog and warning messages were sent to the persons involved. Depending on the category of the document, a web workflow was followed to accelerate the approval.
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Web 2.0 and Project Management
Communication ranked first when the benefits of the use of Web 2.0 tools were listed by the project’s participants. It was closely followed by team working and conflict management with less than 14% of frequency difference. Capacity to integrate parts and knowledge in project management were equally appraised and within 18% of difference from the top one. Concerning the tools from a maximum possible of 50 hits, we observe that social networking (46 hits) as the best appraised one, followed by wiki (42) and blog (41) (Figure 8). Both tagging and RSS received zero hits. It is worth noting that unlike the previous case there was not a clear preference on the tool choice of any particular issue category. Comparing potential versus observed usefulness (Figure 9), there are a couple of points to be noted. The use of a Blog matched its expectation for communication and capacity to integrate parts and it also performed close to what was expected on team working and knowledge in project management, but it has fallen 40% short of its expected number of hits as a lever for conflict management. Wiki had a performance close to its expectation for all items. Figure 7. Document structure
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There were no surprising results in this case. Looking at Figure 13, this case indicated a somewhat better initial project team common knowledge basis than the previous one, but its weakness became clear with the low (80%) and high (20%) numbers.
Comments on Web 2.0 Use Project Managers’ Comments • •
•
•
Improved integrated vision of the methodology and concepts learning. Agility in managing the development of the project by controlling documentation and phases via project web site, blogged news and message notifications. Project risks awareness and full understanding of the consequences could be easily shared. Better perception of agility and impacts of tasks done by teams from different companies over the whole project timing.
Web 2.0 and Project Management
Figure 8. Potential usefulness of Web 2.0 components to address the Brazilian PMI issues (Petroquisa)
Figure 9. Potential versus observed usefulness of wikis and blogs at Petroquisa
Team Members’ Comments • •
•
Better communication with sponsors. Visualization of support and collaboration among teams by their posted comments in order to help the resolution of the project’s technical problems. If on the one hand team accountability increased because their contents were ex-
•
posed by web reports, and therefore deadlines couldn’t be changed and the sponsors could read them at anytime. On the other, it took some time to develop a web 2.0 culture until all of the team’s members became familiar with the web 2.0 tools. The online exposure of work progress caused a great deal of anxiety and anticipated charging.
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The comments reinforce our previous conjectures and are aligned with the results of the polling. Project managers’ comments indirectly highlight communication improvement, directly address topics related to team working, capacity to integrate parts and knowledge in project management. As for the team members’ comments, there is significant coincidence with the previous case, which means emphasis of the benefits first for communication; second, for team working; and third, for conflict management. This time, however, they also send a cautionary message in the sense that anxiety and anticipation of checking could generate other problems.
Development of High Availability Database Solution for an Insurance Company The organization where the project was done did not give us permission to disclose its name in the publication.
Project Summary To design and implement database solution to replicate data and provide high availability of data systems located in two geographically different datacenters. The project was considered of high technological complexity since it would demand expertise from all the companies involved in order to: integrate three different technology suppliers (Microsoft, Global Crossing and Telefônica); develop a compatible hardware and software solution; and fully test the application. Four project managers plus 18 project team members and 59 technical consultants were involved in this project. The approximate budget was of US$ 4 million and the timeline was from 2008 to 2009. The core of the project involved the replication of the entire production environment. So, a play safe approach was chosen which required hardware and software to be identical to avoid loss of application functionality and performance
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problems in case of switching from one environment to the other. From a practical operational point of view, two segmented database sets were considered, one at Telefônica and another at Global Crossing—each one focused on their current customers’ portfolio. A contingence element (Database Mirroring) was added in a way that each database would have its own contingence base in the complementary site, Figure 10.
Potential and Practical Uses of Web 2.0 The web 2.0 tools were used to detect and record risk occurrence, to activate the communication plan and workflow for synchronizing activities. Also wikis were used to document lessons learned among the companies for process improvement of the following phases, risk qualification and closing of additional scope. The Governance scheme using web 2.0 was established during the project planning. Figure 11 shows the results that are somewhat close to those of the previous cases. Communication is once again the top pick, closely followed by team working, capacity to integrate parts and knowledge in project management, equally appraised and within 15% apart from the top one. The dissonant note was attributed to conflict management with just 57% of the hits awarded to communication. Concerning the tools from a maximum possible of 70 hits, we observe that wiki (70 hits) was a unanimous choice, social networking (67) came as a close second and blog (56) was third. On the low end there is tagging (10) and no hits for RSS. A striking difference here is that they did not see any utility in the use of blogs for project management. Looking at Figure 12, we notice that neither blog nor wiki has fulfilled its expectation for any of the PMI issues. In general wiki has performed closer to its potential value than blog and on average this group of respondents indicated a somewhat greater gap between expected and
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Figure 10. The implemented system
delivered value. A possible explanation is the fact this was the group that indicated the best initial project team common knowledge basis 71% high and 29% low and as such they did not have use those tools for catching up like the other teams.
Team Members’ Comments on Web 2.0 Use
Comments on Web 2.0 Use
•
Project Managers’ Comments on Web 2.0 Use • •
•
Better agility concerning communication. Better alignment between teams, despite of the fact that they worked for different companies. Collective mobilization on evaluating and managing risks.
•
• •
•
Better and more agile perception of the impacts of tasks done by teams of different companies over the whole project timing.
Better communication of what should be done and visualization of impacts of activities that followed. Better collaboration to solve technical questions. More pressure to finish of activities on time. Sometimes the work load was exhaustive to meet the schedule. Performance visibility caused a lot of anxiety and, sometimes, backfired as a motivation factor.
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Figure 11. Potential usefulness of web 2.0 components to address the Brazilian PMI issues (Insurance)
Figure 12. Potential versus observed usefulness of wikis and blogs at an insurance company
•
People perceived higher working needs then predicted in the schedule. The commitment to deliver and the easy access to the work environment, from anywhere, were perceived as catchy and people worked more hours than they were used to.
Here one can note a significant coincidence to the emphasis placed by both managers and team members on communication and team working.
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Managers also indirectly address possible benefits to the capacity of integrating parts and conflict management. While acknowledging its benefits to the entire work, team members send warning messages concerning anxiety and a possible overload, for people spent more time on it, as they were “logged on” all the time. They added more weight to the possibility of backfiring their use if “too much of it” got into the project culture.
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Summing Up the Analysis Most of our analysis is aimed at dissecting the cases individually and then cross analyzing the findings, trying to explain similarities and differences based on the characteristics of project teams. The choice of these characteristics was based on the reviewed literature. Unfortunately, the use of quantitative methods, even simple descriptive statistics, is not very meaningful because of the size of our samples. Let us deepen this argument. Suppose that I want to use the value of the mean to make some argument and I want to use the requirements that: (a) the acceptable sample error be of one standard deviation; (b) for an error probability of 5%; and (c) the confidence interval (or sample power) be 95%. The needed sample size would be 16, in this case. We can also use the freeware G*Power (Erdfelder et al., 1996) to make up a table to give us a better feeling of what we are able to achieve with the sample sizes that we have (Table 7). Despite being of significant sizes with respect to the targeted population, that is, of 72%, 43% and 64%, respectively, the samples do not have the statistical power to satisfy the usual requirements for a solid quantitative analysis. For these reasons, we have worked only with categorical and ordinal variables. The only exception was for the culture classification graph where we have assumed an interval variable for the aggregated sociability and solidarity scores, for the purposes of producing a bubble graph. Table 7. Sample size for 5% error probability (sample error expressed in standard deviations) Confidence interval std sample error
90%
95%
0.5
44
54
0.8
19
23
1.0
13
16
1.2
10
12
It must be pointed out that we have used careful wording in a way to induce the respondent to think of an interval scale. In the future, if we manage to expand the sample, a quantitative analysis can be undertaken. Regarding budget, all of the projects fit into the medium to large size category group if we follow the same division of the Brazilian PMI survey, Table 2. Team size and time span were also not so different for all of them. According to the PMBOK (PMI, 2004) managing a project includes, among other things, to balance competing project constrains such as: scope, quality, schedule, budget, resources and risk. The way project owners and their representatives manifest their requirements and make their emphasis clear have implications on culture manifestations of the project’s team. Therefore we will discuss noticeable differences and similarities concerning the most important competing constrains, for each project, based on project managers’ notes and interviews.
A Small Extract from the Project’s Managers’ Notes The Vivo project had a large breath of scope, but not a very complex one, because it was a scale up. It was contracted on fixed price basis and therefore the pressure on schedule was upon the main supplier/contractor. Quality has also been emphasized by the owner and was considered a top priority in balancing the competing constrains. The deliverables of this project had strong connections with the delivery of services and products to clients. The project’s performance could directly affect the perception of quality by the company’s clients. The Petroquisa project was somewhat narrower in scope and also of low complexity, with mostly standard modules and very little customization. The project was contracted on a time-materialworkload fashion, so the owners were very emphatic regarding the schedule to avoid extra costs. Project deliverables were related to the
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Figure 13. Common knowledge basis at the onset of the project
improvement of internal processes and were not connected to clients and had also a frail link with the company’s operation. The insurance company case had a large and complex scope. It was also contracted on a fixed price basis. Quality, especially for items related to system availability and stability, was highly emphasized by the owners, as the deliverables would play a role in critical tasks of the company’s operations. The burden on schedule was transferred to the main contractor (systems integrator), because delays would reduce his profit margin.
Figure 14. Culture classification according to Goffee and Jones scheme (1996)
Final Comments Figure 13 shows how the teams have classified their initial common knowledge basis. The insurance company had the highest and Vivo, the lowest. Comments on how it could influence their responses have already been made, when commenting the cases’ results. As for culture, all of the groups are classified in the same quadrant (communal) with a high display of sociability and solidarity characteristics. Vivo is further to the top, followed by the insurance company and Petroquisa, more distant somewhat.
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One can spot some patterns relating to culture classification of the group’s answers (Figure 14). General outcomes: for the general manifestations, it becomes clear from observing all of the graphs that, the more communal the culture is, the smaller is the spread of opinions within the group. Potential usefulness: looking at the graphs, a similar pattern is suggested as groups with more communal culture tend to find more potential uses. Experienced uses: no general pattern emerged here from the potential versus the real graphs.
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Overall, the comments made by the groups were aligned with our previous conjectures and the results of the polling. The comments extracted from project managers’ notes also shed some light on the more significant differences, as it has been commented on the analysis of each case. Finally with regard to the further of web 2.0, the 37 respondents have unanimously agreed that they are using more intensively, in more projects and more tools besides blogs and wikis.
CONCLUSION Most of the so called web 2.0 principles are consolidated, but they will yield or evolve into more advanced and fit strains. A cultural transformation is in course and, like some biologists would say, the bee is not the sustainable organism, the beehive is. Web 2.0 services and applications are not targeted at individuals, but at the crowd. Project management applications and services for, or related to, the construction industry seem to have jumped ahead if compared to other business fields in terms of value adaptation to the web 2.0. The current literature and also the impressions gathered from users’ experiences of project management 2.0 indicated that there is no coming back, but instead they want more, both in depth as in breadth. Our case studies, in Brazil, have shown a great potential of web 2.0 components to cope with the five most important issues raised by a countrywide PMI survey. Also for Blogs and wikis that were used in project cases, their experienced usefulness was near expectations. Culture characteristics seem to explain some tendencies manifested in the answers and on free willing commentaries from case participants. We suggest a confirmatory quantitative study covering other areas of work scope, to consolidate or change the exploratory findings described here.
REFERENCES Alavi, M., & Leidner, D. E. (2001). Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. Management Information Systems Quarterly, 25(1), 107–136. doi:10.2307/3250961 Alshawi, M., & Ingirige, B. (2003). Web-enabled project management: An emerging paradigm in construction. Automation in Construction, 12, 349–364. doi:10.1016/S0926-5805(03)00003-7 Bannan, K. J. (2007). Social climbing. PM Network, 21(12), 40–46. Chassiakos, A. P., & Sakellaropoulos, S. P. (2008). AWeb-based system for managing construction information. Advances in Engineering Software, 39, 865–876. doi:10.1016/j.advengsoft.2008.05.006 Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Cambridge, MA: Harvard Business School Press. Dul, J., & Hak, T. (2008). Case study methodology in business research. Burlington, MA: Butterworth-Heinemann, Elsevier. Erdfelder, E., Faul, F., & Buchner, A. (1996). GPOWER: A general power analysis program. Behavior Research Methods, Instruments, & Computers, 28, 1–11. doi:10.3758/BF03203630 Filev, A. (2006). Social project management or project management 2.0? Retrieved May 11, 2010, from www.wrike.com Ford, J. (2000). Employee attitudes and characteristics. In J. Ford & Associates (Eds.), Conflict management: Facts and figures. Retrieved October, 2010, from http://www.mediate.com/johnford /factsignup.cfm?fuseaction=done&CFID =36146071&CFTOKEN=25453300
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Goffee, R., & Jones, G. (1996). What holds the modern company together? Harvard Business Review, 74(6), 133–148. Hoffman, T. (2009). 9 hottest skills for 2009. Computerworld, 43(1), 26–27. Kamara, J. M., Anumba, C. J., Carrillo, P. M., & Bouchlaghem, N. M. (2003). Conceptual framework for live capture of project knowledge. In R. Amor (Ed.), Construction IT: Bridging the distance, Proc. CIBW078. International Conference on Information Technology for Construction, Waiheke Island, New Zealand, 23–35 April, 2003 (pp. 178–185). Lévy, P. (1997). Collective intelligence: Mankind’s emerging world in cyberspace (trans. R. Bononno). New York, NY: Plenun Trade. Nitithamyong, P., & Skibniewski, M. (2004). Web-based construction project management systems: How to make them successful? Automation in Construction, 13(4), 491–506. doi:10.1016/j. autcon.2004.02.003 O’Brien, W. J. (2000). Implementation issues in project websites: A practitioner’s viewpoint. Journal of Management Engineering, 16(3), 34–39. doi:10.1061/(ASCE)0742-597X(2000)16:3(34) Project Management Institute (PMI). (2004). Um Guia do Conjunto de Conhecimentos em Gerenciamento de Projetos (Guia PMBOK) 3rd ed. PA, EUA. Retrieved June, 2010, from http:// www.pmi.org.br Project Management Institute (PMI). (2008 & 2009). Estudo de Benchmarking em Gerenciamento de Projetos 2008 e 2009: Relatório Principal – Perspectiva Geral. Project Management Institute – Chapters Brasileiros. Retrieved June, 2010, from http://www.pmi.org.br
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Rojas, E. M., & Songer, A. D. (1999). Webcentric systems: A new paradigm for collaboration engineering. Journal of Management Engineering, 15(1), 39–45. doi:10.1061/(ASCE)0742597X(1999)15:1(39) Sawyer, T. (2001). Research new survey points to spending growth. ENR: Engineering NewsRecord, 246(21), 21. Schein, E. H. (2009). The corporate culture survival guide, new and (revised ed.). San Francisco, CA: John Wiley & Sons. Scott, D., Cheong, M. K. W., & Li, W. (2008). Web-based construction information management systems. The Australian Journal of Construction Economics and Building, 3(1), 43–52. Speakman, J., & Ryals, L. (2010). A re-evaluation of conflict theory for the management of multiple, simultaneous conflict episodes. The International Journal of Conflict Management, 2(2), 186–201. doi:10.1108/10444061011037404 Tan, H. C., Udeja, C. E., Carrillo, P. M., Kamara, J. M., Anumba, C. J., & Bouchlaghem, N. M. (2004). Knowledge capture and re-use in construction projects: Concepts, practices and tools. Loughborough University. ISBN: 1 897911 28 9 Thamhain, H. J., & Wilemon, D. L. (1986). Criteria for controlling projects according to plan. Project Management Journal, 17(2), 75–81. Udeaja, C. E., Kamara, J. M., Carrillo, P. M., Anumba, C. J., Bouchlaghem, N., & Tan, H. C. (2008). A Web-based prototype for live capture and reuse of construction project knowledge. Automation in Construction, 17, 839–851. doi:10.1016/j. autcon.2008.02.009 Winans, T. B., & Brown, J. S. (2009). Cloud computing: A collection of work papers. Deloitte Center for the Edge. Retrived May, 2009, from http://www.johnseelybrown.com /cloudcomputingpapers.pdf
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Yin, R. K. (2003). Case study research – Design and methods. California, USA: Sage Publications.
ADDITIONAL READING Argote, L., McEvily, B., & Reagans, R. (2003). Managing knowledge in organizations: An integrative framework and review of emerging themes. Management Science, 49, 571–582. doi:10.1287/ mnsc.49.4.571.14424 Cummings, J. N. (2004). Work groups, structural diversity, and knowledge sharing in a global organization. Management Science, 50, 352–364. doi:10.1287/mnsc.1030.0134 Project Management Institute (Ed.). (2001). People in Projects. Pennsylvania, USA: PMI Inc. Terra, J. C. (Ed.). (2009). Gestão 2.0: Como integrar a colaboração e a participação em massa para o sucesso nos negócios. Ed. Campus & Elsevier, R.J., Brazil.
KEY TERMS AND DEFINITIONS Analysis Framework: A mental construct that synthesizes the supporting theories, relate them to the authors’ hypothesis and research instruments, providing the roadmap for the targeted research. Common Knowledge Basis: Within a project, it means the core common knowledge
that all participants must have in order to allow communications and knowledge to flow among them with minimum amount of ambiguity or misinterpretation. Knowledge Management 2.0: In essence means managing knowledge in light of the web 2.0 is making available. It has to be described and appraised from both the technological and sociocultural viewpoints. So it is an evolving concept. Organizational Culture Classification: A way of differentiate culture types for a given use or research, here two factors (sociability and solidarity) and seven indicators for each was used. Within a group, sociability measures the friendliness among members and solidarity the commitment to pursue elected goals. Project Management 2.0: Means both the use of web 2.0 services and applications to project management and a new mind frame in managing projects. Among other things, it involves taking advantage of flexible working schedule, many-to-many communication, agile decisions, thoughtful self-coordination and clever ways of managing teams. Web 2.0: Is associated with concepts of: (a) the internet as the platform business operations inter and intra organizations; (b) building and deploying applications that harness network effects to get better the more people use them. Web-Based Project Management: It means to use tools and systems that operate over the web to manage projects.
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Chapter 10
The Evolution of KM Practices: The Case of the Renault-Nissan International Strategic Alliance Nabyla Daidj TELECOM Business School, France
ABSTRACT The objective of this chapter was to understand how a “hybrid organization” (two automobile manufacturers Renault and Nissan within a strategic alliance) uses social networking and Web 2.0 tools to collaborate not only inside traditional organizational boundaries and within the alliance structure but also across geographical frontiers. Nissan has gradually lost its historic status as keiretsu as a result of its strategic alliance with the Renault. This alliance has had numerous consequences for the organizational structure of Nissan, even though both companies have maintained their identity by maintaining the two brands internationally. KM practices have evolved since the beginning of the strategic alliance. Two phases can be considered. During the first three years of the alliance, the two car manufacturers relied mainly on their own specific KM practices and processes. The second phase started in 2004 with the development of KM 2.0 and Web 2.0 tools. The adoption of these tools by Renault has led to increased collaboration between the two manufacturers.
DOI: 10.4018/978-1-61350-195-5.ch010
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The Evolution of KM Practices
INTRODUCTION Competitive advantage is no longer completely dependent on capital and equipment; information and knowledge assets are increasingly important. More and more value generation lies in distribution, financing, marketing and service rather than manufacturing products. Knowledge and the potential of ICTs penetrate every step of the value chain. The result is a new challenge to the practice of management. Knowledge Management (KM) is a set of techniques and tools to uncover and utilize information and knowledge assets—especially tacit knowledge. KM 2.0 is a new step. Companies are undergoing another transformation toward “socialization,” as new usages of information and knowledge sharing emerge. KM 2.0 practices can be used to enhance external knowledge sharing among the network (alliance, business ecosystem) and to capture and share tacit knowledge within an organization with several consequences on value chains. Successful companies are becoming more networked in a fiercely competitive environment. Few industries have a greater reliance on knowledge management than the automotive sector. This industry concentrates a huge quantity of information in several areas because the processes involve thousands and thousands of documents and facts. It is one of the reasons explaining our choice to examine, in this chapter, the evolution of knowledge sharing, KM practices, at Nissan, which is a “Japanese” car manufacturer. This case is interesting because since the end of the 1990s Nissan has undergone drastic changes in terms of organisation and production methods. Nissan was considered for many years as a vertical keiretsu. Vertical keiretsu (manufacturing) are vertical groups of companies that are more or less independent from one another (small subcontracting firms, suppliers and equipment manufacturers) but are under the umbrella of a prime manufacturer. They are quite common and above all are well-represented in cars (Nissan,
Toyota). But the Japanese recession in the 1990s had profound effects on the keiretsu. In addition, cross-borders M&A and strategic alliances with foreign partners in the 1990s have reshaped the Japanese automotive industry. It is within this context that in 1999 Nissan and Renault have entered into a strategic alliance. This alliance married two culturally different parties. Another major challenge to large automotive firms engaged in alliances is, then, the diffusion throughout the firm of the capability learning from a partner and the diffusion of knowledge management practices (from KM to KM 2.0). It is precisely this issue we propose to analyse in this chapter. The structure of the chapter is as follows: the next section (1) presents the historical and economic development of Nissan keiretsu. The Renault-Nissan strategic alliance is described in section 2. The following Section (3) deals with the impact of the strategic alliance on the evolution of knowledge management practices. The chapter concludes with a summary of the chapter’s argument and some implications.
THE NISSAN KEIRETSU: AN HISTORICAL RETROSPECT The history of the automotive industry in Japan and the main automotive manufacturers (Toyota, Honda, and Nissan) during the last half century has been shaped by the existence of keiretsu defining the boundaries for the players’ behaviours.
From Zaibatsu to Keiretsu: Historical Background Whether called zaibatsu or more recently keiretsu, corporate groupings have been a distinctive part of Japanese industry for decades. The keiretsu has its origins in the Meiji era. At the end of the 19th century, the Meiji government accelerated the industrialisation of Japan by creating family-controlled large industrial and
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financial enterprises (banking, insurance, mining, shipbuilding, manufacturing of cement, paper) known as the zaibatsu. These giant conglomerates, controlled by ten families (or clans), became the drivers of the pre–World War II Japanese industry and economy. They were very powerful groups (among them Mitsubishi, Mitsui, Sumitomo and Yasuda) and were involved in industries such as steel, shipbuilding, international trading and banking. During World War II, zaibatsu produced a large part of the country’s weaponry. In addition, they were seen to be monopolies by the Americans after the war. Consequently, between 1946 and 1948, following the American occupation forces, the zaibatsu dissolution program was imposed by different laws. But in the end of the 1940s, the allied forces changed policy. This resulting change in occupation policy is often called the “reverse course” focusing on the economic recovery and political rehabilitation of Japan. Consequently, to prevent the weakening of its economy, the Japanese government concerned with concentrating on scarce industries crucial to Japan’s long-term economic security encouraged a re-formation of the old zaibatsu, to be known as keiretsu. Several keiretsu emerged from the zaibatsu, whereas others were new groupings of companies.
Horizontal vs. Vertical Keiretsu Most large Japanese firms have links with affiliated companies with which they form a system called keiretsu. There are mainly two types of keiretsu (Miyashita & Russel, 1994), which may be horizontal (conglomerate) or vertical (many suppliers – subcontractors under the “umbrella” of a large industrial firm): •
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Horizontal (financial) keiretsu include a large number of major companies belonging to a wide range of unrelated industries with common ties to a main and powerful bank (shuryoku ginkô). The main bank pro-
•
vides debt financing to member firms with favourable conditions (low interest rates, long term loans) and owns large amounts of their common stock. Vertical (“production” or non financial) keiretsu are quite different. They represent a pyramidal structure of intercorporate equity holdings. They are generally industrybased (mainly in manufacturing such as automobile, steel and electronics industries but also in trading activities and financial services) with a large manufacturing company having equity (controlling in some cases affiliated suppliers) and other links to firms up and down the “production chain” and along the value chain.
The Organisational Structure of Vertical Keiretsu The spectacular growth of Japan originated partly from keiretsu. Keiretsu and more specifically ‘vertical keiretsu’ have been widely recognized as an important source of strength for Japanese industries. They contributed largely to boost post Second World War Japanese growth. They were a key feature of Japan’s economy, affecting directly or indirectly economic transactions within and across industries. They also structured the Japanese industrial system. They can be analyzed as both an organizational phenomenon and a means which has enabled Japanese firms to expand their production capacities, their competitiveness and their exports growth (Aoki, 1988) until the 1990s. The following characteristics of keiretsu can explain Japanese economic success.
A “Pyramidal” Structure Based on Long Term Agreements and a Nexus of Relationships Vertical keiretsu represents a group of independent firms developing complementary resources (human, technological) and competencies, orga-
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nized around a prime manufacturing company, the main company (motouke). The cohesion of the keiretsu is based on a long term commitment between the main manufacturer and other firms and on regular (formal and informal) relationships (supply chain, production, financial, commercial) between members. The economic logic is based on mutual trust and self-enforcing commitments. The contracts are generally determined for several years and are adjusted every six months depending on economic evolution and the respect of quality and cost conditions by subcontractors. They help to ensure consistent and reliable quality, dependable delivery etc. The supply structure, following the keiretsu model with 1st, 2nd and 3rd tier suppliers, has been widely imitated by a large number of manufacturers worldwide. These trends have been encouraged by several factors: •
•
•
•
The widespread use of “project-management” organisational modes related to new processes, also called simultaneous or concurrent engineering (Leclerc et al., 1997) ; Production methods (just-in-time, Toyotism), fewer total platforms, also design systems with increasingly short lead-times; A conception of cars seen as a systemproduct (Clark & Fujimoto, 1991) resulting from the assembly of many components; The shift from a manufacturing system based on vertical integration toward the externalisation of a large part of design, manufacturing and module assembly activities entrusted to the equipment manufacturers.
Network, Culture and Tacit Knowledge The influence of culture in the knowledge transfer process has been analysed by different authors such as Hofstede (1991). Culture represents the values and beliefs that individuals of a same organization share. It defines how individuals are involved in
the company and what is relevant for learning (Schein, 1992). The knowledge management must be founded on a culture of sharing information. According to Marchand (1999), it can be defined as values, attitudes and behaviours that influence the way to collect, organize, communicate and use information. A strong culture of sharing information allows one to increase information flow and to resolve issues of loss of power. The level of sharing is then determined by the collaborative climate that prevails (Sveiby & Simons, 2001). In addition, Kaweevisultrakul and Chan (2007) identified four ways in which culture influences knowledge-related behaviour. •
•
• •
Culture influences the perceived usefulness and the importance of valid knowledge within an organisation; Culture determines whether knowledge remains under the control of individuals or if knowledge belongs to the organisation; Culture creates a context for social interaction; Culture shapes the creation and adoption of new knowledge.
Within Keiretsu, culture is one of the key factors explaining knowledge sharing and transfer issues. Many observers have praised Japanese firms’ ability to share knowledge within and among themselves. However, there are, arguably, differences in the learning that occurs within a Japanese firm (or related ones), and the learning that takes place in Silicon Valley. Ideas seem to circulate in Japan through more structured channels, such as those organized around membership in a firm, university, or high school alumni associations. Keiretsu, or keiretsu-type relationships, as well as the tradition of the “network state” inserting itself as a mediator among competing firms, may constrain cross-firm knowledge-sharing (Rowen & Toyoda, 2002, p. 20).
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Other scholars have advanced similar arguments about the importance of tacit knowledge (and, to a lesser extent, trust) shared within networks of individuals and firms in Japan. There are two distinctly different types of knowledge (explicit and tacit) than can be shared within an organisation. “When the Japanese want to express their thoughts, they constantly make reference to the context in order to interpret the non-explicit dimensions of the messages (communication with implicit message and strong context). Consequently, they are used to guessing what the other wants to say, and to a rather sophisticated thinking process whereby they always must guess the meaning rather than find it in an explicit sentence. Indeed, the Japanese are usually very alert to the signals, whereas westerners are primarily concerned about the clarity of what they communicate (communication with explicit message and weak context)” (Blanchot & Kalika, 2002).
Corporate Governance and Stable Shareholding (Kabushiki Antei Hoyuu) Cross-shareholding is at the centre of businessto-business relationships (keiretsu), of businessto-bank relationships (main bank relationships) and business-to-employee relationships (Okabe, 2001), representing a system of mutual support and of “institutional complementarity” (Aoki, 1995; Aoki & Okuno-Fujiwara, 1996). Each keiretsu member holds some of the shares issued by the others and agrees not to trade them (around 70% of a firms equity is never traded). These stable shareholders (e.g. banks, financial institutions, industrial firms) explain partly why there is no market for corporate control (Nakamura, 2003; Jackson & Moerke, 2005). Sheard (1994) emphasizes the importance of reciprocal shareholdings and other transactional ties to the stability of the Japanese system.
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The Evolution of Nissan Keiretsu: from Background and Global Strategy up to the Strategic Alliance Nissan Motor, created in 1933 is a vertical keiretsu affiliated with the horizontal keiretsu Fuyo but largely independent. At its origin, Nissan was a small automaker producing components before becoming in the 1980s one of the world leaders in automobiles. But in the 1990s, Nissan lost money and market share. Finally in 1999, Nissan was nearly bankrupt in spite of the implementation of the Global Business Reform Plan (see Table 1). The 1998 Nissan annual report emphasises the implementation of a Global Business Reform Plan to achieve a sustainable competitive advantage, to favour profitability and to continue overseas development, especially in the US. But this plan was adopted too late. Debt was huge. In this context, an agreement was signed in Tokyo on March 27th 1999 between Nissan and the French automobile manufacturer Renault, giving birth to the Renault-Nissan alliance. The first meetings were initiated as early as June 1998 whereas Louis Schweitzer, Renault’s CEO, had been looking for an Asian partner since 1997. According to Louis Schweitzer, Nissan was a “weak keiretsu.” In this section, we have presented the historical context of the keiretsu and described organizational practices and relational strategies between Japanese firms before the entry of foreign investors. The Renault-Nissan partnership is historic for both partners. The impact was very important, especially at the organizational level as we’ll see in the next part.
FROM NISSAN TO THE RENAULT-NISSAN ALLIANCE The 1990s saw significant growth in international strategic alliances (Mowery, 1988; Mytelka, 1991; Hagedoorn, 1996), paralleling the increase in cross-border mergers and acquisitions (M&As).
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Table 1. The global business reform plan Main goals New organisational structure
• Clarify responsibilities of the management team. • Accelerate the decision process by delegating more responsibility and authority to middle management.
New development structure
• Reorganise the Product division to create more successful products. • Give priority to more profitable products. • Reduce the number of platforms and strengthen marketing.
Rationalisation of the Japanese distribution network
• Move from a 4- to a 2-channel distribution network.
Rebuilding of American operations
• Change the organisation so as to develop market focus and speed up decision making (closer links between US HQ and US sales subsidiaries), • Introduce new models at an aggressive pace. • Reduce manufacturing costs, inventories…. • Strengthen the corporate brand name by introducing a beacon model
Increase productivity
Improvement of the financial position
• Develop production of differentiated models sharing a common platform and assembled on the same production line, with the use of flexible production techniques. • Develop transmission manufacturing through outside sales to drive costs down • Sell assets • Reduce inventory.
Source: Adapted from Nissan annual report 1998, www.nissan-global.com.
The “hypercompetition” context (D’Aveni & MacMillan, 1994) has created a significant incentive for organizations to collaborate particularly in the automotive industry. In this sector at a general level, car manufacturers look for alliances to achieve global economies of scale in production (and then to reduce costs), to attain a critical mass, and also to secure sufficient financial resources to develop leading-edge technologies for the next generation of “eco-friendly” cars (Kang & Sakai, 2000).
Structural Changes The dramatic changes in the Japanese economy in the last decade linked with the economic recession, the bursting of the financial bubble, the deregulation of domestic capital markets and finally the slow recovery since the early 1990s have had a great impact on firm competitiveness. Japanese groups have to compete more and more, in sectors where they were very competitive for many years such as automobiles, chemicals, and consumer electronics. Both horizontal and vertical Kei-
retsu are directly concerned. In particular, stable shareholders (around a main bank) and closer supplier relationships have finally inhibited fair competition among firms in Japan and have led to market share reductions on a worldwide scale. The slowdown of growth opportunities for Japanese firms and the 1990s wave of mergers (the increasing part of foreign acquisitions) across vertical keiretsu may have weakened the governance mechanisms in the keiretsu groups. These changes in share ownership affect the management of Japanese firms: foreign investors attach a great importance to their return on investment and equity (ROE) accelerating a trend toward the dissolution of cross-holdings (Okabe, 2001). Since 2000, vertical keiretsu tend to break up: in the automobile industry for example, the nine manufacturers (except Toyota and Honda) are now partially in the hands of foreign investors, who have limited their connections with Japanese banks. The agreement between Mitsubishi Motors and DaimlerChrysler AG could have jeopardized its relationship with Tokyo-Mitsubishi bank and Mitsubishi Steel Manufacturing Co., but also with
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members of its own network of suppliers. This situation has already occurred: the restructuring of Nissan, under the watchful supervision of Renault, involved a drastic downsizing in the number of its suppliers. The banks themselves seem to have encouraged the disappearance of keiretsu. Until the 1990s, the consortium of keiretsu members led to an exclusion of foreign competitors from the Japanese market. But more recently in the automobile industry, which is one of the most exposed to the competitive global market, three major firms had been taken over by foreign concerns: Mazda by Ford in 1996, Nissan by Renault in 1999, and Mitsubishi by Daimler-Chrysler in 2000 (even if the break-up between DaimlerChrysler and Mitsubishi in 2004 put a halt to this trend as Tokyo-Mitsubishi bank intervened once more to save the group from bankruptcy). These operations have had a great impact on keiretsu.
The Main Purposes of the Renault-Nissan Alliance The Conceptual Framework: Strategic Alliances and KM Processes Definitions of alliances are numerous. In general, strategic alliances can be considered as “agreements characterized by the commitment of two or more firms to reach a common goal entailing the pooling of their resources and activities” (Teece, 1992, p. 19). A substantial number of theoretical and empirical studies, both in economics and strategic management, have focussed on co-operation (in the form of agreements or alliances) between companies. These studies are based on a variety of theories including the theory of the firm (theory of transaction costs, agency theory, and property rights theory), the resource-based view (RBV), the Knowledge-based view (KBV), the evolutionary theory and game theory. Many authors distinguish strategic alliances between rival companies (with the aim of developing a sustainable competitive advantage) from other forms of co-operation which are 196
more traditionally regarded as ‘tactical’ (Porter & Fuller, 1986), in other words, responding to a specific and isolated problem. This classification is important because of the different implications it has on the management of the alliance. Alliances with competing firms impose the protection of the company from losing its distinctive resources and core competencies (such as knowledge). Though this is true for all alliances involving rival firms, it is more important for complementary alliances (like that of Renault and Nissan). Within an alliance, the interests between the partners could be conflicting and: [A]ctors use their knowledge of the network as well as their relationships with other actors in order to increase their control” (Haakansson & Johanson, 1992, p. 30). Consequently, one must therefore exclude partnerships between clients and suppliers, subcontractors and manufacturers within the same economic sector, from strategic alliances, because these relationships do not deal with the problem of rivalry between allies (Dussauge & Garrette, 1991). Therefore, strategic alliances do not only have an impact outside the coalition, but also within it on the partners themselves, because the partners, while developing close collaborations in certain fields, find themselves in competition in others. Even if the term strategic alliance has become widely used to describe a variety of different cooperation agreements ranging from shared research, production and marketing to formal joint ventures, strategic alliances can be categorized in two broad groupings of agreements (Grant 2002; IMF, 2004): equity (including joint ventures and minority equity investments) and non-equity forms of alliances (including a host of inter-firm co-operative agreements such as R&D collaboration, technology sharing, co-production contract, marketing agreements, R&D and production consortia, supply arrangements, long-term sourcing agreements).
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The general motivation of strategic alliances is to reduce costs (economizing on production and research costs), to share technology and product developments, to strengthen market presence and to have a better access to capital, to intangible assets of other firms such as managerial skills and knowledge of markets and customers. Strategic alliances are effective only when a firm’s distinctive capability make it attractive enough for a partner also to benefit from exchanges of resources, competencies, skills and knowledge. Strategic alliances are considered as an efficient means to combine the distinctive resources and the core competencies of organisations to achieve a sustainable competitive advantage. Central to this strategy is the ability to create knowledge (Gehani 2002; Grant 1996; Nonaka & Takeuchi, 1995) and the contribution of tacit knowledge and valuable knowledge resources difficult to imitate (Darroch, 2003; Lundvall & Nielsen, 2007). Consequently, the need to form knowledge alliances is the most frequent factor in the rise of inter-firm alliances (Powell, 1998; Badaracco, 1991) and particularly in joint-ventures (Inkpen, 1996; Tiemessen et a., 1997). Learning processes in the context of inter-firm networks have been studied in the international business literature, namely by Kogut (2000), Lam (1997) and the authors focusing on the industrial networks approach (Axelsson & Easton, 1992; Haakansson & Johanson, 1993; Blankenburg-Holm & Johanson, 1997). As mentioned by Grant and Baden-Fuller (2004, p. 62-63): [S]everal studies of strategic alliances have identified the sharing of knowledge (including technology, know-how and organizational capability) as their dominant objective (Ciborra, 1991; Dyer and Nobeoka, 2000; Inkpen and Crossan, 1995; Kale et al., 2000; Khanna et al., 1998; Larsson et al., 1998; Lyles, 1988; Mody, 1993; Mowery et al., 1996, 1997; Simonin, 1997, 1999).
In addition, in the first stages of knowledge creation, knowledge tends to be tacit. The market is not an efficient transfer mechanism for tacit and/or dense knowledge (Liebeskind et al., 1996). There are numerous definitions and taxonomies of knowledge management (KM) that contribute to theory and praxis from a variety of perspectives. But we share the common idea that Knowledge management’s goal is the creation, collection and conversion of individual knowledge into organisational knowledge (Bollinger & Smith, 2001; Pemberton & Stonehouse, 2000; Spender, 1996) for the purpose of adding value and benefiting all stakeholders (Jones, 2001; Rowley, 1999). Knowledge management can improve efficiency and effectiveness, and increase responsiveness to market changes (Leng & Shepherdson, 2000). According to Love et al. (2003), effective KM also facilitates innovation, reduces project duration, and can improve both quality and customer satisfaction. Sharing knowledge among geographicallydispersed organizations has been a practice for many years (Hayes, 2001). With the development of Web-based technology and IT-based tools, the network perspective of KM has become a key issue especially in the case of strategic alliances between two firms located in different countries (Hayes, 2001; Swan & Newell, 2000). With advanced communications, teams (separated by time and distance and even by cultural factors) can still work as effective virtual teams (Nonaka, 1991; Ruokonen, 2001; Stough et al., 2000). Since the beginning of their cooperation, Renault and Nissan have had to face these challenges.
The Key Features of the Renault-Nissan Alliance The Renault-Nissan alliance is an equity form type. The agreement calls for an equity investment of Renault in Nissan. Renault holds a 44.3% stake
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in Nissan, while Nissan owns 15% of Renault’s shares (each company has a direct interest in the results of its partners). Renault-Nissan BV (RNBV), was founded on March 28, 2002 to oversee the strategy of the alliance and all activities undertaken by the two firms. Renault-Nissan BV is jointly and equally owned by Renault and Nissan and hosts the Alliance Board, which met for the first time on May 29, 2002. The objective of the Renault-Nissan alliance is to combine the strengths of both companies and to develop synergies through common organisations, cross company teams, shared platforms and components. Renault-Nissan set up joint project structure covering most of both companies’ activities. In July 1999, a signed Charter set out the principles of “a shared ambition, mutual trust, respect of each partners of the Renault-Nissan Alliance, completed by operating and confidentiality rules.” It promotes the common values of the new Group and common work rules for everyday. The two companies were quite complementary in geographic scope and skills. The main complementarities can be analysed in terms of market breakdown, technology and costs reduction: Renault was strong in Europe and was mainly a European manufacturer looking for opportunities to globalize its operations; Nissan had a strong presence in Japan, North America and Asia. Renault’s strong advantage was design, offering conceptually innovative car models (such as Espace, Twingo, Kangoo, Vel Satis), while Nissan’s production and engine technology could benefit Renault. Combining platforms and purchasing will cut costs.
The Impact of the Strategic Alliance The Renault-Nissan alliance has had a great impact on supplier relationships (Daidj et al., 2008), governance (Daidj, 2009), organizational structure, culture (Mayrhoefer & Barmeyer, 2009) and management practices leading to a reorganization/dissolution of keiretsu.
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The Impact on Equity, Management and Corporate Governance As mentioned by Fujimoto and Arturo Heller (2004): [T]he transfer of COO Carlos Ghosn, a central person in Renault’s revival from Renault to Nissan may be regarded as the key to the success of this alliance (p. 7). Carlos Ghosn (former deputy CEO of Renault) was appointed to the position of Chief Operating Officer and member of Nissan’s Board (June 27th 1999) upon leaving Renault, C. Ghosn hired twenty Renault managers who joined him in Japan and launched the Nissan Revival Plan (NRP) based on development of new automobiles, cost reduction, reinvestment in Research & Development and improvement of Nissan’s brand image. This plan included the closure of five plants (in Japan), the cutting of 21,000 jobs all around the world and a reduction of the number of suppliers by one half. A year later (June 20th 2000), C. Ghosn was appointed CEO of Nissan and imposed a new management structure: Nissan’s management team was completely reshaped. Nissan reduced the number of its Board members from 37 to 10. With respect to the structure of the relationship between the two partners, the agreement outlines the setting up of a deciding body, technical committees or implementation structures and supporting and liaison bodies. Consequently, the corporate governance structure is organized as follows: •
A deciding body (Global Alliance Committee, GAC, or Strategic Committee): It was the alliance’s governing structure defining joint strategy and deciding on co-operations or synergies as proposed by the CCTs during monthly meetings.
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•
•
An Alliance board: The Alliance Board steers the Alliance’s strategy and coordinates joint activities at the international level. Renault and Nissan run their operations under their respective Executive Committees, accountable to their Board of Directors, and remain individually responsible for their day-to-day management. An Alliance Coordination Bureau: This structure (with one office in Renault – Paris and one in Nissan – Tokyo) coordinates the work of the Steering Committees (SCs), Cross-Company Teams (CCTs), Functional Task Teams (FTTs), and Task Teams (TTs) and prepares the meetings of the Alliance Board.
The Impact of the Alliance on the Organisational Structure and Projects Management Although their brands are still fully autonomous from an operational point of view, two major cooperation areas have led to the creation of two joint-ventures between Renault and Nissan. RNPO (Renault-Nissan Purchasing Organization) was founded in April 2001 to optimize purchasing performance across the Alliance. To achieve its goal, RNPO defines worldwide purchasing strategy by product family and selects the best suppliers project by project. The Renault and Nissan Alliance Board agreed in July 2002, to establish Renault-Nissan Information Services (RNIS), the second joint venture between Alliance partners following the establishment of Renault Nissan Purchasing Organisation. RNIS was established to deliver global information services to Renault’s and Nissan’s information systems departments, thereby combining their knowledge. The structure of joint projects and synergies is primarily based on the work of 19 Cross-Company Teams (CCTs), made up of employees of both companies. Their mission is to act as opportunity hunters and problem solvers. They are also
responsible for following up on the implementation of action items. CCTs explore opportunities for synergies between Renault and Nissan, draw up joint projects and monitor their implementation, follow up and implement action plans and decisions of each party and finally report to the responsible SC or Executive Vice President/Senior Vice President. Functional Task Teams (FTTs) assist the work of the CCTs and contribute to synergies between Renault and Nissan in support functions (process, standards, management and information tools, etc). They solve the issues raised by the CCTs or the GAC (especially in the area of Information Systems, quality, tax, legal issues), align procedures and tools for an effective implementation of the alliance and develop exchanges on best practices. In addition, whenever a specific subject arises, a task team (TT) is assigned to work on it until it is accomplished. In this part, the main features of Renault-Nissan have been described. Finally, Carlos Ghosn has proceeded step by step to the dissolution of the Nissan vertical keiretsu. The whole organization has been redesigned, project management practices have been improved along with the introduction of new governance rules. It now remains for us to consider the implications of the strategic alliance on KM, KM 2.0 and Web 2.0. These issues will be developed in the following section.
THE EVOLUTION OF THE STRATEGIC ALLIANCE: TOWARDS NEW KM PRACTICES? In this section, we analyze the repercussions of the alliance on KM processes and the evolution of KM practices until the adoption of web 2.0 tools. Since the end of the 2000s, these tools have become not only a “hot” topic but also a key issue to understand the “e-transformation” of companies. Until recently, literature has mainly focused on knowledge management in the context of strategic
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alliances (see section 2) and less on the impact of KM and web 2.0 tools within a network. We propose here to describe how KM and web 2.0 tools have been implemented at the alliance level. This study aims to further the understanding of the process that characterises the evolution of KM practices in a specific situation of a strategic alliance between two major players of the automotive industry and to analyse the impact of this alliance on KM practices and on the adoption of Web 2.0 tools.
The Evolution of Renault and Nissan KM Practices: 1990-2002 Managing Knowledge: A Priority at Renault Like most industrial companies and more specifically car manufacturers, managing corporate knowledge has been an ongoing concern for Renault since the beginning of the 1980s. In the 1990s, Merex, the well-known method, was designed and applied at Renault, and used most notably in R&D. More recently in the 2000s, Renault launched different KM projects. Among them, the manufacturer created a “R&D Knowledge Base” including 300 technical domains in the R&D department. The project started in 2000 with an exploration phase and was officially launched and staffed by the Vehicle Engineering division at the beginning of 2001. As David (2004) explains it “the project’s motto was ‘act first, react quickly.” According to David (2004), other KM projects deal with capturing knowledge, search, classification and text mining and Knowledge-based innovation methods. For over ten years, Renault has also actively promoted bottom-up approaches building on employee initiatives and creativity to solve a problem. All levels of management are involved in the promotion and recognition of the process.
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The Adoption of KM Strategies by Nissan, a Multinational Company (MNC) Many automotive Asian firms have adopted corporate knowledge strategies during the late 1990s and early 2000s. It is the case of Nissan. Teleos, an independent knowledge management and intellectual capital research firm, administers the Most Admired Knowledge Enterprises (MAKE) program. The KNOW Network is a Web-based global community of organizations dedicated to achieving superior performance through benchmarking, networking and best practice knowledge sharing. The MAKE research program, conducted in association with The KNOW Network, consists of the annual Global MAKE study – the international benchmark for world-class knowledge-driven organizations – and regional/national MAKE studies. The Asian MAKE study was established in 2002 to recognize organizations (founded and headquartered in Asia) for their ability to create shareholder value (or in the case of public and non-profit organizations, to increase stakeholder value) by transforming new as well as existing enterprise knowledge into superior products/ services/solutions. The Asian MAKE research is based on the Delphi methodology. This research tool employs an expert panel’s perceptual knowledge to identify critical issues – in the case of the Asian MAKE study to identify those organizations which are leaders in creating organizational intellectual capital and value through the transformation of individual/enterprise knowledge into world-class products/services/solutions. The Asian MAKE Finalists are ranked against each of the eight knowledge performance dimensions which form the MAKE framework and are the visible drivers of wealth creation:
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• • • • • • • •
Creating a knowledge-driven enterprise culture Developing knowledge leaders and workers Innovation (R&D, creativity and new product/solution/service design and delivery) Maximizing enterprise intellectual capital Enterprise-wide collaboration and knowledge sharing Creating a learning organization Managing customer / stakeholder knowledge Transforming corporate knowledge into shareholder / stakeholder value
A total of 52 organizations were nominated as 2009 Asian Most Admired Knowledge Enterprises among them Nissan (Teleos [http://www. knowledgebusiness.com]). Many companies face difficulties in managing their knowledge assets, especially if they operate in different countries in a multi-cultural context. Research has been conducted to study the barriers and facilitators to KM from the perspective of Nissan (Rall, 2008). The author has analysed KM practices during the last decade in different units: Nissan South Africa (NSA), Nissan Europe (NTCE), Nissan Thailand (NTCSEA) and Nissan Japan (NML). According to the literature, two main groups of barriers to KM can be identified: •
•
People-related barriers: culture, time, tacit knowledge and trust, value identification, language and preferential sharing; Organizational related barriers: strategy alignment, reward and recognition, allocation of resources, top management support, organisational structure, staff turnover, organisational culture, one directional KM, competition and the power of management.
The results of this study are interesting as they show the difficulties for a MNC to effectively identify and overcome the barriers to successful KM activities in order to capitalise on the valuable resource of knowledge between the different subsidiaries. Most of the barriers presented previously have been found. But, the author also highlights people and organisational related facilitators. In the first group, three elements have been mentioned by employees: perception change, culture and dual commitment. In the second category, organisational culture, business alignment and structural changes are considered as facilitators (in descending order, based on their perceived importance to employees).
Building Knowledge Interactions Between Renault and Nissan: From KM to KM 2.0 and Web 2.0? According to a Teleos study (2009), “advanced IT-enabled enterprise collaborative knowledge sharing and social networking tools are now a core competency for MAKE (Most Admired Knowledge Enterprises) Winners. Asian (among them Nissan), European and North American MAKE leaders show equal skills in applying new Internet-based tools to effectively share and reuse knowledge in an increasingly global workplace. That said, knowledge-driven organizations which are able to harness Web 2.0 tools to engage ‘Generation Y’ staff seem to have a competitive advantage over enterprises continuing to rely on codified knowledge databases and repositories.” As the experiences are very recent, it is difficult to make an in-depth analysis of the use of social networks by the automakers and to evaluate the repercussions on KM practices. However, we propose here to present a first assessment of these collaborative communication tools.
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The Development of KM 2.0 and Web 2.0 Tools The first generation of collaboration tools relied on documents created and shared by individuals who used one device: the PC. Collaboration 2.0 concerns groups of individuals (partners, customers, and suppliers) interacting across company and geographic frontiers, participating in blogs, videos, wikis, social networks and conferences from a variety of devices. Figure 1 shows these different ways of collaborating. One of the most important tools is probably the blog and the use of RSS technology which was launched in 1997. The concept of “Web 2.0” was launched during the first Web 2.0 Conference in October 2004. There is no specific definition of Web 2.0, however O’Reilly (2005) has been one of the first authors to mention this “new concept” and to propose a definition: “Web 2.0 is the business Figure 1. The different collaborative tools
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revolution in the computer industry caused by the move to the Internet as platform, and an attempt to understand the rules for success on that new platform (…). Like many important concepts, Web 2.0 doesn’t have a hard boundary, but rather, a gravitational core (…). The central principle behind the success of the giants born in the Web 1.0 era who have survived to lead the Web 2.0 era appears to be this, that they have embraced the power of the web to harness collective intelligence (…). Network effects from user contributions are the key to market dominance in the Web 2.0 era.” Another characteristic of Web 2.0 can be added. It is related to Anderson’s “long tail” concept (Anderson, 2006). This strategy allows companies to realize profits out of selling limited volumes of hard-to-find products to many customers instead of selling large volumes of a reduced number of popular items.
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Web 2.0 has a long tail (…). Monetizing the long tail – encouraging the nutritious leaves of small – and medium-size advertisers who are new to online advertizing – is how Web 2.0 converts the Web into wealth.” (Shuen, 2008, p. xvii). Constantinides and Fountain (2008) view web 2.0 as an umbrella term of web applications, including social media. But Social networking is not only a specific Web 2.0 application. (…) social networks permeate and enrich Web 2.0 projects even if they aren’t the central focus. Social networks are a natural conduit for network effects and a key field for community-building that can strengthen your project’s appeal” (Shuen, 2008, p. 160). Social tools put knowledge-sharing power in the hands of the users themselves (see Figure 2). Social networks and communities of practices catalyze and reinforce the potential of existing
exchanges around company processes and knowledge; that’s the way the enterprise 2.0 is increasing its “knowledge capital.” So “if the central question asked by managers in the K.M 1.0 world was ‘how do we make people share’, the question of the KM 2.0 era is ‘how do we better share, learn and work together’” (Gurteen, 2008).
Renault-Nissan: The Development of Knowledge Interactions To understand the development of knowledge interactions between the two companies, we can refer to two key elements: Cross-Company Teams (CCTs) and joint platforms. CCTs can explain the progressive “social amalgamation process” between Renault and Nissan (Morosini, 2005). The creation of these teams was the first step in the social initiation experience before developing more formal frameworks of collaboration and knowledge exchanges.
Figure 2. From enterprise 1.0 to enterprise 2.0: increase of “knowledge capital”
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This social approach was found to be so effective in nurturing collaboration between Renault and Nissan, that all other formal aspects – i.e. legal, structural, organizational – were made secondary to it (Morosini, 2005, p. 10). The first joint platform development was a means for both partners to try to explore the potential synergies of their alliance. The policy of building common platforms, on which each brand will develop its own specific product range, could set up common organisational routines and synchronisation mechanisms that make possible the effective transfer of knowledge (Gulati & Singh, 1998; Saxenian, 1994) and the adoption of common KM practices. But it was not really the case. As Segrestin (2005, p.4) mentioned: [W]e observed that the engineering teams were not merged but, rather, worked independently from one another in the first years of the Alliance in order to limit coordination costs and avoid irreversible commitments. Moreover, the implementation of such coordination mechanisms was hindered by a high degree of uncertainty: did the partners know what they wanted to learn from each other? More recently, in February 2009, the two automakers announced plans to strengthen their strategic alliance. The aim is to build “greater synergies” in eight areas: manufacturing and logistics, powertrains, vehicle engineering, light commercial vehicles, purchasing, sales and marketing, information systems and support functions, research and advanced technology. The common projects in different fields will be reinforced by sharing manufacturing facilities, co-owning engine families, use of common platforms and interchangeable components, creating one common platform in Europe to build two differentiated light commercial vehicles. These “new” cooperative orientations should have repercussions on KM for both automakers in the future.
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Supporting Collaboration within the Strategic Alliance KM 2.0 practices lead to interactions between people exchanging problems and knowledge (methods, guidelines and good practices) among networks, communities of practice and problemsolving taskforces. Supporting collaboration across the “extended” enterprise is a key element for rolling out KM projects and a key issue within a strategic alliance between two partners such as Renault and Nissan. In order to understand the current processes and the evolution of KM methods Renault and Nissan adopted, we have to distinguish between two separate stages. The first consists in the launch of the strategic alliance (from 1999 to 2004). As we explained in the previous section, the two car manufacturers had their own practices and used specific KM tools especially in-house tools for collaboration. The second phase consists in the adoption of “new and common” tools in 2003-2004. Since mid-2000, Renault and Nissan have decided to use two key collaboration tools to address the need for globalizing operations to enable collaboration between employees located in engineering centers and plants around the world. Part of Renault’s collaboration methodology includes an approach to encourage collaboration practices—such as how to manage documents, how to establish communities of practice, and how to share information. These tools are eRoom, considered as a “virtual desktop” (see Table 2) and eConf, a virtual meeting solution, for improving teamwork and collaboration at the internal level and with their suppliers. The eRoom solution allows the Renault-Nissan teams to work with their suppliers and partners with no time or place constraints. It is secure web-based internet work tool which enables people to communicate and share documents, and makes team-work coordination much easier.
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Table 2. The adoption of new media tools eRoom: an on-line document sharing tool
eConf: a real-time collaborative work tool
eRoom is a document sharing tool implemented by RENAULT.
It allows:
eRoom is the name which has been given to the solution (DOCUMENTUM) chosen by RENAULT-NISSAN. This solution allows the RENAULT-NISSAN teams to work with their suppliers and partner with no time or place constraints.
to organise and hold re-mote, real-time meetings.
It is secure web-based internet work tool which enables teams to communicate and share documents, and makes coordinating a team’s work far easier.
to present, share or work on the same document or the same application with contacts all over the world whilst sitting at your own computer.
It notably enables users to:
The tool can be used in many different situations:
Share documents such as texts, Excel Files, Slides, Planning documents, 3D view (Okyz)... with update contents,
hold real time meetings without anyone having to travel
Exchange alerts and notifications,
monitor the progress of a project
Consult regularly update files, databases, schedule,
share 3D images in order to finalize a modification (on PC)
Carry out project management tasks,
finalise a document (specifications, presentations, business plans)
Favour the use of approvals as part of the decision making process,
present slides during a remote intervention in a seminar.
Manage simple operations (Task monitoring, LUP, Project schedule...).
introduce others to a new product (document, software)
It is free of charge for a partner or suppliers to work in an eRoom. Source: Renault web site
Renault’s transition to global engineering centers spurred the need to use Web 2.0 and new media tools to enable collaboration between employees located in engineering centers and plants around the world. eRoom (an online document-sharing solution) and eConf (a virtual meeting solution) are two key collaboration tools to address this need for globalizing operations. Part of Renault’s collaboration methodology includes an approach to encourage collaboration practices—such as how to manage documents, how to establish communities of practice, and how to share information (Collaboration Consortium, 2009, p. 22) How, then, should the results of the development of these tools be evaluated? Clearly, there are positive for both companies at the international level as members are often spread between sites and across countries.
“More than 45,000 people are registered users of eTool, including 10,000 users outside France located in over 40 countries. eTool has been very rapidly adopted by users and departments. It has become “the way people work, and very important for the company,” according to Jean- Marc David.” (Collaboration Consortium, 2009).
The Categorization of Web 2.0 Tools: Application to the Renault-Nissan Alliance from Nissan Perspective In addition to common projects described previously, Renault and Nissan have launched their own social networking initiatives. Table 3 focuses on Nissan’s. Since 2007, Nissan has shifted to social networking at the internal level by creating a social networking site for its employees called N-Square.
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Table 3. The adoption of Web 2.0 tools by Nissan ICATEGORY
IITOOLS
IIIFOCUS
1. BLOGS AND PODCASTS
Traditional blogs, vlogs, podcasts, videocasts
Informing about current events and novelties
Blogs by Dell, podcasts from interviews
Yes
2. SOCIAL NETWORKS
Social networks
Content sharing, maintaining relationships, networking
MySpace, Facebook, IRC-Gallery, LinkedIn, ITToolbox
Yes
Member-initiated
Members’ mutual interests and reciprocal interaction
Communities formed around similar interests e.g. Aukea.net (photography)
Organization-sponsored
Business transactions, brand building, interaction among organization and customers, cocreation of products
Communities by Mozilla, Fiscars, Dell and Salesforce.com
Third-party established
Enable communication and transactions between buyers and sellers
eBay
3. COMMUNITIES
IVGENERAL EXAMPLES
VAdoption of web 2.0 tools by Nissan
Online communities Yes (Nico: Nissan Infiniti Car Owners)
Content communities Content sharing sites, wikis
Content sharing
YouTube, Flickr, Picasa, Pikeo, dotPhoto, GoogleVideo, Wikipedia
Nissan via YouTube, Dailymotion
Forums/bulletin boards
Discussion of mutual interests
B2Bexchanges, Alibaba, Zentrada, Go4worldbusiness
Automotive Bulletin Boards
4. CONTENT AGGREGATORS
RSS, widgets, bookmarks, tagging services etc.
Categorizing and customization of web content
Delicious, Yahoo! Widgets
/
5. VIRTUAL WORLDS
Virtual worlds
Substitute for the real world
Second Life, World of Warcraft, Kaneva, Universe, Habbo
Nissan is present in Second life
Source: Adapted from Constantinides and Fountain (2008) and Lehtimäki et al. (2009) for the first four columns (the categorization of web 2.0 tools). The fifth one has been elaborated by the author.
Site users (180,000 employees have access) can create online profiles, blogs, online communities, discussion groups and share data files. The objective in the short term is to develop links between employees and to share expertise. In the long term, the site could also make employees feel more connected to their jobs. Since July 2009, Nissan has proposed a dedicated social community for its global electric-vehicle (EV) buyers through the use of blogs, forums and
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applications that allow drivers to compare their motoring skills. Nissan innovated also by launching new marketing campaigns for its Cube cars. The “campaign” was begun in Canada in June 2009 by the targeting of specific consumers via social networks. One of the objectives was to find core, early adopters who could have an influence on a larger group. In this nationwide contest, participants (bloggers, artists etc.) were asked not only
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to give their impressions and suggestions but also to submit creations. Nissan offered one million dollars worth of prizes corresponding to 50 Cubes. The carmaker invited twitterers (Anglophone and Francophone users) to take part and to form a panel to select the 50 winners. Finally, in October 2009, Nissan opened the debate among sports cars lovers in France by launching its first social website. Members can defend their position and ask friends to join their community through a connect feature with other social networks (YouTube, Facebook, Twitter…) and RSS feeds.
MAIN LESSONS AND FUTURE RESEARCH DIRECTIONS The case study method allows for analytical generalizations based on the research findings. The analysis of the Renault-Nissan Alliance provides the analytical basis for generalizing some findings of this research and its transferability to other companies to a certain extent. The objective of this chapter was to understand how a “hybrid organization” (two automobile manufacturers partners Renault and Nissan within a strategic alliance) uses social networking and Web 2.0 tools to collaborate not only inside traditional organizational boundaries and within the alliance structure but also across geographical frontiers. We propose here to summarize the main results: A successful alliance operation. At the beginning of the alliance, several questions have raised about this risky operation conducted by Renault: “ever since this agreement was signed, it has been easier to evaluate the risks (Nissan’s high debt levels; potential social problems; misunderstandings and incomprehension between the partners) as well as the potential upside (similar product ranges in certain segments enable a sharing of platforms and mechanical subsystems; co-ordinated and pooled
purchasing; a marriage between Renault’s stylistic competency and Nissan’s mechanical excellence; complementary markets; the utilisation of each firm’s under-employed capacities; joint research efforts; establishment of joint sales organisations in certain parts of the world, etc.) as mentioned by Freyssenet (2003, p. 18-19). The nature of this complementary alliance results in the optimization of the resources of both companies. Finally, we can consider that this strategic alliance is a success in spite of cultural differences and specific identities. Not all consolidations (mergers & acquisitions) and alliances during this decade have been successful (MacNeill & Chanaron, 2004). A high degree of cooperation between the two car manufacturers. Co-operative arrangements have been actively implemented leading to common platforms three years after the signature of the alliance. Renault-Nissan has also participated with GM, Ford, and PSA in the creation of a online procurement company ‘Covisint’. The “results have been less than expected and suppliers have resisted putting sensitive information online” (MacNeill & Chanaron, 2004). Knowledge transfers have been also important between the two firms even if they are difficult to evaluate (Fujimoto & Arturo Heller, 2001; Freyssenet, 2009). KM practices have evolved since the beginning of the strategic alliance. We can consider in fact two phases. During the first three years of the alliance, the two car manufacturers relied mainly on their own specific KM practices and processes. This strategy can be explained by the nature of the partnership “in which both collective identity and common goals were ill-defined” (Segrestin, 2005, p. 16). The second phase started in 2004 with the development of KM 2.0 and web 2.0 tools. The adoption of these tools by Renault has led to increased collaboration between the two manufacturers. This should probably develop in the future not only coordination, which was the initial goal of Renault-Nissan Alliance, but also
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cohesion teams. This will give rise to a number of new opportunities by building common purposes with the active contribution of employees of both companies. Two main research orientations should be conducted in the future: an in-depth analysis of KM and the impact of Web 2.0. tools on the entire performance of the Renault-Nissan alliance. The second axis concerns the comparative analysis with other car manufacturers involved in international strategic alliances.
CONCLUSION The present chapter is aimed at providing an additional contribution towards the understanding of KM and web 2.0 in a strategic alliance context. Renault-Nissan is a particularly interesting case to examine from this perspective. It is a first empirical research based on a case study. We presented the evolution of knowledge management practices in the case of an automobile manufacturer that has experienced significant changes during the last decade. Nissan has gradually lost its historic status of keiretsu as a result of its strategic alliance with Renault. This alliance has had an important impact on the organizational structure of Nissan even though both companies have maintained their identity by maintaining two brands internationally. Since 1999, the ties between the two automakers have been steadily growing. Therefore, the establishment of common practices in knowledge management in a more collaborative sharing of information will certainly be preferred. Currently, Nissan and Renault have launched Web 2.0 operations in different ways. It is too early to draw lessons from these practices and especially to analyze the impact of the tools of Web 2.0 and KM 2.0 on the performance of these companies. This could be for future research.
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Another issue could also be studied. It is linked with the integration of cultural factors in the development of collaborative tools. Do these factors still play a role in the development and adoption of tools of Web 2.0 and KM 2.0? This research will be useful for any company involved in international activities that have already implemented or plan to implement KM over various divisions and cultures.
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ADDITIONAL READING
KEY TERMS AND DEFINITIONS
“Alliance facts & figures 2007” available on Renault’ web site. Retrieved September 30, 2010 from: http://www.renault.com/renault_com/en/ images/Alliance-F-F_2007_tcm1120-707767.pdf
Hybrid Organization: Organization between “market” and “hierarchy” (related to the transaction cost theory). Joint Platforms: Use of common platforms and interchangeable components leading to a reduction of costs. KM 2.0 Practices: Used to enhance external knowledge sharing among the network and to capture and share tacit knowledge within an organization. Knowledge Alliances: Sharing knowledge (including technology, know-how and organizational capability) within alliances. Strategic Alliances: Signed between rival companies; have an impact outside the coalition, but also within it on the partners themselves, because the partners, while developing close collaborations in certain fields, find themselves in competition in others. Vertical Keiretsu: Groups of companies more or less independent from one another (subcontracting small firms, suppliers and equipment manufacturers) but under the umbrella of a prime manufacturer. Web 2.0 Tools: New Internet-based tools to effectively share and reuse knowledge.
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Chapter 11
KMS for Fostering Behavior Change:
A Case Study on Microsoft Hohm Magda David Hercheui Westminster Business School, UK & London School of Economics and Political Science, UK
ABSTRACT This chapter proposes a new theoretical framework for understanding how knowledge management systems may foster behavior change. Drawing upon knowledge management research and institutional theory, the framework proposes that Information Systems and social media channels might support strategies for institutionalizing new patterned behaviors. More specifically, this chapter argues that Information Systems may speed up the diffusion of explicit knowledge and the articulation of tacit knowledge that favor behavior change. In making access to knowledge easier, these tools might build and strengthen new patterned behaviors. Using the proposed theoretical lenses, this chapter discusses an empirical example, Microsoft Hohm, which aims to promote behavior change in the domain of energy consumption in American residences.
INTRODUCTION This chapter proposes a new approach to knowledge management systems (KMS) discussed from the perspective of behavior change. Drawing upon institutional theory, this study attempts to show DOI: 10.4018/978-1-61350-195-5.ch011
how KMS may be designed to offer mechanisms that foster new patterned behaviors through diffusing knowledge on specific domains. The idea is that institutionalized behaviors may be challenged through legitimate mechanisms and that knowledge is a legitimate means for challenging current patterned behaviors and in turn fostering the emergence of new ones.
Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
KMS for Fostering Behavior Change
This chapter focuses on the role of KMS in supporting the diffusion of knowledge, exploring the notion that changes in current knowledge frameworks may favor behavior change when the changes in knowledge affect the way people understand the world. In other words, information systems may foster behavior change through diffusing new legitimate knowledge that allows people to interpret the world in different ways. Drawing upon the idea that KMS are information systems which allow for creating, stocking and sharing pieces of knowledge on a domain or organization (Alavi & Leidner, 2001), this research adopts a broad conceptualization, understanding KMS as any information system that supports the management of knowledge at the organizational or societal levels. This definition has the advantage of including all types of sorts of information systems, including Internet tools and social media, as far as they support the processes of knowledge creation or diffusion. In addition, this research takes into consideration that knowledge is mainly a human expression, which depends on cognitive and social processes, thus KMS should pay closer attention to instruments that allow more socialization, as explained below (Thomas et al., 2001). It is proposed that KMS may also aim to foster behavior change whilst taking into consideration the institutional mechanisms that support established practices, understanding that knowledge frameworks influence the way people behave in society. This perspective impacts researchers and practitioners by showing how technology may be designed and applied to foster specific changes in society and organizations. It also suggests organizations may associate different tools to obtain a better management of knowledge in organizations, especially when it is necessary to cultivate spaces for socialization. However, the chapter does not suggest that technology by itself is going to bring changes in behavior; rather, technology may only create a proper environment, providing people with the means to enact new forms of action. Technology
does not cause change in behavior per se, but it is an important element and allows people to understand the world through new perspectives and it gives people the mechanisms to change behavior if they wish. In addition, it is necessary to be careful about what sorts of change one would like to promote, and what the reasons and reasoning are behind such changes. Companies and societies may have many reasons to foster behavior change. This chapter does not discuss these reasons and the legitimacy of nurturing change. It is solely focused on the role of KMS in cultivating change through diffusing and creating new knowledge frameworks. This theoretical perspective is explored in this chapter through the analysis of Microsoft Hohm, an Internet tool that enables American residences to improve the management of energy consumption. The tool has been chosen considering the relevance of fostering change in energy consumption behavior in contemporary societies in order to create more sustainable economies. The last decades have seen a crescent concern on whether economic development will be sustainable in the long term considering current production practices. In the broader domain of sustainable development, a major challenge is that the amount of information and knowledge is permanently increasing and under revision. In this context a major concern for researchers and practitioners is related to the need for improving the efficiency of information and knowledge management on sustainability (Bell & Morse, 2008; Haas, Kanie & Murphy, 2004; Kanie & Haas, 2004; Melnick et al., 2005; Pachauri & Reisinger, 2008). Indeed, research shows that information and communication technologies are important resources to help organizations and societies manage complex databases and diffuse knowledge that fosters the adoption of more sustainable economic practices (Alavi & Tiwana, 2003; Hilty, 2008). Mastering the complexity of data and information in the domain of sustainability will not be enough if the related knowledge is not diffused
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and incorporated into practices. Changing institutionalized practices and behavior, however, is not easy. Socially accepted behaviors are legitimatized through repetition in the long term and tend to be reproduced by inertia (Jepperson, 1991; Powell, 1991; Scott, 2001). Furthermore, in the domain of sustainability, behavior towards how resources are used depends on social contexts (Kanie & Haas, 2004). In other words, it is necessary to understand the institutional context in which behavioral patterns have been developed in order to understand the potential for changing behavior. Knowledge diffusion may bring new understandings of reality, then fostering the emergence of new patterned behavior. From the perspective of KMS, Microsoft Hohm has two main channels for diffusing knowledge: the more formalized software that embeds mathematical models which analyze energy consumption against ideal and actual practices, and social media spaces for communities of users and supporters of the tool. These two channels permit the diffusion of knowledge through different mechanisms—discussed below—potentially fostering behavior change through legitimizing new norms, values and beliefs. In this chapter, the analysis of Microsoft Hohm is just exploratory, to show the direction in which the proposed theoretical framework links with the practices of companies in incorporating information systems and social media in their efforts in diffusing knowledge. Further research is necessary to understand the detailed mechanisms through which this diffusion happens. The claims in this chapter are developed more in the theoretical level than through empirical data; however, the case study adds effective hints that the theoretical argument proposed here resonates with actual corporative practices. This chapter develops as follows. Firstly it interprets the concept of institutions as behavior patterns, explaining the contexts in which institutional change may happen; for example, the emergence of new scientific paradigms. It is argued that diffusing scientific, formalized knowledge
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on a domain is a mechanism for fostering the institutionalization of new behaviors. Secondly, it explores Microsoft Hohm and its virtual spaces of interaction, showing how KMS may support the diffusion of knowledge on a domain and consequently promote behavior change. The discussion chapter explores the broad lessons learnt from the theoretical perspective: how using knowledge diffusion to build new perspectives might foster the emergence of new patterned behaviors. Lastly, the conclusion emphasizes the limitations and contributions of this chapter, suggesting further research.
THEORETICAL FRAMEWORK This chapter develops a theoretical framework grounded on institutional theory. It starts from the assumption that institutions may be interpreted as patterned behaviors (Berger & Luckmann, 1967; DiMaggio & Powell, 1991; Porpora, 1998; Scott, 2001). Socially accepted behaviors have a high degree of resilience because social groups are inclined to repeat the same actions in defined situations. Society is structured upon institutions. These patterned behaviors regulate social interactions and define what is acceptable in society. From a different perspective, there are regulative, normative and cultural-cognitive systems that support institutions in society. These systems, represented by social constructs such as rules, norms, beliefs and cognitive schemas, influence the way people behave (Berger & Luckmann, 1967; Scott, 2001; Stinchcombe, 1968). From the perspective of the proposed framework, cognitive schemas and beliefs are particularly important, because knowledge frameworks influence the way people frame their understanding of the world and their beliefs. It is in this direction that KMS, in fostering new knowledge perspectives, may influence people to change their behavior at both individual and collective levels, thus favoring behavior change.
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Furthermore, behavior patterns are reinforced by mechanisms of legitimacy that frame which actions are appropriate for particular situations, thus promoting the reproduction of institutionalized social structures and systems (Deephouse & Suchman, 2008; March, 1994; Scott, 2001). Legitimate actions are understood as meaningful and they validate institutions (i.e. patterned social behavior). Again knowledge frameworks are important for legitimizing particular behavioral patterns in society. Indeed, knowledge frameworks have a dynamic interaction with institutionalized social structures, in such a way that social structures influence the emergence and maintenance of particular knowledge perspectives and established knowledge perspectives legitimate institutionalized behavior (Foucault, 1980). The emergence of new institutionalized behavior is linked with the emergence of new knowledge frameworks. Although institutions are highly resilient, individuals and groups may change their behavior through time. Many mechanisms are behind changes in institutionalized behavior. People change the interpretation of their institutions when new contexts and situations emerge because institutions are ambiguous and individuals are supposed to decide which patterned behaviors are appropriate to each situation (Avgerou, 2002; Jepperson, 1991; March & Olsen, 1989; Scott, 2005). Contemporary societies are influenced by national and global institutions that naturally expose people to conflicting social structures (Jepperson, 1991; Powell, 1991; Scott, 2005). Furthermore, every individual assumes a variety of roles and identities in different environments. People play with their roles and identities in order to foster institutional change that favors their interests (March, 1994; Scott, 2005). Of course, societies will change institutionalized social structures through time, incrementally or revolutionarily (Jepperson, 1991; Scott, 2001). As the perception of adequate behavior is built socially through time, relational networks are particularly relevant for fostering the reproduction
or change of institutions (March & Olsen, 1989; Powell, 1991). Relational networks reinforce common norms and beliefs and legitimatize specific behaviors within groups and organizations and at broad societal levels. The more people change their opinion about what would be adequate behavior in a circumstance, the more other members of close relational networks will feel pressure to change their behavior or opinion in the same direction and to adopt new beliefs, values and perspectives about a social aspect of their lives. Indeed, sanction mechanisms of reward and punishment are very important in defining behavior: even when people do not agree with institutions or have individual interests for not complying with rules, they may respect laws and regulations in order to avoid punishment; from a mild social sanction such as complaining if a person jumps a queue, to a more formal penalty imposed by a judiciary system (Jepperson, 1991; Scott, 2005). Thus, social pressure is an important sanction mechanism as people try to fit themselves into social groups, and, in general, they prefer to be accepted in society rather than be ostracized. Norms that emerge in groups, for instance, are respected even though they are not formally written as law or regulation. Sanction mechanisms, through relational networks, thus influence the way people behave and their perception of what constitutes adequate behavior in a particular situation. The more members in a group understand that the use of plastic bags is not appropriate behavior, the more group members will be pressured to avoid using plastic bags. More recently, social media tools have become important channels of influence for relational networks, either because they offer channels for more social interactions or because they offer individuals the possibility of being related to different social networks (Castells, 2001; McAfee, 2009; Rheingold, 2000). The effects of these relational networks on society are ambiguous: people may expose themselves to new ideas, but they may also constrain their social circles to those who share
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similar beliefs and interests. Theoretically, social groups may be subjected to broader institutional influences, but not necessarily in practice. Organizations, governments and society as a whole may create spaces of interaction in which particular institutional perspectives may be fostered.
KNOWLEDGE PERSPECTIVE From the perspective of designing and using KMS, integrating relational networks to KMS may offer spaces for interaction and socialization and so become important channels for diffusing knowledge and fostering institutional change (Alavi & Leidner, 2001; McAfee, 2009). Social media mainly changes the access people have to other people, reinforcing existing social ties and building social ties that were not available beforehand through other communication channels (McAfee, 2009). This phenomenon completely changes the process of diffusing information and knowledge: social media channels allow a level of interaction and socialization between individuals and groups that would not be possible without such Internet tools. It is notable that a social network such as Facebook has more than 500 million members around the world, and Twitter has around 200 million accounts, numbers that are increasing quickly every day. Through social media channels people exchange relevant links and opinions, and are easily informed by their peers and related groups about the topics they are most interested in. Indeed, this change in patterns of socialization, permitting the interaction among people that do not know each other but share a common interest, is fundamental to the argument of this research. The literature on knowledge management explores the differences between tacit and explicit knowledge. At the tacit level, knowledge is within human minds, being defined as the know-how that people have difficulty in communicating and representing through languages and schemas. As the tacit knowledge is difficult to transmit and
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articulate, it is necessary to have social interactions (socialization) to permit people to build a common understanding of what they want to learn to the point that these pieces of knowledge are internalized and become new practices or new behavior (Lave & Wenger, 1991; Nonaka & Konno, 1998). From this perspective, knowledge influences behavior when internalized; and the internalization of knowledge depends on having spaces for socialization that permit the sharing of ideas and the creation of common meaning within a given context. At the explicit level, knowledge is those aspects that can be communicated more easily through languages and schemas (i.e. words, graphs: mathematical and schematic models). In other words, explicit aspects of knowledge may be codified and in this codified state knowledge may be transferred through settings. KMS make ambiguous and complex reasoning clearer, measurable and operational. The complexity of formulae and models can be translated into interfaces, tables and graphs that may be easily understandable and used in specific domains. In this way it becomes easier to understand the meaning of a complex situation and the need to change behavior in specific directions. At this level socialization is not as necessary to permit the diffusion of knowledge. However, knowledge management research clearly points out that the tacit and explicit aspects of knowledge are interrelated, and that the diffusion of explicit knowledge most of the time depends on having spaces of socialization for sharing tacit knowledge (Hislop, 2009; Polanyi, 1983). In the process of knowledge exchange, tacit aspects of knowledge may become articulated and explicit (Bloodgood & Salisbury, 2001; Herschel et al., 2001). Indeed, some authors would argue that one cannot define the boundaries between tacit and explicit knowledge, since any expression of knowledge has elements of both, intertwined in a complex tissue (Nonaka & Toyama, 2003), and knowledge creation is grounded in the tacit aspects of knowledge (Nonaka & Konno, 1998).
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This intrinsic interaction between tacit and explicit knowledge is the fundamental assumption of the SECI’s model which aims to explain the process of knowledge creation (Nonaka, 1994; Nonaka & Takeuchi, 1995). In this model, there are four phases through which knowledge is created and shared. In the first phase, through socialization people share and transmit tacit knowledge. In the second phase, through externalization tacit knowledge is converted into explicit knowledge through processes of articulation. In the third phase, through combination different pieces of explicit knowledge are aggregated creating something new. Finally, in the fourth phase, through internalization explicit knowledge is converted into tacit knowledge (e.g. in learning). By doing, people internalize pieces of knowledge that beforehand were just codified knowledge outside their expertise. This model supports the argument in this article that providing environments for socialization and communication are important steps in sharing tacit knowledge and permitting the conversion of tacit knowledge into explicit knowledge through efforts of articulation. Considering the presented dichotomy, the fact that tacit knowledge is not easily articulated does not mean that it cannot be articulated at all. Trying to solve the conundrum of how tacit knowledge becomes articulated, Griffith et al. (2003) proposes a different framework in which there are tacit, implicit and explicit aspects of knowledge that are a continuum of knowledge. In this framework, the implicit aspects of knowledge would be those that are not yet “declarative but could be made so,” meanwhile tacit knowledge would be the knowledge that could not likely be declarative (Griffith et al., 2003: 270). This differentiation could help to understand how non-explicit aspects of knowledge become articulated, although most authors in knowledge management adopt the dual definition of tacit and explicit knowledge.
In this research, tacit knowledge is understood as the aspects of knowledge that have not been yet articulated, but they may become explicit. It also considers that knowledge is a continuum that intertwines tacit and explicit aspects, being both necessary to the process of its diffusion. In other words, the diffusion of knowledge depends on cultivating spaces for socialization for sharing tacit and explicit knowledge, in which people explore different meanings through the interpretation of knowledge in different situations. Social interaction allows new pieces of knowledge to be embedded in practice thus fostering behavior change (Brown & Duguid, 1998; Nonaka & Konno, 1998). Thus virtual spaces for interaction are fundamental in diffusing knowledge and may leverage the impact of tools that focus on the communication of explicit knowledge. Knowledge has aspects that may be codified and aspects that develop through community interaction and the flow of knowledge (Alavi & Leidner, 2001). Firstly, the explicit codified knowledge is packaged in a way that makes understanding easier and more accessible and adequate to the needs of specific audiences. Secondly, the social spaces of interaction complete the work of embedment of knowledge through internalization and common social construction of meaning. Institutional theory explains that institutionalized aspects of knowledge influence beliefs, the way people understand the world (mindsets, cognitive schemas), and their perspective on what constitutes adequate behavior (March, 1994; Meyer & Rowan, 1977; Scott, 2001). In relation to the discussion on climate change for instance, there are disputes around whether humans are the main agent responsible for observed environmental changes in the world; however, there is a consensus that societies need to develop sustainable practices considering Earths natural resources are limited in relation to current consumption patterns (Hilty, 2008). At the level of institution-
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alized knowledge, it is currently understood that human behavior towards economic production should become sustainable. Relational networks that promote beliefs and identities aligned with this knowledge may become an efficient strategy for motivating behavior change.
VIRTUAL COMMUNITIES In the academic literature, studies on virtual communities have shown that online interactions offer spaces for sharing information and knowledge about common interests and even emotional support. Indeed, it has been argued that sharing information and knowledge is a major reason for maintaining online interactions (Butler, 2001; Jones, 1998; Mansell & Steinmueller, 2000). Furthermore, virtual communities have been understood as spaces in which social groups build identities, beliefs, values and meanings (Castells, 2001; Delanty, 2003; Friedman, 2007; Rheingold, 2000). Through interaction, social groups create their sense of community, building common identities and understanding (beliefs and frame of mind) by exchanging support among members with mutual influence (Blanchard, 2008; Rheingold, 2000). It is known that some virtual communities depend mainly on the interest of members in building good reputations in an expert domain for fostering collaborative behavior (Bergquist & Ljungberg, 2001; Matzat, 2004). This interest in building reputation may be explored in other domains as a way of engaging common citizens who could become champions of institutional change. Organizations and groups may foster this interest in creating reputation to motivate people to interact in social media spaces associated to KMS. Organizations, governments and civil society movements are increasingly incorporating new social media channels in their communication efforts, recognizing that virtual spaces are relevant for the diffusing of information and knowledge
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and fostering new identities and behavioral change (McAfee, 2009). However, academic research is still to investigate in depth the mutual influence of institutional environments and virtual spaces (i.e. how institutionalized behaviors influence the way people interact in virtual environments and how these very same virtual environments influence the way people behave when offline) (Hercheui, forthcoming). As proposed by institutional theory, cognitive schemas, identities and beliefs are carriers of institutionalized social structures in the sense of influencing behavior (Berger & Luckmann, 1967; Scott 2001). From the theoretical perspective, virtual interactions may influence the emergence and reproduction of new behavioral patterns, a perspective that needs to be properly explored by empirical research. The following section discusses the example of an Internet tool, Microsoft Hohm, which aims to foster behavior change in relation to the consumption of energy. It uses channels for the diffusion of explicit knowledge, easier and uncomplicated interfaces for fostering virtual interaction and diffusion of tacit knowledge. It discusses the tool from the perspective of KMS, explaining how its interfaces diffuse the explicit aspects of knowledge and how the associated social media channels cope with the tacit aspects of knowledge. The reinterpretation of the tool as an instrument for institutional change through fostering the diffusion of knowledge is presented in the discussion section.
MICROSOFT HOHM This section analyses Microsoft Hohm (https:// www.microsoft-hohm.com), a free-of-charge Internet tool that enables American residences to calculate their energy consumption and contrasts individual figures with neighborhood results and best practice recommendations. The choice of this tool derives from the current global debate on the relevance of adopting new behaviors towards the
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consumption of energy and resources in general considering that our current economic models are not sustainable in the long term, as explained in the introduction (Alavi & Tiwana, 2003; Hilty, 2008). This research has also preferred to focus on one unique case study because the primary intention in this chapter is to uncover empirical data that may support the development of a theoretical argument (Yin, 2003). The presented explorative analysis is based on the qualitative study of Microsoft Hohm and on the observation of the virtual spaces of interaction related to the tool (social media channels). The qualitative research is adequate to explore a phenomenon that is very complex from the sociological perspective, such as the case of knowledge sharing and diffusion (Mason, 2002; Orlikowski & Baroudi, 1991). Considering that social order emerges from the way people interact, it is a valid approach to explore how social actors understand their own action. In this research, postings from members in social media channels have been used as the main source for exploring how members interpret their interaction with the tool and the virtual space. In addition, as a first approach to understand the phenomenon through the proposed theoretical lenses, this researcher has preferred to have an open mind to observe what was there, without trying to frame the possible interpretations since the beginning through using a more quantitative approach (such as surveys). Future research can adopt a more test-driven approach than the exploratory perspective followed in this investigation. This researcher has used the tool in order to understand its interface, its mathematical models, and the reports on recommendations. The tool has been tested many times, changing the inputted information, to understand how the system would perform adjustments in the outputs and recommendations. All the statements presented in this chapter may be checked by any other re-
searcher. As Microsoft Hohm is open for free on the Internet, other researchers can freely check the validity of my claims. The nature of the debate and the interactions among users on social media channels has been uncovered through content analysis of the declarations published by Microsoft professionals and community members (Mason, 2002; Schwandt, 1997). This published content has been classified by this researcher in order to understand the nature of exchange in these environments. Firstly, the published content has been read without any previous category, looking for ideas that could fit and improve the theoretical development. Secondly, aware of the available content, posts were read, trying to fit to the developed categorization. This categorization and its description (as presented in Table 1) is a second-order construct, based on my own interpretation of the primary-order constructs originally contributed by community members, this is a valid approach in qualitative research (Schutz, 1962). The same posting may bring content that belongs to different classifications; thus the objective of the investigation was not to classify postings but to understand the general content of the debates in the studied channels. The classification has not been exhaustive in the sense of including all postings, as the objective was only to explore the kind of content that has been exchanged in those channels. In this way, this research has collected examples to build an understanding of the kind of content exchange, focusing on the aspects that could corroborate the proposed theoretical framework of knowledge sharing and behavior change. Other forms of classifying the very same content are possible, and the presented classification does not cover all discussed topics but only those that are relevant here. So the results should be understood more as an exploratory study on the tool and its social media channels rather than a map of debates on social media related to Microsoft Hohm.
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This research has not accessed data from the company or interviewed members of Microsoft Hohm’s community. The analysis is based only on the observation and analysis of the cited social media spaces. Again these data are open and available on the Internet for the investigation of any other researcher. As the company keeps the content of previous discussions, it was possible to analyze the content of discussions chronologically. This research has been conducted independently by the author, not being mandated by Microsoft or any other company or institution.
EXPLICIT KNOWLEDGE Firstly, through observation and use, this research has explored how the tool copes with the explicit aspects of knowledge by analyzing its technical interfaces. Microsoft Hohm offers tables in which users input data related to their energy consumption at home. The tool calculates the level of energy consumption for the residence in consideration of the information provided - based on mathematical models - and elaborates formal recommendations comparing the results to best practice and average consumption in the same neighborhood. Microsoft Holm brings a detailed set of tables which embed mathematical formulae to help American residents to reduce their energy consumption starting from their actual consumption patterns. As these mathematical models are related to American standards, Microsoft Hohm may be used only by US residents. The tool requests a postal code to set up the account; this permits the tool to calculate the ideal parameters for the same neighborhood since the consumption standards vary considerably in a large country. The tool embeds technical data for energy efficient buildings provided by the Department of Energy (DOE) and analytics from Lawrence Berkeley National Laboratories. In other words, Microsoft
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provides a software interface but the knowledge behind the elaboration of the tool is legitimized by research conducted by expert organizations. Starting from a knowledge management perspective, Microsoft Hohm may be analyzed in accordance with the way it treats explicit codified knowledge, vis-à-vis its social media channels which foster socialization and sharing of tacit knowledge. Starting with the codified knowledge, the tool offers two modules. In the first, users input the data referent to their energy consumption and the kind of building in which they live. This information is used to compare the individual consumption with standards in terms of best practice and neighborhood averages. In the second, the module provides a report with a list of recommendations considering the current consumption patterns of the residence. Thus the input of data and the output of recommendations depend on the formalized aspects of the tool based on the explicit aspects of knowledge that are embedded in the software and databases that support the interfaces. In order to use the tool, individuals need to create an account and input information related to their energy consumption at home, the characteristics of electric devices used at home, and the materials used in the infrastructure of their residence. This Internet interface has many detailed tables, which demand users to have knowledge about technical aspects related to electric devices and materials used in the residencies material infrastructure. This approach of demanding users to input too many technical details has advantages: the more precise the information, the better the recommendations for the user’s particular situation. However, in order to get the best from the tool users need to domain technical knowledge that not all may have. In order to circumvent this limitation, most fields in the tables have by default standardized information. In other words, if the user does not know a piece of information about
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the material used in the house, the tool considers that the default material is used in the house. In this way, residents may use the tool even when they have a small amount of technical knowledge. Users who have more technical knowledge related to their consumption of energy and the characteristics of the domestic appliances obtain better and more precise analyses and recommendations. Others may still gain reasonable feedback from the tool considering the information inputted in association with the default information. The codified aspect of the tool gives users two different forms of feedback. First it compares the individual situation with others in the neighborhood, permitting users to know their relative position in relation to others. Second, it provides a long list of recommendations on how the residence may reduce its energy consumption in absolute terms in relation to best practice. Then even if the residence is better off than others in a neighborhood there is still space for improving results and reducing the consumption of energy and the tool shows these extra steps in the direction of saving energy. The recommendations also inform the related costs for implementing the suggested changes.
TACIT KNOWLEDGE At the level of tacit knowledge, Microsoft Hohm cultivates different spaces of virtual interaction using social media channels, such as blogs, Facebook, Twitter and YouTube. The service also includes the possibility of sending individual emails for those that do not want to clarify doubts through public discussions. In these social media spaces both Microsoft representatives and members of the user community interact. Microsoft professionals are mainly responsible for clarifying doubts about the tool, although users also have an active role in suggesting how the tool could be improved.
Indeed, some ideas suggested by members have been added to the tool, as informed by Microsoft Hohm in these channels. Interestingly, Microsoft Hohm communities do not restrict their debates only to the tool. Although the tool is the primary interest of community members there is also a general discussion on how to save energy in workplaces and on other best practice behavior related to saving resources in general. The exchange of ideas on energy saving and other sustainable practices permit members to build a sense of community: people become a member of these spaces because they share a common interest, one of the main reasons why individuals join virtual spaces for interaction (Hercheui forthcoming). Even members who cannot use the tool because they do not live in the United States enter these communities and benefit from receiving advice and developing a sense of belonging through sharing common interests with people who have similar perspectives. Indeed, Microsoft professionals are permanently giving advice in order to foster the conversation within and between social media channels. Their participation in fostering interaction is very important. After their intervention, it is common to see members adding their own comments, experiences or doubts about a particular topic. In the sequence Microsoft professionals or other members come with clarification and further information, articulating aspects of knowledge that were not explicit previously and permitting the creation of new perspectives. Community members are very active in giving feedback to Microsoft, and many suggestions have been incorporated into the tool, as informed by the company in these virtual spaces, demonstrating the relevance of social media channels to foster the diffusion and creation of new knowledge. It is common to have posts in one social media channel referring to other spaces of interaction used by Microsoft Hohm. This approach is inter-
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esting because the company may use the strengths of each social media platform – which enables different sorts of interaction through different features –, without fragmenting the community. On Facebook for instance, the Microsoft Hohm page links to its contents on YouTube and Twitter. Community members can become involved to the degree that they want and the many channels complement each other providing a broad interactive platform that permits the sharing of knowledge through socialization. Naturally this approach demands more investment, as there is a permanent cost for keeping employees communicating to community members. However, this effort fosters more people to use the tool, because doubts are clarified and enhancements are incorporated and passed on to the community, showing the value of contributing to the development of the tool. In sum, this research has found four categories of content in the social media channels, that foster the sharing of tacit knowledge and the legitimacy of new behavior which takes into account the urgent need for sustainable societies. They are summarized in Table 1.
DISCUSSION Considering the knowledge management perspective adopted in this study, Microsoft Hohm has adopted an interesting strategy for diffusing knowledge on how to save energy consumption. Firstly, Microsoft Hohm incorporates explicit pieces of knowledge into the software, building an Internet interface that relies upon mathematical formulas to calculate individual consumption contrasted with ideal consumption standards and the average of consumption in the same neighborhood. At this level, the amount of codified knowledge is impressive, from the simple value of energy consumption to the many details related to the used electric devices and the materials used in the building. The materials used in the construc-
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tion and its characteristics, such as the number of windows, are fundamental to build good recommendations that fit the individual needs of the user instead of offering generic advice. The tool then copes with the explicit aspects of knowledge in a very efficient way, providing sophistication through rigorous mathematical formulae and detailed recommendations. Using the tool and its recommendations, people have information about their behavior and how to change it in the desired direction. In other words, the explicit aspects of the tool become a relevant instrument to foster behavior change. Secondly, Microsoft Hohm opens space for interaction and communication by using social media channels. Socialization is a fundamental pillar for the diffusion of knowledge and it offers the opportunity for sharing tacit knowledge. As explained above, the division between tacit and explicit knowledge is an analytical device since in practice both aspects are intertwined as knowledge. The explicit aspects of knowledge are fundamental to permit its diffusion; however, tacit knowledge is essential for supporting the spread of explicit knowledge. The virtual spaces of interaction allow users to discuss the use of Microsoft Hohm, energy consumption as a whole, and other broader topics on sustainability, thus offering an opportunity for sharing similar interests with community members.
Fostering Behavior Change As a tool for diffusion of knowledge on energy consumption, Microsoft Hohm may be understood as a knowledge management system which fosters behavioral change. Firstly, the tool embeds institutionalized knowledge on energy consumption, making available for non-technical American residents updated knowledge in the domain. In providing concrete forms of measurement, in absolute and relative terms (contrasting individual results with best practice and neighborhood averages), the tool converts abstract and complex
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Table 1. Content of category Content
Description
€€€€€€€€€€Clarifications on Microsoft Holm
€€€€€€€€€€In these interactions, the main objective is to clarify something related to the tool. Either Microsoft professionals or members start the discussion, posting questions or statements. In the sequence, if the topic calls attention, other community members start engaging in the discussion, clarifying doubts or adding more information and feedback. The goal of these interactions is to clarify something about the tool specifically. In these interactions, tacit knowledge needs to be articulated more formally (as explicit knowledge) or shared as ambiguous impressions that are not necessarily clear and final.
€€€€€€€€€€Clarifications on other topics €€€€€€€€€€Related to sustainability
€€€€€€€€€€In these interactions, the main objective is to extend the discussion to other topics related to sustainability and adequate use of resources. Here community members are not concerned about Microsoft Hohm directly. They may discuss any sort of topic that fits their broader interests on sustainability, using the virtual space provided by Microsoft Holm. Interesting, the company permits members to keep this interaction, somehow broadening the scope of their social media spaces. Again these discussions permit the sharing of tacit knowledge, in a more or less articulated format. They also emphasize the broader mission of the space in fostering behavior change in other areas furthermore energy consumption, reinforcing the sense of identity among members.
€€€€€€€€€€Suggestions for improving €€€€€€€€€€Microsoft Holm
€€€€€€€€€€The content under this category aims mainly to give suggestions to Microsoft in how to improve the tool. All sorts of feedback may be given, and professionals are prone to respond to the comments and to push changes in the tool when they are possible. Microsoft’s professionals feedback the community with the changes that have been done because of members’ suggestions. In this direction, tacit knowledge that comes from the community becomes articulated and explicit into the software (as new pieces of code and new features).
€€€€€€€€€€Community identity building
€€€€€€€€€€In this category, members focus on emphasizing the sense of belonging to the community, its general value, general benefit they have obtained for changing their behavior in relation to energy consumption, and the good feeling they have in participating in these virtual spaces of interaction and helping to reduce the energy consumption. In this kind of posting, the concern is not about clarifying doubts or giving suggestions, but just to show the value of being together having common interests for sharing, and changing their energy consumption. Although this is not a category directly linked to the diffusion and articulation of tacit knowledge, from an institutional perspective this kind of interaction is very relevant for fostering behavior change, because it affects the way people understand the world, their identities and values. The role of relational networks in changing behavior becomes more evident in this category of posting.
knowledge into digestible parameters that may be understood by the average citizen. In other words, the tool brings formalized knowledge that builds awareness on more appropriate behaviors, thus fostering behavioral change through the spread of knowledge. Indeed, what people understand as knowledge is behind many social beliefs that frame our behavior in society. In showing users that the tool is grounded on technical, legitimate knowledge, Microsoft Hohm reinforces its potential for fostering behavioral change.
Virtual interactions are also important for reinforcing this diffusion of new institutionalized knowledge as explained above in the interplay between tacit and explicit knowledge. However, these spaces for socialization are important not only for the sharing of tacit knowledge, but also for building proper communities. Research in social media shows that some virtual spaces develop interactive dynamics which characterize them as being virtual communities of interest since they share common focuses, rules of interaction and clear boundaries that define who legitimate mem-
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bers are (Graham, 1999). In these communities members share emotional support, information and knowledge, and through time they even build social identities and strong emotional ties. In other words, virtual communities of interests may become important relational networks for fostering behavioral change by creating and developing a process of behavior change, a phenomenon that is observed in face-to-face relational networks (Meyer & Rowan, 1977). The more people aggregate in similar communities and share the same beliefs about the need for adopting more sustainable behavior in the consumption of resources, the more bottom-up pressure society as a whole will feel to change the institutionalized structures of economic production towards sustainable models. As new identities emerge in virtual environments that also provide social cohesiveness, people will call for institutional change that fulfills the new needs and expectations in relation to their interests (Blanchard, 2008; Castells, 2001). Tools such as Microsoft Hohm offer interesting models on how Internet tools may support knowledge diffusion and foster institutional change, thus qualifying as knowledge management systems, considering the broader definition adopted by this research. The first necessary step in this direction is transforming complex knowledge into more digestible pieces that can be understood by nonexpert people. Having instruments to measure the impact of their behavioral change and comparing individual results with collective ones, people may incorporate this information into their routines and change their behavior. The second step is to offer space for socialization through social media channels. In this sense, the tool becomes more than a mechanism for knowledge diffusion; it offers an opportunity for developing relational networks that cultivate identities, values and beliefs that support institutional change favoring a more sustainable behavior in relation to resource consumption.
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Indeed, drawing upon an example related to the domain of sustainability, this chapter develops the argument that knowledge management techniques are important mechanisms for building new institutional environments and fostering behavior change. As discussed above in terms of institutional change the institutional context changes for many reasons, one of these being the emergence of new knowledge about a domain. When a new knowledge paradigm emerges, new beliefs and norms are created that affect the way people interpret their patterned behavior. Socialization offers the space for diffusing knowledge, but it also creates an opportunity for discussing institutional change. In this direction, strategic knowledge management for diffusing new practices and technologies may also foster new institutions and behavior change. The very same social space that permits sharing of tacit knowledge also fosters the emergence of new interpretations, identities and beliefs which may influence the way people and societies behave.
CONCLUSION Drawing upon the proposed theoretical perspective, this study claims that KMS may be used as resources for fostering change in institutionalized behavior. The study proposes that KMS offer capacities for diffusing legitimate knowledge and building relational networks through the interactivity, and that particular attention should be paid to social media channels and other types of virtual spaces for interaction when aiming to change behavior. Efforts for fostering behavior change may draw upon these characteristics of KMS as channels for diffusing knowledge and fostering relational networks that legitimatize new institutionalized behaviors. Indeed, companies do not need to build or buy proprietary software for fostering such interaction. Social media channels that are open on the Internet
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(such as Facebook and Twitter, in addition to forums and blogs) offer interesting opportunities for associating these interfaces with other proprietary information systems, including KMS. It is a matter of fact that access to the Internet is increasing all around the world, including those people who access the Internet through mobile technologies. The more people join virtual spaces of interaction the more relevant online relational networks become and the easier it is to diffuse KMS that rely on these channels or similar interfaces. People use these tools in their daily activities, thus the easiness of transferring the skills to operate these social media interfaces to other similar tools. This chapter proposes that academic research needs to put more emphasis on understanding the role of KMS in fostering behavior change. This study limits itself to the discussion of a theoretical argument that draws upon knowledge management and institutional theory research. In order to show how such an argument may be explored in an empirical research model, this study analyses an Internet tool, Microsoft Hohm, understood here as a KMS for its role in diffusing and creating knowledge. This study focuses on the analysis of the tool and the conversations in Microsoft Hohm’ social media spaces, to understand the role of the tool and respective communication channels in fostering knowledge diffusion and creation. The study also shows that at least at the level of discourse (only online posts have been analyzed), community members inform that they have changed their behavior after using Microsoft Hohm, and show a sense of belonging to such a community. It is necessary to add, however, that the interactions in social media channels do not necessarily occur spontaneously at the beginning. Many virtual communities demand animators and facilitators to build an interesting flow of interaction. In some environments these members are called champions (e.g. those who are supposed to foster the development of their virtual communities). In the studied virtual environments, Microsoft has professionals
that keep the discussion alive in all communication channels. This does not mean that members are not active in these communities; however it is notable that Microsoft Hohm’s team invests time to feed the communities with news and interactions. Organizations that aim to foster the diffusion of knowledge using social media should take this aspect into consideration to estimate the investment such a project would involve. The ideal model is to develop communities that are robust enough to sustain their interactions because of their interests, with minimum dependency on community champions. Further empirical research is necessary to show how KMS may effectively influence behavior change, from their more formalized spaces (sharing of explicit knowledge) to their less formal spaces for interaction, such as social media (sharing of tacit knowledge). An interesting line of research would be to understand the impact of KMS upon behavior change at the level of individuals and groups, and then how those impacted by the related systems act upon institutionalized social systems (including governments, corporations and civil society organizations) to promote behavior change. The influence of virtual environments in offline relations and vice-versa has not yet been deeply explored in the literature of information systems in general. Based on the developed arguments, this chapter proposes that governments, corporations and civil society organizations should take into account the potential benefits and limitations of information systems for fostering behavior change through the diffusion of knowledge. There are opportunities for exploring what is known about the virtual spaces of interaction in terms of building identities, values and beliefs that may be extended to fostering the emergence of new norms and even cognitive frameworks. Knowledge management systems may create and nurture virtual spaces in which people access knowledge and have the opportunity to socialize for sharing tacit knowledge and articulating tacit knowledge in a more formal
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fashion. New legitimate behavior is to emerge from very complex social interactions. Offering spaces for building better informed relational networks is an important step to contribute to more positive institutional changes.
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Griffith, T. L., Sawyer, J. E., & Neale, M. A. (2003). Virtualness and knowledge teams: Managing the love triangle of organizations, individuals, and Information Technology. Management Information Systems Quarterly, 27(2), 265–287.
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ADDITIONAL READING Brinton, M. C., & Nee, V. (Eds.). (1998). The New Institutionalism in Sociology. Stanford, CA: Stanford University Press. de Souza, C. S., Nicolaci-da-Costa, A. M., da Silva, E. J., & Prates, R. O. (2004). Compulsory institutionalisation: investigating the paradox of computer-supported informal social processes. Interacting with Computers, 16(4), 635–656. doi:10.1016/j.intcom.2004.07.003
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DiMaggio, P., Hargittai, E., Neuman, W. R., & Robinson, J. P. (2001). Social Implications of the Internet. Annual Review of Sociology, 27, 307–336. doi:10.1146/annurev.soc.27.1.307 DiMaggio, P. J., & 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 Douglas, M. (1987). How Institutions Think. London: Routledge and Kegan Paul. Easterby-Smith, M., & Lyles, M. A. (Eds.). (2003). Organizational Learning and Knowledge Management. Malden, MA, Oxford: Blackwell Publishing. Gosain, S. (2004). Enterprise Information Systems as Objects and Carriers of Institutional Forces: The New Iron Cage? Journal of the Association for Information Systems, 5(4), 151–182. Greenwood, R., Oliver, C., Sahlin, K., & Suddab, R. (Eds.). (2008). The Sage Handbook of Organizational Institutionalism. Los Angeles, London, New Delhi, Singapore: Sage. Hornby, S., & Clarke, Z. (Eds.). (2003). Challenge and Change in the Information Society. London: Facet Publishing. Knorr-Cetina, K., & Cicourel, A. V. (Eds.). (1981). Advances in Social Theory and Methodology – Toward an Integration of Micro and MacroSociologies. Boston, London, Henley: Routledge and Kegan Paul. Koh, J., & Kim, Y. G. (2004). Knowledge sharing in virtual communities: an e-business perspective. Expert Systems with Applications, 26, 155–166. doi:10.1016/S0957-4174(03)00116-7 Kraatz, M. S., & Moore, J. H. (2002). Executive Migration and Institutional Change. Academy of Management Journal, 45(1), 120–143. doi:10.2307/3069288
Machlup, F. (1962). The Production and Distribution of Knowledge in the United States. Princeton, NJ: Princeton University Press. Meyer, J. W., & Scott, W. R. (Eds.). (1992). Organizational Environments: Ritual and Rationality. Newbury Park, London, New Delhi: Sage Publications. North, D. C. (1990). Institutions, Institutional Change and Economic Performance. Cambridge: Cambridge University Press. Powell, W. W., & DiMaggio, P. J. (Eds.). (1991). The New Institutionalism in Organizational Analysis. Chicago, London: The University of Chicago Press. Scott, W. R. (1998). Organizations: Rational, Natural and Open Systems (4th ed.). Upper Saddle River, NJ: Prentice Hall International. Scott, W. R. (2003). Institutional carriers: reviewing modes of transporting ideas over time and space and considering their consequences. Industrial and Corporate Change, 12(4), 879–894. doi:10.1093/icc/12.4.879 Scott, W. R., & Meyer, J. W. (Eds.). (1994). Institutional Environments and Organizations. Thousands Oaks. London, New Delhi: Sage Publications. Silva, L., & Backhouse, J. (1997). Becoming Part of the Furniture: The Institutionalisation of Information Systems. In Lee, A. S., Liebenau, J., & DeGross, J. I. (Eds.), Information Systems and Qualitative Research. London, Weinheim, New York, Tokyo, Melbourne, Madras: Chapman & Hall. Slevin, J. (2000). The Internet and Society. Cambridge: Polity. Smith, M. A., & Kollock, P. (Eds.). (1999). Communities in Cyberspace. London, New York: Routledge.
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Swanson, E. B., & Ramiller, N. (1997). The Organizing Vision in Information Systems Innovation. Organization Science, 8(5), 458–474. doi:10.1287/orsc.8.5.458 Webster, F. (2002). Theories of the Information Society. London: Routledge. Wellman, B. (2004). The three ages of Internet studies: ten, five and zero years ago. New Media & Society, 6(1), 123–129. doi:10.1177/1461444804040633
KEY TERMS AND DEFINITIONS Behavior Change: Any sort of change in patterned, institutionalized behavior within society. In the context of this chapter it is the adoption of new behavior that is fostered by the diffusion of new understanding grounded in the diffusion of knowledge. Institutional Change: Although institutions are resilient and people tend to reproduce them through time, institutions also change. Institutional change occurs for many reasons, from the emergence of new contexts and new interpretations of reality, to the conflict between social groups,
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and ambiguities and contradictions within the institutional framework. Institutions: Resilient social structures in society, such as marriage and hand shaking, that people tend to reproduce. It may be equated to patterned behavior and social systems (such as organizations). In this study it is understood as patterned behavior. Knowledge: A broader framework in the human mind that is taken as truth and permits people to interpret the world and make sense of new events and information, creating new pieces of knowledge. Knowledge Management Systems: Information systems that support the management of knowledge at the organizational or societal levels. Social Media: All sorts of Internet applications that permit people to interact, such as forums, blogs, social networks (e.g. Facebook, MySpace and Orkut), Twitter, and Flickr, among others. Virtual Communities: All sorts of social interactions that are mediated by Internet applications, especially those that are regular, focus on common interests and respect sets of rules. In proper virtual communities, people easily may identify whether they are members or not.
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About the Contributors
Imed Boughzala is an Associate Professor (and Deputy Chair from December 2005 to March 2008) at the Department of Information Systems at TELECOM Business School. Prior to joining the Institut Telecom, he was Assistant Professor at the University of Technology of Troyes and before, he managed several IT and KM projects on behalf of several companies. His research interests are related to Collaboration Engineering and KM. As part of his research and consulting missions, he is working with companies as an expert in knowledge mapping and modeling techniques, and as facilitator for virtual projects. From September 2006 to September 2008, he was the Executive Vice-President of the French Knowledge Management Club, an association of industrial companies. He is Associate Editor of the Information and Management, and also editor/author of several books in the area. In 2008 and 2009, he was visiting Professor for three successive semesters at Brunel West London University (UK), University of Arkansas, and University of Nebraska (USA). Aurélie Dudezert is an Associate Professor (and Vice-Dean of Ecole Centrale Paris PhD School since 2008) at Laboratoire Génie Industriel at Ecole Centrale Paris. Prior to joining Ecole Centrale Paris, she was knowledge manager at Ernst & Young Center for Business Knowledge in Paris and then at TOTAL. Her research interests are related to Knowledge Centric Organization. As part of his research and consulting missions, she is working with companies as an expert in knowledge management audit and knowledge management organizational modes and practices. Since 2003 she is member of the French community of practices COP-1 that gather among 80 knowledge managers from industrial companies. She is editor/author of several refereed papers and books in the area. *** Antonio Carlos De Oliveira Barroso (PhD MIT ‘77), is a Professor and Senior Researcher at IPEN, an institute of CNEN (National Nuclear Energy Commission). He leads a research group at IPEN aimed at applications of Knowledge Management for Nuclear technology. He is also an Associate Researcher and Consultant of TerraForum Consultores, the leading Brazilian Consulting Company for Knowledge Management. Previously (1994-2003) he has served as R&D Director, Chairman, and Commissioner of CNEN, also as a Brazilian Alternate Governor at the Board of the International Atomic Energy Agency – IAEA. He is currently a member of the editorial boards of the International Journal of Nuclear Knowledge Management and of the International Journal of Nuclear Energy Science and Technology.
About the Contributors
Thomas Bebensee works as a Partner Manager for Google Shopping at Google in Dublin, Ireland. He studied physics, economics, and management at Heidelberg University, Germany and Paris-Sud University, France and holds the degree MSc in Physics with specialization in management from ParisSud University. Subsequently, he pursued his studies in business informatics at Utrecht University, The Netherlands and the University of Florida in Gainesville, USA. In 2010, Thomas graduated from Utrecht University with the degree MSc in Information Science with distinction. In his Master’s thesis project he specialized on the topics of knowledge management and Web 2.0 by analyzing the impact of Web 2.0 applications on knowledge management practices of two student-run organizations. Thomas has published papers in the Proceedings of ECKM and REFSQ and acted as a reviewer for PAKM, IIMA, and the IWSPM. Giuseppe Berio is Professor of Computer Science at the University of South Brittany, France, and affiliated to the Lab-STICC laboratory (www.lab-sticc.fr). Previously, he was senior researcher at the University of Turin, Italy, working in the Department of Computer Science. Prof. Berio holds the “Laurea” degree (1990) in Computer Science cum Laude from University of Turin, Master (1991) and PhD (1995) degrees both in Information Systems from Polytechnic of Turin. During his PhD, he was a visiting researcher at INRIA Rhône-Alpes, a French research institute in computer science and automatic control. In 1997, he was granted the Marie Curie Fellowship from European Communities for a two-year assignment to Laboratory for Industrial Engineering and Mechanical Production (LGIPM) of University of Metz, France. His main research work is in Information Systems and in interoperability of enterprise software applications. He has participated to the development of the M*-OBJECT conceptual modelling language called PDN, the CRAI model for representing human competences in Information Systems, and the UEML (Unified Enterprise Modelling Language). He was in the core members of the UEML Thematic Network and INTEROP Network of Excellence (www.inteop-noe.org), both projects funded by the European Commission. Prof. Berio is currently member of IFIP Working Group 8.1 “Design and Evaluation of Information Systems” and IFAC Technical Committee 5.3 “Enterprise Integration and Networking.” Alain Chapdaniel is Engineer of the Ecole Centrale Paris with a PhD in Economy; he has a supply chain expertise as a consultant and as an operational manager in large international groups. He has created several companies in services and education. He is also working with the Ecole Centrale Paris (teaching and research) on supply chain, purchases, and management. His last book (written in French) is: “Supply chain, management et dynamique d’évolution,” Hermes Sciences (2010). Edward T. Chen is a Professor of Management Information Systems in the Operations and Information Systems Department at University of Massachusetts Lowell. Dr. Chen has published numerous research articles in scholarly journals such as Information & Management, Journal of Computer Information Systems, Project Management, Comparative Technology Transfer and Society, Journal of International Technology and Information Management, and International Journal of Innovation and Learning. Dr. Chen has been serving as vice-president, journal editor, board director, editorial reviewer, track chair, and session chair of many professional associations. Professor Chen has received the Irwin Distinguished Paper Award at the Southwestern Federation of Administrative Disciplines conference and the Best Paper Award at the International Conference on Accounting and Information Technology. His main research interests are project management, knowledge management, and green IT. 257
About the Contributors
Lynne P. Cooper is Knowledge Strategist and Senior Engineer at JPL where she is responsible for Information System and process development to support JPL’s science and technology proposal efforts. She received her B.S. in Electrical and Computer Engineering from Lehigh University, and M.S. in Computer Engineering and Ph.D. in Industrial and Systems Engineering from the University of Southern California. Her work has been published in Management Science, Journal of Engineering and Technology Management, and the International Journal of Knowledge Management. She co-chairs the Knowledge and Innovation Systems mini-track at the Hawaii International Conference System Sciences. Her awards include the NASA Exceptional Service Medal for her work in automation, numerous NASA Group Achievement Awards, and the Best Paper, Academy of Management Organizational Communication and Information Systems Division (2001). Nabyla Daidj received her Doctorate in Economics in 1994 at the Sorbonne University (Paris). Since 2003, she is Associate Professor in Strategy at TELECOM Business School (known as Telecom Ecole de Management) and Head of Management, Marketing & Strategy Department. Her teaching and research interests are international business development and MNEs strategies in a context of hypercompetition and coopetition; evolution of inter-organizational relationships and cooperative strategies (partnerships, strategic alliances, networks, business ecosystems, clusters)and analysis of organisational structures (conglomerates, keiretsu), governance, and performances. She published a book in 2008 about cooperation, games theory, and strategic management. Currently, she is studying the sources of value creation in international firms. François Deltour is Assistant Professor in Business Administration and Information Systems Management at Ecole des Mines Engineering School, Nantes (France). He is a member of the LEMNA research center. He obtained his PhD in Management Sciences in 2004 from the Lille University of Business Administration. His doctoral dissertation dealt with users’ evaluation of intranets. He published several papers focused on ERP implementation and knowledge management practices. Jair Anunciação De Azevedo, Jr. is PhD Student of Nuclear Technology program at the University of São Paulo. He holds a Master’s in Business Administration with emphasis in Risk Management and Knowledge Management (KM) in IT Projects. He is PMP certified by PMI and ITIL certified by EXIN. At present, he is Senior Project Manager at SAP. He was also Program Manager at Microsoft and Project Manager at Xerox. He is specialized in Distribution Systems by Federal University of Bahia (UFBA), Business Process Methodology (BPM) and he has wide experience with enterprise project management (EPM), UML, fusion point analysis, IBM Rational Rose, IBM Rational Requisite Pro, ARIS Toolset, and risk assessment in projects with @Risk tool. Antonio Di Leva received the “Laurea” degree and the post-doctorial (PhD) degree in Physics cum Laude from the University of Torino - Italy in 1968. At present, he is an Associate Professor of Information Systems in the Dipartimento di Informatica - University of Torino, where he carries on his teaching and researching activities. He has held visiting position at the Data Division of C.E.R.N. (Geneva - Suisse), at the OLIVETTI (Ivrea - Italy), at the University P. et M. Curie (Paris VI - France), and at the National Research Council of Canada - Laboratory for Intelligent Systems (Ottawa - Canada). Moreover, he was the national coordinator of a 5-year (1980-1985) research project of the Italian National Research Council
258
About the Contributors
whose main purpose was the development of methodologies and tools for database design. Since 1978, his research work has been dealing with theory and applications of data bases, Information Systems design and analysis, business process modeling, and simulation. In these areas, he is co-author of over 100 technical papers and co-editor of the book “Computer Aided Database Design - the DATAID Approach” North Holland (1985). He has participated to the development of the M*-OBJECT methodology for Information System analysis and design, and he has participated or collaborated in several ESPRIT research projects (ESTEAM, CIMOSA, PSIM, PARADIGMA, INTEROP Network of Excellence). Panorea Gaitanou works at the Benaki Museum Library since February 2002. She is a PhD candidate in Department of Archives and Library Science, Ionian University and member of the DBIS (Database and Information Systems) team of the Laboratory of Digital Libraries and Electronic Publishing (Ionian University). Her research interests are in the areas of metadata standards, and especially digital heritage metadata, metadata interoperability and integration, Semantic and Social Web. She holds a degree in Libriarianship, (Technological Educational Institute of Athens) and an MSc in “Information Science: Library Management and Organization, emphasizing on new information technologies.” Cécile Gaumand has been working as Supply Chain Manager for 15 years. She has developed her supply chain and management skills in several industrial companies. After a Master’s in Logistics and Systemic, she is realizing a PhD thesis in Ecole Central Paris. Her PhD deals with the consequences of knowledge management system in supply chain in organization. Bhojaraju Gunjal lives in Bangalore, India and serves as the Project Manager/Knowledge Management (KM) Consultant at one of the world’s leading Information Technology companies. He has more than ten years of professional experience in knowledge management & library administration in IT sector. Presently he is pursuing a PhD in Library & Information Science (LIS) on the topic “Knowledge Organisation Systems in Digital Libraries: A Case of ETDs” from the University of Mysore. He holds an MLIS (Master of Library & Information Science) from Karnatak University, Dharwar securing high First Class and Gold Medal. He is the Founder and moderator of KM-Forum: an initiative from India – an e-discussion group for global KM & LIS professionals. He designed and developed KM Cyberary: a gateway to Knowledge Resources - for KM, LIS professionals and other internet users searching for information in various subjects. Mounira Harzallah graduated from the Ecole Nationale d’Ingénieurs de Tunis (Tunisia). She received a Ph.D. degree in industrial engineering (2000) from the University of Metz (France) and was granted a post-doctoral position (2001) at the laboratory LLP/CESALP (Laboratoire de Logiciels pour la Productique / Centre des Sciences Appliquées à la Production) of the University of Savoie (Annecy, France). She is currently Assistant Professor at the University of Nantes at the LINA (Computer Science Research Institute, Nantes, France). Her research is in the field of enterprise modeling and knowledge engineering, especially focusing on human competence modeling, enterprise interoperability, and similarity measures for ontology building and validation. Dr. Harzallah has been involved in various national and international research projects, among them the INTEROP Network of Excellence (www. inteop-noe.org) funded by European Commission. Currently, she is member of the International Virtual Laboratory for Enterprise Interoperability (http://www.interop-vlab.eu/).
259
About the Contributors
Remko Helms is an Assistant Professor at the Department of Information and Computing Science at Utrecht University, The Netherlands. He received his MSc and PhD from Eindhoven University of Technology, The Netherlands. Currently, his research focuses on knowledge management and social media applications in the manufacturing and software industry, with a particular interest in knowledge sharing and transfer practices and structural analysis of (online) communities using social network analysis. He serves on several program committees, e.g. ECKM and PAKM, and acts as a reviewer for several major IS conferences, e.g. ECIS and ICIS, and IS journals, e.g. International Journal on Information Management and Information Systems Journal. At the end of 2009 he was a visiting researcher to Melbourne University, Victoria, Australia. Magda David Hercheui is a Senior Lecturer in Project Management at Westminster Business School and Associate Researcher at London School of Economics and Political Science. She researches social media and virtual communities, and the application of Information Systems for information and knowledge management on sustainability. She also coordinates New Media Knowledge, a knowledge community with more than 8,000 professionals specialized in digital industries and social media. Magda is a consultant on social media, and speaks in academic and industry conferences. Previously to her academic career, Magda has developed Information Systems for media and banking industries, and has been an editor of Economics and Finance. Loïc Ple is Assistant Professor and Director of the New Educational Technologies division at IÉSEG School of Management, France. He received his Ph.D. in 2006 from the University of Paris-Dauphine (France). His research topics deal with intra-organizational coordination and the impact of the customer on firms’ organization. His research has been published in several academic and professional journals. He won the 2010 M@n@gement award delivered to the best paper of the AIMS Conference (Association Internationale de Management Stratégique). Rita Izabel Ricciardi is Science and Technology Analyst at IPEN, an institute of CNEN (National Nuclear Energy Commission), carrying out research on knowledge management (KM) and developing projects for KM implementation in nuclear areas. She earned Master of Science in 2003 at the University of São Paulo; Ph.D. in 2009 on Nuclear Technology with emphasis on Management of Technology – major KM – and her thesis was developed in co-orientation with the University of São Paulo and TELECOM & Management SudParis, France. She also did specialization courses on KM at the University of Technology of Troyes, France, by the auspices of IAEA. At IPEN, she worked previously for human resources support and was responsible for the international exchange and technical cooperation area. Mark Rober is a Mechanical Engineer at the Jet Propulsion Laboratory in Pasadena, CA. In addition to being the Chief Architect of JPL Wired, he recently just delivered the Inlet Cover Assemblies which will reside on the top deck of the next Mars Rover (Mars Science Laboratory) scheduled to launch in October 2011. In his six years at JPL he has worked on the AMT, GRAIL, SMAP and MSL flight projects. Mark graduated from BYU with a BS in Mechanical Engineering in 2004 and is currently pursuing a MS in Mechanical Engineering from USC.
260
About the Contributors
Giovanni Maria Sacco is Associate Professor of Information Systems and HCI with the Department of Informatics, University of Torino, Italy. Before that, he had worked at Purdue University, at the IBM San Jose Research Lab (in the System-R group), and at the University of Maryland, among others. Sacco’s work on security with Dorothy Denning was the first attack on key distribution protocols and one of the bases of MIT’s Kerberos. His work with Mario Schkolnick on buffer management for relational database systems introduced predictive buffer management. He introduced fragmentation, later known as recursive hash partitioning, the first subsort/merge join method, which is widely implemented in industry. Since the 80s he has been active in the area of information retrieval, in which he led research and industrial projects. He introduced dynamic taxonomies (aka faceted search) and has published over 25 papers on this topic. He edited, with Yannis Tzitzikas, the book Dynamic Taxonomies and Faceted Search – Theory, Practice, and Experience, published by Springer in 2009. Caroline Sargis Roussel obtained a PhD in Management Sciences from the University of Lille 1 (France). She is an Assistant Professor at IAE Lille and IESEG School of Management where she teaches management control, accounting, and knowledge management. She is a member of the Lille Economy and Management Research Centre. She is interested in knowledge management and her main research subject is knowledge creation, diffusion, and integration in IS projects, using a qualitative methodology. She has published several articles dealing with these subjects. Marco Spruit is an Assistant Professor at the Department of Information and Computing Science at Utrecht University, The Netherlands. He received his PhD from the University of Amsterdam, The Netherlands. His research revolves around knowledge discovery processes to help achieve organizational goals through data mining techniques, business intelligence methods, linguistic engineering techniques, and social Web technologies. Additionally, he investigates information security models and cloud computing frameworks as infrastructural safeguards and enablers for knowledge discovery processes. His strategic research objective is to realize an interdisciplinary knowledge discovery platform. Please visit http://m.spru.it for more information. Sarah Yasin is an e-Content Bibliographer at YBP Library Services in New Hampshire (USA). She holds an MLIS from the University of South Florida, and specializes in digital collections. Sarah has been at the forefront of the transition from print to electronic books for Academic Libraries. Her guidance in the development of order management systems has shaped the evolution of content delivery both for publishers and end-users.
261
262
Index
A abilities, skills, knowledge etc. (ASKe) 106-107 action-research 147, 149-150, 152, 154-157, 163 Ambient Technology 12 analysis framework 189 artificial intelligence 77, 119, 142 ASAP Methodology 179 ASLOG 150-151, 157 Asynchronous JavaScript and XML (AJAX) 87 Authority 55, 60, 63, 79
B balanced scorecard 153, 157, 159, 161 behavior change 214-216, 219-221, 224, 226-227, 232 Behind the Firewall (BTF) 44-46, 48, 54-56, 58, 60, 63 Bonfiglioli 142, 147-152, 156 boolean expressions 114 Bottom-Up Network 81 Brazilian panorama 165, 170, 173 Business Process Owner (BPO) 151
C case study research (CSR) 24, 38-39, 41, 62, 175, 189, 212, 230 Cedar Crestone report 103 champions 9, 49-50, 78, 91, 220, 227 cloud computing 12, 165, 188 cognitive schemas transformation 151-152, 154 Collaboration 2.0 1-2, 4-8, 10-13, 15, 202 CollectedData 108 collective intelligence 1-2, 4, 6, 13-15, 21, 35, 42, 86, 95, 100, 167-168, 188, 202 Collective Membership 45, 63 collective reasoning 167
common knowledge basis 174, 177, 180, 183, 186, 189 Community Governance 45, 59, 63 Community of Interest 45, 63 Competence 103-110, 112-115, 117-120, 145 competence acquisition 104-105, 107, 117-118 competence assessment 104-105, 108, 112, 117 Competence knowledge usage 104-105 Competence Management 103-104, 107, 110, 112115, 117-118, 120 Competence, Resource, Aspect, Individual (CRAI) 103, 105-110, 120 complacency factor 166 complex project scope 170 Computer-Aided Design (CAD) 7, 16 conflict management 170-171, 173, 177, 179-180, 182, 184, 187-188 core competencies 86, 196-197 corporate governance 62, 141, 194, 198, 209-212 Corporate Wiki 44, 58-59, 61, 63, 80 council of logistics management 144, 162 C-Resource 108-110, 120 crowdsourcing 1-2, 164 culture assessment 174 Customer Relationship Managment (CRM) 7, 143, 149, 151
D Decision Knowledge Sharing (DKS) 157 DeclaredData 108 Department of Energy (DOE) 222 diffusion of knowledge 191, 215-216, 218-220, 224, 227, 232 Digital Natives 2, 15 distinctive resources 196-197 Dynamic Taxonomies 103, 105, 107, 110-115, 117, 119 Dynamic Taxonomy Search 120
Index
E Efficient Customer Response (ECR) 143, 157 energy consumption 11, 214-216, 220, 222-224 Enterprise 2.0 1-2, 4-5, 7, 14-15, 18, 40, 203, 229 Enterprise Document Management System (EDMS) 176 Enterprise Resource Planning (ERP) 7, 16, 139, 143-144, 149, 151-153, 155, 159, 163 Enterprise Social Software 1, 15 Eureka 132-135, 139 explicit knowledge 7, 16, 19-20, 123-124, 173, 214, 218-220, 222, 224-225, 227, 229
Information and Communication Science and Technology (ICST) 7, 16 institutional change 216-218, 220, 226, 231-232 institutional influences 218 institutional theory 214, 216, 219-220, 227, 230 Internet of things 2, 12, 14 inter-organizational 10, 143, 145-146, 157-158 Interpersonal knowledge 4, 6-7, 12, 16 InTouch 132, 134-135 intra-organizational 38, 142-143, 145, 147, 154, 156, 158, 163 Intrapedia 44, 46-47, 49-50, 53, 56, 63 Italian SME 142-143, 147
F
J
Facebook 2, 6, 18, 27, 31, 33, 35-36, 39, 42, 68, 71, 74-75, 77-78, 86, 93, 95-97, 139, 166, 207, 218, 223-224, 227, 232 field inspection reporting system 168 focal knowledge 123 four macro-enterprise processes 104 further use 174
joint platforms 203-204, 213
G Generation Y (GenY) 1-2, 5-6, 9-11, 13, 15, 124, 201 Global Positioning System (GPS) 11, 16 global quality approach 155 Governance 44-45, 59-60, 62-63, 141, 179, 182, 194-195, 198-199, 209-212, 229 Group Decision Support Systems 16, 22 Group Decision Systems 16 Groupware 7
H horizontal keiretsu 194 Hosting Environment 63 Human Resource software systems (HR systems) 103-105, 107, 118 hybrid organization 190, 207, 213
I Impact Model 18, 21, 32, 34, 37 implicit knowledge 16 Implied Warranty 44, 55, 58, 63 IMS RDCEO (IMS Reusable Definition of Educational Objective) 107 infobase 110-111, 113, 115
K keiretsu 190-196, 198-199, 208-209, 211-213 KM 2.0 1-2, 4, 7, 10-11, 13-15, 17-18, 21, 32, 34, 37-38, 40, 70, 75, 77-79, 138, 159, 190-191, 199, 201-204, 207-208, 213 KM 2.0 practices 10, 191, 204, 213 KM researchers 169 KM solutions 84-85 KM spectrum 20, 22, 24-25, 29, 32-34, 38 KM system for capture and reuse 169 knowledge alliances 197, 213 Knowledge-Based View (KBV) 157, 160, 196 knowledge bases 25, 49, 144, 153, 173, 200 Knowledge capital 6, 64, 149, 203 knowledge formalization 144, 151 knowledge frameworks 215-217 knowledge logisticians 153 Knowledge Management 2.0 2, 18, 21, 38, 189 knowledge management (KM) 1-2, 4, 7, 10-15, 17-22, 24-42, 44, 46, 49-50, 55, 60-62, 64-66, 68, 70-73, 75-81, 84-85, 94, 97, 100-102, 110, 118-120, 122-123, 125, 131-132, 134-135, 137145, 147, 151-153, 155-165, 167-169, 171-173, 187, 189-191, 193, 196-197, 199-204, 207-215, 218-219, 222, 224, 226-232 knowledge management lens 164-165 knowledge management systems (KMS) 7, 46, 55, 60, 84-85, 119, 142-147, 149, 152, 154-156, 158-159, 161, 163, 187, 214-216, 218, 220, 224, 226-228, 232 knowledge map 149-150, 152, 154, 158 knowledge perspective 218
263
Index
knowledge sharing 1, 6, 11, 15, 25-26, 28, 36-37, 40, 42, 44-45, 60, 62, 64-66, 75, 79-81, 84-85, 94-95, 99, 122-126, 128-132, 134-141, 149, 152, 155, 157, 166, 173, 189, 191, 193, 200201, 213, 221, 231 knowledge sharing 2.0 123, 125-126, 128-129, 131132, 135, 141 knowledge worker 39, 157-158 KNOW network 200
Organization 2.0 1-7, 10-13, 15, 142-143 organizational culture 25, 59, 85, 125, 137-138, 142, 148, 174, 189, 212 organizational culture classification 189
P
late product differentiations 143 Law of Least Effort 70, 81 lean management 143 Leverage the Long Tail 21, 42 Linkedin 6, 68, 71, 74, 77-78, 86, 93, 95, 104 Lotus Domino system 25
Personal Digital Assistant (PDA) 16, 86 Personal knowledge 16, 55 Petroquisa 179, 181, 185-186 pod people 166 potential usefulness 174, 178, 181, 184, 186 process knowledge 146, 151-152, 154-155, 158 project management 9, 30, 46, 123, 131, 164-170, 173, 175, 177-178, 180, 182, 187-189, 199, 211 Project Management Institute (PMI) 165, 170-172, 174, 176-178, 181-182, 184-185, 187-189 Project Management Office (PMO) 170-172
M
R
Market Team (MT) 24, 28-33, 36, 40 mashups 1, 15, 41, 93, 100, 102 Mass collaboration 1, 6, 11-12, 15, 91, 100 Massively-Multiplayer Online Role-Playing Game (MMORPG) 10, 16 Microsoft Hohm 214-216, 220-227 middle management 142-143, 156, 158 Milennials 2 Monarchy Model of Information Politics 81 Most Admired Knowledge Enterprises (MAKE) 11, 19, 21, 24-25, 27, 31, 39, 41, 48, 51, 55-57, 59, 63, 65-66, 69, 71-73, 76, 86, 91, 93-96, 98, 106, 125, 131, 134, 141, 145, 157-159, 165-166, 173, 185, 188, 194, 197, 200-201, 203-204, 206, 212, 218, 232 MySpace 33, 77-78, 86, 90, 93, 95, 97, 166, 232
Radio Frequency Information Device (RFID) 143 Rawdata 108 Really Simple Syndication (RSS) 1, 16, 74, 84-86, 89-90, 93, 99-100, 102, 124, 165, 177, 180, 182, 202, 207 reconciliation theory 156 Renault-Nissan alliance (RNBV) 194, 196-198, 205, 207-208, 213 Renault-Nissan Information Services (RNIS) 199 Renault-Nissan Purchasing Organization (RNPO) 199 renewed knowledge sharing practices 122 required competence identification 104 Resource-Based View (RBV) 63, 142, 162-163, 196 Responsibility 45, 55, 58-59, 63, 209 Return on Investment (ROE) 18, 59, 97, 195, 213 Reusable Definition of Educational Objective (RDCEO) 107-108, 118 RSS feeds 74, 84-86, 89-90, 93, 99, 207
L
N Network Effects 21, 36, 42, 124, 189, 202-203 networks of professionals 104 new knowledge perspectives 216 Nissan Europe (NTCE) 201 Nissan Japan (NML) 201 Nissan South Africa (NSA) 201 Nissan Thailand (NTCSEA) 201
O Ontology 12, 114-115, 118, 120 Open Innovation 1-2, 5-6, 11, 13, 15, 39 Open Source 6, 60, 86, 91, 102, 228
264
S sanction mechanisms 217 SCOR 151, 157 SC processes 149, 152-153 SECI model 156 semantic web 12, 41, 104, 110 Small and Medium Enterprise (SMEs) 7, 16, 142143, 147 Smart World 2, 12, 14 Social Bookmarking 66, 74, 78, 80, 89-90, 101, 165
Index
social capital 1-2, 4, 6, 13-16, 122-123, 126-130, 135-141, 167 Social-CRAI model 103, 108-109, 112, 117 socialization 4, 6-8, 10, 16, 18, 130, 191, 215, 218219, 222, 224-226 social media 2, 14, 32, 65, 68, 72, 74, 78, 81, 101, 203, 214-218, 220-227, 232 Social Networks (SNs) 1, 6, 9-10, 12, 35, 64-66, 68-82, 85-86, 93-105, 108-110, 117, 124, 126127, 129, 134, 137, 139, 145, 149, 160, 165166, 201-203, 206-207, 211, 213, 217-218, 232 social sciences 24, 122, 126, 142 Social Software 1, 15-16, 64-66, 71, 79-81, 101 stable shareholding 194 strategic alliance 190-191, 194, 196, 198-200, 204, 207-208 strategic key drivers 142, 149, 151 supplies synchronization 143 supply chain actors 147, 151 supply chain department 143, 148-150 supply chain knowledge characteristics 146, 148 Supply Chain Management (SCM) 7, 16, 142, 144, 157, 159-161, 163 supply chain objectives 146 supply chain performance 144, 150, 157, 159 Supply Chain (SC) 16, 142-163, 193, 199
T tacit knowledge 4, 15-16, 19-20, 123-124, 137, 141, 143, 145-146, 154, 156, 173, 191, 193-194, 197, 201, 213-214, 218-220, 222-227 Tags 26, 42, 72-73, 84-86, 89-90, 92, 98, 124 Task Team (TT) 199 Taxonomy 72, 81, 86, 107, 110-115, 117, 120, 160 technical online communities 132 techno-centric 12 total quality management 152-153 transversal function 143-144, 158
U Ubiquitous Internet 2 Unbounded Collaboration 17, 21, 35-37, 42 usefulness in the case 174 User-Generated Content 17, 21, 35-36, 38, 41-43
V vertical keiretsu 191-192, 194-195, 199, 209, 213 Victoria University (VU) 73, 75 virtual communities 60, 68, 80, 128, 139, 220, 225227, 229, 231-232 Virtual Environments 65, 68, 81, 220, 226-227 Virtual Reality (VR) 12 virtual teams 15, 28, 30, 34, 36, 161, 197 Vivo 176-178, 185-186
W Washington Research Library Consortium (WRLC) 73-74 Web 1.0 81, 124, 202 Web 2.0 1-2, 4-9, 11, 13, 15-18, 20-43, 46, 64-65, 67-68, 70, 73, 75, 80-81, 84-90, 92-93, 99-102, 104, 122-126, 129-130, 132, 135-143, 164-168, 170-184, 187, 189-190, 199-203, 205-209, 211-213 Web 2.0 tools 25, 31, 67, 100, 122-126, 129-130, 135-136, 141, 168, 170-175, 177, 180-182, 190, 199-202, 205-207, 213 Web-Based Project Management 165, 169, 189 web-log (Blog) 7, 34, 68, 72, 77-79, 88-90, 93, 100102, 166, 176-177, 179-180, 182, 202 Widgets 84-86, 89, 102, 124 Wikis 1, 7, 15, 18, 21, 25-38, 40-41, 44-63, 66, 74, 77-78, 80, 84-86, 91, 93, 99-102, 124, 137, 141, 165, 176-182, 184, 187, 202 Work-Wiki 50, 53, 55-56, 63
Z zaibatsu 191-192
265
