Modelling intellectual capital

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ISSN 1469-1930

Volume 4 Number 3 2003

Journal of

Intellectual Capital Modelling intellectual capital – papers from the 6th World Congress on Intellectual Capital Guest Editors: Nick Bontis and Christopher K. Bart

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Journal of Intellectual Capital

ISSN 1469-1930 Volume 4 Number 3 2003

Modelling intellectual capital – papers from the 6th World Congress on Intellectual Capital Guest Editors Nick Bontis and Christopher K. Bart

Access this journal online __________________________ 279 Editorial advisory board ___________________________ 280 Abstracts and keywords ___________________________ 281 Guest editorial ____________________________________ 284 Evaluating intellectual capital in the hotel industry Truls E.J. Engstro¨m, Petter Westnes and Siren Furdal Westnes __________

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The impact of reputation capital on the career paths of departing employees Monika Hamori ________________________________________________

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From implementing strategy to embodying strategy: linking strategy, identity and intellectual capital Anna Rylander and Joe Peppard ___________________________________

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Validating and measuring IC in the biotechnology and telecommunication industries Daniel Palacios-Marque´s and Fernando Jose´ Garrigo´s-Simo´n ____________

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Intellectual capital and traditional measures of corporate performance Steven Firer and S. Mitchell Williams _______________________________

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CONTENTS

CONTENTS continued

Distinguishing between the board and management in company mission: implications for corporate governance Chris Bart and Nick Bontis _______________________________________

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An empirical evaluation of option pricing in intellectual capital Sanjoy Bose and Kok-Boon Oh ____________________________________

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The IC-dVAL approach Ahmed Bounfour _______________________________________________

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Awards for Excellence _____________________________ 413 Best student paper award __________________________ 415 Call for papers ____________________________________ 416

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Journal of Intellectual Capital Vol. 4 No. 3, 2003 p. 280 # MCB UP Limited 1469-1930

EDITORIAL ADVISORY BOARD Guy Ahonen Professor in KM, Department of Management and Organization, Swedish School of Economics and Business Administration, Finland Sabin Azua Partner of Strategy and Knowledge Services, KPMG Consulting, Spain Margareta Barchan Co-founder and Executive Board Member, Celemi, Sweden Derek Binney Chief Knowledge and Technology Officer, CSC, Australia David H. Brett CEO and Founder, KNEXA, Canada Annie Brooking Chief Executive Officer, Lux Inflecta, Iceland Wendi R. Bukowitz Associate Principal, People Value Consulting, Buck Consultants, Inc., USA Leif Edvinsson Managing Director, Universal Networking Intellectual Capital AB, Sweden Luiz Antonio Joia Associate Professor, Brazilian School of Public and Business Administration (EBAPE), and Getulio Vargas Foundation (FGV), Brazil Baruch Lev Philip Bardes Professor of Accounting and Finance, Stern School of Business, New York University, USA

Jose´ Marı´a Viedma Marti Professor of Business Administration, Polytechnic University of Catalonia, and President of Intellectual Capital Management Systems (ICMS), Spain Jan Mouritsen Professor, Department of Operations Management, Copenhagen Business School, Denmark Sharon L. Oriel Director, Global Intellectual Asset Tech Center, The Dow Chemical Company, USA Richard Petty Lecturer, Faculty of Business and Economics, The University of Hong Kong, Hong Kong, China Kurt P. Ramin Commercial Director, International Accounting Standards Board, UK Go¨ran Roos Chairman, Intellectual Capital Services Ltd, UK Hubert Saint-Onge Chief Executive Officer, Konverge Digital Solutions Corp., Canada Patrick Sullivan President, Intellectual Capital Management Group, USA Karl-Erik Sveiby Professor, Swedish School of Economics and Business Administration, Finland

Evaluating intellectual capital in the hotel industry Truls E.J. Engstro¨m, Petter Westnes and Siren Furdal Westnes Keywords Intellectual capital, Hotel and catering industry, Function evaluation, Hospitality management, Norway A single embedded case study design was applied to evaluate the intellectual capital of 13 hotels in the Radisson SAS Hotels and Resorts hotel chain. By using the ICAP methodology and multiple sources data the study investigated the knowledge and data produced by an intellectual capital evaluation, and explored the potential relationship between intellectual capital and business performance. The results conclude that it is possible to evaluate intellectual capital in a hotel chain, and the knowledge and data from the intellectual capital evaluation provide useful information regarding the areas of identifying focal areas, resource allocation, strengths and weaknesses, benchmarking, and managing the future. In addition, the findings indicate that it is useful to evaluate a hotel’s intellectual capital due to its potential relationship with business performance. The impact of reputation capital on the career paths of departing employees Monika Hamori Keywords Human capital, Career development, Corporate image This paper examines the impact of corporate reputation capital on employees’ career progression in the case of inter-organizational transitions. A proprietary database that contains career history data on professionals, managers and executives in the financial services industry is used to test the hypotheses. The paper finds that reputation capital is most strongly determined by organization size, not operational efficiency. Reputation capital is an important predictor of the size of the promotions that employees receive as they change organizations, and may signal underlying individual capabilities and performance. Further, employees are willing to forgo a promotion in order to be able to join organizations with high reputation capital.

From implementing strategy to embodying strategy: linking strategy, identity and intellectual capital Anna Rylander and Joe Peppard Keywords Corporate strategy, Corporate identity, Knowledge organizations, Intellectual capital For most knowledge-intensive companies at present, the business environment where they compete is complex, characterized by rapid change and uncertainty. Employees and other intangible resources (i.e. intellectual capital) generally represent the most critical resources in the value creation process. Crafting strategy in such contexts is not helped by conventional models and tools of strategy. The assumptions which underpin many of them do not hold in the present competitive environment, making them at best irrelevant, but at worst leading to the development of strategies that can put the success of a company in jeopardy. New metaphors for describing these companies and their competitive realities, as well as tools for navigating in them, are required, if the strategy discipline is to remain relevant for practitioners. In this paper, it is suggested that the intellectual capital perspective can provide a bridge to the practical application of a visionand values-based strategy through the notion of embodying strategy in organizational resources. A conceptualization of strategy, that links strategy, identity and intellectual capital, more suitable to knowledge-intensive companies competing in uncertain environments, is introduced and described.

Validating and measuring IC in the biotechnology and telecommunication industries Daniel Palacios-Marque´s and Fernando Jose´ Garrigo´s-Simo´n Keywords Intellectual capital, Delphi method, Performance levels This paper specifies how to construct and validate an intellectual capital (IC) measurement scale on the basis of management perceptions. In order to construct the scales, a process based on the works of Churchill and DeVellis,

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complemented by the Delphi technique and structural equations models, was used. The use of this methodology was illustrated in an empirical study carried out in the biotechnology and telecommunication sectors. As a result, a validated instrument for IC research is obtained in view of the faithful and rigorous measurement of its key construct.

Intellectual capital and traditional measures of corporate performance Steven Firer and S. Mitchell Williams Keywords Intellectual capital, Productivity rate, South Africa The principal purpose of this study is to investigate the association between the efficiency of value added (VA) by the major components of a firm’s resource base (physical capital, human capital and structural capital) and three traditional dimensions of corporate performance: profitability, productivity and market valuation. Data are drawn from a sample of 75 publicly traded firms from South Africa from business sectors heavily reliant on intellectual capital. Empirical analysis is conducted using correlation and linear multiple regression analysis. Findings from the empirical analysis indicate that associations between the efficiency of VA by a firm’s major resource bases and profitability, productivity and market valuation are generally limited and mixed. Overall, the empirical findings suggest that physical capital remains the most significant underlying resource of corporate performance in South Africa despite efforts to increase the nation’s intellectual capital base.

Distinguishing between the board and management in company mission: implications for corporate governance Chris Bart and Nick Bontis Keywords Mission statements, Corporate governance A relationship between board/management “involvement” and “awareness” with organizational mission and their link to

“employee commitment” and “organizational performance” was modeled by drawing on previous research. The model was tested with data from 339 large Canadian and US organizations. It was determined that “mission awareness” on the part of both the board and senior management is an important consideration in the determination of employees’ commitment to the mission. However, the impacts of board and management involvement with the mission are not identical. The results emphasize the strong and important role that the board performs when it is actively engaged in the development of the organization’s mission.

An empirical evaluation of option pricing in intellectual capital Sanjoy Bose and Kok-Boon Oh Keywords Intellectual property, Assets valuation The investments in intellectual capital by firms in the knowledge economy are a critical driver for growth, profitability and competitiveness. This paper reviews the basic option-pricing models for pricing financial instruments and evaluates their characteristics in relation to their applicability to intellectual property, focusing on two distinct characteristics, i.e. past decisions that influence future technological options, and the inherent uncertainty over future innovation opportunities. The findings in this study include the discovery and confirmation of certain financial characteristics that are important for the successful implementation of the option pricing methodology in high technology financial planning and management. This paper attempts to summarise the current strand of literature pertaining to the use of option pricing in the intellectual capital-intensive sector by evaluating their strengths and weaknesses, and make recommendations as to how they can be effectively addressed to produce better results in the valuation process.

The IC-dVAL approach Ahmed Bounfour Keywords Resource management, Intellectual capital, Competitive advantage Over the last five years several frameworks have been suggested for the development of corporate competitive advantage, on the basis of their intangible resources. These frameworks are mainly managerially oriented; they require the design of a set of metrics dealing with organisational inputs. Hence the importance of making the link between internal and external perspectives, especially those related to financial

performance. Making such a link is the main aim of the intellectual capital dynamic value (IC-dVALw) approach, which integrates four dimensions for measurement – inputs, processes, assets, and outputs – and defines ad hoc metrics for measuring intellectual capital in a dynamic way. This approach is now used at the corporate level in several contexts. It is also under consideration for implementation at the mesoeconomic and even the macroeconomic levels. The paper also presents how such an approach can be used at the country level, especially in Europe.

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Guest editorial The following collection of papers addresses the Special Issue theme: “Modelling intellectual capital”. The need for empirically-based studies continues to be an important issue for the field to attain critical mass and the following papers address this need with various conceptualizations and models which examine intellectual capital from complementary perspectives. All of the selected papers in this Issue deal with model development and are generally empirically-based and address the issue of intellectual capital measurement in some way. As a collection, this Issue sets the groundwork for many years of future hypothesis development and testing. The authors in this Special Issue examine intellectual capital from a variety of functional perspectives including strategic management, human resource management, accounting and information technology. This Special Issue is also international in its scope, illustrating the global appeal of intellectual capital research. The first paper in this Issue was recipient of the “Best Paper Award” at the 6th World Congress on Intellectual Capital which took place 15-17 January 2003 in Hamilton, Ontario, Canada. The conference attracted over 300 abstracts, from which 150 were invited for submission. Of these submissions, the peer-review process yielded 60 that were invited to present at the conference. Truls Engstro¨m et al. are worthy winners of this prestigious award. Their paper evaluates the intellectual capital development practices of 13 hotels in the Radisson SAS Hotels and Resorts chain. The results conclude that it is possible to evaluate intellectual capital in a hotel chain, and the results from the intellectual capital evaluation provide useful information regarding identifying focal areas, resource allocation, strengths and weaknesses, benchmarking, and managing the future. Monika Hamori was the recipient of the “Best Student Paper Award” at the 6th World Congress on Intellectual Capital. Her paper examines the impact of corporate reputation capital on employees’ career progression in the case of inter-organizational transitions. She examined 968 inter-organizational movements within 2,000 financial services organizations. She concludes that reputation capital is an important predictor of the size of the promotions that employees receive as they change organizations, and may signal underlying individual capabilities and performance. Anna Rylander and Joe Peppard describe new metaphors linking strategy, identity and intellectual capital. The intellectual capital perspective can provide a bridge to the practical application of a vision- and values-based strategy through the notion of embodying strategy in organizational resources. A new

model is proposed which is more suitable to knowledge-intensive companies competing in uncertain environments. Daniel Palacios-Marque´s and Fernando Jose´ Garrigo´s-Simo´n advance the modelling and measurement of intellectual capital in their paper. They develop an IC scale based on a process developed by Churchill (1979a, b) and De Vellis (1991) which was complemented by the Delphi technique and structural equation modelling. The use of this methodology was illustrated in an empirical study carried out in the biotechnology and telecommunication sectors. The purpose of the fifth paper in this Special Issue is to investigate the association between the efficiency of value added by the major components of a firm’s resource base (physical capital, human capital and structural capital) and three traditional dimensions of corporate performance (profitability, productivity and market valuation). Steven Firer and Mitchell Williams draw data from a sample of 75 publicly traded firms in South Africa from business sectors heavily reliant on intellectual capital. They conclude that physical capital remains the most significant underlying resource of corporate performance in South Africa despite efforts to increase the nation’s intellectual capital base. Chris Bart and Nick Bontis evaluate the relationship between board and management “involvement” and “awareness” with organizational mission and their link to “employee commitment” and “organizational performance”. A model is developed with data received from 339 large Canadian and US organizations. The results emphasize the strong and important role that the board performs when it is actively engaged in the development of the organization’s mission. The seventh paper in this Issue reviews the basic option-pricing models for pricing financial instruments and evaluates their characteristics in relation to their applicability to intellectual property, focusing on two distinct characteristics, i.e. past decisions that influence future technological options, and the inherent uncertainty over future innovation opportunities. Sanjoy Bose and Kok-Boon Oh make recommendations as to how option-pricing models can produce better results in the intellectual capital valuation process. Finally, Ahmed Bounfour describes the IC-dVAL approach which integrates four dimensions for measurement – inputs, processes, assets, and outputs – and defines ad hoc metrics for measuring intellectual capital in a dynamic way. The paper presents how such an approach can be used to evaluate intellectual capital at the country level, especially in Europe. We would like to acknowledge the support of two students who helped in the processing and administration of several hundred papers that led to this Special Issue: Alexander Serenko and Sheliza Bardai. We also invite you all to

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participate in the 25th McMaster World Congress which will take place on 14-16 January 2004. Please be sure to visit our Web site at http://worldcongress. mcmaster.ca for further information. Nick Bontis and Christopher K. Bart Management of Innovation and Technology Research Centre, DeGroote Business School, McMaster University, Hamilton, Ontario, Canada

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The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1469-1930.htm

Evaluating intellectual capital in the hotel industry Truls E.J. Engstro¨m, Petter Westnes and Siren Furdal Westnes

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Norwegian School of Hotel Management, Stavanger, Norway Keywords Intellectual capital, Hotel and catering industry, Function evaluation, Hospitality management, Norway Abstract A single embedded case study design was applied to evaluate the intellectual capital of 13 hotels in the Radisson SAS Hotels and Resorts hotel chain. By using the ICAP methodology and multiple source data the study investigated the knowledge and data produced by an intellectual capital evaluation, and explored the potential relationship between intellectual capital and business performance. The results conclude that it is possible to evaluate intellectual capital in a hotel chain, and the knowledge and data from the intellectual capital evaluation provide useful information regarding the areas of identifying focal areas, resource allocation, strengths and weaknesses, benchmarking, and managing the future. In addition, the findings indicate that it is useful to evaluate a hotel’s intellectual capital due to its potential relationship with business performance.

Introduction The motivation for the present study is to make a contribution to the research field of intellectual capital by concentrating on an industry where it must be considered unfamiliar. The purpose of this paper is to explore the concept of intellectual capital in the hotel industry. Even though hotels are not primarily considered knowledge-intensive, they are providers of service. Both individual knowledge of the employees working in hotels and the organizational knowledge of hotels, expressed in routines, systems, customer databases etc. are considered important elements of effectively running a hotel in a competitive environment. This study particularly explores whether a hotel chain should evaluate its intellectual capital and, if so, why? Literature review Since other sources have extensively reviewed the literature on intellectual capital (Bontis, 1999, 2001, 2002; Bontis et al., 1999; Choo and Bontis, 2002; Guthrie and Petty, 2000), we will turn to review areas that are relevant to the issues of this paper: what is intellectual capital and why should companies measure it? No unified definition of intellectual capital is found in the literature; however, after reviewing some of the many definitions used, four major observations are presented: (1) There is no uniform definition of intellectual capital. (2) The concept of value creation occurs frequently. This suggests that intellectual capital is not useful unless it results in some form of increase in value to the organization.

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(3) Most of the definitions basically contain the same words: knowledge, skills, know-how, experiences, intangible assets, information, processes, and value creation. (4) The distinction between human capital, organizational capital, and customer capital is widely accepted. A number of classification schemes divide intellectual capital into the categories of external (customer-related) capital, internal (structural) capital, and human capital (Bontis, 1996; Bontis and Fitz-enz, 2002; Edvinsson and Malone, 1997; Roos et al., 1997; Stewart, 1997; Sveiby, 1997). The distinction has been widely accepted in facilitating the preparation of “intellectual capital accounts” which are employed differently in making decisions regarding organizational value that are more encompassing than decisions made previously (Guthrie and Petty, 1999; Sveiby, 1997). Human capital Human capital represents the individual stock of an organization as represented by its employees (Bontis, 1998; Bontis et al., 2002). Roos et al. (1997) argue that employees generate intellectual capital through their competence, attitude and intellectual agility. Competence includes skills and education, while attitude covers the behavioral component of the employees’ work. Intellectual agility enables one to change practices and to think of innovative solutions to problems. Even though employees are considered the most important corporate asset in a learning organization, they are not owned by the organization. Edvinsson and Malone (1997) define human capital as the combined knowledge, skill, innovativeness, and ability of the company’s individual employees to meet the task at hand. It also includes the company’s values, culture, and philosophy. Structural capital Structural capital includes all the non-human storehouses of knowledge in organizations. Edvinsson and Malone (1997) define structural capital as the hardware, software, databases, organizational structure, patents, trade marks, and all organizational capabilities that support the employees’ productivity. Bontis (1999) also argues that structural capital includes process manuals, strategies, routines and anything whose value to the company is higher than its material value. Roos et al. (1997) describe structural capital as what remains in the company when employees go home for the night. According to Bontis (1998), if an organization has poor systems and procedures to track its actions, the overall intellectual capital will not reach its fullest potential. Customer capital Customer capital is both the current value of an organization’s relationship with its customers and the potential future value of these relationships. The essence of customer capital therefore lies in the knowledge embedded in the marketing

channels and customer relationships that an organization develops through the course of its existence (Bontis et al., 2000). Customer capital represents the potential an organization has due to ex-firm intangibles (Bontis, 1999). Why should companies measure their intellectual capital? A range of “whys” to measure intellectual capital is presented in the literature. It is easily observed that most of these reasons are the meanings and hypotheses of academics and practitioners. Only a small amount of reliable research has been done on the actual effects of measuring a company’s intellectual capital. A study conducted by the Danish Agency for Trade and Industry (1998) of ten firms working on measuring intellectual capital found that measuring and actively managing intellectual capital were important for a company’s long-term success. Companies measuring and managing their intellectual capital clearly outperformed other companies. Bontis’ (1998) exploratory study of the relation between a company’s investments in intellectual capital and its business performance shows a significant and substantive causal link between dimensions of intellectual capital and business performance. This relationship supports the idea of investing resources in understanding and gaining knowledge about how these important intellectual assets can be further enhanced in organizations. Bontis et al. (2000) replicate this study using Malaysian data and find similar results. Ferrier and McKenzie’s (1999) study of Australian companies and the benefits they experienced when focusing on intellectual capital is also important. They concluded with the following main areas of benefits: . improvements in information provided to shareholders, supporting investment; . increased information to support and guide decision making; . support and provide guidance in the management of human resources; . support and provide guidance in the management of customer relationship. These benefits are information-intensive. They can be indirect results of focusing on intellectual capital and therefore difficult to logically explain as results of measuring a company’s intellectual capital. Methodology This research used a somewhat different approach to address the research question we asked – whether a hotel chain should evaluate its intellectual capital and, if so, why? An embedded case study strategy is chosen, including results from 13 hotels within the same chain. Further, actual intellectual capital evaluations (surveys) were conducted within the case study, in combination with an archival analysis and a history study. The use of multiple sources of evidence (construct validity) and the establishing of a chain of evidence that

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can be reviewed and repeated by other researchers (reliability) are meant to strengthen the quality of the current research design. Two analyses address the research question. First, an analysis of the information and knowledge provided through an evaluation provides insight into the potential usefulness of conducting an intellectual capital evaluation. Second, investigating intellectual capital’s potential relation to business performance will indicate intellectual assets’ relative importance for performing well in the hotel industry and therefore establish arguments whether resources should be invested in this process or not. There exists a range of different methods aiming to measure or evaluate a company’s knowledge (either stocks or flow). (See Bontis (2001) for a review of some of these methods and Sveiby (2001) for a comprehensive overview.) For the present study, the ICAP methodology developed by Teleplan AS was chosen. There were three main reasons for choosing this particular method: (1) they were a Norwegian-based company; (2) they had internally developed a tool for evaluating intellectual capital; (3) they had had solid experience from successful projects since 1998. Teleplan AS is one of the world’s leading privately owned companies in the fields of telecommunications and information technology. Further, Radisson SAS Hotels and Resorts (Radisson SAS) was chosen as a research object. This chain of hotels is represented in Norway with a total number of 19 hotels, including three franchise hotels. The ICAP methodology The ICAP methodology is a somewhat different approach to evaluate intellectual capital (for more details see Irgens et al. (2002)). First, it does not strive to measure but to evaluate intellectual capital, and by doing so it allows a much more subjective approach. Second, the ICAP model is not a shelf-application, but a tailor-made model that varies from organization to organization. The organization-specific model is based on each organization’s value chain and an analysis of the intellectual capital needed for that value chain to work the best and generate the most income. By focusing on the value chain, the ICAP method emphasizes the strong link between intellectual capital and business performance. The ICAP methodology is organized as a knowledge-focused project with consultant and client participation in all major processes. This collaboration is meant to produce the organization-specific ICAP model that reflects the organization’s value creation through an identification of their strategic intellectual capital elements. The identification happens through an analysis of the organization’s goals, strategies, and value-creating activities. The ICAP project workflow consists of five steps, where the first four are applicable to this study:

(1) (2) (3) (4) (5)

preparations; creating the model; evaluating the intellectual capital; reporting; and follow-up.

Setting ambitious and realistic goals is a critical project activity (Irgens et al., 2002). Together with top management at Radisson SAS decisions were made to pursue five project goals: (1) determine critical intellectual capital related to overall goals; (2) assess critical intellectual capital at hand; (3) make employee investments more efficient; (4) provide a management tool for handling intellectual capital systematically and effectively; (5) explore the intellectual capital needed to improve performance and reach business goals. In creating the model, Radisson SAS’ business plans, strategy documents, organizational charts, job descriptions, and value-creating activities were analyzed. Further, objectives and strategies pertaining to the future were examined. Identifying the value chain was the next step. Value chain analysis was originally developed by Porter (1985) and was later widely adopted as a framework for analyzing value-driven activities in modern businesses. Value activities can be divided into two major categories: primary activities; and support activities. Primary activities contribute to the actual creation of the product, its sale and transfer to the buyer and after-sales service. Support activities assist the primary activities and one another. Three main processes were decided to count for Radisson SAS: (1) delivering the room experience; (2) delivering the food and beverage experience; and (3) sales and marketing. Activities directly involved in these processes were regarded as primary activities and all other support functions, such as accounting, yield management, janitor services etc., were considered to be support functions. Once the value chain was identified, intellectual capital assets were found by exploring three questions: (1) Which systems and procedures are necessary for value activities? (Structural capital assets).

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(2) Which roles and tasks are necessary for value activities, and what are the demands on the person filling the role? (Human capital assets). (3) Which external relationships are necessary for value activities? (Customer capital assets). Developing survey questions that were supposed to address the above questions should in the end result in a model for evaluating intellectual capital in the Radisson SAS. Further, the assets (questions) are organized into the model in the form of a hierarchy and given weights. Weighting is supposed to reflect any given asset’s relative importance in optimizing the value chain. Intellectual capital questionnaire According to the ICAP methodology, evaluating individual capital (human capital) is supposed to be a non-anonymous survey. A pilot questionnaire was distributed to one of the hotels. Only 13 percent of the respondents responded non-anonymously. This indicated a potential problem and the preliminary questionnaire was rejected. A new questionnaire based on Bontis (1998) was developed. For the new questionnaire to fit the purpose of the present study, changes were made based on the results from the value-chain analysis. The final questionnaire contained 46 statements, to which respondents indicated their agreement on a seven-point Likert scale (1 ¼ strongly disagree and 7 ¼ strongly agree). Combining the ICAP methodology and the Bontis format resulted in the Radisson SAS ICAP value scheme (Figure 1) and a set of accompanying measures (see Table I for a summary of these measures). Within Radisson SAS, 16 hotels were included in the present research (total of 254 questionnaires). Owing to their knowledge about the hotel and their ability to

Figure 1. Radisson SAS ICAP value scheme

Level 1

Level 2

Level 3

Human capital

Competence Improvement “systems”

Competence ideal level Succession training programme Cross-departmental cooperation Upgrade employees’ skills Recruitment programme comprehensive Consequences if key employees left Come up with new ideas Employees voice opinions Individuals learn from one another Employees are best in industry Get the most out of employees Employee satisfaction Employees perform their best Employees think actions through Employees perform with “energy” Affect one another positively Employees give it their all

Intellectual agility Performance Attitude and motivation

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Customer capital Customer loyalty and satisfaction Customer satisfaction Customer loyalty Degree of customer repurchase Confident of future with customer Market share Market share improving Market share is highest Market orientation Hotel is market-oriented Meet with customer Customer information disseminated Understand target markets Care what customer wants Launch what customers want Handling customers Reduce time to handle complaints Value added service Feedback with customer Structural capital Efficiency and effectiveness

Renewal and development

Systems and procedures Atmosphere

Most effective processes Improving cost per revenue Increase in revenue per employee Revenue per employee is best Transaction time decreasing Hotel is efficient Implement new ideas Supports development of new ideas Develops most ideas in industry Procedures support innovation Systems allow easy info access Hotel is not a bureaucratic nightmare Not too far removed from one another Atmosphere is supportive

Table I. Summary of measures (questionnaires)

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give valid answers, only managers and middle managers were asked to answer the questionnaires. Of the 16 hotels, 13 involved qualified to be further analyzed. The final sample of 190 subjects resulted in a 75 percent total response rate. Business performance Business performance was divided into organizational performance and financial performance. Organizational performance was evaluated based on Radisson SAS’s own focus areas; degree of sick-leave and working climate. Sick-leave was measured for total sick-leave (as at 31 December 2001) and consists of short-term sick-leave (, eight weeks) and long-term sick leave (. eight weeks). Working climate analysis is conducted annually throughout the chain of hotels, and the total working climate score is based on a 30-item questionnaire covering areas such as communication, cooperation, job satisfaction, empowerment, goals, and leadership. Radisson SAS focus strongly on the economics of their business. The indicators used, gross operating profit (GOP) percent, RevPar, occupancy percent, rooms profit, F&B profit, and personnel cost, are reported periodically by all hotels in the chain and generally regarded as important and reliable key financial indicators in the hotel industry (Schmidgall, 1995) (see Table II for description of the key financial indicators). Analysis The ICAP reports When analyzing data from the intellectual capital evaluation, the software-tool ICAP 2.1 was used to produce key figures, descriptive information and focal areas. The focal areas are of particular interest because they are combinations of assets with high weight and low scores. Therefore, they represent the areas Indicator

Explanation

GOP percent

A measure of management’s ability to generate sales and control expenses; calculated by dividing income before fixed charges by total revenue Revenue per available room. A combination of paid occupancy percentage and average daily rate. Room revenues divided by available revenues or, alternatively, paid occupancy percentage times average daily rate A ratio indicating management’s success in selling its product; calculating by dividing the number of rooms sold by the number of rooms available A profitability indicator comparing the cost of room sold with room sales A profitability indicator comparing the cost of food sold with food sales A ratio of the cost of personnel in relation to revenue

RevPar

Occupancy percent Rooms profit Table II. Key hotel financial performance indicators

F&B profit Personnel cost

that need the most attention in the future to improve the value-creating activities and create competitive power (Irgens et al., 2002). ICAP reports are meant to present the results of an intellectual capital evaluation. The report contains information about the hotels’ available asset capacities on all three levels of the model. Capacity is calculated based on the average answers in the survey from each hotel. The assessment scale (Table III) shows that an average score of seven gives a capacity score of 120, which is the highest and best score a hotel can get for each asset (question). Local weights are set on each asset according to their importance and relevance for optimizing the value-creating activities in the hotel chain. The calculated value and priority in the report provide an understanding of strengths, weaknesses and focal areas. Each asset’s value is calculated by subtracting the capacity score from max. score (120) and multiplying it with the asset’s local weight. The higher the value score, the higher the priority.

Evaluating intellectual capital 295

Intellectual capital and business performance The low number of n (13 hotels) and the nature of exploratory case study design make it difficult to perform statistical analysis of the potential causal relationship between intellectual capital performance and business performance. Therefore, this potential relationship has to be explored using a more qualitative approach, namely benchmark analyses. Each hotel’s current status (intellectually, financially, and organizationally) is benchmarked in relation to the other hotels. In order to explore whether the same relationship between the three components of intellectual capital exists for the present study as for earlier studies (Bontis, 1998), there is a need for analyzing their inter-relationship. Focusing on intellectual capital will improve the value-creating activities and finally the financial results (Irgens et al., 2002). GOP includes all value-creating activities in the hotel (room, F&B, and sales and marketing) and, therefore, the present study will explore whether there are indications of a relationship between the total ICAP score and GOP. Further, rooms’ profit is a financial term that excludes all other activities not related to delivering “the hotel room product”. Therefore, exploring the potential relationship between this objective efficiency-indicator and structural capital might give an idea of how structural capital is related to effectively delivering “the room product”. The same argument can be built on food and beverage profit to explore how structural capital relates to delivering these products. Occupancy rate is considered a good indicator of how well the hotel is visited and can to a certain degree be influenced by customer loyalty and willingness to return. It is therefore interesting to explore whether there exists a potential Likert-scale Capacity

1 0

2 20

3 40

4 60

5 80

6 100

7 120

Table III. Assessment scale

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relationship between this performance indicator and customer capital, which is argued as representing customer loyalty and satisfaction, market share, how the hotel is handling customers, and their market orientation. RevPar is based on paid occupancy percentage and average daily rate and will follow the same pattern as occupancy rate. Hence, an analysis of one of the variables will in reality give the same result as for the other variable. Sick-leave is often explained by two different and competing perspectives; the push or pull theory (Mykletun, 2001). The push theory argues that employees are “pushed” into sick-leave by elements in the social setting external to employee control. The pull theory, on the other hand, argues that employees are “pulled” out in sick-leave by rational individual choices. Further, the pull theory argues that, if an employee is highly motivated and enjoys working, and provided that the financial compensation for taking sick-leave is relatively below going to work, an employee prefers working. By relying on the pull theory, work motivation and sick-leave should to a certain degree be related. Further, motivation is included as a construct in the theory of human capital and, therefore, this study intends to explore whether there might be a potential relationship between sick-leave and human capital. If motivation affects sick-leave, then what affects motivation? It depends on a range of variables and affecting conditions. Working climate can be argued to affect the employee’s motivation in certain ways, but also vice versa. Therefore, this study intends to explore whether there might be a potential relationship between working climate and total ICAP. Personnel cost is a ratio describing the cost of personnel in relation to total revenue. It can therefore be argued that it is an indicator of employee efficiency in a hotel. A range of factors affecting personnel cost and human capital might be one of them. This study intends to explore this by analyzing whether there might be a potential relationship between these two performance indicators. Table IV presents an overview of the analyses performed. Results ICAP reports An example of the ICAP report is presented to highlight the data and knowledge produced by an ICAP evaluation. The degree of details is different Human capital

Table IV. Overview of the analyses performed

Total ICAP Total ICAP Human capital Human capital Structural capital Structural capital Customer capital

$

Customer capital $ $ $ $ $ $ $

$

Structural capital GOP Total climate Total sick-leave Personnel cost Room profit F&B profit Occupancy

at each level in the ICAP report (see Figure 2 for an example, Hotel 106). Level three (3) is the most detailed level and presents the average response from each hotel to each question in the survey. The results in the different intellectual capital components are listed in order of priority. Low capacity score equals high value, and leads to high priority (priority 1). Intellectual capital and business performance An overview of the benchmarking results is presented in Figure 3. A score of 1 is the best and score of 13 is the worst a hotel can get on the benchmarking scale. The benchmarking results are divided into three different grey scale- and score categories: light grey is good (score 1-3), medium grey is average (score 4-10), and dark gray is poor (score 11-13). IC components. There are tendencies towards a tight relationship between human, structural, and customer capital. Out of the 13 hotels, 11 show internal consistency between all three aspects of intellectual capital. When calculating an absolute value between the three different components, it is found that the relationship is closer between human and structural capital than between any of the two other combinations of intellectual capital components. ICAP and GOP. There are tendencies towards a weak relationship between ICAP and GOP. The link is seen in six out of the 13 hotels where the score is very high, average, or very low on both variables. Total ICAP and total climate. Six hotels with an average or low rank of total ICAP also have an average or low ranking of the total climate. The three best scores in any of the variables represent the most extreme differences and do not indicate any relationship with one another. Human capital and total sick-leave. Eight out of the 13 hotels show a pattern between human capital and total sick-leave. This indicates a possible relationship. Human capital and personnel cost. A pattern (nine out of 13 hotels) indicates that there might be a relationship between human capital and personnel cost. Structural capital and rooms profit. Apart from the extremes represented in three out of the 13 hotels there is a tendency towards a high score on structural capital, indicating a high rooms profit, contrary to low scores. Structural capital and F&B profit. There are tendencies towards a possibly tight link between the benchmark score for structural capital and F&B profit (nine of the 13 hotels). Customer and occupancy. A pattern (nine out of the 13 hotels) indicates that there might be a relationship between customer capital and the occupancy rate. Discussion The Radisson SAS ICAP evaluation model is, like all evaluation models based on the ICAP methodology, organization-specific. However, there are reasons to believe that most full-service hotels’ value chains are more or less similar. This

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Figure 2. ICAP report example

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Figure 3. Benchmarking results overview

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means that, even though the model is tailor-made for Radisson SAS, it will also work for other similar chains of hotels. There might be good reasons to change the weighting of the assets according to their relative importance to the chain’s goals and strategies, but still the structure can remain the same. The present model has received a somewhat neutral weighting. If the weightings had been slightly different, different results would appear. It is therefore important to be aware of how weighting affects the end result. How to weight the assets is decided through value chain analysis, but most of all by the consultant’s subjective feelings, ideas about right and wrong, and “gut feeling”. It can therefore be argued that this kind of weighting of assets weakens the truthfulness of the intellectual capital evaluation. However, it can, on the other hand, be argued that it is better to know something about an organization’s intellectual capital, even though it is not the accurate description of reality, than nothing at all. There are still unanswered questions about the model: . Do the questions in our model really reflect the constructs it is meant to operationalize? . Does the model represent the essential of intellectual capital? . What is the truthfulness of our model? . Can we measure or control whether we succeeded in developing the model? In general, these questions represent some of the basic criticisms stated against intellectual capital as a concept. They are difficult to answer, if not impossible. The reports It is argued that the reports are good devices for managing intellectual capital (Irgens et al., 2002). This, however, assumes that the model is correct and provides valid information. It is the same rule for the ICAP reports as for any software report tool: garbage in ¼ garbage out. The report is structured in a clear and easy to follow manner, pointing out the focal areas that need future attention to presumably improve the value-creating activities. Each hotel should be given the opportunity to allocate their resources according to the priority given in the reports. The hotels should also receive benchmark ratings for all the hotels in their chain in order to follow up their relative position in the benchmark test. Further, the value of the knowledge provided by the reports can increase if the hotels use the ICAP tool as a management tool where they set accurate goals for each individual. This provides the opportunity to reach organizational goals in a more controlled manner. Intellectual capital and business performance When analyzing the relationship between the three intellectual capital components, indications of a relationship between them were found. However,

a stronger relationship between human capital and structural capital was found than between human capital and customer capital or customer capital and structural capital. The latter is a contradiction of the empirical study within two industry sectors in Malaysia conducted by Bontis et al. (2000). They detected a significant relationship between human capital and structural capital for non-service industries, and a not significant but positive relationship for the service industries, implying that it is more difficult to transform individual employee knowledge into non-human knowledge for service industries. However, even though hotels are not primarily considered knowledge intensive, they are providers of service. Both individual knowledge of the employees working in hotels and the organizational knowledge of hotels, expressed in routines, systems, customer databases etc., are considered important elements of effectively running a hotel in a competitive environment. A weak relationship between the benchmarking results of total ICAP and GOP was detected. However, the relationships between structural capital and financial performance figures that are elements of GOP – rooms profit and F&B profit – were much stronger and more plausible. Contrary to the Malaysian study, the current study used objective financial data and non-subjective financial data based on answers from a survey. Still, both studies represent similar findings; there is a positive relationship between structural capital and business performance. To sum up, the current study’s findings related to business performance indicate that hotels with both high human and structural capital will yield a greater profit. Support is also found for the motivational construct of pull and human capital theory. The results indicate a relationship between human capital and total sick-leave, meaning that hotels that score high on human capital have more motivated employees, which again leads to a low sick-leave rate. According to Bontis et al. (2000), a customer-focused and market-driven organization will ultimately create efficient organizational routines and processes that service their clientele well. This relationship between customer capital and structural capital that leads to higher business performance is supported by the current study’s findings, which state that hotels with a high customer capital also achieve a high occupancy rate. No indications of a relationship between the total ICAP score and the total climate score were found. This was unexpected, especially since one of the ICAP evaluations’ intentions was to supplement the hotels’ annual climate analysis. One possible explanation is that the climate analysis does not focus on the organization’s relationship with customers, while total ICAP does. This argument is supported by the fact that the three best hotels in total climate are ranked, respectively, as numbers 13, 11, and 10 on customer capital.

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Conclusion Conclusion can be made that, even though the actual truthfulness of the ICAP method can be questioned, it is possible to evaluate intellectual capital in a hotel chain. Further, a model for evaluating intellectual capital in a hotel chain has been built and can be put to use with the supposition that the weightings are properly adjusted to each organization. As mentioned earlier, there exists a range of methods to measure or evaluate intellectual capital. None of these methods, nor the one used in the current study, have been properly validated for research purposes. It is therefore difficult to state with certainty that the hotel’s actual intellectual capital is successfully captured. But, whether it was or not, confidence rises that steps have been made in the right direction. Further, reports have been produced that give information about a hotel’s current intellectual capital status. These reports consist of valuable data that give each hotel an opportunity to consciously work with and improve their intellectual capital. Working with intellectual capital is in theory argued to improve business performance and the current study’s findings support this relationship. References Bontis, N. (1996), “There’s a price on your head: managing intellectual capital strategically”, Business Quarterly, Summer, pp. 40-7. Bontis, N. (1998), “Intellectual capital: an exploratory study that develops measures and models”, Management Decision, Vol. 36 No. 2, pp. 63-76. Bontis, N. (1999), “Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field”, International Journal of Technology Management, Vol. 18 No. 5-8, pp. 433-62. Bontis, N. (2001), “Assessing knowledge assets: a review of the models used to measure intellectual capital”, International Journal of Management Reviews, Vol. 3 No. 1, pp. 41-60. Bontis, N. (2002), World Congress of Intellectual Capital Readings, Butterworth-Heinemann-KMCI Press, Boston, MA. Bontis, N. and Fitz-enz, J. (2002), “Intellectual capital ROI: a causal map of human capital antecedents and consequents”, Journal of Intellectual Capital, Vol. 3 No. 3, pp. 223-47. Bontis, N., Chua, W. and Richardson, S. (2000), “Intellectual capital and the nature of business in Malaysia”, Journal of Intellectual Capital, Vol. 1 No. 1, pp. 85-100. Bontis, N., Crossan, M. and Hulland, J. (2002), “Managing an organizational learning system by aligning stocks and flows”, Journal of Management Studies, Vol. 39 No. 4, pp. 437-69. Bontis, N., Dragonetti, N., Jacobsen, K. and Roos, G. (1999), “The knowledge toolbox: a review of the tools available to measure and manage intangible resources”, European Management Journal, Vol. 17 No. 4, pp. 391-402. Choo, C.W. and Bontis, N. (2002), The Strategic Management of Intellectual Capital and Organizational Knowledge, Oxford University Press, New York, NY. Danish Agency for Trade and Industry (1998), Intellectual Capital Accounts – Reporting and Managing Intellectual Capital, Erhvervsfremme Styrelsen, available at: www.efs.dk/ publikationer/rapporter/engvidenregn (accessed February 2001).

Edvinsson, L. and Malone, M. (1997), Intellectual Capital: The Proven Way to Establish Your Company’s Real Value by Measuring its Hidden Brainpower, Biddles Ltd, Guildford, King’s Lynn and London. Ferrier, F. and Mckenzie, P. (1999), “Looking ahead: an enterprise information and self-evaluation kit”, paper presented at the International Symposium on Measuring and Reporting Intellectual Capital: Experiences, Issues, and Prospects, OECD, Amsterdam. Guthrie, J. and Petty, R. (1999), “Managing intellectual capital: from theory to practice”, Australian CPA, Vol. 69 No. 7, pp. 18-21. Guthrie, J. and Petty, R. (2000), “Intellectual capital literature review: measurement, reporting and management”, Journal of Intellectual Capital, Vol. 1 No. 2, pp. 155-76. Irgens, E., Brekke, E. and Syvertsen, C. (2002), “Evaluating intellectual capital for improved performance”, Proceedings of 5th World Congress on Intellectual Capital, McMaster University, Hamilton. Mykletun, A. (2001), Utstøtningsmodellen og attraksjonsmodellen: En kort teoretisk innføring med referanseliste, Høgskolen i Stavanger, Avd. Norsk Hotellhøgskole, Stavanger. Porter, M. (1985), Competitive Advantage: Creating and Sustaining Superior Performance, The Free Press, New York, NY. Roos, J., Roos, G., Dragonetti, N. and Edvinsson, L. (1997), Intellectual Capital: Navigating the New Business Landscape, Macmillan Press Ltd, London. Schmidgall, R.S. (1995), Hospitality Industry, Managerial Accounting, 3rd ed., Educational Institute of the American Hotel and Motel Association, East Lansing, MI. Stewart, T.A. (1997), Intellectual Capital: The New Wealth of Organizations, Nicholas Brealey Publishing, London. Sveiby, K.E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-Based Assets, Berrett-Koehler Publishers Inc., San Francisco, CA. Sveiby, K.E. (2001), “Methods for measuring intangible assets”, available at: www.sveiby.com. au/IntangibleMethods.html (accessed February 2001). Further reading Kohli, A.K. and Jaworski, B.J. (2000), “Market orientation: the construct, research propositions, and managerial implications”, Journal of Marketing, Vol. 54, pp. 1-18. Organization for Economic Cooperation and Development (1996), “Guidelines and instructions for OECD Symposium”, International Symposium on Measuring and Reporting Intellectual Capital: Experiences, Issues, and Prospects, OECD, Paris. Organization for Economic Cooperation and Development (1999), Measuring What People Know, Human Capital Accounting for the Knowledge Economy, OECD, Amsterdam. Saint-Onge, H. (1996), “Tacit knowledge: the key to the strategic alignment of intellectual capital”, Strategy & Leadership, Vol. 24 No. 2, pp. 10-14. Schein, E.H. (1999), Process Consultation Revisited: Building the Helping Relationship, Addison-Wesley Publishing Company, New York, NY. Skyrme, D.J. and Amidon, D.M. (1998), “New measures of success”, Journal of Business Strategy, Vol. 19 No. 1, pp. 20-4.

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The impact of reputation capital on the career paths of departing employees Monika Hamori Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA Keywords Human capital, Career development, Corporate image Abstract This paper examines the impact of corporate reputation capital on employees’ career progression in the case of inter-organizational transitions. A proprietary database that contains career history data on professionals, managers and executives in the financial services industry is used to test the hypotheses. The paper finds that reputation capital is most strongly determined by organization size, not operational efficiency. Reputation capital is an important predictor of the size of the promotions that employees receive as they change organizations, and may signal underlying individual capabilities and performance. Further, employees are willing to forgo a promotion in order to be able to join organizations with high reputation capital.

Introduction In the intense “war for talent” of the late 1990s (Chambers et al., 1998), recruiters customarily advised companies to poach talent from “academy companies”. These included organizations like Federal Express, General Electric, McKinsey & Co., PepsiCo. and Procter & Gamble, all known for their excellence in talent development (Greco, 1997). As anecdotal evidence reveals, the reputation of the organization with which individuals are affiliated is a powerful determinant of career success: it serves as a tool for employers and recruiters to make inferences about the person’s performance. Despite the widely recognized impact of corporate affiliation on individuals’ career paths among practitioners, however, there has not been significant academic research on the ways in which organizational characteristics affect the career path of individuals as they leave the organization (Hall, 2002). This study focuses on the ways in which corporate reputation influences the career paths of employees as they switch over to another organization.

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 304-315 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487770

Theoretical foundations Organizational reputation capital Reputation capital signifies the value created by the image of the firm’s key characteristics (Oswald, 1996), based on stakeholders’ experience with the company or on any other contact that provides information about the firm’s actions compared with its rivals (Gotsi and Wilson, 2001). The current study starts by exploring the dimensions of corporate reputation capital in the financial services industry where the sample of the study is taken. Primarily, it

examines whether reputation is reflected in corporate financial indicators. Previous literature in management cited the high quality of products, innovativeness, the corporation’s high value as a long-term investment and the soundness of corporate financial position as the most common determinants of corporate reputation (Shenkar and Yuchtman-Yaar, 1997), arguing that these factors increase an organization’s profitability and market value and improve its financial indicators. Szwajkowski and Figlewicz (1997) found that financial measures accounted for a significant portion of the variance in corporate reputation ratings. Further, Gardberg and Fombrun (2002) used financial indicators as an aspect of the Global Reputation Quotient, a cross-nationally validated instrument designed to measure corporate reputation. The above suggests that financial performance contributes to corporate reputation capital. H1. Financial performance indicators will positively impact corporate reputation capital. The impact of reputation capital on the career paths of departing employees. Previous literature linked corporate reputation capital to several positive outcomes, such as customers’ intention to buy a service, favorable attitude to products, high product quality, an organization’s ability to deter competitor entry into a market, the corporation’s attraction for investors and employees’ strong identification with the organization (Caruana, 1997). No empirical paper, however, has examined how corporate reputation determines the status of individuals and enhances the value of organizational members for other organizations (Shenkar and Yuchtman-Yaar, 1997). This paper looks at the effect of reputation capital on the career success of organization members. It argues that high reputation capital secures two types of favorable career outcomes for employees affiliated with the corporation: increased visibility in the labor market and increased gains – promotion – when employees are recruited by another organization. Earlier, no empirical paper has linked reputation capital to higher employee visibility in the labor market. Previous literature, nevertheless, implies that reputation may increase an organization’s visibility. March and Simon (1958) proposed that visibility was a function of the “prestige” of the organization. Organizational visibility, in turn, may provide more visibility to organizational members. The work by March and Simon implies that visible organizations are the initial target of recruiters because decision-makers often conduct a limited search for candidates. H2. Corporate reputation capital will positively impact employees’ visibility in the labor market. Second, this paper argues that organizations grant higher promotions upon entry to employees who leave organizations with high reputation capital. Members from reputable organizations may be more desirable for other

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employers for several reasons. First, recruiting employees from outside is an effective means of acquiring human capital that the organization does not possess currently (Boeker, 1997; Bontis and Fitz-enz, 2002; Bontis et al., 2000; Rao and Drazin, 2002). Companies with a high reputation capital – leaders in their industries – are especially desirable targets of recruitment efforts because organizations tend to imitate and gain human resources from market leaders (Haveman, 1993). Good corporate reputation also acts as a guarantee for the high performance of employees (Spence, 1974). Reputation capital may be considered a proxy for individual performance and a determinant of human capital, because reputable organizations are assumed to be selective in their hiring efforts and demand high performance on the job. The recruiting organization’s reliance on objective cues such as the reputation of the employing organization is especially important when the productivity of employees cannot be directly observed at hiring. Reputable organizations secure greater career success for employees in other ways as well: they place a “halo” over their members, independent of the individual’s actual performance. Useem and Karabel (1986) showed that individuals’ ascent to top corporate positions was most facilitated by earning a Bachelor’s degree, an MBA degree, or a law degree from a top-ranking college or university. An MBA degree, however, did not significantly help those who received their Bachelor’s degree from a top-ranking institution, because the reputation of the undergraduate institution alone propelled them into a high-ranking position. Similarly, Crane (1965) found that scientists who attended a major prestigious university were more recognized by their peers, recognition being a function not only of the scientists’ performance, but also of the prestige of the academic institution. H3. Reputation capital will positively impact the size of the promotions that individuals receive when they move to another organization. Research design Data collection and sample The data come from the proprietary search database of a US executive search firm. Candidates in the database were contacted for previous and current search assignments and were identified from sources including industry publications, directories and recommendations by clients and key industry players. The database contains information on 14,000 employees in the financial services sector (including asset management companies, banks, consumer finance companies and investment banks). This study uses a random sample of 2,000 organizations of the original database and analyzes only inter-organizational movements within this sample ðn ¼ 968Þ: The database population comprises non-managerial employees, managers, directors, vice-presidents, senior and executive vice-presidents and “C-level” executives (COOs, CFOs, CEOs, etc.). Data on each person contain information

on the individual’s current and past job: name of his or her employing organization, title, functional background (e.g. “finance”) and function segment (“credit card operations”), industry affiliation and industry segment, the month and year when the person started and ended the job, educational background and international experience. Additional data were collected from the Hoover’s (Hoover’s Online, 2003) database on the organizations’ size, public or private status and financial performance. Measures The size of the promotion that individuals receive when they switch over to another company is calculated as the difference in levels between the person’s current and former positions. Titles/positions were coded and the number assigned to the former position was deducted from the number assigned to the current position. The codes distinguished between non-managerial positions and seven types of managerial positions: managers, directors, assistant vice-presidents, vice-presidents/chief functional officers (CTOs, CFOs, etc.), executive vice-presidents, senior vice-presidents and CEOs/partners/ founders/managing directors. The value ranges from 27 to 7. Reputation capital was computed on the basis of Fortune magazine’s “America’s most admired” and “Global most admired” rankings. The Fortune rankings take the ten largest companies (by revenues) in 58 industries and have 10,000 executives, directors, and securities analysts rate the companies in their own industries based on eight criteria: innovation, financial soundness, employee talent, use of corporate assets, long-term investment value, social responsibility, quality of management, and quality of products and services. The rank score ranges from 1 to 10 (Sung and Tkaczyk, 2002). The Fortune rankings have induced significant controversy, attracting arguments pro (Szwajkowski and Figlewicz, 1997) and con (Baucus, 1995). My field research, however, revealed that executive search consultants in financial services consider the Fortune rankings as one of the most reliable sources of company prestige rankings (Hamori, 2003). Control variables. Among the many factors that predict career success, human capital attributes – educational credentials and work-related experience – were shown to be the strongest and most consistent predictors (Kirchmeyer, 1998). This study uses years of education, professional degree (MBA), functional background, tenure on the job and international experience, the most commonly employed human capital indicators in the past research, to control for human capital. Years of education ranges from 12 to 20 years. MBA, international experience, and functional background are dichotomous variables. Organizational tenure is calculated by deducting the starting date (month and year) of the employee’s job from the date when he or she left the job. In addition, the regression models of this study use controls for industry affiliation, organization size and the “former” job title (position) of the individual.

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Results Table I presents the key variables with their mean, standard deviation and the Pearson correlations. The means in Table I outline the profile of professionals, managers and executives in financial services. The average person was promoted 0.73 level when switching to a new job with another organization: out of 100 inter-organizational transitions, 73 included a promotion of one hierarchical level (e.g. from manager to director, from assistant vice-president to vice-president), while 27 involved lateral career moves. A notable result in Table I is the individuals’ high level of education: average years of schooling is 17.3 years (i.e. a Bachelor’s degree and more than one year of graduate education on average). An extremely high percentage, 42.3 percent, of the persons in the database have an MBA. Every fifth person has worked in a foreign country (20.25 percent). The individuals’ tenure with their former organization is 3.8 years. The Pearson correlations reveal that promotion size has a significant, 0.08, correlation with corporate reputation capital: higher reputation capital earns individuals larger promotions when they leave for another organization, if no other variables are considered. Further, career success is negatively correlated to the reputation capital of the organization to which the individuals switch, implying that employees are willing to forgo a promotion when they change to a reputable organization. Regarding the characteristics of the employing organizations, the most striking finding is the high percentage of reputable companies in the database: 33.7 percent of the companies to which the individuals in the database are affiliated are included in the Fortune rankings. This result supports H2 that individuals in reputable organizations enjoy greater visibility in their respective industries and they have a much greater chance of being input into a search firm’s target database, which signifies the first step of being hired into an attractive position with another organization. In order to explore the organizational characteristics that are most strongly related to reputation capital and to determine the unique contribution of each independent variable in explaining the variance in reputation capital, hierarchical regressions were run with reputation capital as the dependent variable and company characteristics and financial indicators as independent variables. The results are presented in Table II. Model 1 uses public status, sales, sales growth, net income and net income growth as predictors of reputation capital. The results reveal that reputation is most strongly predicted by the organization’s public status and size. The two variables explain the largest portion, 25.8 percent of the variance. Variables representing the organizational growth and efficiency, however, do not predict organizational reputation. Sales growth and net income growth have a negative coefficient and explain only a small part of the variance in organizational

1

2

3

4

20.07 0.05

0.03 2 0.02

0.00 20.09

0.402 20.01 3.600 0.03

0.05

2 0.01 0.01 2 0.04

0.08* 20.40** 20.16**

5.953 20.08* 20.14** 20.04 1.243 0.00 20.02 0.05 0.494 0.06 0.02 0.05

7.281

2.599 1.00 20.10* 0.00 0.10* 0.440 20.10* 1.00 20.30** 2 0.28** 0.400 0.00 20.30** 1.00 2 0.23** 0.383 0.10* 20.28** 20.23** 1.00 0.399 0.06 20.30** 20.25** 2 0.23** 0.370 20.05 20.26** 20.22** 2 0.21**

St. dev.

Notes: n ¼ 968; *p , 0.05; **p , 0.001

Movement capital 0.727 Size 1 0.261 Size 2 0.199 Size 3 0.178 Size 4 0.198 Size 5 0.163 Reputation, former org. 1.71 Reputation, current org. 1.54 Education 17.3 MBA 0.423 Int’l experience 0.202 Tenure 3.791

Mean

0.04 0.06

7

8

9

0.29**

0.00 0.01

20.01 20.01

0.02 0.00

0.01

0.06 0.02 0.05 20.04 20.04 0.00

10

0.03 2 0.09 0.05 2 0.02 0.06 0.01

2 0.01

2 0.01 0.00 2 0.07 0.03 0.04 0.00

2 0.01

0.10 0.12**

0.04 0.05

1.00 2 0.06

2 0.06 1.00

0.00 0.12** 0.05

12

11

20.01 20.05 2 0.01 1.00 0.50** 0.10** 0.50** 1.00 0.04

0.14** 20.02

0.14** 1.00 20.02 20.01 0.01 20.05

1.00

2 0.05 0.08* 20.08* 0.00 2 0.26** 20.40** 20.14** 20.02 2 0.22** 20.16** 20.04 0.05 2 0.21** 0.05 20.01 0.01 2 0.22** 0.28** 0.13** 20.01 1.00 0.29** 0.07 20.03

6

0.13** 0.07 2 0.01 2 0.03 2 0.04 0.00

0.28**

0.06 2 0.30** 2 0.25** 2 0.23** 1.00 2 0.22**

5

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Table I. Means, standard deviations and Pearson correlations for key variables

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Table II. Hierarchical regression models predicting corporate reputation capital

Beta (stand.)

R-squared

R-squared change

F

Model 1/Variablesa Industry dummies Public status Sales Sales growth Income Income growth

– 0.189*** 0.376*** 20.059** 0.033 20.067**

0.032 0.097 0.258 0.261 0.262 0.266

0.032 0.065 0.161 0.003 0.001 0.004

10.8*** 26.0*** 67.7*** 57.4*** 49.3*** 44.1***

Model 2/Variablesb Industry dummies Profit margin Return on equity Return on assets Price-to-earnings ratio Price-to-book ratio Market value

– 20.021 0.074 20.394*** 0.065* 0.208*** 0.256***

0.047 0.068 0.082 0.157 0.169 0.205 0.246

0.047 0.021 0.014 0.075 0.012 0.036 0.041

14.5*** 16.1*** 15.6*** 27.2*** 25.4*** 28.2*** 31.8***

Notes: an ¼ 968; b For public companies, n ¼ 416; *p , 0.1; **p , 0.05; ***p , 0.001

reputation (0.07 percent), while the coefficient for net income is positive, but non-significant. Model 2 of Table II examines the relationship between the other financial indicators and reputation capital for public companies. It reinforces the conclusions from Model 1, demonstrating the importance of size in corporate reputation capital. Model 2 also suggests that stock markets place greater trust in reputable companies: both the price-to-book and the price-to-earnings ratios have significant and positive coefficients with reputation capital. Companies with strong reputations, however, do not enjoy higher operational efficiency: profit margin and return on equity have non-significant coefficients, while return on assets is negatively related to reputation capital. Thus, H1, suggesting that reputation capital is strongly related to financial performance, is not supported. Table III analyzes the impact of reputation capital on the size of the promotions that employees receive as they leave for another organization. It Table III. Size of the promotions (number of levels) received by employees who change between organizations. Means comparisons (t-tests)

Reputation capital of the organization to which employees transition (“current” organization) Reputation capital of the employing organization (“former” organization) Low High Notes: *p , 0.05; **p , 0.005

All organizations

High

Low

0.62* 1.06*

0.45 0.26

0.67** 1.44**

presents means comparisons of the size of individuals’ promotions as a function of the reputation capital (low or high) of their employing organization (“former organization”) and of the organization to which they change (“current organization”). For this analysis, reputation capital is operationalized as a binary variable, determined by the company’s absence or presence on the Fortune rankings. Two trends are apparent from Table III: the reputation capital of the employing organization has a significant impact on individual careers. Employees leaving organizations with high reputation capital receive, on average, larger promotions than those leaving organizations with low reputation capital, no matter where they switch. The means are 1.06 and 0.62 levels, respectively (t ¼ 2:11; p , 0:05), the difference being almost 0.5 level. The differences in promotions that result from the differences in the reputation capital of the “former” organization are largest in the case of movements to a “current” organization with low reputation capital: individuals who leave organizations with high reputation capital for those with low reputation capital receive the largest promotions (1.44 level). At the same time, those who also change to a company with low reputation capital, but depart from an organization with low reputation capital, earn only 0.67 level of promotions (t ¼ 2:97; p , 0:005). The difference in promotions is 0.8 level. Second, the size of the promotions is equally strongly determined by the reputation capital of both the “former” and the “current” organization: the differences are large between individuals who leave reputable organizations for equally reputable ones (0.26 level), and individuals who depart for organizations with low reputation capital (1.44 level). Contrary to expectations, the t-test for employees who change to organizations with a high reputation capital and leave organizations with high versus low reputation capital is not significant ðp ¼ 0:559Þ: Ordinary least squares regressions were used to measure the effect of reputation capital (independent variable) on the size of the promotion that individuals receive as they leave the organization (dependent variable). Since promotion size takes values that range from 2 7 to 7, OLS regression proved to be the best method to test the effect of reputation capital (Tabachnick and Fidell, 1989, p. 8). Owing to the distribution of the dependent variable (70 percent of the observations take five values: 22, 21, 0, 1, and 2, while still a considerable proportion, 30 percent, take the rest of the values in the defined range), logistic regression models were not considered. Table IV presents the results of the OLS regressions. Model 1 uses industry, organization size and job title controls and enters individual human capital attributes into the equation. None of the human capital attributes is significant. Model 2 adds the organizational reputation variables to the equation. Since Table III suggested that it is important to consider both former and current organizational reputation capital in

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Table IV. OLS regressions predicting promotion size

Variables

1

2

Constant Size controls (former organization) Size 1 0.018 0.033 Size 2 20.006 0.002 Size 3 0.069 0.063 Size 4 0.124** 0.122** Industry controls (former organization) Position controls (former organization) Human capital variables Years of education 20.002 20.002 MBA 0.065 0.065 International experience 0.020 0.025 Tenure 0.028 0.027 Finance function 20.095 20.093 Industry controls (current organization) Organizational characteristics Reputation, former organization – 0.050 Reputation, current organization – 20.104** F 5.457*** 5.453*** R-squared 0.340 0.349 Notes: Standardized coefficients are reported. Coefficients for industry controls (asset management, banks, finance companies, investment banks) and position controls (non-managerial, CEO and founder) are not reported here, but are available from the author upon request; *p , 0.1; **p , 0.05; ***p , 0.001

predicting the size of the promotions that employees receive, the model simultaneously enters both variables. The reputation capital variables increase the variance in movement capital by 0.09. The coefficients for both former and current reputation capital have the expected sign: former reputation capital is positive, although not significant ðp , 0:2Þ: The results of the correlations (Table I), means comparisons (Table III) and regressions (Table IV) only partly support H3 that the high reputation capital of the employing organization garners larger promotion for organization members. Current reputation capital is negative and significant ðp , 0:05Þ: The coefficient for the reputation capital of the potential organization is 20.11: a nine-fold increase in the reputation capital of the organization to which the individual switches decreases the individual’s size of promotion by one level. That is, a director transitioning from SCI Investors, Inc. to the Citigroup will earn a promotion that is one level lower (e.g. to an assistant vice-president position, instead of vice-president) than the promotion that (s)he would have earned if (s)he had transitioned to a “peer” organization, say to Bellmeade Capital Partners, LLC. Regarding the size of individuals’ employing organization, the regressions reiterate the findings of Table III. Small size has a non-significant coefficient,

while large size has a positive and significant coefficient, indicating that large-sized organizations garner larger promotions for their employees as they change to another organization. The results imply that professionals, managers and executives from large-sized organizations are more attractive for other employers.

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Discussion and conclusions While the literature on managerial and non-managerial career progression overwhelmingly centers on careers inside a single organization, this paper contributes to the relatively unexplored literature on inter-firm mobility and represents one of the few analyses that looks at the effect of organization-level attributes on career success. The important theoretical contribution of the study is the suggestion that the reputation capital of an individual’s employing organization may be considered as an aspect of human capital, because it is perceived by outside constituents as an approximation of the individual’s expertise and performance. Two results came out differently from predicted by the hypotheses: unlike the findings in previous literature, financial performance measures did not predict corporate reputation capital. There is one explanation for this counter-intuitive finding. Both the reputation measures and the financial indicators in this paper were collected from the same year (2001). Corporate reputation, however, is often gauged by outside constituents on the basis of the organization’s financial performance in previous years. Moreover, the author’s interviews with executive search consultants revealed that, for some stakeholders, the notion of good corporate reputation did not exclude an organization under a temporary financial turmoil. Search consultants in the search firm that created the database admitted that they often focused on targeting professionals and managers in companies that had good technology, but were experiencing financial difficulties. One of them commented “[ABC Co.] is under turmoil right now, so it should be really easy to pull people out of there. It would be easy to take people out of companies with stocks that are watered down” (Hamori, 2003). Also contrary to expectations, the reputation capital of individuals’ employing organization was not a significant predictor of promotion size in the regression models, while the reputation capital of the organization to which the individual transitioned had a more significant impact on the size of the promotions. The latter finding corresponds to the propositions of previous conceptual papers. These suggested that organizational reputation is an indicator of the organization’s ability to attract talented people and proposed that job candidates are more likely to agree to lower compensation when they are hired by organizations with a “high standing” (Shenkar and Yuchtman-Yaar, 1997). This paper represents the first empirical verification of these propositions.

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The analyses reveal important facets about the selection of professionals, managers and executives that takes place with the mediation of an executive search firm. The executive search firm, the database of which is used for the analyses, aims to recruit individuals employed by organizations with a high reputation capital. Individuals who work for large-sized organizations and for organizations that are in the Fortune rankings have a greater chance of being considered for search assignments than the employees of small to mid-sized companies that are not included in the Fortune rankings, even though these firms may have solid financial indicators. The methodology of other search firms is similar to that of the database search firm. The findings therefore also indicate a mainstream approach to the selection of professionals, managers and executives, who are identified and contacted by search firms not only on the basis of their human capital attributes, but also – and even more so – on the basis of the organizations to which they are affiliated. References Baucus, M.S. (1995), “Halo-adjusted residuals – prolonging the life of a terminally ill measure of corporate social performance”, Business and Society, Vol. 34 No. 2, pp. 227-35. Boeker, W. (1997), “Executive migration and strategic change: the effect of top manager movement on product-market entry”, Administrative Science Quarterly, Vol. 42 No. 2, pp. 213-37. Bontis, N. and Fitz-enz, J. (2002), “Intellectual capital ROI: a causal map of human capital antecedents and consequents”, Journal of Intellectual Capital, Vol. 3 No. 3, pp. 223-47. Bontis, N., Chua, W. and Richardson, S. (2000), “Intellectual capital and the nature of business in Malaysia”, Journal of Intellectual Capital, Vol. 1 No. 1, pp. 85-100. Caruana, A. (1997), “Corporate reputation: concept and measurement”, Journal of Product & Brand Management, Vol. 6 No. 2, pp. 109-18. Chambers, E.G., Foulon, M., Hadfield-Jones, H., Hankin, S.M. and Michales, E.G. (1998), “The war for talent”, McKinsey Quarterly, Vol. 35 No. 3, pp. 44-57. Crane, D. (1965), “Scientists at major and minor universities: a study of productivity and recognition”, American Sociological Review, Vol. 30 No. 5, pp. 699-714. Gardberg, N.A. and Fombrun, C.J. (2002), “The global reputation quotient project: first steps towards a cross-nationally valid measure of corporate reputation”, Corporate Reputation Review, Vol. 4 No. 4, pp. 303-7. Gotsi, M. and Wilson, A.M. (2001), “Corporate reputation: seeking a definition”, Corporate Communications, Vol. 6 No. 1, pp. 24-30. Greco, J. (1997), “The search goes on”, Journal of Business Strategy, Vol. 18 No. 5, pp. 22-5. Hall, D.T. (2002), Careers in and out of Organizations, Sage, Thousand Oaks, CA. Hamori, M. (2003), interview transcripts with 45 executive search consultants, Philadelphia, PA. Haveman, H. (1993), “Follow the leader: mimetic isomorphism and entry into new markets”, Administrative Science Quarterly, Vol. 38 No. 4, pp. 593-627. Hoover’s Online (2003), International Company Directory, Hoover’s Inc.. Kirchmeyer, C. (1998), “Determinants of managerial career success: evidence and explanation of male/female differences”, Journal of Management, Vol. 24 No. 6, pp. 673-93.

March, J.G. and Simon, H.A. (1958), Organizations, Wiley, New York, NY. Oswald, J. (1996), “Human resources, scientists, and internal reputation: the role of climate and job satisfaction”, Human Relations, Vol. 49 No. 3, pp. 269-93. Rao, H. and Drazin, R. (2002), “Overcoming resource constraints on product innovation by recruiting talent from rivals: a study of the mutual fund industry, 1986-1994”, Academy of Management Journal, Vol. 45 No. 3, pp. 491-507. Shenkar, O. and Yuchtman-Yaar, E. (1997), “Reputation, image, prestige, and goodwill: an interdisciplinary approach to organizational standing”, Human Relations, Vol. 50 No. 11, pp. 1361-81. Spence, M.A. (1974), Market Signaling, Harvard University Press, Cambridge, MA. Sung, J. and Tkaczyk, J. (2002), “Who’s on top and who flopped”, Fortune, March 4. Szwajkowski, E. and Figlewicz, R.E. (1997), “Of babies and bathwater”, Business and Society, Vol. 36 No. 4, pp. 362-86. Tabachnick, B.G. and Fidell, L.S. (1989), Using Multivariate Statistics, HarperCollins Publishers, New York, NY. Useem, M. and Karabel, J. (1986), “Pathways to top corporate management”, American Sociological Review, Vol. 51 No. 2, pp. 184-200.

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The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1469-1930.htm

From implementing strategy to embodying strategy Linking strategy, identity and intellectual capital Anna Rylander Royal Institute of Technology, KTH Syd, Design and Health, Haninge, Sweden, and

Joe Peppard Cranfield School of Management, Cranfield, Bedford, UK Keywords Corporate strategy, Corporate identity, Knowledge organizations, Intellectual capital Abstract For most knowledge-intensive companies at present, the business environment where they compete is complex, characterized by rapid change and uncertainty. Employees and other intangible resources (i.e. intellectual capital) generally represent the most critical resources in the value creation process. Crafting strategy in such contexts is not helped by conventional models and tools of strategy. The assumptions which underpin many of them do not hold in the present competitive environment, making them at best irrelevant, but at worst leading to the development of strategies that can put the success of a company in jeopardy. New metaphors for describing these companies and their competitive realities, as well as tools for navigating in them, are required, if the strategy discipline is to remain relevant for practitioners. In this paper, it is suggested that the intellectual capital perspective can provide a bridge to the practical application of a vision- and values-based strategy through the notion of embodying strategy in organizational resources. A conceptualization of strategy, that links strategy, identity and intellectual capital, more suitable to knowledge-intensive companies competing in uncertain environments, is introduced and described.

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 316-331 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487789

Introduction Consider the predicament of Videsti. This company was established in 2000 and represents the merger of Viscom and Digital Innovations. This merger saw the bringing-together of Viscom’s strengths in broadcasting and audio-visual (AV) systems design and integration and Digital Innovations’ expertise and experience in the Internet, telecommunications, and systems integration. The synergies were expected to lead to a considerable impact on value creation. During the early days of the merger, the focus of senior management’s attention was to successfully integrate the employees of both companies. The new company also embarked on a process of expanding its range of consultancy services in order to enhance its knowledge base in the rapidly evolving “digital media landscape”. Research and development (R&D) activity also increased with a view to developing commercial products, as this would ultimately result in a higher valuation of the company by the capital markets. The extent of the company’s activities was considerable, ranging from the installation of AV equipment in the Sandy Lane Hotel in Barbados, to the

construction of an on-air TV studio, editing facilities, incoming lines (via Strategy, identity microwave and satellite), and automated play-out of pre-compiled and IC programming for CNBC, a cable and satellite broadcaster based in Hong Kong, to designing the online betting exchange Betaq.com The objective of the newly merged company is to become a player in the fledgling domain of interactive digital TV (IDTV). They saw this space as 317 enabling them to leverage their skills and knowledge in TV broadcasting, the Internet (both fixed and wireless) and telecommunications. The company sought to develop a strategy to position themselves in this competitive space and then, through planning activities, to galvanize employee actions behind this strategy. With this objective, a strategy process was initiated. The company engaged the authors to work with the senior management team to construct and shape a strategy for growth. However, early in the process, it becomes very clear that developing this strategy was going to prove more difficult than initially envisaged. For a start, the competitive space was impossible to define, as it was emergent and changing almost on a daily basis. Many forces were shaping the industry, including the regulatory framework, customer adoption and technology developments and these were continually evolving. For example, during the early days of the strategy process ITV Digital went bankrupt and the UK government announced that it was pushing out the date for turning off the analogue signal by two years, further delaying the arrival of IDTV. In addition, standards would have to be developed and agreed among many players – broadcasters, film and programme makers, cable companies, and personal video-recorder (PVR) manufacturers. While the vision of IDTV and the services that it would support, from video-on-demand to communication to commerce to delivering public services right into the sitting-rooms of households, is appealing, reaching that end goal is not likely to be a smooth path and will take many years. In such an environment, what is strategy anyway? The traditional militaristic view of strategy that has dominated thinking in the field of strategic management, and indeed framed the view of strategy held by Videsti’s senior management team, is unhelpful. As Videsti came to discover, it is not possible to construct a strategy in the conventional understanding of the notion; strategy is not about being directive and planning. In this paper, we develop the arguments that, for knowledge-intensive companies, strategy should have a behavioural underpinning to guide knowledge workers rather than providing a directive strategic plan. We then present a different conceptualization of strategy and a framework for linking the vision-based strategy to day-to-day management. Strategy management: a discipline in crisis? The field of strategic management is dominated by models and theories that hold little relevance for practitioners in guiding action in knowledge-intensive

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companies competing in turbulent environments. In addition, the assumptions which underpin many of the traditional tools of strategy do not hold true, making them at best irrelevant, but at worst leading to the development of strategies that can put the success of a company in jeopardy (Courtney et al., 1997). If we are going to progress the field of strategy, we need to revisit these assumptions and explore their implications and relevance in the present environment. We also need to understand the conditions under which organizations compete and create novel approaches to meet these new demands. However, a limitation to this quest is the dominance of research approaches to knowledge production that are inappropriate, given the ontological nature of strategy and the strategic management discipline, and do not produce practically relevant knowledge. To address this deficiency, Gary Hamel, in a keynote address to the 2001 Strategic Management Conference, strongly espoused the need for strategy researchers and academics to “get their hands dirty”. The emerging “Strategy as Practice” School within the strategic management discipline emphasizes the requirement for this practical aspect to strategy and the need to understand what really happens in the strategy process[1]. The assertion that the traditional models and theories and the assumptions that underpin them are no longer valid for the current competitive conditions is not new (Bettis and Hitt, 1995; Campbell and Alexander, 1997; Courtney et al., 1997; Coyne and Subramanian, 1996; Eisenhardt and Brown, 1998; Hamel, 1998; Markides, 1999; Normann, 2001). Approaches to strategy formulation ascribe to top managers almost “superhuman powers that enable them to identify sources of competitive advantage and then to direct their business to secure strategic objectives” (Alvesson and Willmott, 1995). The industrial organization, which provided the bedrock for the development of most “theories of the firm”, is no longer an appropriate vehicle to use in many of the present business environments. More critical from a practice perspective, theories, while useful in explaining ex post what happened, are weak in guiding action. For example, resource-based theory (RBT), in vogue for the past two decades, illustrates the relationships between input resources and competencies and the performance of the firm. However, it fails to show how to mobilize, marshal and manage those resources to create value (Ambrosini and Bowman, 2001; Haanes and Fjeldstad, 2000; Peppard and Rylander, 2001). At present, strategy is under attack from uncertainty. For many knowledge-intensive organizations, the competitive environment they face is radically different from that assumed by many models of strategy, which are based on a microeconomic model of industry. There seems to be no single new theory or model emerging that covers all the areas under attack. For example, to deal with the central ingredient of knowledge, a knowledge-based theory of the firm is being formulated. However, rather than being a formal theory, in the true sense of the word, it is a set of assumptions and observations about the nature of

knowledge and its role in production (Grant, 1996). This, of course, may be Strategy, identity because there is no single set of assumptions that are valid for all organizations and IC in all situations. Organizations competing in stable, mature industries producing industrial goods may very well still benefit from classic strategy models and processes. However, for Videsti and many other knowledge-intensive organizations, the following set of conditions shapes 319 their competitive environment: . The marketplace is evolving and immature and its boundaries are unclear. The concept of industry, so critical to the operational of traditional tools of strategy, is inappropriate in these contexts. . Rapid rate of change and technological innovation mean organizations have to be agile and flexible – in terms of both strategy and structure. The disruptive impact of technology and faster time-to-obsolescence characterises these competitive spaces. . Markets and their operating environments are becoming more complex as traditional industries converge and the supply of products and services increases in diversity. Shorter product/service lifecycles, blurring of the distinction between products and services, more discerning and knowledgeable customers all add to the increasing complexity of the competitive environment. . The increasing importance of intangibles as key value drivers. Currently, many companies are knowledge-intensive and dependent on their employees for their success. This also calls for an organization that is built so as to support the creative process of these individuals as well as the conversion of ideas into marketable products or services. . There is a high percentage of knowledge and information components in products and services. Neither are well understood nor adequately dealt with in traditional strategy models. These conditions have been identified by many researchers (see, for example, Eisenhardt and Brown, 1998; Williamson, 1999) and their implications are profound. Their implications for strategy analysis, processes and outcomes include the following: . Requirement for a proactive rather than reactive approach to competing in competitive spaces (Hamel, 1996; Hamel and Prahalad, 1994). Organizations need to drive the development – and definition – of the market (if they have the resources) or identify the drivers (in terms of both companies and trends). . Uncertainties and rapid change mean that a planning approach to strategy does not function in most cases, and that the distinction between formulation and implementation is unsustainable (Mintzberg, 1990). Kanter (2002) suggested that companies that want to outpace the

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competition throw out “the script” and improvise their way to new strategies. Industry value chains are being replaced by more complex value networks (Normann and Ramı´rez, 1993; Parolini, 1999; Stabell and Fjeldstad, 1998). Consequently, organizations are required to carve out roles in a network of players, often opting for competition, rather than seeking a profitable position among competitors in a clearly defined market. Organizations have to look to their internal resources for sources of competitive advantage in an uncertain market (Barney, 1991; Collis and Montgomery, 1995). In a knowledge-intensive company, this often means competence and other intangible assets such as brands, intellectual property or relationships. In this environment, innovation and the ability to propel ideas to market quickly become crucial. Values and beliefs and vision become critical when people are the key value drivers, as they guide and align the behaviours of employees (Collins and Porras, 2000; Davidson, 2002).

Yacht racing provides a useful metaphor for describing the role of “strategy” in these emergent competitive spaces. In this sport, man and boat pit themselves against the ocean and weather as they strive to conquer their rivals in the race to be first across the finishing line. Competition is a battle not only with competitors, but also against the elements. The strategy of each boat cannot be plotted out in advance, but will depend on the conditions and the position of competing boats. The crew must be able to sense these ever-changing conditions and respond to them in real-time. Weather forecasts can give some guidance as to the likely weather and sea conditions, but this is an inexact science. In the middle of the ocean, conditions can change very quickly. A skipper can make a decision to follow a particular route, even though it may not be the most direct, in the hope of getting more favourable conditions and thus greater speed in the long term – although this is not guaranteed. Despite all the technology now available, success is still about skills and knowledge. The skipper and her crew have to be fast and flexible in responding to changing conditions. This requires a common language and code of conduct within the team. A completely new team that has never sailed together before is unlikely to be as successful in responding in a rapid and coherent way as a team with long experience of sailing together that has established a common value system and patterns of communication and action. This metaphor of the yacht pitting itself against the elements as well as competitors may be a more appropriate metaphor for the present knowledge-intensive company, living with uncertainty rather than adopting a militaristic perspective. But, if this is the case, we also need to rethink the role of strategy.

Reconceptualizing strategy in uncertain environments Strategy, identity In the context described in the earlier sections, the role of a strategy is not to and IC provide a pre-defined course of action. Given the high level of uncertainty and rate of change, the heavy dependence on people in creating value, we propose that the key role for strategy is providing a common vision of what the organization is to achieve, and a purpose or fundamental reason for being. It 321 should also provide managers with a shared context for decision-making and to guide the behaviours of all employees. A frequent theme in the strategic management literature during the 1990s was the challenge to manage the balance between stability and flexibility (Lindgren, 2002). The strategy should be able to allow for change when environmental or internal conditions change and it should also permit enough discretion for employees to be innovative and improvise whilst still moving towards the same goal, following the same codes of conduct. A detailed strategic plan would at best become irrelevant, at worst guide actions towards the wrong goals, given that environmental conditions would have changed, probably before the ink is even dry. Strategy, in this context, is not a point concept, but a process. It needs to be reviewed and modified regularly based on changing conditions in the environment. This can be a very challenging prospect and it can be difficult for employees to cope with these changes. Under these circumstances, what will hold the organization together and be relatively stable is the values and beliefs held by the members of the organization. Employees are bounded by what they know and what they value; they are sensitive to the norms of what is appropriate behaviour (Kogut and Zander, 1996). The vision, providing the organization with some form of goal(s), be it at a high level, towards which to strive, should also be robust enough to withstand turbulence in the environment. From an external perspective, the organization must cultivate a reputation. Reputation is something that is earned through past actions and its core values are not easily changed. They therefore have to reflect the vision and purpose. Figure 1 shows how this concept of strategy can be expressed. A practical application of this model can be found in Peppard and Rylander (2002). Crucial for the strategy to work in practice is consistency and alignment among the “three corners” and the values they represent. There are three key “processes” linking the three value sets[2]. Leadership is critical to link the vision, which often is developed by top management, with the values and beliefs held by the employees. Here, the role of leadership is to act as an interpreter and negotiator (picking up signals from employees as they relate to their ideas for the vision and explain and instil a clear understanding of the vision among the employees), engaging employees in framing corporate ambitions, and acting as role model, living with the values of the organization. Positioning is the “process” of communicating the vision and purpose and explaining the value of the offering to the outside world. Communicating the

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Figure 1. Representation of strategy for knowledge-intensive companies in uncertain environments

vision, which implies keeping a dialogue with external stakeholders as opposed to merely advertising the product or service, is especially important in uncertain markets. Products can easily become obsolete, but the vision should be more long-term and enduring. It is also important to point out that customers are not the only target group for the communication. Potential employees, partners, suppliers, standard-setting committees and industry groups may be equally important in certain stages of the development. Finally, “production” is the “process” of creating and delivering value to customers (and other stakeholders), which in the case of service companies is highly interactive, and the outcome (value delivered as perceived by the customer) will strongly reflect the values, beliefs and behaviour of the employees. If strategy is about providing a common vision and context in an uncertain environment, then the process for developing it is not about following a linear process based on detailed data collection and rigorous analysis of these data. It is about having strategic conversations among the management team, establishing a common language to explore internal and external issues, and about sense-making of events and trends in the environment. The process has to be circular and iterative as it tests ideas and has to make sure that they are well understood and accepted by all involved. A relatively established position today is that strategy for knowledge-intensive companies in turbulent environments should be based on vision and values, and does not benefit from detailed strategic planning. But there has been nothing to replace the concept of planning – how do you actually “make the vision happen”? As pointed out by Collins and Porras (2000), it is very important to stop and think about vision. But, even more important, we have to align the organization to preserve the core ideology (its core values and core purpose) and stimulate progress toward the envisioned

future, not merely write a statement. Although the visionary companies in Strategy, identity Collins and Porras’ study (i.e. widely admired, successful companies that have and IC been premier institutions in their industries for more than 70 years, yielding extraordinary long-term returns to their shareholders) tended to write mission, vision, purpose and values statements more than the comparison companies, this is by no means a key to success in implementing them – it is just one of 323 many steps on the way. Indeed, most vision and mission programmes seem to fail to deliver on their proclamations (Davidson, 2002).

Linking strategy to identity and intellectual capital in knowledge-intensive companies As opposed to most theories in strategic management, the intellectual capital (IC) perspective emerged from work by practitioners as a language and framework for visualising and managing intangible assets. Managers were struggling with the lack of relevance of traditional, accounting-based tools that they saw as inappropriate for managing intangible resources (Bontis and Nikitopoulos, 2001). The aim of the IC perspective is to provide a balanced and holistic view of the company, which includes all value-creating resources a company has at its disposal to create value. These include financial or monetary capital, physical capital and intellectual capital, usually divided into human, organizational and relationship capital (Peppard and Rylander, 2001). Its usefulness is illustrated by its widespread adoption by practitioners as well as academics, since it first entered the management literature in the late 1990s (Bontis, 1996, 1998, 1999, 2001, 2002; Bontis and Fitz-enz, 2002; Bontis et al., 1999, 2000, 2002; Brooking, 1996; Choo and Bontis, 2002; Edvinsson and Malone, 1997; Roos et al., 1997; Stewart, 1997; Sveiby, 1997). The model shown in Figure 2 describes the linkages between “the strategy” (as represented in Figure 1) and the resources, using the terminology of the IC perspective, that are to be mobilized to “make the strategy happen”.

Figure 2. Mobilizing resources to support the vision

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This model illustrates the concept of “identity” as providing the integrative mechanism between the high-level, abstract vision and the organization’s resources. It also provides the starting-point for the “strategy process” as an iterative and continuous process. The identity is something that already exists and reflects the values and beliefs held by the employees and therefore provides the context for what vision is feasible in reality. As noted by many management and social thinkers (Castells, 2000; Gergen, 1991), identity and identification are becoming increasingly important for individuals and organizations in general, in an increasingly abstract, dynamic and complex world where traditional social structures are breaking down. Identity is particularly important for knowledge-intensive companies. The ambiguity of knowledge and knowledge work (i.e. difficulties in assessing knowledge, what knowledge workers do and the results of their work) creates abilities to deal with rhetoric, regulate images and manage relationships and interactions with clients central for knowledge-intensive companies. This implies that controlling and securing work and organizational identities are a vital part of management (Alvesson, 2001). In addition, Normann (2001) argues that the increasing lack of boundaries and definition in the physical world paradoxically requires us to think more rather than less of boundaries. If we are to keep our sense of identity and purpose, we must have a sense of what and who we are. Kogut and Zander (1996) suggest that what makes an organization’s boundaries distinctive is that the rules of coordination and the process of learning are situated not only physically in locality, but also mentally in an identity. As organizations are forced to continuously reshape themselves in this world of increasing abstraction, they need to search for identity more in values, capabilities and principles than in their physical manifestations (Normann, 2001). Also interesting to note is that the link to organizational identity, so critical in the present turbulent environments, is not discussed at all, or even assumed in the industrial organization literature on strategy (Bu¨rgi and Roos, 2002). Most theoretical developments on organizational identity within the organizational science literature take Albert and Whetten’s (1985) definition of identity as the point of departure. They have defined identity as that which is central, enduring, and distinct about an organization’s character, and note that core features of identity are presumed to be resistant to ephemeral or faddish attempts at alteration, because of their ties to the organization’s history. This view does not consider the influence of the environment on the organizational identity. Recently, however, there has been much debate about the interconnectedness among identity, culture, image and reputation (Kowalczyk, 2001), putting the definition of Albert and Whetten into question. For example, Hatch and Schultz (1997) assert that culture, identity and image form three related parts of a system of meaning and sense-making that defines an organization to its various constituencies. Furthermore, they argue that,

increasingly, the actions and statements of top managers simultaneously affect Strategy, identity organizational identity and image, partly due to the increasing levels of and IC interaction between organizational members and suppliers, customers, regulators and other environmental factors, as well as the multiple roles of organizational members who act both as “insiders” (i.e. as employees) and “outsiders” (e.g. as customers, community members and/or members of special 325 interest groups). Research by Dutton et al. (1994) has shown that a person’s wellbeing and behaviour are affected by how both organizational members and outsiders view the organization. When members believe that outsiders see the organization in a positive light, they “bask in the reflected glory” of the organization, which may translate into desirable outcomes such as greater co-operation and citizenship behaviours. Perceived negative views by outsiders, on the other hand, may lead members to experience negative personal outcomes such as depression and stress, which in turn could lead to increased competition among members and reduced effort in the long term. Balmer and Greyser (2002) proposed that any organization has five different identities (actual, communicated, conceived, ideal, and desired) and these have to be reviewed and regularly managed to avoid potentially harmful misalignments. Goia et al. (2000) argue that there is a close reciprocal relationship between organizational identity and various forms of image, and that this is becoming increasingly important as companies compete in complex and turbulent environments and as the role of the media in organizational life becomes more pronounced. Furthermore, they contend that this ongoing interrelationship between organizational identity and image leads to a certain degree of instability of the identity which is actually adaptive in facilitating organizational change. The apparent durability put forth in earlier theories on organizational identity is somewhat illusory according to this view, and is actually contained in the stability of the labels used by organizational members to express what they believe the organization to be. But the meaning, or the interpretation, of these labels changes so that the identity is actually mutable (Goia et al., 2000). This recent, more flexible view of identity is more appropriate for the knowledge-intensive companies under focus in this paper and allows us to link identity to the outside world. In Figure 2, identity is portrayed as a bonding mechanism that encompasses the values and beliefs held by outsiders as well as organizational members. Note that we use the word reputation to denote the collective judgements by outsiders of an organization’s actions and achievements (Fombrun, 1996). Not only do the values and beliefs held by the organizational members impact what vision is likely to be successful, but also the values and beliefs about the organization held by relevant stakeholders outside the organization. This is to avoid confusion of the many connotations of the word “image”, which has been the subject of many different conceptualizations and definitional debate, and is often referred to as the way organizational members believe, or desire, others to view the organization.

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“Making strategy happen”: from implementing strategy to embodying strategy In the previous section, we highlighted the link between a vision- and values-based strategy (outlining what and where the company wants to be in the future) and the concept of identity (what the company is) as a flexible system reflecting and integrating the values and beliefs held by internal and external stakeholders. The identity acts as an “interpreter” and “translator” of the vision and purpose within the context of changes in the external (and internal) environment, and thus provides a means of making sense of the vision and provides the guidelines or “codes of conduct” for knowledge workers. Scholars have well attested the idea that organizational identity acts as a perceptual screen that affects individual members’ information processing and interpretation of issues (Brown and Starkey, 2000). Ka¨rreman and Alvesson (2001) argue that, because the identity or self-image of a person offers guidelines for action, organizing can be portrayed as constructing and maintaining identities to facilitate collective action. The trouble for managers is, of course, that identity, as described in this paper, while affecting how knowledge workers behave and view themselves, the organization and stakeholders, cannot be directly managed – prompting the question “how are identities constructed and how can they be changed?” According to Dowling (2002), to improve a company’s image[3], one has to identify the major factors that combine to influence how people perceive an organization. In essence, these are the set of activities that influence every aspect of how a typical organization communicates with both its internal and external stakeholders. This view is similar to that of many corporate communications departments, influenced by Olins’ (1989) view of “corporate identity”, focusing on how the “central idea” of a company is presented to its various constituents[4]. Ka¨rreman and Alvesson (2001) take the view that identity is socially constructed and suggest that identities are developed, maintained and reconfigured through accounts; taking the form of narration or conversation. The emphasis is on social interactions and negotiations of meaning in groups. Ashforth and Mael (1989) assert that managers have a vested interest in managing symbolic interactions to impart their view of the organization’s identity. Symbolic interactionism holds that meaning is not given, but evolves from the verbal and non-verbal interactions of individuals. Symbolic management involves the use of stories and myths, distinctive language and metaphors, traditions and rituals, physical setting, rewards and status symbols, and so on to shape the interpretation of given jobs by corporate members (Ashforth and Kreiner, 1999). Because of the complexity and pervasiveness of the concept of identity, different scholars and practitioners focus on different aspects, and the above are just a few examples. But they highlight the importance of communication and interactions in their different forms for the emergence of organizational

identity. This implies that, to influence identity, organizations need to manage Strategy, identity not only their formal corporate communications, but also symbols as well as and IC the settings in which social interactions (internal as well as external) occur. The latter may be particularly important to understand for knowledge-intensive companies because personal relationships is a means of reducing ambiguity (i.e. in knowledge-intensive contexts, people tend to stick with actors they know 327 well in the absence of the availability of competition parameters such as price and quality) (Alvesson, 2001). The IC perspective provides a helpful and practical framework for describing all the resources at an organization’s disposal and can therefore be helpful for managers in addressing the concept of identity – and resources can be managed or at least influenced. Many of the most critical resources in a knowledge-intensive firm are IC resources; structures, processes, systems, culture, brands, competencies, relationships and so forth, and they all influence social interactions and can carry symbolic meaning. The physical resources (particularly the physical environment, products and other physical manifestations of the organization’s output) support (or indeed hinder) the IC resources and can be powerful media for communicating the identity. Embodying strategy means mobilizing IC and physical resources to support and facilitate the construction of identity. This implies supporting behaviours and reflecting values rather than providing a set of directions. How can we tailor processes and structures to influence interactions? How do relationships with external stakeholders impact identity? The physical resources “frame” the IC resources. Architecture enables people to meet in a certain space, for a certain purpose, in a certain context. But rather than being a neutral, impartial backdrop for social relations, the physical environment places social relationships in a context (Gillespie, 2002). Spaces form important constituent parts of settings, comprising both the social and physical environment, which influence, or even constrain, our behaviour. Along with a particular setting comes a series of social norms and expected behaviours (Lawson, 2001). How is the identity affected by the setting? How can changes of settings impact organizational identity? The notion of embodying strategy in organizational resources implies a new approach to strategy and its implementation and may raise more questions than it answers. What are the interrelations between identity, IC and physical resources? How is identity reflected in IC resources? In physical resources? How does the existing identity impact IC resources? How do IC and physical resources relate to each other in the construction of identity? However, this may be a more suitable approach for knowledge-intensive companies in uncertain environments than less dynamic processes such as the traditional concept of strategic planning, and we believe that it could provide a fruitful area for further research.

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Conclusions The increasing lack of practical relevance of the strategy discipline reflects the differences between the underpinning assumptions and principles of traditional strategic management theory and the reality of the present day’s knowledge-intensive companies competing in dynamic and uncertain environments. This misfit between theory and practice calls for new conceptualizations of strategy – reviewing what strategy is, why and how to do it in the present context. For new approaches to be successful, they have to provide a link between theories aimed at understanding an increasingly abstract and complex organizational environment and practical tools that operationalize the theoretical implications and make them accessible to managers. In this paper, we have suggested a model that bridges a vision- and values-based strategy (a theoretical construct) with the IC perspective (a practitioner based framework with a diverse set of managerial tools for measuring and managing the organization’s intangible resources already developed and widely used) with the concept of organizational identity. Identity is seen as a bonding mechanism between the elements of strategy, as expressed in Figure 1, as well as between the future and the present day, and finally between the abstract vision and the resources. We suggested replacing the focus on a planned implementation, inappropriate for knowledge-intensive companies competing in uncertain environments, with the notion of “embodying” strategy, which implies enshrining shared values and beliefs that guide behaviours through managing organizational resources. We believe that the approach we have presented in this paper addresses the theory-practice gap, and can provide a fruitful platform for further research exploring the linkages between “strategy” and its operationalization in knowledge-intensive organizations through empirical studies. As pointed out by Albert et al. (2000), it is because identity is so problematic – and yet so critical to how and what one thinks, feels and does in organizations – that the dynamics of identity need to be better understood. Notes 1. See www.strategy-as-practice.org; also, the Journal of Management Studies has a special issue on this theme in Winter, 2002. 2. We use “process” for lack of a better word for describing the overall collection of activities, planned or improvised, intended or unintended, that can be categorized under the three headings. 3. Corporate image in Dowling’s terms is “the global evaluation (comprising of a set of beliefs and feelings) a person has about an organization” (2002, p. 19). It includes the views of all different stakeholders, including employees, and is therefore close to the view of identity taken in this paper. 4. The focus according to this view of “corporate identity” is on managing the visual elements that can play a part in helping stakeholders identify the organization such as name, logo, company buildings, office de´cor, signage, stationery, uniforms and so on.

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Brooking, A. (1996), Intellectual Capital: Core Assets for the Third Millennium Enterprise, Thomson Business Press, London. Brown, A.D. and Starkey, K. (2000), “Organizational identity and learning: a psychodynamic perspective”, Academy of Management Review, Vol. 25 No. 1, pp. 102-20. Bu¨rgi, P. and Roos, J. (2002), “Organizational identity, imagination and strategy”, Working Paper WP 2002-2, Imagination Lab, Lausanne. Campbell, A. and Alexander, M. (1997), “What’s wrong with strategy?”, Harvard Business Review, November-December, pp. 42-51. Castells, M. (2000), The Information Age: Economy, Society and Culture: The Rise of the Network Society, Blackwell Publishers Ltd, Oxford. Choo, C.W. and Bontis, N. (2002), The Strategic Management of Intellectual Capital and Organizational Knowledge, Oxford University Press, New York, NY. Collins, J. and Porras, J. (2000), Built to Last, Random House Business Books, London, UK. Collis, D.J. and Montgomery, C.A. (1995), “Competing on resources: strategy in the 1990s”, Harvard Business Review, July-August, pp. 119-28. Courtney, H., Kirkland, J. and Viguerie, P. (1997), “Strategy under uncertainty”, Harvard Business Review, November-December, pp. 66-79. Coyne, K.P. and Subramanian, S. (1996), “Bringing discipline to strategy”, McKinsey Quarterly, No. 4, p. 11. Davidson, H. (2002), The Committed Enterprise, Butterworth-Heinemann, Oxford. Dowling, G. (2002), Creating Corporate Reputations: Identity, Image, and Performance, Oxford University Press, Oxford. Dutton, J.E., Dukerich, J.M. and Harquail, C.V. (1994), “Organizational images and member identification”, Administrative Science Quarterly, Vol. 39, pp. 239-63. Edvinsson, L. and Malone, M.S. (1997), Intellectual Capital: Realizing Your Company’s True Value by Finding its Hidden Brainpower, Harper Business, New York, NY. Eisenhardt, K.M. and Brown, S.L. (1998), “Time pacing – competing in markets that won’t stand still”, Harvard Business Review, March-April, pp. 59-69. Fombrun, C.J. (1996), Reputation: Realizing Value from the Corporate Image, Harvard Business School Press, Boston, MA. Gergen, K.J. (1991), The Saturated Self: Dilemmas of Identity in Contemporary Life, Basic Books, New York, NY. Gillespie, R. (2002), “Architecture and power: a family-planned clinic as a case study”, Health & Place, No 8, pp. 211-20. Goia, D.A., Schultz, M. and Corley, K.J. (2000), “Organizational identity, image, and adaptive instability”, Academy of Management Review, Vol. 25 No. 1, pp. 63-81. Grant, R.M. (1996), “Towards a knowledge-based theory of the firm”, Strategic Management Journal, Vol. 17, pp. 109-22. Haanes, K. and Fjeldstad, Ø. (2000), “Linking intangible resources and competition”, European Management Review, Vol. 18 No. 1, pp. 52-62. Hamel, G. (1996), “Strategy as revolution”, Harvard Business Review, July-August, pp. 69-82. Hamel, G. (1998), “Strategy, innovation and the quest for value”, Sloan Management Review, Winter, pp. 7-14. Hamel, G. and Prahalad, C.K. (1994), Competing for the Future, Harvard Business School Press, Boston, MA.

Hatch, M. and Schultz, M. (1997), “Relations between culture, identity and image”, European Journal of Marketing, Vol. 31 No. 5, pp. 356-65. Kanter, R.M. (2002), “Strategy as improvisational theatre”, Sloan Management Review, Winter, pp. 76-81. Ka¨rreman, D. and Alvesson, M. (2001), “Making newsmakers: conversational identity at work”, Organization Science, Vol. 22 No. 1, pp. 59-91. Kogut, B. and Zander, U. (1996), “What firms do? Coordination, identity, and learning”, Organization Science, Vol. 7 No. 5, pp. 502-18. Kowalczyk, S.J. (2001), “Corporate branding at Silicon Valley firms: do external perceptions of organizational culture help construct reputations?”, paper presented at the 21st Annual International Conference of the Strategic Management Society, San Francisco, CA. Lawson, B. (2001), The Language of Space, Architectural Press, Oxford. Lindgren, M. (2002), “How much does strategic flexibility matter?”, paper presented at the 22nd Annual International Conference of the Strategic Management Society, Paris. Markides, C.C. (1999), “A dynamic view of strategy”, Sloan Management Review, Spring, pp. 55-63. Mintzberg, H. (1990), “The design school: reconsidering the basic premises of strategic management”, Strategic Management Journal, Vol. 11, pp. 171-95. Normann, R. (2001), Reframing Business: When the Map Changes the Landscape, Wiley, Chichester. Normann, R. and Ramı´rez, R. (1993), “From value chain to value constellation: designing interactive strategy”, Harvard Business Review, July-August, pp. 65-77. Olins, W. (1989), Corporate Identity: Making Business Strategy Visible Through Design, Harvard Business School Press, Boston, MA. Parolini, C. (1999), The Value Net: A Tool for Competitive Strategy, Wiley, Chichester. Peppard, J. and Rylander, A. (2001), “Using an intellectual capital perspective to design and implement a growth strategy”, European Management Journal, October, pp. 510-25. Peppard, J. and Rylander, A. (2002), “Shaping strategy in emergent competitive spaces”, paper presented at the 22nd Annual International Conference of the Strategic Management Society, INSEAD, Paris. Roos, J., Roos, G., Dragonetti, N.C. and Edvinsson, L. (1997), Intellectual Capital: Navigating the New Business Landscape, Macmillan Press, London. Stabell, C.B. and Fjeldstad, Ø.D. (1998), “Configuring value for competitive advantage: on chains, shops and networks”, Strategic Management Journal, Vol. 19 No. 5, pp. 413-37. Stewart, T. (1997), Intellectual Capital. The New Wealth of Organizations, Currency Doubleday, New York, NY. Sveiby, K.E. (1997), The New Organizational Wealth, Berrett-Koehler Publishers Inc., San Francisco, CA. Wiliamson, P. (1999), “Strategy as option on the future”, Sloan Management Review, Spring, pp. 117-26. Further reading Abell, D.F. (1999), “Competing today while preparing for tomorrow”, Sloan Management Review, pp. 73-81.

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Validating and measuring IC in the biotechnology and telecommunication industries Daniel Palacios-Marque´s and Fernando Jose´ Garrigo´s-Simo´n Department of Management, University Jaume I, Castello´n, Spain Keywords Intellectual capital, Delphi method, Performance levels Abstract This paper specifies how to construct and validate an intellectual capital (IC) measurement scale on the basis of management perceptions. In order to construct the scales, a process based on the works of Churchill and DeVellis, complemented by the Delphi technique and structural equations models was used. The use of this methodology was illustrated in an empirical study carried out in the biotechnology and telecommunication sectors. As a result, a validated instrument for IC research is obtained in view of the faithful and rigorous measurement of its key construct.

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 332-347 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487798

Introduction The effect of knowledge on the organization is of key importance, as the creation and application of organizational knowledge are essential to the ability of business organizations to change, adapt, and seize new opportunities in a rapidly changing global world (Binney, 2001), where organizations need to focus strategically on the identification of viable new opportunities beyond existing competences (Hamel and Prahalad, 1989) if they are to survive. But what sort of infrastructure enables a greater orientation towards seeing opportunities and acting on them? Krueger (2000, p. 6) notes that organizations that successfully identify new opportunities have an intangible or cognitive infrastructure that supports its members in perceiving opportunities and acting on them. The development of the “new economy” is based increasingly on firms’ intangible assets. Accordingly, many firms and academics are currently attempting to find better ways of measuring and managing these intangible resources (Lo¨vingsson et al., 2000). Organizations work mainly with two management concepts: knowledge management (KM) and intellectual capital (IC). However, although the delineation between these terms seems unclear, some authors stress that KM, as a function, describes the act of managing IC (Petty and Guthrie, 2000, p. 159). Thus, IC has become a subject of principal interest to and study by both the academic and business worlds in the last decade (Bontis, 1999, 2001, 2002). Nevertheless, as Bontis (1998) states, the real problem with IC lies in the complexity of its valuation. Many studies attempt to conceptualize IC, but few have adopted a prescriptive perspective (for exceptions see Bontis and Fitz-enz, 2002; Bontis et al., 2002), which would be able to shed light on how IC management is a successful strategy for the enterprise and how it relates to

company performance. However, this requires a valuable and feasible measurement mechanism. A tool developed from a well-delimited conceptual definition of IC, which can be used to collect information about firms and to find out the extent to which enterprises are concerned with IC management, is essential (Bontis, 1998). The failure to measure and record IC can lead to the misallocation of capital, under-investment in IC, creating activities such as training, and unrealistic income reporting. In addition, the use of this instrument will allow for a comparison of the theoretical models developed for IC, and for advances to be made in IC research. The main purpose of this study is to develop a measurement instrument for IC. In addition, the paper investigates the weight of the three elements comprising IC. It is structured in three parts. The first section defines the domain of the IC construct. The second attempts to operationalize this construct by devising a Likert-type multi-item scale of measurement. Finally, the measuring instrument is validated through the carrying out of various tests. IC measurement: literature review According to Edvinsson and Malone (1997), the notion of IC refers to the value of intangible assets accumulated by the enterprise. However, other authors point to different perspectives of this concept (Carroll and Tansey, 2000). Initially, Edvinsson (1997) divided IC into two groups: human capital and structural capital. Many perspectives on IC can be found within the frameworks of human capital and structural capital, such as those described by Bontis (1996), Edvinsson and Malone (1997), Sveiby (1997), Bontis and Girardi, (2000), Bontis and Nikitopoulos (2001) and Bontis et al. (1999, 2000). Nevertheless, this approach has been criticized by some authors and, over recent years, additional perspectives have appeared in the literature (see Choo and Bontis (2002) for a review). Following this pioneer research, structural capital was divided into customer capital and organizational capital. In turn, organizational capital was split into innovation capital and process capital (Lo¨vingsson et al., 2000, p. 148). In more recent works, IC has been divided into external or relational capital (i.e. consumer-related), internal capital (structural or organizational) and human capital (Bontis et al., 2000; Roos et al., 1997). In accordance with this recent literature, this paper uses the following three elements to operationalize the IC construct. Human capital According to Guthrie (2001, p. 36), one aspect of IC that has received a significant amount of attention is the area of human capital. It comprises all the knowledge assets (tacit and explicit) placed in individuals. This area considers not only all the knowledge and skills acquired by employees to be important,

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but also their relationship with other employees for the creation of teams to work within the company. The magnitude of this capital is conditioned by the commitment of each individual and factors such as their motivation, the correlation between their individual goals and team goals, etc. In a similar way, human capital is defined as the know-how, information, relationships, and general capabilities that individuals bring to bear on behalf of the firm through the employment relation (Galunic and Anderson, 2000, p. 3), or as a combination of genetic heritage, education, experience, or life and business attitudes. Finally, Bontis (1998) describes human capital as the collective capability of one firm to extract the best solutions from the knowledge of its individuals. Structural capital As defined by Carroll and Tansey (2000), measures of structural capital are those that help to identify the elements of organizational processes and activities and link them to the creation of company value. It is also described by Roos et al. (1997, p. 42) as the value of what is left when the human capital or employees go home at night. This concept embraces knowledge assets which have been systematized, made explicit or internalized by the organization such as: (1) explicit ideas subject to intellectual property rights, and (2) knowledge materialized in infrastructure assets, which can be transmitted between or shared by certain individuals; internalized knowledge plus shared informally inside the organization. Relational capital According to Bowman and Ambrosini (2000, p. 211), analytical procedures require excellent information on competitors, markets, customers and the internal position of the firm. Unfortunately, the required quality of information is rarely routinely available inside the organization, which can affect the goodness of results. Relational capital includes all knowledge assets accumulated by the enterprise from its relationships with other agents in the same environment. This concept derives from the initial notion of customer capital, which was amplified to consider the knowledge obtained through all kinds of relationships with competitors, suppliers, associations, government or other organizations that interact in the organizational environment (Bontis, 1996, 1998). IC operationalization This research has taken Churchill (1979a, b) and De Vellis (1991) as a base from which to develop the IC measurement scale. Both methodologies start with a literature review. The steps are described below.

Identifying the observable attributes of the measuring scale and their reduction by means of the Delphi study First, a broad sample of items was generated to capture the greatest possible number of attributes configuring all the dimensions of the domain of the construct (Churchill, 1979a, p. 67-8). The generation of items for the IC scales was based on the specialist literature in each field. In order to reduce the measuring instrument as much as possible for a more practical application, we then selected only the attributes that were relevant in determining the evaluation, using the Delphi technique and, subsequently, a pre-test questionnaire. The panel of experts comprised 22 people from both academic and managerial backgrounds with knowledge or experience relating to IC. The first questionnaire was evaluated by the panel of experts, who expressed their degree of agreement/disagreement with the use of the different items on a Likert scale of five points. After two rounds of the Delphi procedure we obtained the final set of items.

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Pre-test The measuring instrument was pre-tested twice, the first time on ten firms, with a request for collaboration from the general management. Doubts, interpretation difficulties and suggested improvements were assessed. The final scale resulting from these processes of refinement and reduction consisted of three subscales (see Appendix). Data collection The questionnaire contained 111 statements to which respondents indicated the extent of their agreement on a seven-point Likert scale (1 ¼ strongly disagree and 7 ¼ strongly agree). The questionnaire respondent was the manager of the firm. The technical specification can be found in Table I. In order to evaluate the IC measurement scale, three requirements had to be met: dimensionality; reliability; and validity. Dimensionality The study assumes IC to be a third-order measurement model, comprising three dimensions (human capital, structural capital, and relational capital). In addition, seven human capital, seven structural capital and four relational capital dimensions are distinguished (Figure 1). If the property of

Sample Scope Sample size Margin of statistical error Date of fieldwork

Biotechnology and telecommunication firms Spanish firms (questionnaire carried out by mail) 222 firms ^ 5.7 percent (95 percent significance level) December 2001 - March 2002

Table I. Technical specifications of the empirical work

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Figure 1. Initial model to measure IC

dimensionality is achieved, one can assume the measurement model proposed in Figure 1 to be valid. Confirmatory factor analysis was employed to observe the dimensionality of the three scales used to measure IC (Table II). The values of the standardized weights are greater than 0.4. This is the minimum value suggested by the literature. Furthermore, all the estimated parameters are statistically significant at the 95 percent level ðt $ 1:96Þ: Figures 2-4 provide the standardized weights for each dimension in every element. The results obtained for the factorial model of third order are shown in Table III. The goodness of fit indicators are good for the IC model. Scale reliability Measurement of internal consistency and stability of the scales. We have used multi-item scales, which are more reliable than single-item scales. Besides, it has also attempted to prevent bias in managers’ true perceptions of the construct due to factors such as the letter of presentation, the wording of the questions, their order, the scale used, etc. We believe that the process of refinement by the Delphi method and the pre-test will have minimized this effect. In our study, we calibrated the reliability of the scales using two

Chi2 SatorraBentler g.l. Human capital Technical knowledge Experience Leadership abilities Team spirit Job stability Management ability for the prospective and in meeting challenges Planning ability Structural capital Knowledge of legally protected internal issues Knowledge of external issues, whether legally protected or not Degree of availability and exploitation of knowledge Degree of effective use of the existing knowledge Availability of social mechanisms of transmission and communication of knowledge Organizational culture of the members of the organization Knowledge level and alignment with strategy

p

BB-NFI

IFI

GFI

AGFI

PGFI

0.9542 0.9408 0.9901 0.9542 0.9884

0.9631 0.9452 0.9935 0.9508 0.9807

0.9776 0.9415 0.9878 0.9543 0.9815

0.9539 0.9198 0.9656 0.9371 0.9601

0.9483 0.9365 0.9877 0.9512 0.9742

0.0662 0.0813 0.0556 0.0693 0.0597

2 1 2 2 2

0.5326 0.2951 0.7352 0.5121 0.5365

0.0726 0.0873

1 2

0.3125 0.9414 0.9406 0.9232 0.9103 0.9289 0.2351 0.9426 0.9462 0.9485 0.9138 0.9343

0.0289

2

0.8595 0.9972 0.9991 0.9949 0.9761 0.9853

0.9653

2

0.5257 0.9549 0.9579 0.9372 0.9107 0.9568

0.8560

2

0.6523 0.9740 0.9795 0.9625 0.9478 0.9785

0.9650

2

0.5263 0.9553 0.9584 0.9377 0.9101 0.9562

0.0365

2

0.8462 0.9947 0.9976 0.9917 0.9744 0.9832

0.0593

2

0.5363 0.9881 0.9803 0.9813 0.9598 0.9739

0.0817

1

0.2962 0.9414 0.9462 0.9423 0.9193 0.9359

Relational capital Knowledge of most important customers 0.9641 2 0.5243 0.9517 0.9498 0.9343 0.9085 0.9543 Development of relationship with suppliers to share knowledge 0.0659 2 0.5221 0.9378 0.9379 0.9487 0.9173 0.9344 Effectiveness in spreading knowledge to capture new clients 0.0872 2 0.2152 0.9924 0.9835 0.9823 0.9632 0.9777 Intensity and structuring of strategic alliances established by the firm with external agents 0.0668 1 0.2933 0.9369 0.9401 0.9272 0.9089 0.9272 Notes: GFI ¼ LISREL goodness of fit index $ 0.90; IFI ¼ incremental fit index (good values around 1); BB-NFI ¼ Bentler-Bonett normed fit index $ 0.90; AGFI ¼ LISREL adjusted goodness of fit index $ 0.90; PGFI ¼ Parsimonious goodness of fit index (good values around 1)

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Table II. Fit indices for the first-order models

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Figure 2. Dimensionality for human capital (95 percent level of significance)

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Figure 3. Dimensionality for structural capital (95 percent level of significance)

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Figure 4. Dimensionality for relational capital (95 percent level of significance)

methods: the compound reliability coefficient and the re-test method, each of which evaluates one of the two dimensions of reliability: consistency and stability. The re-test procedure. The re-test was sent to the first 200 respondents to the survey. The time between the two measurements was approximately 45 days. A total of 172 firms finally participated in this re-test exercise, but three had to be rejected due to defects of form or inconsistencies of content, leaving the final rate of response to the re-test at 84.5 percent.

Table III. Factorial model (third-order) for IC

IC

S.B. Chi2

g.l.

p

GFI

IFI

BB-NFI

AGFI

NC

217.234

215

0.7152

0.9231

0.9488

0.9312

0.8923

1.01

Note: GFI $ 0.90; IFI (good values around 1); BB-NFI $ 0.90; AGFI $ 0.90; NC ¼ good values between 1 and 2

The compound reliability coefficient. The statistic we use for determining the reliability of the measurement based on its internal consistency is the compound reliability coefficient. The results of the coefficients of reliability for every dimension are $ 0.7, which represents the acceptable minimum. It confirms the accuracy of the measurement. Although the individual reliability of some items is , 0.50, we do not consider their elimination necessary, since they adequately capture the content of the dimension, which is necessary to prove the content validity.

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Validity of the scales In contrast with the case of reliability, no statistic offers a general index of validity of the measurements made. There are three basic types of validity, as described below. Content validity. Content validity indicates that the procedure for developing the measuring instrument is adequate (Peter and Churchill, 1986, p. 1). One frequently used procedure is to verify whether the process of construction of the scale fits the criteria suggested in the literature, both in methodology and in the techniques and coefficients used. With regard to methodology, this study was carried out in accordance with the recommendations made by Churchill (1979a, b). This methodology, with adaptations, has been used by a wide range of authors to construct scales for measuring key constructs in strategy. With regard to techniques or coefficients, our scales were developed with the instruments normally used in this type of study, such as the literature review or the compound reliability coefficients. When elements other than those listed by Churchill (1979a, b) were introduced, they were in all cases adapted from earlier studies on measurement scales, as with the Delphi methodology for reducing the scale or the re-test method for evaluating the reliability of the scale (Conant et al., 1990). Convergent validity. Convergent validity is said to exist when the measurement is strongly and positively correlated with other measurements of the same construct (Churchill, 1979a, p. 70) or with the variable with which it should theoretically correlate (Cronin and Taylor, 1992). We have used confirmatory factor analysis to observe the convergent validity of the three scales used to measure IC. The minimum squares method was used in its calculation, the only option possible due to the large size of the scale and therefore of the correlation matrix. F1 Human capital (F1) Structural capital (F2) Relational capital (F3) Notes: p # 0.001; compound reliability

F2

0.92 0.578 0.78 0.759 0.472 is on the main diagonal

F3

0.864

Table IV. Correlation matrix and compound reliability

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The indicators of goodness of fit are good for all the scales. The confirmatory factor analyses performed in order to affirm the convergent validity of the scales proposed for measuring IC therefore show satisfactory results. Discriminant validity. Discriminant validity indicates to what extent two measures developed for similar but conceptually different constructs are related (Bearden et al., 1993, p. 4). The discriminant validity of the measuring scales for IC was verified by comparing the compound reliability of each of them with the correlation of that scale with all the other scales. This type of validity is confirmed if the compound reliability for each scale is higher than any of that scale’s correlations with the rest. This condition is demonstrated by the data shown in Table IV. Conclusions The results of the research are of great value to both academics and managers. The scales constructed enable us to measure with ease the different elements of IC (human capital, structural capital and relational capital) and therefore IC as a global construct. It deserves to be highlighted that, in this attempt at empirical validation and self-replication, the method designed for conceptualizing and operationalizing IC has been shown to be robust, irrespective of the methodological decisions (sample, respondents and methods) taken for the empirical work. One important result of the research is that all the scales meet the sociometric properties (dimensionality, reliability and validity) required for measurement scales in business administration. The reliability and the validity of measuring by this means lead us to consider the replacement of objective measures based on proxy variables whose representation of the construct attributes tend to lack completeness. With reference to the various elements of IC, the study concludes that human capital best explains the IC construct, since the standardized weight is 0.902. Relational capital has a standardized weight of 0.746 and finally structural capital, a weight of 0.645. These results are consonant with the sectors studied, since both have a common feature: they are knowledge-intensive sectors. The next phase of this research is to relate IC with other constructs, such as performance or dynamic competences, using the same methodology, with other samples drawn from different countries or sectors. References Bearden, W.O., Netemeyer, R.G. and Mobley, M.F. (1993), Handbook of Marketing Scales. Multi-item Measures for Marketing and Consumer Behavior Research, Sage Publications, Newbury Park, CA. Binney, D. (2001), “The knowledge management spectrum – understanding the KM landscape”, Journal of Knowledge Management, Vol. 2 No. 3, pp. 33-42. Bontis, N. (1996), “There’s a price on your head: managing intellectual capital strategically”, Business Quarterly, Summer, pp. 40-7.

Bontis, N. (1998), “Intellectual capital: an exploratory study that develops measures and models”, Management Decision, Vol. 36 No. 2, pp. 63-76. Bontis, N. (1999), “Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field”, International Journal of Technology Management, Vol. 18 No. 5-8, pp. 433-62. Bontis, N. (2001), “Assessing knowledge assets: a review of the models used to measure intellectual capital”, International Journal of Management Reviews, Vol. 3 No. 1, pp. 41-60. Bontis, N. (2002), World Congress of Intellectual Capital Readings, Butterworth-Heinemann-KMCI Press, Boston, MA. Bontis, N. and Fitz-enz, J. (2002), “Intellectual capital ROI: a causal map of human capital antecedents and consequents”, Journal of Intellectual Capital, Vol. 3 No. 3, pp. 223-47. Bontis, N. and Girardi, J. (2000), “Teaching knowledge management and intellectual capital lessons: an empirical examination of the TANGO simulation”, International Journal of Technology Management, Vol. 20 No. 5-8, pp. 545-55. Bontis, N. and Nikitopoulos, D. (2001), “Thought leadership on intellectual capital”, Journal of Intellectual Capital, Vol. 2 No. 3, pp. 183-91. Bontis, N., Chua, W. and Richardson, S. (2000), “Intellectual capital and the nature of business in Malaysia”, Journal of Intellectual Capital, Vol. 1 No. 1, pp. 85-100. Bontis, N., Crossan, M. and Hulland, J. (2002), “Managing an organizational learning system by aligning stocks and flows”, Journal of Management Studies, Vol. 39 No. 4, pp. 437-69. Bontis, N., Dragonetti, N., Jacobsen, K. and Roos, G. (1999), “The knowledge toolbox: a review of the tools available to measure and manage intangible resources”, European Management Journal, Vol. 17 No. 4, pp. 391-402. Bowman, C. and Ambrosini, V. (2000), “Strategy from an individual perspective”, European Management Journal, Vol. 18 No. 2, pp. 207-15. Carroll, R.F. and Tansey, R.R. (2000), “Intellectual capital in the new Internet economy – its meaning, measurement and management for enhancing quality”, Journal of Intellectual Capital, Vol. 1 No. 4, pp. 296-312. Choo, C.W. and Bontis, N. (2002), The Strategic Management of Intellectual Capital and Organizational Knowledge, Oxford University Press, New York, NY. Churchill, G.A. (1979a), “A paradigm for developing better measures of marketing constructs”, Journal of Marketing Research, Vol. 16 No. 1, pp. 64-73. Churchill, G.A. (1979b), Marketing Research. Methodological Foundations, Dryden, New York, NY. Conant, J.S., Mokwa, M.P. and Varadarajan, P.R. (1990), “Strategic types, distinctive marketing competencies and organizational performance: a multiple measures-based study”, Strategic Management Journal, Vol. 11 No. 5, pp. 365-83. Cronin, J. and Taylor, S. (1992), “Measuring service quality. A re-examination and extension”, Journal of Marketing, Vol. 56, pp. 55-68. De Vellis, R.F. (1991), Scale Development: Theory and Applications, Sage Publications, Newbury Park, CA. Edvinsson, L. (1997), “Developing intellectual capital at Skandia”, Long Range Planning, Vol. 30 No. 3, pp. 366-73. Edvinsson, L. and Malone, M. (1997), Intellectual Capital, HarperBusiness, New York, NY. Galunic, C.D. and Anderson, E. (2000), “From security to mobility: generalized investments in human capital and agent commitment”, Organization Science, Vol. 11 No. 1, pp. 1-20.

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Guthrie, J. (2001), “The management, measurement and the reporting of intellectual capital”, Journal of Intellectual Capital, Vol. 2 No. 1, pp. 27-41. Hamel, G. and Prahalad, C.K. (1989), “Strategic intent”, Harvard Business Review, Vol. 67 No. 3, pp. 63-76. Krueger, N.F. Jr (2000), “The cognitive infrastructure of opportunity emergence”, Entrepreneurship Theory and Practice, pp. 5-23. Lo¨vingsson, F., Dell’ Orto, S. and Baladin, P. (2000), “Navigating with new managerial tools”, Journal of Intellectual Capital, Vol. 1 No. 2, Spring, pp. 147-54. Peter, J.P. and Churchill, G.A. (1986), “Relationship among research design choices and psychometric properties of rating scales: a meta-analysis”, Journal of Marketing Research, Vol. 23, pp. 1-10. Petty, R. and Guthrie, J. (2000), “Intellectual capital literature review. Measurement, reporting and management”, Journal of Intellectual Capital, Vol. 1 No. 2, pp. 155-76. Roos, J., Roos, G., Dragonetti, N.C. and Edvinsson, L. (1997), Intellectual Capital: Navigating the New Business Landscape, Macmillan Press, London. Sveiby, K.E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge Based Assets, Berrett-Koehler Publishers, San Francisco, CA. Appendix Human capital (1) Technical qualifications of employees (2) Special qualification for innovation in personnel (3) Firm’s training undertakings (4) Technical qualifications of top level managers (5) Technical qualifications of middle management* (6) Qualification of technical and scientific employees (7) Professional qualification of support and advisory personnel (8) Managers’ international experience (9) Management ability acquired in multinational companies (10) Ability to manage from an intercultural perspective (11) Managers’ professional experience (12) Seniority in the company* (13) Employees’ professional experience (14) Ability to encourage acceptance of change (15) Communication capacity (16) Faithfulness to the firm and to own commitments (17) Ability to delegate authority* (18) Ability to act as a model for others (19) Ability to support initiatives and suggestions (20) Ability to evaluate one’s own value fairly* (21) Authority based on the group, not on status (22) Ability to adapt to difficult situations

(23) (24) (25) (26) (27) (28) (29) (30) (31) (32) (33) (34) (35) (36) (37) (38) (39) (40) (41) (42) (43) (44) (45) (46) (47) (48)

Ability to regulate behavior and human relations according to a set of moral rules* Ability to act based on confidence of success Ability for global understanding Ability to develop consensus Ability to incorporate members of a team Ability to promote teamwork Ability to treat conflicts through self-criticism and continual improvement, not by relying on legal means Negotiation ability and acceptance of diverse opinions Ability and willingness to collaborate Stability of top-managers Stability of qualified employees Stability of technical and scientific employees Stability of support and advisory employees Competence to solve problems creatively Openness to the environment Ability to anticipate new opportunities and threats Manager orientation toward the future Manager entrepreneurial orientation* Ability to manage change Proactive behaviour in critical situations, not simply “wait and see” Management ability to adopt initiatives* Management ability to assume risk when promoting new projects Ability to analyze and select the best decisions Ability to sustain effort to achieve aims Ability to plan long-term Strategic view of the firm

Structural capital (1) Ability to create and defend product patents (2) Ability to create and defend process patents (3) Creation of innovative ideas expressed in patents (4) Creation of ideas to innovate based on non-built-in technology (5) Efficient performance of patents in external or internal processes (6) Level of knowledge in the market of firm’s brands (7) Level of knowledge in the market of firm’s market symbols (8) Reputation as an innovative firm* (9) Reputation as a quality firm* (10) Reputation as a cutting-edge technology firm (11) Reputation as a leading firm

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(12) (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29) (30) (31) (32) (33) (34) (35) (36) (37) (38) (39) (40)

Public image of the firm in its environment Knowledge used to create a diversified product portfolio Ability in the product’s technological differentiation Ability in the product’s commercial differentiation Documentation and routine in the product creation process Capacity to assimilate useful new technologies and innovation, which have proven potential Degree of advantage taken from organizational knowledge Degree of advantage taken from individual tacit knowledge Degree of advantage taken from environmental knowledge Availability of formal knowledge communication and transmission systems Availability of informal knowledge communication and transmission systems* Availability of decentralized and informal control and coordination processes, which stimulate employee participation Knowledge shared through polyvalence in defining tasks and jobs Knowledge shared through rotation of tasks and jobs* Knowledge shared through internal benchmarking procedures Knowledge shared through inter-departmental rotation Knowledge shared through inter-disciplinary work practices Loyalty to the enterprise and personnel’s own commitments Degree of knowledge and acceptance of evaluation, promotion and reward criteria Knowledge held by personnel on the history and important achievements of the firm Knowledge held by organization members on positive symbols only understood by its members There are behavioral models which employees can imitate There are ritual activities that positively reflect the firm’s values Degree of implementation of long-term formal and informal systems of commitment to the employee Firm’s record of honesty with all the groups related to the organization General acceptance of the commitment to achieve goals Personnel commitment to the organization strategy Degree of personnel participation in the definition of strategy and its development Employee participation in strategic decisions

Relational capital (1) Availability of systems and resources for continual and up-to-date customer study (2) Capacity for obtaining information from present customers and markets (3) Firm’s ability to target goal markets (4) Firm’s ability to measure its customers’ attraction and profitability (5) Ability to obtain information from suppliers and subcontractors

(6) Ability to develop cooperation agreements to generate competitive advantages through productive externalization (7) Firm’s ability to stabilize long-term relations of trust with suppliers (8) Importance of cooperation with suppliers as a way to generate ideas on innovative activity * (9) Availability and effectiveness of formal and informal systems to share resources with suppliers (10) Availability and effectiveness of communication systems with suppliers (11) Orientation toward contact with the firm’s main supplier (12) Public presence of firm employees and managers in conferences and forums (13) Public presence of firm employees and managers in associations (14) Diffusion of knowledge through publications (15) Degree of development of activity for informing and training customers (16) Public presence in events in recognition of achievements (17) Availability of cooperation agreements with other organizations (18) Availability of R&D cooperation agreements with other organizations (19) Ability to manage strategic alliances (20) Ability to achieve effective collaboration with other organizations in R&D (21) Importance of cooperation with experts and consultancy firms as a source for the creation of innovative ideas * (22) Importance of cooperation with other firms as a source for the creation of innovative ideas (23) Importance of cooperation with universities and research institutes as a source for the creation of innovative ideas Note: Items with * have been eliminated to obtain the third-order level.

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The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/1469-1930.htm

Intellectual capital and traditional measures of corporate performance Steven Firer Faculty of Business and Economics, Monash University-South Africa, Ruimsig, South Africa, and

S. Mitchell Williams School of Accountancy, Singapore Management University, Singapore Keywords Intellectual capital, Productivity rate, South Africa Abstract The principal purpose of this study is to investigate the association between the efficiency of value added (VA) by the major components of a firm’s resource base (physical capital, human capital and structural capital) and three traditional dimensions of corporate performance: profitability, productivity, and market valuation. Data are drawn from a sample of 75 publicly traded firms from South Africa from business sectors heavily reliant on intellectual capital. Empirical analysis is conducted using correlation and linear multiple regression analysis. Findings from the empirical analysis indicate that associations between the efficiency of VA by a firm’s major resource bases and profitability, productivity and market valuation are generally limited and mixed. Overall, the empirical findings suggest that physical capital remains the most significant underlying resource of corporate performance in South Africa despite efforts to increase the nation’s intellectual capital base.

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 348-360 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487806

Introduction A precise definition of corporate performance proves to be highly elusive despite frequent use by various special interest stakeholder groups, scholars and policy makers alike. The lack of consensus may arise because this concept is associated with a variety of facets of a firm’s overall wellbeing, ranging from financial profitability to output levels to market returns. For more than 200 years – since the publication of Adam Smith’s Wealth of Nations – neoclassical economic principles were the general corner-stone of the dominant theoretical paradigms in business disciplines such as management, finance and accounting. Labor and capital were considered as the primary factors of production determining corporate wellbeing. Recently, the development of alternative economic theoretical frameworks and theories of the firm, a growing recognition that traditional underlying factors of production have changed, and an increasingly dynamic business environment have added to the growing gulf in perceptions of corporate performance. Some seminal work attempts to bridge the gap between traditional and emerging views, though primarily at a theoretical level. In the new economic era, where intellectual capital assets are increasingly recognized as the pivotal driving force behind wealth creation, an important empirical question remains.

Specifically, do traditional measures of corporate performance effectively IC and corporate capture the same constructs of corporate performance as emerging intellectual performance capital-based measures? This study is unique in empirically examining the association between a measure of intellectual capital being increasingly applied in business and academic applications – namely the Value Added Intellectual Coefficiente (VAICe) developed by Ante Pulic and his colleagues at the 349 Austrian IC Research Centre (Pulic, 1998, 2000; Pulic and Borhemann, 1999) – and three traditional measures of key notions of corporate performance (i.e. profitability, productivity, and market valuation). The study further contributes to the literature by focusing on South Africa rather than a developed Western economy as employed in related work. Key reasons support this focus. For instance, archival evidence of the understanding and development of intellectual capital (IC) concepts in emerging economies is still very much in its infancy. With global prosperity and stability increasingly dependent on emerging economies, a need to establish evidence of intellectual capital development in different socio-political and economic settings persists. Also, since emerging from apartheid South Africa has been a nation in transition. Part of this transition involves efforts to alter the nation’s economic base from a traditional reliance on natural resources to one that encompasses intellectual capital. Evidence from the present study may provide insights into the impact of intellectual capital in economies under transition such as those in Eastern Europe. Finally, the concept of value added (VA) which forms an important tenet of the measure of intellectual capital used in the study (and also other emerging measures) has a strong historical past in South Africa. This assisted in the capture of data used in measuring intellectual capital performance. The analysis presented is based on a sample of 75 South African publicly listed firms from four IC intensive industry sectors: (1) banking; (2) electrical; (3) information technology; and (4) services. Results are of interest to numerous parties. For example, policy makers capable of influencing the direction and nature of the South African business environment can utilize findings to determine possible required changes to present policies to further promote the development of the nation’s intellectual capital resource base. Also, findings aid unsophisticated investors to better understand the changing face of South African business, plus the suitability of the study’s underlying measure of intellectual capital performance for evaluating the impact on firm value of change. Finally, findings provide archival evidence of whether South African firms continue to rely on traditional business practices and perceptions (that is, reliance on natural resources for

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wealth creation), or are shifting toward a greater use of intellectual capital factors. The remainder of the present paper is organized as follows. The next section develops the propositions underlying this study. Empirical results are presented with conclusions and ideas for future research directions described in the last section. Developing intuitive research propositions Donaldson and Preston (1995) argue that since Adam Smith the dominant view of the firm is that it obtains its resources from investors, employees and suppliers to produce goods and services for its customers. In principle, this traditional view contrives corporate performance to be the financial returns to a firm’s owners from the consumption of tangible resources. Alternatively, more recent theoretical views suggest investors, employees, suppliers, customers and other relevant stakeholders (such as unions, government) both contribute and receive benefits from a firm (Turnbull, 1997). Further, alternative theoretical views, such as resource-based theory, conceive firms as collections of physical and intangible assets and capabilities. These contrasting views also provide different views of corporate performance. Advocates of resource-based theory, for example, suggest that corporate performance is a function of the effective and efficient use of the respective tangible and intangible assets of the firm. Further, VA (also called wealth creation) is considered as the appropriate means of conceptualizing corporate performance rather than the mere financial returns to a firm’s owner. Sveiby (2000, 2001), for example, suggests that VA epitomizes an effective measure of an economy’s production ability in the new knowledge economy, whilst illustrating the shortfalls of traditional financial measures. The measure of income highlights the contrasting financial and VA perceptions of corporate performance. The inquiry into whose income accountants are striving to measure has been largely ignored (Suojanen, 1954; Williams, 2001). A commonly accepted view is that income is the rewards due to shareholders from their investment (Morley, 1979). A significant factor that underlies the acceptance of this view is the dominance of “contractual theories of the company” within the accounting discipline (Williams, 2001). The emergence of alternative theories of the firm has also led to different perceptions of the income accountants attempt to measure. The enterprise theory of the firm, for example, is one alternative theoretical perspective providing an alternative notion of income (Van Staden, 1998). Suojanen (1954), for example, in using enterprise theory conceived the firm as a decision-making center for the people (also termed participants or stakeholders), however, fleeting or intimate their contacts with the organization. Participants include shareholders, employees, customers, creditors and the government. Under enterprise theory, income is the reward participants get for their participation

in the firm (Morley, 1979). This alternative interpretation of income is termed IC and corporate VA, specifically defined as the wealth created or distributed by the firm performance through the utilization of its essential productive resources. In our opinion and supported statements of other researchers (Bontis, 1998, 1999, 2001, 2002, 2003; Edvinsson, 1997; Pulic, 1998, 2000; Stewart, 1997; Sveiby, 2000, 2001), traditional measures of corporate performance – based on 351 conventional accounting principles of determining income – may be unsuitable in the new economic world where competitive advantage is driven by intellectual capital. Use of traditional measures may lead investors and other relevant stakeholders to make inappropriate decisions when allocating scarce resources. These views can be expressed in the following questions: first, if knowledge is the key to future success, but is not adequately reflected in traditional accounting financial measures, and second, financial measures are the main drivers of top management’s decision making, what measuring system would fulfil the requirements of the new economy and the needs of modern companies? Given that traditional measures continue to dominate, it is important to determine the extent to which such measures may intrinsically capture the contribution from intellectual capital resources such as human resources, customer reputation and research and development. This is of particular importance in emerging economies that often have borrowed long-held financial models from developed economies, but are striving to strengthen their intellectual capital base to increase economic development. The present study explores this issue, empirically analyzing the association between a relevant measure of intellectual capital and the three commonly used measures of different traditional sub-constructs of corporate performance: productivity, profitability, and market evaluation[1]. Given the study’s exploratory nature, no formal hypotheses are formed. Nonetheless, intuition implies some possible formative propositions. For example, by convention most traditional measures of profitability focus on the financial returns from tangible assets. Consequently, it is likely that such measures are unlikely to capture the VA by intangible assets. Alternatively, market evaluation considers the broader aspects of a firm including both its intangible and tangible assets. As a result, there is likely to be a closer association between market evaluation measures of corporate performance than those for profitability. The following section describes the research method employed in the present study to explore these issues. Research method Measure of dependent variables To conduct the relevant analysis in the present study, three dependent variables – related to the dimensions of profitability, productivity, and market valuation (henceforth denoted ROA, ATO and MB), respectively – are used. The literature documents various accounting- and market-based measures that

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may be utilized as a proxy measure designed to capture the respective properties of the three dependent variables. Presently, there is no specific theoretical perspective or empirical evidence supporting any specific proxy measure over another. It is decided, therefore, that for the purposes of the present study the use of proxy measures used widely in the prior literature is defined as follows: . ROA: ratio of the net income (less preference dividends) divided by book value of total assets as reported in the 2001 annual report; . ATO: ratio of the total revenue to total book value of assets as reported in the 2001 annual report; . MB: ratio of the total market capitalization (share price times number of outstanding common shares) to book value of net assets. Measure of independent variables The VAICe (Pulic, 1998) forms the underlying measurement basis for the three major independent variables in the present study. VAICe is an analytical procedure designed to enable management, shareholders and other relevant stakeholders to effectively monitor and evaluate the efficiency of VA by a firm’s total resources and each major resource component. Formally, VAICe is a composite sum of three separate indicators: (1) Capital employed efficiency (CEE) – indicator of VA efficiency of capital employed. (2) Human capital efficiency (HCE) – indicator of VA efficiency of human capital. (3) Structural capital efficiency (SCE) – indicator of VA efficiency of structural capital. The following equation formalizes the relationship algebraically: VAICei ¼ CEEi þ HCEi þ SCEi where VAICei ¼ VA intellectual coefficient for firm i; CEEi ¼ VAi/CEi; VA capital employed coefficient for firm i; HCEi ¼ VAi/HCi; human capital coefficient for firm i; and SCEi ¼ SCi/VAi; structural capital VA for firm i; VAi ¼ Ii + DPi + Di + Ti + Mi + Ri[2]; VA for firm i computed as the sum of interest expenses (Ii); depreciation expenses (DPi); dividends (Di); corporate taxes (Ti); equity of minority shareholders in net income of subsidiaries (Mi); profits retained for the year (Ri); CEi ¼ book value of the net assets for firm i;

HCi ¼ total investment salary and wages for firm i; SCi ¼ VAi2HCi; structural capital for firm i. Several key reasons support the use of VAICe. First, VAICe provides a standardized and consistent basis of measure (Pulic and Bornemann, 1999), thereby better enabling the effective conduct of an international comparative analysis using a large sample size across various industrial sectors. Alternative IC measures are limited in that they: (1) utilize information associated with a select group of firms (for example, stock data); (2) involve unique financial and non-financial indicators that can be readily combined into a single comprehensive measure; and/or (3) are customized to fit the profile of individual firms (Bontis et al., 1999; Roos et al., 1997; Sullivan, 2000). Consequently, the ability to apply alternative IC measures consistently across a large and diversified sample for comparative analysis is diminished. Second, all data used in the VAICe calculation are based on the audited information; therefore, calculations can be considered objective and verifiable (Pulic, 1998, 2000). Other IC measures have been criticized due to the subjectivity associated with their underlying indicators (Sveiby, 2000; Williams, 2001). Additionally, concerns have been raised about difficulties in verifying information used in calculating indicators comprising other IC measures. Third, VAICe is a straightforward technique that enhances cognitive understanding and enables ease of calculation by various internal and external stakeholders (Schneider, 1999). Ease of calculation enhanced the universal acceptance of many traditional measures of corporate performance. Alternative IC measures are limited as they will be calculated only by internal parties or rely upon sophisticated models, analysis and principles. Finally, the VAICe methodology is utilized in the present study as it is receiving increasing research attention (see, for example, International Business Efficiency Consulting, Inc., 2002; Williams, 2001) and applied use (see, for example, Nova Kreditna banka Mariba (2000)). Control variables Correlation and linear multiple regression tests form the underlying statistical analysis presented. For the linear multiple regression analysis four control variables (size of the firm, leverage, financial performance[3], and industry type) are generally included: (1) Size of the firm (LCAP): natural log of total market capitalization. (2) Leverage (Lev): total debt divided by book value of total assets as reported in each firm’s 2001 annual report.

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(3) Return on equity (ROE): ratio of the net income (less preference dividends) divided by book value of total shareholders’ equity as reported in the 2001 annual report. (4) Industry type (BANK, ELEC, IT and SER): dummy variables representing four major industries within the service sector. Sample selection and descriptive statistics Data are hand-collected from the 2001 fiscal year annual reports of 75 South African publicly traded companies (listed on the Johannesburg Stock Exchange (JSE)) from industry sectors extensively reliant on intellectual capital (namely, bank, electronic, information and service sectors). The sample is limited to these industries, given the study’s exploratory nature and a desire to investigate a homogeneous sample. Table I presents the mean, median and standard deviation of the untransformed dependent variables, independent variables and control factors for the final usable sample. Profitability (ROA) and productivity (ATO) have means (medians) of 15.9 percent (9.9 percent) and 1.066 (0.840), respectively. The mean for market valuation (MB) indicates that investors generally valued the sample firms in excess of the value of the book value of net assets as reported in the financial statements. Comparison of CEE, HCE and SCE values suggests that during 2001 the sample firms were generally more effective in generating value from its human resource assets than from physical and structural assets. This finding is consistent with prior research of South African publicly traded firms based on the 1999 data (Ho and Williams, 2002). The final usable sample comprises a range of both large and small firms as indicated by total assets. Overall financial performance of the sample firms is quite sound as indicated by the reasonably high ROA and ROE. Leverage levels are similar to those in other nations. Finally, the majority of the sample firms are affiliated with the services sector followed by the information technology sector. Results Correlation analysis Correlation analysis is the initial statistical technique employed to analyze the relationship between the dependent and the independent variables[4]. Findings from Pearson pairwise correlations indicate that CEE is significantly negatively associated ( p , 0.05) with ATO. CEE is also significantly positively correlated with MB ( p , 0.01). This independent variable, however, is not significantly correlated with ROA. Results show a significant negative association between HCE and ATO ( p , 0.01). HCE is not significantly correlated with the remaining two dependent variables. Finally, SCE is not significantly correlated with any of the dependent variables. Overall, correlation results imply that sample firms with a higher level of efficiency of VA from their physical capital were associated with lower levels of

Variable description

Variable name

Mean

Profitability: ratio of net income to total assets ROA 0.159 Productivity: ratio of total turnover to total assets ATO 1.066 Market valuation: ratio of the firm’s market capitalization to the firm’s book value of net assets MB 1.505 Value added capital coefficient: ratio of the total VA divided by the total amount of capital employed CEE 0.468 Value added human capital: ratio of the total VA divided by the total salary and wages spent by the firm on its employees HCE 2.078 Structural capital value added: ratio of a firm’s structural capital divided by the total VA SCE 20.313 Market capitalization: total number of outstanding common shares multiplied by share price at the end of 2000 CAP(Rand) 4.61E+09 Leverage: ratio of the firm’s total debt to total assets Lev 0.650 Return on equity: ratio of net income to firm’s total shareholders’ equity ROE 0.220 Bank sector: dummy variable with firms from the banking sector coded one, otherwise zero BANK 12.16 percent Electronic sector: dummy variable with firms from the electronic sector coded one, otherwise zero ELEC 13.51 percent Information technology sector: dummy variable with firms from the information technology sector coded one, otherwise zero IT 22.97 percent Service sector: dummy variable with firms from the service sector coded one, otherwise zero SER 51.35 percent

Median

Standard deviation

0.099

0.364

0.840

1.000

1.267

1.042

0.377

0.349

1.074

2.327

0.069

1.238

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7.43E+08 9.63E+09 0.489

0.535

0.179

0.603

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

productivity, but higher levels of market valuation. Further, sample firms with higher levels of efficiency of VA by their human capital were associated with lower levels of productivity. Linear multiple regression results Table II presents results of three linear multiple regressions. The linear regressions reported in Table II (Panel B, and C) are highly significant ( p , 0.001). In contrast, the linear regression reported in Table II (Panel A) is not statistically significant, indicating that the independent variables and control

Table I. Descriptive statistics of untransformed variables

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Table II. Linear multiple regression results

Panel A: profitability

Panel B: productivity

Panel C: market valuation

75 0.048 1.459 0.190

75 0.435 7.250 0.000a Std. b t-stat. N/A 22.965a 0.700 20.393 0.091

n Adjusted R 2 F-statistic Significance Intercept

Std. b N/A

t-stat. 2.983b

75 0.309 4.630 0.000a Std. b t-stat. N/A 2.173b

Independent variables CEE HCE SCE

2 0.050 2 0.004 0.261

20.291 20.023 1.674g

0.240 2 0.298 2 0.109

1.629 2 2.124b 2 0.801

5.257a 23.094a 0.741

Control factors 2 0.163 2 1.204 0.455 3.704 LCAP 2 0.373 2 2.383b Lev 0.027 0.174 2 0.113 2 0.849 20.168 2 1.399 ROE N/A N/A 0.156 1.511 0.071 0.757 BANK 2 0.048 20.253 2 0.242 2 1.495 20.291 21.990g ELEC 2 0.068 20.488 0.046 0.386 0.175 1.614 SER 2 0.181 21.142 2 0.119 2 0.878 0.072 0.590 Notes: The Table shows standardized coefficients and t-statistics for the respective independent variables and control factors in the model. a ¼ significant at 1 percent confidence level; b ¼ significant at 5 percent confidence level; g ¼ significant at 10 percent confidence level. LCAP ¼ natural logarithm of the firm’s total market capitalization. See Table I for definitions of dependent variables, independent variables and control factors

factors are poor explanatory factors of variations in the dependent variable. Across the three linear regressions reported in Table II, the adjusted coefficient of determination varies from a high of 43.5 percent (Panel C) to a low of 4.8 percent (Panel A). For the first linear multiple regression reported in Table II (Panel A) only coefficients representing SCE ( p , 0.10) and LCAP ( p , 0.05) are statistically significant. The directional signs on the coefficients for these two statistically significant explanatory factors are positive and negative, respectively. In the second linear multiple regression reported in Table II (Panel B), the coefficient representing HCE is statistically negatively significant. None of the other coefficients representing the independent variables and control factors is statistically significant in this linear multiple regression. Finally, for results of the last linear multiple regression reported in Table II (Panel C) the coefficients representing CEE, HCE and BANK are statistically significant ( p , 0.05, p , 0.05 and p , 0.10, respectively). The directional sign on coefficients for HCE and BANK is negative whilst for CEE it is positive. Discussion and conclusions Empirical findings fail to find any strong association between the efficiency of VA by the major components of a firm’s resource base and profitability. At best

there is only a moderately positive association between the efficiency of VA by IC and corporate a firm’s structural capital and profitability. The overall lack of association may performance potentially result from the concepts of VA and profitability capturing two distinctive and completely unrelated dimensions of corporate performance. For instance, profitability may be conceived strictly as financial and accounting concern focusing on returns to the firm’s owners, solely within monetary terms. 357 Alternatively, VA defines the contribution to be the overall increase in potential and wealth to the various stakeholders of a firm other than just the owners. Another possible explanation for the lack of association between profitability and VA is that there is a lack of variation in the dependent and independent variables to conduct meaningful empirical analysis. With respect to productivity, only the efficiency of VA by a firm’s human resources is to be significantly associated. Empirical findings suggest that this association is negative. This result implies that publicly traded firms and the business environment in South Africa may dictate a trade-off between tangible assets and human capital. That is, firms in South Africa seeking to increase productivity through the employment of tangible assets put less effort into utilizing its human resource base. Alternatively, a firm focusing attention on human resource assets appeared to give less emphasis to the effective use of tangible assets. Findings related to the association between market valuation and the efficiency of VA by a firm’s major resource components provides some interesting insights. First, findings imply that the market in South Africa places a significant emphasis on returns from physical resource assets. Consequently, firms that provide an indication that physical assets have been utilized effectively in generating such returns are likely to be more highly valued. Second, whilst the market appears to consider human resource assets, findings suggest that the market may react negatively if a firm concentrates on enhancing this resource base at the expense of its development of physical capital resources. Third, empirical findings suggest that the South African market appears to give significantly less attention to the structural capital resources of a firm relative to physical capital and human capital resources. Overall, the latter findings suggest that in general the South African market continues to place greater faith and value in physical capital assets than intellectual capital assets. Finally, empirical findings indicate that firm size, leverage, financial performance and industry type contribute very little to the explanatory power of the linear multiple regression results. Indeed, these control factors were of statistical significance in only two isolated cases. Consequently, the following conclusions regarding the association between the control variables and dependent variables can be summarized as follows: . firm size appears not to be associated with the dimensions of productivity and market valuation;

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leverage is not associated with profitability, productivity or market valuation; there is no association between financial performance and productivity and market valuation; and industry type is only moderately associated with market valuation and neither profitability nor productivity.

Overall, the empirical findings, based on correlation and linear multiple regression analysis, indicate that the association between the efficiency of VA by a firm’s major resource components and the three traditional dimensions of corporate performance is limited and mixed. In general, empirical findings suggest that despite the efforts to improve its intellectual capital base the business environment and market in South Africa still appear to place greater weight on corporate performance based on physical capital assets. A possible policy implication of these findings from this study may be that policymakers may have to adjust or intensify initiatives to encourage greater acceptance and understanding of the concept of intellectual capital, and the development of related assets. As South Africa continues efforts to join the international community and increase its level of economic development beyond that of an emerging economy, a continued aversion from and apathetic view toward intellectual capital amongst South African firms and the business community may have negative consequences. Whilst providing various insights that should be of interest to scholars, shareholders, institutional investigations, policymakers and other relevant stakeholders, the findings from the present study indicate avenues for further investigation. For example, findings from the present study are cross-sectional. Future research can be undertaken to investigate the associations studied in the present paper across time. Also, analysis in the present study draws on data from a single nation and from firms within business sectors reliant on intellectual capital. Additional research should be conducted using data from alternative domestic settings and/or firms from non-intellectual capital business sectors. Despite possible limitations of using single-period data, a relatively focused sample and a single domestic location, it is felt that the results from the present study provide valuable insights into the association between intellectual capital and traditional perceptions of corporate performance. Further, this study helps to expand the current research agenda within the intellectual capital discipline toward alternative areas of interest. Notes 1. Productivity (or efficiency) described which inputs are converted to outputs. Conversely, profitability described corporate performance as the degree to which a firm’s revenues exceed costs. Finally, market evaluation concentrates on the degree to which a firm’s market value exceeds its book value. This last dimension is related to a firm’s performance because

if the firm was not operating well (not performing), then its market value would probably be limited to the net book value of its assets. 2. Prior research has defined VA by the following algebraic equation: Rev 2 B þ Inv ¼ W þ I þ DP þ D þ T þ M þ R

IC and corporate performance

ð1aÞ

or

359 S 2 B þ Inv 2 DP ¼ W þ I þ DP þ D þ T þ M þ R:

ð1bÞ

Equation (1a) is commonly referred to as the gross VA and Equation (1b) is termed the net VA. Theoretical arguments have been forwarded supporting both approaches. Empirical research indicates that both methods have been used in practice. Pulic (1998) argues that, because of the central active role human resources plays in the value creation process, labor costs (wages expense) should not be included in the VA computations. This view is consistent with the opinions of other IC experts (Edvinsson, 1997; Sveiby, 2000). 3. In the linear multiple regression with profitability as the dependent variable the control factor of financial performance (denoted as ROE) is not included, as the return on equity may also be used as a proxy for the dependent variable. 4. Spearman correlations were also performed. These alternative correlations tests yield the same results. Owing to space limitations correlation values are not formally presented in the present paper. Results of correlation analysis can be obtained from the authors upon request. References Bontis, N. (1998), “Intellectual capital: an exploratory study that develops measures and models”, Management Decision, Vol. 36 No. 2, pp. 63-76. Bontis, N. (1999), “Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field”, International Journal of Technology Management, Vol. 18 No. 5-8, pp. 433-62. Bontis, N. (2001), “Assessing knowledge assets: a review of the models used to measure intellectual capital”, International Journal of Management Reviews, Vol. 3 No. 1, pp. 41-60. Bontis, N. (2002), World Congress of Intellectual Capital Readings, Butterworth-Heinemann-KMCI Press, Boston, MA. Bontis, N. (2003), “Intellectual capital disclosure in Canadian corporations”, Journal of Human Resource Costing and Accounting, forthcoming. Bontis, N., Dragonetti, N., Jacobsen, K. and Roos, G. (1999), “The knowledge toolbox: a review of the tools available to measure and manage intangible resources”, European Management Journal, Vol. 17 No. 4, pp. 391-402. Donaldson, T. and Preston, L.E. (1995), “The stakeholder theory of the corporation: concepts, evidence and implications”, The Academy of Management Review, Vol. 20 No. 1, pp. 65-91. Edvinsson, L. (1997), “Developing intellectual capital at Skandia”, Long Range Planning, Vol. 30 No. 3, pp. 266-373. Ho, C.W.P. and Williams, S.L.M. (2002), “International comparative analysis of the association between board structure and efficiency of value added by a firm’s physical capital and intellectual capital”, paper presented at The International Journal of Accounting International Summer School Conference, Champaign, IL. International Business Efficiency Consulting (IBEC) Inc. (2002), Intellectual Capital: Efficiency of Croatian Economy, IBEC, Inc., Dover, OH.

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Morley, M.F. (1979), “The value added statement in Britain”, The Accounting Review, Vol. 54 No. 3, pp. 618-29. Nova Kreditna banka Mariba, (2000), Annual Report, Nova Kreditna banka Mariba, Maribor. Pulic, A. (1998), “Measuring the performance of intellectual potential in knowledge economy”, available at: www.measuring-ip.at/Opapers/Pulic/Vaictxt.vaictxt.html (accessed 11 March, 2003). Pulic, A. (2000), “An accounting tool for IC management”, available at: www.measuring-ip.at/ Papers/ham99txt.htm (accessed 11 March, 2003). Pulic, A. and Bornemann, M. (1999), “The physical and intellectual capital of Austrian banks”, available at: www.measuring-ip.at/Papers/Pubic/Bank/en-bank.html (accessed 11 March, 2003). Roos, J., Roos, G., Dragonetti, N.C. and Edvinsson, L. (1997), Intellectual Capital: Navigating in the New Business Landscape, Macmillan, Basingstoke. Schneider, U. (1999), “The Austrian approach to the measurement of intellectual potential”, available at: www.measuring-ip.at/Opapers/Schneider/Canada/theoreticalframework.html (accessed 11 March, 2003). Stewart, T.A. (1997), Intellectual Capital: The New Wealth of Organizations, Doubleday/Currency, New York, NY. Sullivan, P.H. (2000), Value-driven Intellectual Capital: How to Convert Intangible Corporate Assets into Market Value, John Wiley & Sons, Toronto. Suojanen, W.W. (1954), “Accounting theory and the large corporation”, The Accounting Review, July, pp. 391-8. Sveiby, K. (2000), “Intellectual capital and knowledge management”, available at: www.sveiby. com.au/BookContents.html (accessed 11 March, 2003). Sveiby, K. (2001), “Methods for measuring intangible assets”, available at: www.sveiby.com.au/ BookContents.html (accessed 11 March, 2003). Turnbull, S. (1997), “Corporate governance: its scope, concerns and theories”, Corporate Governance: An International Review, Vol. 5 No. 4, pp. 180-205. Van Staden, C.J. (1998), “The usefulness of the value added statement in South Africa”, Managerial Finance, Vol. 24 No. 11, pp. 44-59. Williams, M. (2001), “Are intellectual capital performance and disclosure practices related?”, Journal of Intellectual Capital, Vol. 2 No. 3, pp. 192-203.

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Distinguishing between the board and management in company mission

Implications for corporate governance 361

Implications for corporate governance Chris Bart and Nick Bontis Michael G. DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada Keywords Mission statements, Corporate governance Abstract A relationship between board/management “involvement” and “awareness” with organizational mission and their link to “employee commitment” and “organizational performance” was modeled by drawing on previous research. The model was tested with data from 339 large Canadian and US organizations. It was determined that “mission awareness” on the part of both the board and senior management is an important consideration in the determination of employees’ commitment to the mission. However, the impact of board and management involvement with the mission is not identical. The results emphasize the strong and important role that the board performs when it is actively engaged in the development of the organization’s mission.

Introduction What is the proper role of the Board of Directors in terms of setting an organization’s mission? Should boards restrict their activities to simply being aware of their organization’s mission (with or without formal final approval) or should they be more actively engaged in terms of determining, evaluating, influencing and eventually approving the mission? Furthermore, what is the organizational outcome on intellectual capital development and performance when this takes place? While for many it may seem that these questions should have been addressed long ago, it is surprising that even today, after the recent scandals of Worldcom, Enron and Tyco, there is no clear definitive answer. An important factor contributing to this situation is the fact that there have been no empirical research studies investigating the potential impact or consequences that varying levels of board involvement with an organization’s mission statement may have. Consequently, this study tackles this problem head-on by assessing the performance implications of both board awareness of and involvement with organizational mission. Mission statements Of all the management tools employed in the world at present, the one that has been cited as the most frequently used – and most popular – is the organizational mission statement (Bart, 1997a). In its most basic form, a

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 361-381 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487815

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Figure 1. Sample mission statements

mission statement is designed to answer the most fundamental questions for every organization: Why do we exist? What are we here for? What is our purpose? As such, mission statements form the corner-stone and the starting-point for any major strategic planning initiative (Bart et al., 2001). They are the launching-pad for setting organizational objectives. They drive organizational priorities and intellectual capital development (Bontis, 1996, 1999, 2001, 2002, 2003a). They set the tone for the organization’s climate and culture (Van der Weyer, 1994). Since the 1980s, the mission statements have been used more and more to define and communicate the kinds of relationships which an organization wishes to establish with each of its major stakeholder groups (e.g. investors, customers, and employees) (Campbell, 1997). Several examples of recent mission statements from major organizations are shown in Figure 1. Interestingly, recent research has proven that not all mission statements are created equal; i.e. it is possible to have “bad” as well as “good” mission statements, and it is important to consider many variables in formulating a good one (Baetz and Bart, 1996; Bart and Baetz, 1998). Considering the impact

that a mission can have on its organization, it is an understatement to say that it is important to create a proper statement (Bart, 1998a, b; Bart and Tabone, 1999). Generally speaking, though, an effective mission statement is one that articulates the specific ways in which an organization intends to secure loyal customers for its products and services and attract dedicated workers who are passionate about and committed to serving the kinds of customers the organization is interested in obtaining. As such, mission statements are written first and foremost for an organization’s workforce. They are designed to communicate the direction in which the organization is headed and to acquire the group cohesiveness – or shared values – which can make the organization a truly formidable competitor. Thus, mission statements can matter – really matter! And a multitude of articles have been written in recent years proclaiming their numerous benefits (Bart, 1997a, b, c, 1998a, b, 1999a, b, 2000, 2001a, b, 2002, 2003a, b; Bart and Baetz, 1998; Bart et al., 2001).

Corporate governance and mission The high-level strategic nature of mission statements and their responsibility for setting the overall direction of an organization, however, have important implications for the field of corporate governance. More specifically, corporate governance is the system by which business corporations are directed and controlled (OECD, 1999). An organization’s system of corporate governance is operationalized through the development of a structure that specifies the distribution of rights and responsibilities among different participants (or “stakeholders”) in the corporation and spells out the rules and procedures for making decisions on corporate affairs. Consequently, a critical corporate governance question is: who should take responsibility for the development, evaluation and approval of an organization’s mission? For company directors and their boards, there is no easy answer because, on the one hand, the job of a board is to give direction to senior management. Directors, as representatives of the shareholders, are stewards of the organization – which according to the Merriam Webster Dictionary is defined as a fiscal agent; one who actively directs affairs. On the other hand, there is a near universal agreement that it is important for directors not to micro-manage the corporation by taking on the roles and responsibilities of management. So what is a director to do? For many writers on corporate governance, one solution to this conundrum is to simply say that each situation is unique and, therefore, all that needs to be done in the interests of good governance is to be transparent about the roles. In other words, write it down! But, boards and directors are also looking for guidance. They want to know: what is the right thing to do? They want to know where the lines and distinctions in the roles between the board and senior management need to be drawn. So, what are the best practices in this regard?

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Unfortunately, again, an easy answer to this question is not readily forthcoming. Based on a review of the extant literature, there is no uniformity in terms of the positions taken. Consequently, directors could become easily frustrated in searching for guidance on how to structure their jobs when it comes to strategy in general and mission in particular. Take the Institute of Corporate Directors of Canada (ICD), for instance. It has stated on one occasion that the task facing the board includes the need to determine strategic objectives as prepared and recommended by management (ICD, 1988). With this statement, the ICD appeared to confer on corporate boards a fairly active role in the actual formulation of mission goals. Yet, four years later, the ICD was seen to claw back the board’s authority for strategy by arguing that a board need only take responsibility for approving strategic objectives (ICD, 1992). No apparent rationale for this change in position was offered. A series of studies by the Canadian Institute of Chartered Accountants (CICA) appears to take a much more uniform position with respect to director involvement in company strategy. One of its early monographs focusing on the governance processes associated with effective control stated that approval and monitoring of the organization’s mission, vision and strategy are one of the board’s most important responsibilities, and that the board should review and approve the mission, vision and strategy on a periodic basis and when major shifts occur (CICA, 1995a). A subsequent monograph, outlining the CICA’s view regarding the criteria that should be used to establish effective control, reiterated the earlier position. It stated that an explicit mission and clear vision are key elements of control and should be approved by the board of directors (CICA, 1995b). A third document, providing guidance for directors with respect to risk, however, seems to soften the directors’ role in strategy considerably when it urges directors to simply have a clear sense of corporate purpose and to be committed to achieving it (CICA, 1999). It is notable that none of the positions taken by the CICA in the documents cited earlier argues for the board’s active participation in the formulation of an organization’s strategy or its revision. In fact, the overall impression created is of a board which just receives and reviews management’s stated mission for the enterprise, poses a few questions and perhaps challenges some assumptions, but in the end raises its hands and simply “approves the damn thing”. The board’s role in strategy is therefore one of interested bystanders and passive approval rather than active engagement. How then, in such circumstances, does effective control by the board occur? The answer appears to lie largely in their monitoring of the company’s performance – relative to the approved mission and strategic plan – whereby failure to achieve the stated goals provides the basis upon which confidence in the CEO is altered. But, so long as the CEO delivers on his/her promises, then no action need be taken. Mission accomplished. However, such an approach to control would seem to support only low-stretch objectives and assumes that

directors – lacking sufficient time, information and expertise – have little choice but to approve strategic plans. A somewhat different perspective occurs when the report of the NACD Blue Ribbon Commission concerning the role of the board in corporate strategy is examined (NACD, 2001). The report identifies a clear need for corporate boards to be actively involved in the development and approval of an organization’s strategy and exhorts boards and management to view board participation in corporate strategy as a cooperative and not as an adversarial process. The report also reinforces the importance of a board’s long-standing and historical strength with respect to strategy (i.e. probing, questioning, and constructively challenging and criticizing organizational strategy). The report, unfortunately though, is confusing and contradictory in terms of its final stance regarding the degree of board involvement in strategy. As a result, it is unclear whether boards should help develop their organization’s mission or not (i.e. the NACD (2001) report in one section on page 4 says that they should not develop strategy and then in another section on page 8 argues that the board should assess, discuss, amend and urge corrections with management). While the report emphasizes the need for boards to be constructively involved in strategy, there is little elaboration concerning what the authors of the report exactly meant by this term. A variation of this was also seen to occur recently when a Canadian task force on corporate governance recommended that the Toronto Stock Exchange (TSX) amend its guidelines to make clear that the board’s responsibility goes beyond the adoption of a strategic planning process (Joint Committee on Corporate Governance, 2001). The report recommended that the board should be responsible for contributing to the development of strategic direction and approving a strategic plan that takes into account an identification of business opportunities and business risks (TSX, 2002). In doing so, the task force authors appear to side clearly with those who argue that the board has a definitive role in shaping an organization’s mission. However, the regulators seem to have heard only half the message. In April 2002, the TSX announced that the role of the board in adopting a strategic planning process would be expanded to include only the approval of a strategic plan – thereby, once again, restricting the board’s involvement in strategy making and direction setting to approval but not development (TSX, 2002). A quick review of various international corporate governance codes only adds further confusion to this state of affairs beyond what is evident in Canada. Thus, when it comes to the development of an organization’s mission statement, there is presently no definitive answer – and no widespread acceptance – regarding the division of responsibilities between the board and the senior management. We contend, though, that a major factor contributing to this situation is that all of the reports (including those not reviewed here) are not based on any solid research. Instead, the findings/recommendations

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contained in the various documents are, in reality, just a compilation of opinions. While those opinions may come from experienced corporate directors and recognized thought leaders, they are still just opinions and not facts. References to empirical studies of board best practices (i.e. strategy formulation, evaluation and monitoring) are virtually non-existent. It is also not apparent that the various reports cited had commissioned any specific research studies to investigate, verify and support their resultant recommendations. Accordingly, this study endeavours to correct this situation by focusing on a set of very specific research questions. Interestingly, a recent presentation of some preliminary findings by one of this paper’s co-authors suggested that a specific and definitive answer to the question of board involvement with mission exists (Bart, 2003b). However, because those findings were deemed provisional, we decided to strengthen the original analysis with more high-powered analytical techniques in order to give the initial conclusions more weight. Along the way, significant new insights were gained. Research questions Numerous questions regarding boards and their mission statements remain unanswered. For instance, to what extent are boards even aware of their organization’s mission statement? This question is important because, if responsibility for mission belongs exclusively to senior management – or if directors do not see such responsibility as falling within their specific role set , then one might expect to find little or no awareness of it on the part of the board and hence little interest on their part in its development or content. Nevertheless, even if the boards are aware of their organization’s mission, they still may or may not feel that their participation in its development is warranted. Of course, an important consideration in determining the board best practices vis-a`-vis mission statements concerns whether or not board awareness and/or involvement with the mission has any impact on the organization. As the earlier discussion demonstrated, there is very little guidance as to what is the correct posture that directors should adopt on these matters. In order to help boards better understand their roles in relation to their organization’s mission statement, a research project was designed which sought to explore the relationship between the selected characteristics of board and senior management awareness/involvement with their missions and selected performance-related outcome measures. The specific questions addressed by this research were as follows: (1) To what extent are boards aware of their organization’s mission? (2) To what extent are boards involved in the creation of their organization’s mission? (3) How does board awareness/involvement compare with that of senior management?

(4) Does the level of awareness/involvement with respect to the mission matter in terms of enhancing the organization’s intellectual capital and performance? (5) What contributes most to the awareness of the mission?

Implications for corporate governance

Method and measures Sample selection and size Surveys were delivered to the top manager (i.e. CEO, President, Executive Director, Board Chairman) of 1,000 North American organizations randomly selected from the Fortune 1000 (USA) and Financial Post 500 (Canada). As informants, senior management is most able to recognize the relative importance of organizational issues, whether they are performance, or strategy related (Glick et al., 1990). The top manager was asked to complete the survey or to delegate the task to someone knowledgeable with the organization’s mission statement and its development. A total of 339 completed questionnaires were returned, representing a response rate of 33.9 percent. The method of sample selection, however, restricts the claims which can be made about the representativeness of the findings, as they do not appear to apply to organizations of all sizes, cultures and sectors. The findings and conclusions in this study appear to have validity only in so far as larger-scale, English-speaking North American organizations are concerned and this fact should be noted when considering the study’s general applicability. Descriptive statistics of the respondent sample closely mirror that of the population from which the sample was derived. Respondent title and response bias. Of the responses received, 37.2 percent were from a top manager (i.e. CEO or Board Chairman), while the remainder were senior level executives or managers (i.e. Senior Executives 26.6 percent; Senior Managers 36.3 percent). A one-way ANOVA for each of the respondent types was examined against three important dependent variables (Figure 2): (1) What is your overall satisfaction with the organization’s financial performance? (Scale from 0 ¼ very dissatisfied to 9 ¼ very satisfied.) (2) Are individuals in the organization committed to the mission statement? (Scale from 0 ¼ not at all to 9 ¼ to the greatest possible extent.) (3) How innovative is your organization? (Scale from 0 ¼ not all innovative to 9 ¼ extremely innovative.)

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Results of the one-way ANOVA show that there is no statistically significant difference in dependent variable outcomes based on respondent-type, thereby yielding no evidence of response-bias in this study (F-stat ¼ 5.33, 7.43, 10.13, p , 0.001). Operationalizing mission awareness and involvement. Respondents were asked to rate separately the extent to which the board and senior management were aware of their organization’s mission statement using a four-point scale (1 ¼ not aware at all; 2 ¼ somewhat aware; 3 ¼ moderately aware; 4 ¼ highly

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Figure 2. ANOVA test for response bias

aware). Managers were then asked (again using a four-point scale) to indicate the degree to which they were involved in developing their organization’s mission statement (1 ¼ no involvement at all; 2 ¼ somewhat involved; 3 ¼ moderately involved; 4 ¼ highly involved). Figure 3 shows that the awareness of mission statements and the involvement in developing them differed between senior management and board members. On average, board members scored lower than their management counterparts in both awareness (3.48 vs 3.66) and involvement

Figure 3. Awareness and involvement by board and senior management

(2.98 vs 3.74). However, in absolute terms, awareness and involvement with the mission by board members and senior managers appears to be fairly high. Mission communication technique usage. There were a variety of mission communication techniques that were measured in this study (see Figure 4). On average, the use of annual reports and employee manuals was the most prominent communication method in use at 67.6 and 63.5 percent, respectively. Alternatively, only 27.3 percent of respondents used advertisements to communicate their mission statements.

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Outcome measures Three outcome measures were used in order to assess the effect of board and senior management awareness and involvement with the mission: (1) the extent to which members throughout the organization are emotionally committed to the mission statement (Bart, 1998a; Bart and Tabone, 1999; Bart et al., 2001); (2) the extent to which respondents were satisfied with the financial performance of their organization (Bart, 1997b, 1998a; Bart and Baetz, 1998; Bart and Tabone, 1999); and (3) the extent of perceived innovativeness of the organization. Respondents were asked to rate each of these outcome measures on a ten-point scale (i.e. 0 ¼ not at all, 9 ¼ to the greatest possible extent). Bontis and his colleagues (Bontis and Fitz-enz, 2002; Bontis and Girardi, 2000; Bontis and Nikitopoulos, 2001; Bontis et al., 1999, 2000; Choo and Bontis, 2002; O’Regan et al., 2001; Stovel and Bontis, 2002) have shown that

Figure 4. Techniques to communicate mission statement

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organizational commitment is a critical antecedent to intellectual capital development and performance outcomes. Furthermore, Bontis (1998) and Bontis et al. (2002) have shown in intellectual capital studies that perceived measures of performance can be a reasonable substitute for objective measures of performance (Dess and Robinson, 1984) and have a significant correlation with objective measures of financial performance (Lyles and Salk, 1997; Venkatraman and Ramnujam, 1987). Accordingly, the interpretation of the results from this study is that respondents were, on average, “moderately satisfied” with members’ commitment to the mission statement (mean ¼ 5.94), financial performance (mean ¼ 5.86) and organizational innovativeness (mean ¼ 5.87). It is also important to note that a control variable was used to limit unnecessary variability of the endogenous constructs. For this study, each organization was asked to provide the year in which the organization first developed a recorded mission statement. That year was converted to the age (i.e. age ¼ 2002 2 year) of the mission statement process since inception. The average year of inception of the mission process for the firms in this study was 1989 (or 13 years). This was required so that variability in performance could not be attributable solely to mission experience. Partial least squares model Hulland (1999) has noted that the use of partial least squares (PLS) as a structural equation modeling technique has received increased interest in the strategic management literature in areas such as intellectual capital management (Bontis, 1998, 2003b; Bontis et al., 2000, 2002) and mission statements (Bart et al., 2001). According to Hulland (1999, pp. 202-3), this is because “causal models such as PLS can help strategic management researchers to achieve new insights . . . As the field of strategic management continues to mature, researchers need to increasingly rise to the challenge”. PLS also allows researchers to develop a systematic and holistic view when establishing measures to solve research problems. For large-sample modeling, LISREL (Bollen, 1990; Jo¨reskog and So¨rbom, 1984) has several relative strengths, whereas, for small-sample predictive research, PLS (Fornell and Bookstein, 1982; Hulland, 1999) is more appropriate. In general, the most complex models will involve: (1) the number of indicators on the most complex formative construct; or (2) the largest number of antecedent constructs leading to an endogenous construct. Sample size requirements become at least ten times the number of predictors from (1) or (2), whichever is greater (Barclay et al., 1995). In this case, there are a total of nine formative indicators on the most complex construct which is communication technique (i.e. advertisement, annual reports, etc.), and a total

of six antecedent constructs leading to the endogenous construct. Therefore, the minimum sample requirements become 9 £ 10 or 90. PLS is an adequate technique for this study since the sample size is 339 respondents. All of the items germane to this study were therefore assigned to their respective scales using PLS, as suggested by Barclay et al. (1995) and Hulland (1999). Reliability and validity The survey items and constructs were subjected to various psychometric evaluations to confirm reliability and validity. A Cronbach alpha’s (a) measure was used to test the reliability of the communication technique construct which contained nine items. The alpha (a) value of 0.839 is above the minimum threshold of 0.7, as supported by Nunnally (1978). Shimp and Sharma (1987) suggest that items have loading values greater than 0.7 to ensure construct validity. This procedure is also supported by Carmines and Zeller (1979) and Hulland (1999). In this case, only three of the nine items had loading values greater than 0.7 and were therefore removed prior to the subsequent modelling exercise. Interestingly, the three remaining communication techniques that were both reliable and valid were not necessarily those most often used by the respondents. Company information kits ðl ¼ 0:732Þ; newsletters ðl ¼ 0:732Þ and internal documents ðl ¼ 0:702Þ were used only by 59.6, 53.1 and 57.4 percent of respondents. Conversely, the most often used communication technique of annual reports was used by two-thirds (67.6 percent) of the respondents. Yet, its construct validity ðl ¼ 0:598Þ was below the threshold, denoting a suspiciously absent nomological connection to the board and management awareness of mission statements (see Figure 5). Similarly, a latent performance construct was created using two of the outcome measures identified earlier – both of which were found to be both valid and reliable. The first item was overall satisfaction with the financial

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Figure 5. Construct validity and reliability of communication technique

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performance of the organization ðl ¼ 0:837Þ and the second item was how innovative the organization was ðl ¼ 0:874Þ: Research limitations With respect to the present results, a number of caveats pertaining to common method, single-respondent, and social desirability biases should be acknowledged. To address the possibility of common method bias, a Herman’s one-factor test on the questionnaire measurement items was conducted (Konrad and Linnehan, 1995; Scott and Bruce, 1994). A principal components factor analysis yielded four factors with eigenvalues greater than 1.0 that accounted for 51 percent of the variance. Since several factors, as opposed to one single factor, were identified and, since the first factor did not account for the majority of the variance (only 29 percent), a substantial amount of common method variance does not appear to be present (Podsakoff and Organ, 1986). Nevertheless, the presence of common method problems cannot be fully discarded. An important methodological imperative for this study was for each respondent to be highly familiar with the mission statement and its resultant organizational effect. In this respect, the study was considered satisfactory since the majority of respondents were top executives in their respective organizations. Given the singularity and specialized knowledge associated with these informants, a single-informant approach was deemed best and was therefore used. We believed that less knowledgeable informants would result in less accurate data. Whereas survey data are sometimes subject to social desirability bias (Arnold and Feldman, 1981; Podsakoff and Organ, 1986), we do not perceive such bias to be a major concern for this study. The topic of investigation, although strategic, was not thought to be so highly sensitive as to be likely to prevent responses that would present the respondent or organization in an unfavourable light. In addition, much of the information obtained was not deemed highly confidential. However, the occurrence of such bias cannot be totally ruled out. Results Figure 6 shows the final specified PLS structural equation model. Each path and beta coefficient displayed are both substantive and significant. The explanatory power of the model is relatively high for survey research at 33.4 percent and denotes a strong confidence in the explanation of performance variance attributable to mission communication, involvement, awareness, and commitment (see Figure 6). Missions communication technique and awareness (b1 and b2) The beta path (b1) coefficient from communication technique to board awareness is 0.362 while the beta path (b2) from communication technique to

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Figure 6. PLS structural equation model

management awareness is 0.294. These results support the notion that the selected mission communication techniques aid in raising awareness of the mission statement for both the board members and senior management. Furthermore, the magnitude of this impact is relatively higher for boards. The communication technique construct, however, was not found to have any direct impact on the measure for member commitment to the mission.

Involvement and awareness (b3, b4 and b5) The beta path (b3) coefficient from board involvement to board awareness is 0.441, while the beta path (b4) from board involvement to management awareness is 0.128. These results support the notion that involvement with the mission development process by the board is important in raising the board’s awareness of the mission statement. Similarly, when the board is involved in developing their organization’s mission, it positively impacts management’s continuing and current awareness of the mission – though this latter relationship is significantly weaker. In contrast, the beta path (b5) coefficient from management involvement to management awareness was found to be just 0.158, while the beta path from management involvement to board awareness was neither substantive nor significant. Therefore, while management’s involvement in the mission development process appears to encourage their continuing awareness of the mission, it does not appear to have any effect on the board’s current awareness.

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Antecedents to commitment (b6, b7 and b8) The beta path (b6) coefficient from management involvement in mission development to members’ commitment to the mission was established to be 0.139, while a beta path from either board involvement to commitment or management involvement to board awareness did not exist. What this suggests is that, while the commitment of an organization’s members to the mission statement can be directly supported by the management’s involvement in the mission development process, the board’s involvement acts as an antecedent to commitment only indirectly and only through the process of raising its own awareness (b3 and b4). Following that, there are substantive and significant paths from both board awareness ðb7 ¼ 0:150Þ and management awareness ðb8 ¼ 0:173Þ to members’ commitment to the mission. Commitment to performance (b9) The beta path (b9) coefficient from individuals’ commitment to the mission statement and performance was 0.583. This is not at all surprising since it replicates the findings of a previous study by Bart et al. (2001). But, the findings continue to underscore the tremendous impact and important role that member commitment to the mission continues to have and to play respectively in terms of enhancing an organization’s performance. Discussion There are a number of important and significant findings which have materialized from the current study. Boards’ awareness of their organization’s mission The findings from Figure 3 suggest that directors and their boards appear to be relatively aware of their organization’s mission – though it was somewhat lower than management’s. Only a small percentage of respondents indicated that their board was “somewhat aware” of the mission and very few stated that there was no awareness at all. Nevertheless, for the most part, there were still a large number of directors who were not highly or fully aware of their organization’s mission. Therefore, the question remains: should they be? In this regard, path analysis results are unequivocal. Continuing board awareness of the mission – whereby directors “know, understand and remember the mission” – is an important and significant contributor to having individuals throughout the organization commit to it. The more aware the boards are of their organization’s mission, the greater their organizational members’ commitment to it will be. Moreover, directors’ awareness of the mission is equivalent in impact (with respect to members’ commitment) in terms of both management’s awareness of the mission and management’s involvement with the mission’s development. Consequently, boards cannot afford to be complacent when it comes to their organizations’ mission and their continuing and current awareness of it.

This is a thought-provoking observation. It suggests that the days of boards being entertained every now and then with PowerPoint presentations of the company mission, while the lobster sandwiches are passed around, are over. Boards must accept that the mission statement is a valuable and important tool in helping to set the strategic direction and positioning of the organization. It should be the corner-stone of every organization’s strategic plan. Given this importance, it cannot be given short shrift once it has been developed and introduced to the organization. Because every mission also needs the continuing commitment and support of all the organizational members if it is to be ultimately achieved, directors have an ongoing responsibility to keep themselves aware of it as well. One obvious way in which they can help do this is to make sure that the mission statement is a part of each board meeting and a part of every board discussion. Directors must refer to their organizations’ mission regularly (not just in a crisis) and use it to test management’s ability to become and remain focused. Having the mission as part of every “board package” would certainly assist in this regard. So would memorizing it in certain circumstances. Directors also need to be assured that the mission is being achieved and that there is accountability for its implementation. This, in turn, suggests that there must be some sort of mechanism in place to measure the organization’s progress against the mission. When actions such as these are taken, directors will help keep their organizations’ mission alive not just for themselves, but for the rest of the gang as well. (Please note, though, that additional comments on enhancing board awareness are being reserved for the following two sections.) Boards’ involvement in the creation of their organization’s mission This paper began with the question of whether or not boards should be involved in the development of their organization’s mission. Unlike the previous discussion on board awareness, the findings of Figure 3 show that involvement by the board of directors in their organization’s mission creation process is generally not a well accepted activity and generated the highest percentage of responses in the category for “not at all”. Whereas 80 percent of the respondents perceived their senior managements to be highly involved in developing their organizations’ mission, only 47 percent believed this to be the case for the board. Moreover, informal conversations with established and senior directors have suggested that board tradition typically dictates that the role of the board vis-a`-vis mission is for “management to propose and for the board to dispose.” The current findings, however, would challenge this viewpoint. Recall that the discussion in the previous section established the pivotal role that board awareness of the mission plays in terms of enhancing organizational commitment to the mission. The results from path analysis in Figure 6, however, have demonstrated the critical importance of the board’s involvement

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in developing the mission if full board awareness of the mission is to be achieved. Indeed, of all the antecedent measures in the study, it was board involvement which obtained the strongest beta (b) score and was the No. 1 driver of board awareness. Moreover, the findings of path analysis show that, while management’s continuing awareness of the mission is also an important consideration in terms of securing organizational commitment to it, that awareness is produced, almost equivalently, from both their own – and the board’s – involvement in mission development. In other words, it takes both the board’s and senior management’s involvement to generate – within the executive ranks – the necessary and continuing knowledge and understanding (i.e. awareness) required to affect members’ commitment to the mission. Interestingly, while management involvement by itself was also found to have a direct influence on organizational commitment to the mission, board involvement did not. Instead the board’s impact on organizational commitment to the mission is “felt” through their ongoing awareness of it. Now this is a provocative notion, since, in the eyes of many individuals, management typically represents and provides, to a greater extent than the board, the pragmatic, ongoing and de facto strategic leadership of the organization. Yet, the results from the current study would argue that directors’ involvement in a mission’s development is a constructive activity on the part of the board and an important contributor to organizational success. Should boards be involved in creating their organization’s mission? The answer would appear to be a definitive “yes”. Directors must now see their role in terms of getting involved in the development of their organization’s mission in order to raise awareness of it for themselves and for management, and raising awareness of the mission for themselves in order to create and influence higher levels of commitment to it throughout the organization. Consequently, the findings should be seen as helping to put to rest the current debate concerning the nature and degree of board involvement in mission development. Boards must get involved and it is wrong for them not to do so. The research findings thus represent, for the first time, a true “best practice” in corporate governance research. The current corporate governance literature needs to be revised to take these results into account. Mission communication and awareness When the various techniques to communicate the mission were analyzed, a number of interesting observation, were made. To begin with, when the relative ranking of the various communication methods (as shown in Figure 4) was reviewed, it appeared that there was no one technique which appeared to be the overwhelming favourite. The annual report appeared to be the most popular – and perhaps the most obvious – place for ensuring the widest possible dissemination of the mission among the various stakeholder populations. After

all, anyone with a serious interest or “stake” in the organization would be sure to see the mission in this document. The employee manual and posters were also seen as logical choices for communicating the mission to employee groups. However, no one technique achieved a usage rating greater than 67 percent and most communication methods could be said to be used only to a moderate extent (mean score range 2.56-2.94) – with the exception of advertisements, which was clearly and indisputably the least favourite technique (mean score 1.84). It therefore came as somewhat of a surprise that, when the communication construct was created, only three communication methods were found to be reliable and valid (i.e. company information kits, company newsletters and other internal documents (such as company strategic and operating plans, budgets, MBO and bonus criteria). Yet, when these results were further dissected and contemplated, they appeared to make considerable sense. For effective communication to take place, a “message” must be sent, received, understood and remembered (Bart, 2002). Accordingly, while annual reports may be the most frequently used document for communicating an organization’s mission, they are not the most effective. This is because they are often not read, not widely read or not completely read. As a result, the mission message, while “sent”, is not necessarily received, understood or remembered. Similarly, employee manuals may – and probably should – contain explicit reference to their organization’s mission. However, how many times has anyone, as employees, ever referred to the mission by quoting it from the company manual? Probably few, if any at all. In contrast, the communication techniques which appear to have a lasting and profound impact in terms of taking a mission message beyond its “sent point” are those which are designed to: . create special attention (i.e. an information kit which is dedicated to explaining the mission and can be used as a reference guide); . create ongoing attention and deal with short attention spans (e.g. company newsletters); and . focus resource allocations (e.g. strategic and operational plans); Thus, when these documents are used, most people pay attention. Furthermore, path analysis confirmed that both the board and management seem to be listening. Indeed, for the board, the communication construct was the second most powerful influencer in terms of its positive impact on board awareness of the mission. Only board involvement with the mission was more important. However, in terms of management’s awareness, results revealed that it was the communication construct which had the most profound impact – almost double that of any other variables! These findings are significant. They show that, in terms of creating continuing awareness on the part of boards with respect to their organizations’

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missions, it is necessary to first and foremost engage them actively and constructively in its development. Involvement begets awareness. To keep them continually aware, various selected communication techniques then need to be deployed. But those techniques will be impotent in terms of their effect if the board has not first made the commitment of time and energy to the development of the organization’s mission. There is no “Viagra” cure when this has not taken place. So, boards need to understand how the timing and sequence of their awareness are created and sustained. Hopefully, this research helps to establish the proper path to be followed. The observations with respect to management awareness of the mission are also intriguing. As with the case of the board, there is no question that management involvement in developing the mission produces a certain level of ongoing awareness. Similarly, one would expect that, when the board is also involved, it acts as a strong signal to management that the mission is more important than might otherwise be found in organizations where the board ignores it. When combined, management’s involvement and awareness have a tremendous effect on the commitment that organizational members have with respect to their mission. But, to sustain management’s interest in the mission and keep their interest in the mission robust, the findings show that it is the communication construct – with its three critical communication techniques – which has the greatest impact. Boards and their managements would do well to ensure that these techniques are being regularly deployed if they are seriously interested in making sure that senior executives do not lose sight of the mission or lose enthusiasm for it. Relentless repetition of the mission message is probably still the only way to ensure that the message is remembered – the last, but essential, component of the rules for effective communication (Bart, 2002). Conclusions If there is one final thought, it is this: boards need to be more involved in developing – and be continuously aware of – their organization’s mission. Board involvement matters. So, too, does their awareness. For too long, there has been a lack of clear guidance with respect to the board’s role in mission. The extant literature is contradictory and confusing. These results, therefore, represent a significant and profound milestone for the literature on corporate governance. The results herein demonstrate and prove “best practice”, while challenging many of the assumptions underlying current board practices in this provocative area. Accordingly, it is recommended that board involvement with a mission’s development – and continuous awareness of it – need to be both recognized formally in an organization’s governance structure (e.g. board charters) and proposed as an amendment to most governance codes currently in force. It is also recommended that, given this new responsibility for mission development, directors need to be sufficiently trained in strategy development so that they can, with management, develop a shared view on what the future of the organization

should be and why it exists. However, to do so effectively, both boards and management need to develop a common language and strategic analysis framework. Recent developments at the newly formed Directors College (a joint venture of the DeGroote Business School at McMaster University and the Conference Board of Canada (see www.thedirectorscollege.com)) should help boards and their managements considerably in this regard. References Arnold, H.J. and Feldman, D.C. (1981), “Social desirability response bias in self-report choice situations”, Academy of Management Journal, Vol. 24, pp. 377-85. Baetz, M.C. and Bart, C.K. (1996), “Developing mission statements which work”, Long Range Planning, Vol. 29 No. 4, pp. 524-31. Barclay, D.W., Higgins, C. and Thompson, R. (1995), “The partial least squares (PLS) approach to causal modeling: personal computer adaptation and use as illustration”, Technology Studies, Vol. 2 No. 2, pp. 285-309. Bart, C.K. (1997a), “Sex, lies and mission statements”, Business Horizons, November-December, pp. 9-18. Bart, C.K. (1997b), “Industrial firms and the power of mission”, Industrial Marketing Management, Vol. 26, pp. 371-83. Bart, C.K. (1997c), “Mission possible”, CA Magazine, September, pp. 33-4. Bart, C.K. (1998a), “A comparison of mission statements and their rationales in innovative and non-innovative firms”, International Journal of Technology Management, Vol. 16 No. 1-3, pp. 64-77. Bart, C.K. (1998b), “Mission matters”, CA Magazine, March, pp. 31-41. Bart, C.K. (1999a), “Making mission statements count”, CA Magazine, March, pp. 37-47. Bart, C.K. (1999b), “Accepting the mission”, CA Magazine, August, pp. 33-4. Bart, C.K. (2000), “Lasting inspiration”, CA Magazine, May, pp. 49-50. Bart, C.K. (2001a), “Measuring the mission effect in human intellectual capital”, Journal of Intellectual Capital Research, Vol. 2 No. 3, pp. 320-30. Bart, C.K. (2001b), “Who’s running the store?”, CA Magazine, August, pp. 22-7. Bart, C.K. (2002), A Tale of Two Employees, Corporate Missions Inc. Press, Hamilton. Bart, C.K. (2003a), “Innovation, mission statements and learning”, International Journal of Innovation and Learning, forthcoming. Bart, C.K. (2003b), “Good governance and intellectual capital”, paper presented at the 24th McMaster World Congress on the Management of Intellectual Capital and Electronic Commerce, Hamilton. Bart, C.K. and Baetz, M.J. (1998), “The relationship between mission statements and firm performance: an exploratory study”, Journal of Management Studies, Vol. 36 No. 6, pp. 823-53. Bart, C.K. and Tabone, J.C. (1999), “Mission statement content and hospital performance in the Canadian not-for-profit health-care sector”, Health Care Management Review, Vol. 24 No. 3, pp. 18-29. Bart, C.K., Bontis, N. and Taggar, S. (2001), “A model of mission statements and firm performance”, Management Decision, Vol. 39 No. 1, pp. 19-35.

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An empirical evaluation of option pricing in intellectual capital Sanjoy Bose and Kok-Boon Oh Graduate School of Management, La Trobe University, Bundoora, Victoria, Australia Keywords Intellectual property, Assets valuation Abstract The investments in intellectual capital by firms in the knowledge economy are a critical driver for growth, profitability and competitiveness. This paper reviews the basic option-pricing models for pricing financial instruments and evaluates their characteristics in relation to their applicability to intellectual property, focusing on two distinct characteristics, i.e. past decisions that influence future technological options, and the inherent uncertainty over future innovation opportunities. The findings in this study include the discovery and confirmation of certain financial characteristics that are important for the successful implementation of the option-pricing methodology in high technology financial planning and management. This paper attempts to summarise the current strand of literature pertaining to the use of option pricing in the intellectual capital-intensive sector by evaluating their strengths and weaknesses, and make recommendations as to how they can be effectively addressed to produce better results in the valuation process.

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 382-395 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487824

Introduction The knowledge economy promotes innovation and provides the foundation for accelerated economic growth in the twenty-first century and is an important driver of technological development that restructures the industrial economy towards the new economy. The accelerated rate of economic growth has modified the traditional structure and institutional basis of the economy and this has been accompanied by by-products of fundamental consequence such as globalisation, the emergence of the knowledge economy, and regional convergences and divergences of economic growth of different countries (Islam et al., 2001; Sheehan and Tegart, 1998). A rapidly changing economy, in which knowledge plays an increasingly important role in restructuring economic activities resulting in strong non-inflationary growth, robust stock market valuations and low unemployment, is evidence of economic progress. In the knowledge economy, intellectual capital has emerged as the key to a firm’s ability to acquire and utilise knowledge-based assets (Bontis, 1999, 2002). Crucial to the process of such acquisitions are capital investments that must be made on a continuous basis. However, the evaluation process for investments in intellectual capital, particularly their valuation, is both difficult and complex. Nevertheless, valuation of intellectual assets is a fundamental necessity for business investments to occur (Oh and Islam, 2001). Thus, we need tools to

determine what these investments are worth in terms of wealth creation. Such Option pricing in tools are particularly important for the knowledge economy, in which firms are intellectual required to make major investments in intellectual property projects, capital particularly in those relating to new technologies, to compete effectively. Methods of valuation that do not map to economic performance would incur financial losses as a result of bad decisions (Ittner and Larcker, 1977). Capital 383 allocations could not be efficient in an environment without appropriate valuation tools, in which ideas could be developed into effective, income-producing products and services, and ensure a continuing stream of cash flow into the future. There are a myriad models for valuing technologies, but one that is deemed particularly credible, meaningful and realistic is the options-pricing model (OPM). The major benefit of this model is that it allows managers to enhance the value of their decision making in relation to capital budgeting for knowledge assets by capturing the flexibilities of creating and preserving options. Its value lies in that it overcomes some of the common problems encountered with traditional models such as the discounted cash flow (DCF) model (Oh and Islam, 2001). OPM and other financial market issues for new applications OPM has traditionally been applied to the valuation of a wide variety of financial instruments and contracts including corporate bonds, futures and insurance policies (Cox and Rubinstein, 1985; Ingersoll, 1987; Mason and Melton, 1985; Smith, 1976). However, its application goes far beyond the more obvious corporate securities and financial derivatives. The recent popularity in the literature on the use of OPM in the valuation of intellectual assets is just another example of OPM as a practical tool in financial applications. Firms make capital investments for the purpose of creating and exploiting profit opportunities. For example, capital investments in research and development (R&D) can eventuate in the creation of patents and new technological inventions that open up those opportunities for further exploitation. Opportunities are, in fact, options. That is, firms have the right but not the obligation to follow up with actions that can lead to increased profitability. Capital investments contain many options, such as the option to defer the investment, proceed with the investment, abandon the investment, or sell the development to date on an “as is” basis. These types of options are commonly referred to as real options. In other words, irreversibility, uncertainty, and the choice of timing alter the capital investment decision in important ways. In such situations, the OPM allows managers to exercise the many options available to them, which is a major advantage compared with other valuation methods available to them.

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Valuation and economic implications of intellectual assets The emergence of the knowledge economy and the difficulties of valuing intangible assets have refocused attention on valuation processes and methodologies (Oh, 2001). The study of knowledge as a key variable for determining value has been given significant attention in economics and finance. Information and knowledge aspects of business have not received the same attention as the trilogy of capital, labour and resources – leading to a situation of uncertainty about the economic impact of information, as a key economic resource, for the exploitation of virtual business or e-commerce. The virtual world is one where many of the conventional constraints of physical economic processes (R&D, manufacturing, distribution and marketing) no longer apply and firms, big or small, can easily compete with anyone in the world. Valuation research is extensive and continually increasing, and is complicated by the emergence of the knowledge economy. Contrary to the conventional economic theory of diminishing returns developed in the nineteenth century, Arthur (1996) advocates the law of increasing returns. The foundations on which the law of increasing returns is based rely on manipulating and exploiting the information and virtual aspects of a business. According to Arthur, increasing returns “are the tendency for that which is ahead to get further ahead, for that which loses advantage to lose further advantage”. This holds true for industries that have no constraints on resources, such as high technology and knowledge-based industries. A business consists of both the physical and virtual and, while the physical may be subject to constraints, the virtual is not. The criteria that define firms subject to increasing returns are those that have made high investments in information systems in their operations (Arthur, 1996). Firms with new technologies, product development ideas, a defensible position in fast-growing markets, or access to potential new markets are considered to own valuable opportunities. For some companies, opportunities are the most valuable things they own because they provide possible avenues for future cash flows. Investment opportunities are commonly encountered with the ensuing valuation problem, and should be considered as possible future operations. How much to spend on R&D (an investment decision problem in the knowledge economy), at present or in the future, or the kind of R&D expenditure that the firm should be making, are decisions involving the valuation of investment options. The decision to make spending commitments creates, not cash flow from operations, but the opportunity to invest again later, depending on market conditions. For example, marketing expenditures that appear to have the same characteristics: spending to create a new or stronger brand probably has immediate pay-off, but it also creates opportunities for brand extensions later. The opportunity may or may not be exploited ultimately, but it is valuable nonetheless (Luehrman, 1998a, b). The absence of a formal process for the valuation of intellectual assets often gives rise to personal, informal procedures that can produce incongruent decisions. Managers with political power within an organisation may promote

opportunities that they regard as valuable, often resulting in over-investment Option pricing in in poor opportunities and under-investment in good ones. Reality appears to be intellectual more complicated and depends a great deal on how managers are evaluated capital and rewarded (Kester, 1984). The question then arises “how do corporations typically evaluate opportunities?” A common approach is not to value them formally until they mature to the point where an investment decision can no 385 longer be deferred. At that time, they join the queue of other investments under consideration for funding. This approach invites criticism as being short-sighted, because it leads companies to undervalue the future and, hence, to under-invest. Some companies use a formal DCF-based approval process, but evaluate strategic projects with special rules. One such rule assigns strategic projects a lower hurdle rate than that assigned to routine investments to compensate for DCF’s tendency to undervalue strategic options. Unfortunately, in many cases, the DCF model’s negative bias is not merely overcome but overwhelmed by such an adjustment. Once again, over-investment can occur in practice, where theory would have managers worrying about under-investment. Another special rule evaluates strategic opportunities off-line, outside the routine DCF system. For better or worse, experienced executives make judgement calls based on heuristics. Sometimes that works well, but the best managers back up their judgements with sound analyses, where possible. In general, the right to start, stop, or modify a business activity at some future time is different from the right to operate it at present. A specific decision, i.e. whether or not to exploit the opportunity, has yet to be made and can be deferred. The right to make the decision optimally is valuable, that is, to do what is best when the time comes. A sound valuation of business opportunity captures its contingent nature: “If R&D proves that the concept is valid, we will go ahead and invest.” The unstated implication is that “if it doesn’t, we won’t” (Hull, 1993). Alternatives for intellectual assets investment An option is a contract giving its owners the right, but not the obligation, to buy or sell, an underlying asset at a fixed price on or before a given date. The buyer uses the option only if there is a financial value in doing it. If there is no value in exercising the option, it would be left to expire. The most widely used model for option pricing, the binomial model (Cox et al., 1979) based on the geometric Brownian motion model, is much more generalised than the B&S model (Black and Scholes, 1973). However, the binomial model does have its limitations in that all sample paths that lead to the same node in the tree have similar risk-neutral probability, volatility – whether it is subjective, objective or realised is indistinguishable, and at the limit the continuous-time sample path is not differentiable at any point. The binomial pricing model can be extended to derive a continuous time equivalent

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B&S model by keeping the time constant and dividing it into more binomial tree’s nodes until the interval between the nodes becomes shorter and shorter: at the limit, we obtain a continuous stochastic process. The B&S model assumes a smooth log-normal distribution while the binomial model is jagged. The binomial model is often used for US-style options where an early exercise feature exists. The most common type of option is a call option, which gives the owner the right to buy an asset at a fixed price during a particular time period. This is analogous to exercising the option to make the investments in a new technology after due consideration of all factors about the project. The price of a call option has been described as a function of five variables (Black and Scholes, 1973). These are: (1) current share price; (2) the exercise (or striking) price; (3) the risk-free rate of return; (4) the time to maturity; and (5) the variance of the share price. Black and Scholes (1973) derived a formula for pricing call options, which is referred to as the B&S options-pricing model, in which they asserted that the price of an option is a function of the five variables stated earlier: C 0 ¼ S 0 N ðd 1 Þ 2 Ee 2rf t Nðd2 Þ pffiffiffiffiffiffiffi d1 ¼ ½lnðS 0 =EÞ þ ðrf þ 1=2s 2 Þt
= s 2 t d2 ¼ d1 2

pffiffiffiffiffiffiffi s 2t

where N(d) ¼Probability that a standardised normally distributed random variable will be less than or equal to d; s 2 ¼Variance (per year) of the continuous return on the stock; t ¼ Time (in years) to expiration date; and rf ¼Continuous risk-free rate of return (annualised). The formula is complicated but the most practical (Ross and Westerfield, 1988) and the attraction of the formula is that four of the parameters are observable: the share price, the exercise price, the risk-free rate of return, and the time to maturity. Only the variance of the share price parameter must be estimated. This aspect of the OPM makes it practical for managers to use it to price various business opportunities, including capital projects.

Companies make conscious investments on an ongoing basis for acquisition Option pricing in of assets, both tangible and intangible, for the purpose of creating and intellectual exploiting profit opportunities for the future. In a knowledge economy, it is capital important for firms to make investments in R&D for the purpose of acquiring patents and trade-marks. At each stage of the development, they are faced with several avenues of opportunities: to proceed with building plants for producing, 387 or sell the technology, or indeed abandon the project, among others. In this regard opportunities are options, that is, the firms have the right, but not the obligation, to take some course of action from the alternatives available, to maximize profits for the future. An option is an asset with pay-offs that are contingent on the value of an underlying asset. Investments in intellectual assets, particularly those involving technological innovations, have two fundamental properties: past decisions that influence future technological options, and an inherent uncertainty over future innovation opportunities (Narayanan, 2001). OPMs have evolved to account for these two characteristics. Thus, a firm facing an opportunity to invest in intellectual capital holds an option: it has the right, but not the obligation, to make the investments at a future time to ensure cash flows from the project. The crucial decision to invest or not will be made after some uncertainty is resolved or when time runs out. In financial terms, this opportunity is analogous to an option. An option provides the right, but not the obligation, to buy or sell something at a specific price on or before some future date. A call option on a stock gives an investor the right to buy that stock at a predetermined price (strike price) and at an agreed time (expiry). If the market price of the stock is currently higher than the strike price, the option clearly is valuable (in-the-money). If the stock is worth less than the strike price, the option has no intrinsic value (out-of-the money), but may still be valuable if the option has not expired, and if the stock price rises in the future. Corporate opportunities have the same feature: “if R&D prove that the concept is valid” is analogous to “if stock price rises in the next few months”. Similarly, “we’ll go ahead and invest” is analogous to “we’ll exercise the option” (Hull, 1993). Knowledge assets The investment opportunities available to a firm may include opportunities to invest in real assets under potentially favourable conditions at some future point in time. These opportunities are called real options, and are analogous to a call option where the underlying asset is the project. When considering the investment opportunities available to the firm, managers should pay attention to the options, which are included within these opportunities. These alternatives in respect of future investment opportunities, representing real options for the firm, are options to invest, expand and/or abandon existing projects. Therefore, the present value of a project on which the firm has an option is analogous to the variable “current share price” in the B&S model.

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Figure 1.

Similarly, the “expected (striking price)” is analogous to the outlay required to undertake the project; “the time to maturity” is analogous to the time left before the decision to invest in the project must be made; and the “variation of the share price” is analogous to the uncertainty associated with the project. Luehrman (1998a, b) states that investments in new technology projects should be seen as a decision-making strategy from the perspective of taking and exercising options. In one of the articles in the series, he illustrates how such options relate to the B&S model. This supported the earlier example provided by Dixit and Pindyck (1995) that investment opportunities were really analogous to call options, and should be valued as such. These investment opportunities are discretionary, and whether or not they are undertaken depends on uncertain future conditions. Bishop et al. (1993) have identified real options found in investment opportunities, which can easily be applied for valuation of intellectual capital projects and include the following: . The option to make follow-on investments (expansion) means that a firm should accept the negative NPV of the initial project to obtain the higher NPV in the future. This is depicted in the pay-off profile of an equivalent call option in Figure 1 (Damodaran, 2001). The follow-on cost of expansion for the project is represented by the strike price of the call option. This project expansion option converts the traditional static NPV to a dynamic option-based NPV and makes an ostensibly unprofitable project worth considering. . The option to wait before investing (defer). This is a call option on the investment project. The underlying goal is to recognise that having an option to an investment project in technology in high-volatility situations is an opportunity to spend a little and learn a little, deferring decisions of major investments until there is much higher certainty of success (Razgaitis, 1999). The strike price of the option is the initial investment in the project and the life of the option is the period prior to which the firm

.

can make a decision on the project. This case is analogous to a US call Option pricing in option. This situation is depicted in Figure 2 (Damodaran, 2001). intellectual The option to abandon the investment project. This overcomes the capital problem with a DCF approach, which assumes that all investment money will be spent, regardless of intermediate outcomes. In reality, what actually happens is that an investor in a technology project can terminate 389 a project early if it looks as if the risks are going to be higher than anticipated, thereby saving some or much of the investment that would have been committed and lost. In contrast with the options to expand or defer, the option to abandon is equivalent to a US put option, as in Figure 3 (Damodaran, 2001).

Evaluation of the options pricing approach The options approach to capital investments for intellectual capital projects can help firms value flexibility in their expansion and asset renewal plans. In the

Figure 2.

Figure 3.

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ever increasing volatility of the business environment, it is important for managers to weigh and value their options, rather than depend on the DCF models, which assume a reversibility in the capital-budgeting process. Damodaran (2002) stated that a corporate investment opportunity as an option is the ability to discern a simple parallel between project and option characteristics. The potential investment to be made corresponds to an option’s exercise price. The operating assets that the company would own, assuming it made the investment, are like stock that one would own, exercising a call option. As stated earlier, the length of time that the company can wait before it has to decide is like the call option’s time to expiration. Uncertainty about the future value of the operating assets is captured by the variance of returns on them; this is analogous to the variation of stock returns for call options. The analytical method is to perform this mapping between the real project and a simple option and, if the simple option captures the contingent nature of the project, then by pricing the option we gain some additional, albeit imperfect, insight into the value of the project (Slywotzky, 1996). An option is valuable and its value clearly depends on the value of the underlying asset. In considering opportunities, it is obvious that cash, time value, and risk are all important, but each of those factors enters the analysis in two ways. The two types of cash flows that are important are cash from the business, and the cash required to enter it, should the option be exercised. Time matters in two ways: the timing of the eventual flows and how long the decision to invest may be deferred. Similarly, risk matters in two ways: the riskiness of the business, assuming that one invests in it, and the risk that circumstances will change (for better or for worse) before managers have to decide. OPM handles simple contingencies better than standard DCF models and has been regarded as a promising approach to valuing business opportunities since the mid-1970s (Narayanan, 2001). However, real businesses are much more complicated than pure and simple puts and calls. A combination of factors – big, active competitors, uncertainties that do not fit neat probability distributions, and the sheer number of relevant variables – makes it impractical to analyse real opportunities formally. As a result, option pricing has not realized its full potential yet for being used as a tool for valuing opportunities (Narayanan, 2001). Some of the general criticisms of the B&S model are sourced in the underlying assumptions, which appear to be severe (Curran, 1988). They are: . there is a risk-free rate known and invariant over the life of the option; . there are no transaction costs and no taxes; . the market functions continuously; . the stock pays no dividends; . the option cannot be exercised until maturity (European option);

.

. .

the stock price is “log-normally” distributed (the stock prices are a Option pricing in log-normal distribution that represents a continuous function of time); intellectual short sales of the stock can be transacted without restrictions; and capital there are no take-overs or other events that can end the option’s life early.

However, a number of characteristics about this model are clearly noticeable. First, an investor’s risk aversion does not affect value, and the formula can be used by anyone, regardless of his or her willingness to bear risk. Second, the formula does not depend on the expected return on the stock. Investors with different assessments of the stock’s expected return will nevertheless agree on the stock price, and that price already balances different investors’ divergent views. Thus, the B&S model should be viewed only as a conceptual framework, and must be modified in practice. Curran (1988) observed that the calculus of the hedge ratio justifying the risk-free rate on the combined portfolio implies that the position will be altered continuously because of changes in underlying variables. Real-world transaction costs involved in altering the portfolio daily, if not continuously, would be prohibitive. As stated earlier, transaction costs, of course, are assumed away in the model. Second, the distribution of stock prices often exhibits discontinuities (jumps). A continuous function, even as an approximation, may be inaccurate. Third, the model does not allow for dividends and taxes; and fourth, the European option differs from the US option: the latter can be exercised anytime before the expiration of the maturity date. Therefore, while none of these problems is insurmountable, they weaken the model as an applied tool. Bishop et al. (1993) also state that there are several problems in applying existing OPMs to real options. The present value of the project, the required outlay and the time left before the investment decision must be made, may not be certain for real options. The required outlay and the time left before the investment decision must be made will vary according to the actions of the firm’s competitors. Real options may not be proprietary; that is, the firm may not be the only one able to exercise the option, such as the development of microcomputers. According to Curran (1988), the problem of using past measures of variability as being representative of future variability can yield a value for a call option not indicative of the future. When the value is compared with the market price of the option and the two differ, the question arises whether the model is wrong or the variance has changed. Past data may not be relevant. Alternatively, even though past data may be indicative of the future, the options market may be inefficient. Finally, the options market may be efficient and the variance may be correct, but the model is an incorrect explanation of how options are priced.

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Modifying OPMs for valuation of knowledge assets While OPMs have gained increasing credibility as tools for valuation of financial and real options, criticisms related to the underlying assumptions have remained topical. Yet, in spite of these criticisms, there are sufficient conditions to make them (the models) credible. If they do not hold, a variation sometimes does. For example, Damodaran (2002) uses the expected cash inflows from introducing the product now, and the strike or exercise price of the stock is replaced with the present value of the costs of developing and introducing the product now, as represented by the following equation: V ¼ Se 2yt N ðd 1 Þ 2 Ke 2rt N ðd2 Þ d1 ¼

lnðS=KÞ þ tðr 2 y þ s 2 Þ pffiffi s t pffiffiffiffiffi d 2 ¼ d 1 2 st

where S ¼ the present value of expected income from introducing the product now; K ¼ the present value of costs of developing and introducing the product now; t ¼ 1/years of market viability or patent life; and r ¼ risk-less rate corresponding to the patent life or “y”. Other modifications to the original B&S model include the replacement of the time to expiration of the option with the market life of the patent, a factor representing (1/patent life) is included and the risk-less rate that corresponds to the patent life is used. Thorpe (1973) examined the short sale constraint, while Leland (1985) allowed for transactions costs. In their research, Ingersoll (1976) and Scholes (1976) considered the effects of differing tax rates on capital gains and dividends. In all cases, it was shown that the basic model worked well for valuation purposes. Long-lived opportunities in volatile business environments are so poorly handled by DCF valuation methods that an option-pricing analysis does not have to be very sophisticated to produce worthwhile insights. A pragmatic way to use option pricing is a supplement, not a replacement, for the valuation methodology already in use. The extra insight may be enough to change, or at least seriously challenge, decisions made on implied traditional DFC analyses. The goal in intellectual capital valuation should be to complement, not replace, existing methods. Therefore, managers would prefer a tool that can use financial inputs and outputs that are common with DCF analysis. The B&S model would be a logical choice because it is the simplest and most versatile of the alternative models. A mapping process between the B&S variables and project characteristics is usually feasible. Even though the model contains five

variables, there is an intuitive way to combine these five into two parameters, Option pricing in each with a logical, managerial interpretation (Razgaitis, 1999). This intuitive intellectual process allows a manager to create a two-dimensional map, which is much easier capital than creating one with five variables. Finally, the B&S model is widely available in commercial software, which means that, if a manager can synthesise the comparable option, a computer can price it quite easily. The crucial skills for 393 managers are the knowledge of how to recognise real options, and how to synthesise them for using with the OPMs. The inputs for real options compared with a financial option are shown in Table I (Trigeorgis, 1996). The similarity between real and call options on stock provides the basis for evaluating intellectual property projects or assets by scrutinising the input variables, i.e. cash flow uncertainty, cost of project for expansion and risk-free rate. Future research and conclusion Increasingly, OPMs are being applied to a variety of valuation problems considerably distant from their original intention, which was to value financial contracts and stock options. It is clear that the fundamental underlying concept can be extended to other investments, such as those in new technologies, intellectual capital project, and a range of financial market issues. OPMs capture managers’ flexibility in capital investment processes, such as the option to defer, expand, abandon or alter a capital investment or a contingent decision. R&D projects are good examples of investments that are likely to open the door to future opportunities, which, if exercised, will provide the firm which additional options as well as generating cash flows. However, modifications will be necessary in order to make them workable. In spite of the problems associated with OPMs, they provide a sound conceptual framework for application to valuation problems in respect of new technologies, and intellectual capital assets. Importantly, the OPM has been applied to a wide variety of financial instruments and contracts including corporate bonds, futures, variable rate mortgages, insurance, and investment-timing advice. Other applications of option-pricing techniques have been in the areas of corporate pension plans and the implicit insurance in government loan guarantees, valuation of market timing advice, and the examination of the efficiency of dynamic portfolio strategies such as contingent immunisation (Ross and Westerfield, 1988). Call option on a stock

Real option on a project

Current price of stock Exercise price Time to expiration Stock volatility Risk-less interest rate

Gross PV of expected cash flow Investment cost Time available to make decision Project value uncertainty Risk-less interest rate

Table I. Comparison between inputs of a call option and a real option

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What is clear is that the realm of applications of option-pricing techniques goes far beyond the more obvious corporate securities where it was primarily used. It has become an important element in the valuation of financial contracting and a practical tool in widespread applications in the fields of economics and finance. Thus, notwithstanding its weaknesses, it provides a sound conceptual framework for valuing investments in new high technology projects, the acquisition of intellectual assets, and a wide variety of financial contracting. Further research in this area will attempt to value new technology projects in several industries using option-pricing techniques, and compare them with the values derived from using other valuation models. Where substantial variances occur, econometric and statistical tests will be carried out to determine their causes.

References Arthur, W.B. (1996), “Increasing returns and the new world of business”, Harvard Business Review, July-August, pp. 99-109. Bishop, S.R., Crapp, H.R., Faff, R.W. and Twite, G. (1993), Corporate Finance, 3rd ed., Holt, Rhinehart & Winston, Sydney. Black, F. and Scholes, M. (1973), “The pricing of options and corporate liabilities”, Journal of Political Economy, Vol. 81, pp. 637-54. Bontis, N. (1999), “Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field”, International Journal of Technology Management, Vol. 18 No. 5-8, pp. 433-62. Bontis, N. (2002), World Congress of Intellectual Capital Readings, Butterworth-Heinemann-KMCI Press, Boston, MA. Cox, J.C. and Rubinstein, M. (1985), Options Markets, Prentice-Hall, Englewood Cliffs, NJ. Cox, J.C., Ross, S. and Rubinstein, M. (1979), “Options pricing: a simplified approach”, Journal of Financial Economics, pp. 229-63. Curran, W.S. (1988), Principles of Corporate Finance, Harcourt Brace Jovanovich, San Diego, CA. Damodaran, A. (2001), “The promise and peril of real options”, Research Paper, Stern School of Business, New York, NY. Damodaran, A. (2002), Investment Valuation: Tools and Techniques for Determining the Value of Any Asset, 2nd ed., Wiley, New York, NY. Dixit, A.K. and Pindyck, R.S. (1995), “The options approach to capital investment”, Harvard Business Review, May-June, pp. 105-15. Hull, J.C. (1993), Options, Futures, and Other Derivative Securities, Prentice-Hall, Newark, NJ. Ingersoll, J.E. (1976), “A theoretical and empirical investigation of the dual purpose funds: an application of contingent-claims analysis”, Journal of Financial Economics, Vol. 3 No. 1/2, pp. 83-123. Ingersoll, J.E. (1987), Theory of Financial Decision Making, Rowman & Littlefield, Totowa, NJ. Islam, S., Billington, N. and Oh, K.B. (2001), “Trade, finance and global economic growth: an optimal growth model and global growth prospects”, paper presented at the European Trade Study Group 2001 Conference, Brussels, 14-16 September.

Ittner, C.D. and Larcker, D. (1977), “Measuring the impact of quality initiatives on firm financial performance”, in Fedor, D.B. and Gosh, S. (Eds), Advances in the Management of Organizational Quality, Vol. 1, JAI Press, Greenwich, CT, pp. 1-37. Kester, W.C. (1984), “Today’s options for tomorrow’s growth”, Harvard Business Review, Vol. 62 No. 2, pp. 153-60. Leland, H.E. (1985), “Options pricing and replication with transactions costs”, Journal of Finance, Vol. 40 No. 5, pp. 1283-301. Luehrman, T.A. (1998a), “Investment opportunities as real options: getting started on the numbers”, Harvard Business Review, July-August, pp. 51-67. Luehrman, T.A. (1998b), “Strategy as a portfolio of real options”, Harvard Business Review, September-October, pp. 89-99. Mason, S.P. and Melton, R.C. (1985), “The role of contingent claims analysis in corporate finance”, in Altman, E.I. and Subramanyam, M.G. (Eds), Recent Advances in Corporate Finance, Richard D. Irwin, New York, NY. Narayanan, V.K. (2001), Managing Technology and Innovation for Competitive Advantage, Prentice-Hall, Newark, NJ. Oh, K.B. (2001), doctoral thesis (DBA), Victoria Graduate School of Business, Victoria University, Melbourne. Oh, K.B. and Islam, S. (2001), “Empirical finance of e-vommerce: a quantitative study of the financial issues of the knowledge economy”, CSES Research Monograph, No. 2/2001, Victoria University, Melbourne. Razgaitis, R. (1999), Early-Stage Technologies – Valuation and Pricing, Wiley, New York, NY. Ross, S.A. and Westerfield, R.W. (1988), Corporate Finance, Times Mirror/Mosby, St Louis, MO. Scholes, M.J. (1976), “Taxes and the pricing of options”, Journal of Finance, Vol. 31 No. 2, pp. 319-32. Sheehan, P. and Tegart, G. (Eds) (1998), Working for the Future: Technology and Employment in the Global Knowledge Economy, Victoria University Press, Melbourne. Slywotzky, A.J. (1996), Value Migration – How to Think Several Moves Ahead of the Competition, Harvard Business School Press, Cambridge, MA. Smith, C.W. (1976), “Option pricing: a review”, Journal of Financial Economics, No. 3, January-March, pp. 3-51. Thorpe, E.O. (1973), “Extensions of the Black-Scholes options model”, Bulletin of the International Statistical Institute, Proceeding of the 39th Session, pp. 522-9. Trigeorgis, L. (1996), Real Options: Managerial Flexibility and Strategy in Resource Allocation, MIT Press, Boston, MA. Further reading Dabek, R.A. (1999), “Valuation of a technology”, paper presented at the Intellectual Property Licensing Seminar, University of Dayton, Dayton, OH, February, available at: www. udayton.edu/ , lawtech/cle99lic-dabek.html (accessed 11 March 2003). Rappaport, A. (1986), Creating Shareholder Value: The New Standard for Business Performance, Free Press, New York, NY. Schumpeter, J. (1934), The Theory of Economic Development, Harvard University Press, Cambridge, MA. Trigeorgis, L. (1993), “Real options and interactions with financial flexibility”, Financial Management, Autumn, pp. 202-24.

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The IC-dVAL approach Ahmed Bounfour Universite´ Marne La Valle´e, Marne La Valle´e, France

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Keywords Resource management, Intellectual capital, Competitive advantage Abstract Over the last five years several frameworks have been suggested for the development of corporate’ competitive advantage, on the basis of their intangible resources. These frameworks are mainly managerially oriented; they require the design of a set of metrics dealing with organisational inputs. Hence the importance of making the link between internal and external perspectives, especially those related to financial performance. Making such a link is the main aim of the intellectual capital dynamic value (IC-dVALw) approach, which integrates four dimensions for measurement – inputs, processes, assets, and outputs – and defines ad hoc metrics for measuring intellectual capital in a dynamic way. This approach is now used at the corporate level in several contexts. It is also under consideration for implementation at the mesoeconomic and even the macroeconomic levels. The paper also presents how such an approach can be used at the country level, especially in Europe.

Introduction The development of intangible resources is an essential issue for companies; it is also a critical issue for public organisations because of its impact on growth and employment. As is the case for companies, public organisations must develop innovative approaches, in particular in the functional “fields”: research and development, systems of education, fiscal policies and public procurement policies. Indeed, the management of intangibles clearly questions public policy at different levels: in its relationship with “productive” sectors and organisations (companies and sectors of activities), but also with regard to the intangible capacity of public organisations themselves. One can even state that the perspective for companies that has been suggested and developed here can also apply to public organisations. For example, one can point out that the development of evaluation and monitoring tools is an important option to be considered. It reinforces the capacity of training and anticipation of public organisations such as the World Bank or the IMF; European institutions; and national or regional administrations. Each of these organisations is now under high policy pressure to increase their policy, output transparency (this is one of the main aims of the policy governance concept in Europe) and reputation building.

Journal of Intellectual Capital Vol. 4 No. 3, 2003 pp. 396-412 q MCB UP Limited 1469-1930 DOI 10.1108/14691930310487833

The microeconomic perspective The recent developments of the strategic management literature underline the growing importance of intangible factors for corporate competitiveness. More generally, various factors explain the growing interest of scholars and analysts in intangibles resources: the strong growth of services activities; the dematerialization of the manufacturing activities themselves; the recognition of knowledge and its infinite combinations as a major source of value creation

within organisations, and the empirical demonstration of the determining character of intangibles (R&D, image, relative quality of the products and services) in the acquisition of durable competitive advantages on the business unit levels (PIMS Associates, 1994). The work of Porter (1980, 1985, 1990) has contributed to the definition and implementation of an interesting analytical framework from which to consider competitiveness. The concept of competitive advantage is at the heart of such a development, on the basis of an analysis of the competitive forces within market structures. However, Porter’s model of the 1980s is now largely challenged by new approaches to competitiveness, especially those focusing on resources – mainly those of an intangible nature – as a main source for competitive advantage. Indeed, as the author has underlined elsewhere (Bounfour, 2000), recent approaches have been developed, focusing on corporate intangible resources, competences and capabilities, as the main lever of creating competitive advantage. In opposition to Porter’s view, these approaches consider the fact that the differences of performance are more important within the individual industries than between industries. Within this approach, we can include different types of research: . approaches based on core intellectual and services competencies (Quinn, 1992); . approaches based on resources – the resource-based view (RBV) (Barney, 1991; Dierickx and Cool, 1989; Grant, 1991, 1996; Itami, 1989; Itami and Roehl, 1987; Penrose, 1959; Peteraf, 1993; Wernerfelt, 1984, 1989) and intangible resources (Bounfour, 1995, 1998a, b, c; Hall, 1993); . approaches based on core competences (Prahalad and Hamel, 1990); . approaches based on knowledge creation dynamics (Nonaka, 1994; Nonaka and Takeuchi, 1995); . approaches based on competences as “organisational routines” (around the work of Nelson and Winter (1982)). All these approaches can be considered as contributions to the foundation of a strategic paradigm for intangibles. The RBV The RBV of the firm is built upon seminal ideas developed by Penrose (1959), who considered the chief determinant of industry structure to be the resources possessed by the firm. Looking at the firms in terms of their resources, it naturally leads to a radical shift from the traditional product/market structure paradigm. There is no unanimity among researchers about the nature and number of resources to be considered. Wernerfelt (1984, p. 172), defines a resource as “anything which could be thought of as a strength or weakness of a given firm. More formally, a firm’s resources at a given time could be defined as those

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(tangible and intangible) assets which are tied semi-permanently to the firm . . . Examples of resources are: brand names, in-house knowledge of technology, employment of skilled personnel, trade contacts, machinery, efficient procedures, capital, etc”. But under what circumstances will a resource lead to high returns over a longer period of time? Wernerfelt (1989) considers competitive advantages in terms of resources (including building barriers to entry for intangibles and not solely for products). For instance, with regard to the bargaining power of suppliers and buyers, as well as the threat posed by substitute resources, different statements could be proposed: if the production of a critical resource is controlled by a monopolistic group, then it will, ceteris paribus, reduce the amount of returns available to the users of this resource (a patent holder versus its licence holder, a good advertising agency versus its client). Dierickx and Cool (1989) stress the importance of building a coherent policy for accumulating strategic intangible assets, especially those of a non-tradable nature (reputation, quality, etc.). In their view, a key dimension of strategic formulation may be identified as the task of making appropriate choices about strategic expenditures (e.g. advertising spending and R&D outlays) with a view to accumulating required resources and skills (e.g. brand loyalty, technological expertise, etc.). In other words, appropriate time paths of relevant flow variables must be chosen to build required asset stocks. Critical or strategic asset stocks are those assets which are “non-tradable, non-imitable and non-substitutable” (Dierickx and Cool, 1989, p. 1506). Sustainability of a firm’s position for a specific asset will then depend on how easily it can be replicated. Different characteristics are therefore considered with regard to this problem of sustainability: time compression diseconomies, asset mass efficiencies, interconnectedness of asset stocks, asset erosion and causal ambiguity. Barney (1991), on the other hand, considers only three resources: physical, human, and organisational. Finally, Grant (1991) considers the following resources: financial, physical, human, technological, reputation and, organisational. Resources are considered as being specific to companies and so non-tradable, non-imitable and non-transferable. Corporate strategy is mainly influenced by the stock of resources available at any particular time. Grant (1996) differentiates between resources and capabilities: resources are an input to the production process and constitute the basis for analysis, whereas capabilities refer to the capacity of a combination of resources to carry out specific tasks or activities. Therefore, capabilities (or competences) are at the basis of establishing competitive advantage. This notion of capability is similar to that of “core competency” developed by Prahalad and Hamel (1990), on the basis of the analysis of NEC’s success factors in information technology and semi-conductors, in comparison with its main competitors (GTE in particular). It can also be related to the concept of “core services competences” suggested by Quinn (1992). The RBV then contributed to the establishment of a new vision of corporate performance, even if some of the developed arguments are not completely new.

The RBV, despite its broad nature, has a simple message for long-term performance: companies have to be considered as a portfolio of resources, tangibles and, more importantly, intangibles. It is these resources that allow the development of competences and therefore the establishment of a sustainable competitive position in the marketplace. This approach seems most suited to the knowledge economy: resources and competences are still “hidden values”, not sufficiently valorised in the marketplace. The main arguments from this literature review are then the following: . a firm’s performance is mainly influenced by its endowment of resources, rather than by its industry’s structure; . firms are heterogeneous with respect to their resources/capabilities endowments; . building (critical) resources may take time; . firms may lack the organisational capabilities needed to develop new competences; . some assets are non-tradable, e.g. tacit knowledge or reputation; . a dynamic and consistent view of intangibles should be developed; . efficient processes have to be implemented, especially those dedicated to combining intangible resources; . a competitive strategy has to be built on firms’ distinctive resources and capabilities. The intellectual capital perspective During the last five years, a set of experiences centred on the measure of intellectual capital (IC) has been initiated. The balanced score-card approach (Kaplan and Norton, 1992, 1993, 1996a, b) has been used in several cases. However, various taxonomies for IC have also been suggested (Bontis, 1996, 1998, 1999, 2001, 2002; Brooking, 1996; Edvinsson and Malone, 1997; IFAC, 1998; Stewart, 1997; Sveiby, 1997). The current practices around the management of intangibles are of two types: those relating to knowledge management (KM), basically as a managerial practice, and those referring more specifically to the measurement and the development of IC. KM is mainly developed around information technologies, whereas IC is more related to financial research and strategic management control. With regard to industrial sectors of applications, several industries are particularly active in both KM and IC including public services, social services, nuclear, aerospace and high-tech industries, to name a few. The IC-dVAL approach The extant literature as well as organisational practice suggested that it is possible to build corporate strategies of IC by integrating a link between the

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financial value of assets and the internal performance of companies (Bounfour, 2000, 2002a, b). From the point of view of the management of organisations, building competitive advantage on the basis of intangibles is mainly ensured via the deployment of a “combinatory function” of these resources in a distinctive and specific way. In other words, the problem is that of the definition of a dynamic approach to corporate competitiveness, starting in particular from the implementation of organisational processes which might be referred to as its routines or patterns of current practices and learning (Teece et al., 1997). Four dimensions In analytical terms, four important dimensions of competitiveness must be integrated (Figure 1): (1) Resources as inputs to the process of production. Tangible resources, investment in R&D, acquisition of technology, etc. The principal point to be considered here is that of the identification of the intangible resources with specific high criticality, and how the level and the mode of exploitation of these resources can be improved by the adoption of specific processes. (2) Processes. It is through processes that the deployment of a dynamic strategy based on intangible factors can really be implemented: processes of establishing knowledge networks, and competences inside and outside the company; processes of combination knowledge; processes of just-in-time for products and services and the whole of the outputs; processes of motivation and training of personnel, etc. (3) The building of intangible assets (IC). These can be built by the combination of intangible resources. Indeed, combining intangible resources can lead to specific results such as collective knowledge, patents, trade marks, reputation, specific routines, and networks of co-operation. For each one of these assets, indicators and methods for valuation can be developed.

Figure 1. The IC-dVAL four dimensions framework

(4) Outputs. It is on this facial level that performance of companies is classically measured, through the analysis of their products and services’ market positioning. Here, one will be interested in indicators such as those relating to market share, quality of products and services, barriers to entry, and establishment of temporary monopolistic positions.

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By integrating these four dimensions, the problem of corporate competitiveness – in the context of the knowledge economy – appears very complex. It should no longer be considered from the only (often static) perspective of market share or industry’s structure. Developing and implementing a set of metrics The deployment of measures is done through an overall architecture of indicators related to items, blocks of items (i.e. resources, processes and outputs), as well as to a global vision of corporate performance, through a synthetic indicator (Figure 2). A set of 25 indicators is included in this framework with organisational performance measured using benchmarking techniques. The overall index of performance (OiP) for the whole company is calculated on the basis of indices. We often use it for the calculation of the dynamic value of the IC. The whole approach has been implemented for dozens of companies and organisations at the European level: large companies, specific lines of activities within companies, as well as public organisations such as town councils. From micro- to meso-/macro-perspectives Over the last few years, several interesting IC initiatives have taken place at the national level (e.g. Sweden, Denmark, The Nordic Project, Israel), but also on a regional level (e.g. the United Nations initiative of benchmarking the Arab region (Bontis, 2002), or the Pacific Islands), with the support of the World Bank, in 1997. Most of these initiatives consisted of analysing existing

Figure 2. Metric model for measuring corporate performance for IC

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data, basically at the input and output level. Bontis (2002), for instance, extended Edvinsson’s approach, with some adaptation to a national context, and developed a structural equation model for national IC development. But we need to go further, especially by focusing on the dynamic dimension of socio-economic performance. Indeed, statistical data are now needed for clusters, communities of practice and sectors of activities, especially at the European level. Table I details the content of each data set. This framework can be used for different public policy dimensions. It has already been used in the assessment of the impact of European RTD programmes. It is also under test for reporting on intangibles in the context of the knowledge economy. Different types of IC are also recommended here for identification and measurement: human capital, innovation capital, social capital, structural capital and market capital. Each of these components is the subject of ongoing research for identification and measurement from the societal point of view. Benchmarking Proxy values were used for benchmarking. A set of metrics has been defined and used along the four elements of the pre-defined framework (see Table I). As was stressed earlier, the objective here is to proceed to a benchmarking of national innovation systems in Europe, in order to determine critical factors of inter-systems learning (Table II). Preliminary results Resource indices (Figure 3) . For public R&D/GDP, Japan is doing better than the USA. But the USA is doing better than the European Union (EU). However, within the EU, Finland is the “best in class”, followed by Sweden and The Netherlands. . For BERD/GDP, Japan and the USA are again better positioned than the EU (average). Sweden and Finland are again better players in Europe. . For venture capital/GDP, we do not have comparable data for the USA and Japan. For this metric, the UK is the best player in Europe. . For new capital/GDP, the USA is doing better than the EU. Within the EU, Finland is the best. Process indices (Figure 4) . Ireland is the best player in Europe for percentage of SMEs innovating in-house. . Denmark is a leading player for percentage of SMEs innovating in cooperation. Therefore, social capital can be considered here as a strong value within this country.

Data set I. Resources (inputs) metrics These are indicators related to measuring companies and economies resources such as: R&D, patents, technology, infrastructure, human resources, information and knowledge (know-why, know-how, know-what, know-whom), software, advertising, market research, vocational training, as inputs (investments) to operators’ activities. Data for two types of metrics are expected to be collected here: (1) Data related to the level of investment in a specific resource – hence the investment in resources indicators, such as human resources, technology resources or information resources (e.g. an expenditure on a market resource study). (2) Data related to the cluster members performance (i.e. how do they perform compared with those best in class. Answering this question necessitates the undertaking of a benchmark exercise). Hence the performance indices. Types of resources considered: human resources, information resources (such as patents or market research); physical resources as well as financial resources are considered as contextual elements.

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Data set II. Processes metrics These are indicators related to measuring defined processes for value creation in the new economy: networking, combining knowledge, virtual organising, alliances, agile organisation, developing routines, developing communities, developing standards, developing new business paradigms, developing communities of practice, developing networks and clustering processes, mobilising human resources, developing financial markets’ trust, and . . . public RTD fund raising, etc. Again two types of data are expected to be collected here: (1) Data related to the level of investment in specific processes, such as a networking process or an internal communication process. Hence the investment in processes indicators. (2) Data related to the cluster members’ performance (i.e. how do they perform compared with those best in class?. Answering this question necessitates the undertaking of a benchmark exercise). Hence the processes indices. Data set III. Outputs metrics Indicators related to measuring defined outputs and performance in the new economy, such as: patents, trade marks, reputation, an increase in turnover, market niches, contractual contacts, communities of use, barriers to entry in specific businesses, increasing net value, etc. Again two types of data are expected to be collected here: (1) Data related to the value for specific output, such as an additional turnover, an increase in market share, a creation of niche due to a first mover advantage. Hence the outputs indicators. (2) Data related to the cluster members’ performance (how do they perform compared with those best in class? Answering this question necessitates the undertaking of a benchmark exercise). Hence the output indices. Data set IV. Assets metrics Indicators related to measuring defined assets, mainly of an intangible nature, in the knowledge economy: human capital (collective routines, knowledge), innovation capital, structural capital (including technology, patents, trade marks, standard software and tools), and market capital (reputation, attractiveness, market niches, standards, etc.). Tangible assets are indicated here as an element of context. All the four types of assets are to be estimated into e, $ or any other currency. This can be done by resorting to traditional financial and economic methods: market-to-book value, turnover multiplier, value of replacement, Tobin Q, etc. Evaluations are carried out at different levels: business unit level, corporate level, group level.

Source: Bounfour (2002b)

Table I. The intangible resources four data sets

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Table II. Metrics used as proxy values for benchmarking EU IC performance

Indicators Resources indices Public expenditures R&D/GDP BERD/GDP Percentage of venture capital/GDP Percentage of new capital/GDP

Year/period 1999 1999 2000 2000

Processes indices Percentage of SMEs innovating in-house Percentage of SMEs innovating in cooperation Percentage of home Internet access Percentage of ICT markets/GDP Percentage of high-tech value added Labour productivity growth – long-term

1996 1996 2000 2000 1997 1991-1999

Output indices Percentage of innovating exports/total sales Unemployment rate Percentage of new-to-market products GDP per capita (PPS) Real GDP growth

1996 1999 1996 1999 1995-1999

Asset indices A – structural capital indices Number of scientific publications per million EPO high-tech patents/population US PTO hi-tech patents/ population

1998 1999 1998

B – Human capital indices Percentage of S&E graduates/20-29-age population Percentage of population with third education Lifelong learning

1999 2000 2000

.

.

.

The USA is doing better than the EU and Japan for percentage of Internet home access. However, within the EU, Nordic countries are outstanding (The Netherlands, Denmark, Sweden). For ICT markets/GDP, the USA is doing better than the EU and Japan. Within the the EU, Finland is the leading player. For hi-tech value added, the USA is the leading player worldwide, followed by Japan and the EU. Within the EU, Ireland and Sweden are the best players.

Output indices (Figure 5) . Sweden is the best player for the ratio: percentage of innovating exports on total sales. . The Netherlands is the best in class for the unemployment rate. On average, the USA is doing better than the EU and Japan.

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Figure 3. Resource indexes

.

.

.

Finland is a good player in new-to-market products, due to Nokia’s success. The USA is the best player for GDP per capita, followed by European Nordic countries (Denmark, The Netherlands, among others). The USA is doing better than Japan and the EU for average annual growth of exports in high-tech products. But within the EU, Finland, The Netherlands and Denmark are excellent.

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Figure 4. Process indices

.

For real GDP growth, the USA is doing better than the EU. Ireland is an excellent player, due to its economic policy, mainly export-oriented; on average, the EU is lagging behind the USA, for most of these indicators.

Asset indices (Figure 6) . The EU is lagging behind the USA for a major ratio: the number of scientific publications per million; . Within the EU, Nordic countries are the best players for this ratio;

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Figure 5. Output indices

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Figure 6. Asset indices

.

.

The same remarks can be applied to two major indicators for patenting: EPO and US PTO indices. For human capital, data attest also to the better performance by Nordic countries, except for one metric: the percentage of S&E graduates among 20-27-age population (the UK is the leading country here).

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409 Average performance indices, national IC indices (Figure 7) On average, we can see that for each of the four dimensions used here Nordic countries are the best in the EU (Figures 7 and 8). Therefore, they appear as those best in class in managing their IC. The question then is to what extent the Nordic countries can be referred to as a benchmark in the European arena or, more specifically, to what extent a process of “learning-by-comparing” can be implemented. This is the main subject of the benchmarking exercise still under way within the EU.

Figure 7. Average performance indices

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Conclusion The four dimensions of the IC-dVAL approach can be used not solely at the microeconomic level, but also at the macroeconomic level, especially in the perspective of benchmarking IC performance. However, data availability poses a problem. Therefore, it is important that a statistical effort be provided for at the meso- or macroeconomic level, in order to achieve a better understanding of national innovation systems, and national performance in the context of the knowledge economy.

References Barney, J. (1991), “Firms’ resources and sustained competitive advantage”, Journal of Management, Vol. 17 No. 1, pp. 99-120. Bontis, N. (1996), “There’s a price on your head: managing intellectual capital strategically”, Business Quarterly, Summer, pp. 40-7. Bontis, N. (1998), “Intellectual capital: an exploratory study that develops measures and models”, Management Decision, Vol. 36 No. 2, pp. 63-76. Bontis, N. (1999), “Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field”, International Journal of Technology Management, Vol. 18 No. 5-8, pp. 433-62. Bontis, N. (2001), “Assessing knowledge assets: a review of the models used to measure intellectual capital”, International Journal of Management Reviews, Vol. 3 No. 1, pp. 41-60. Bontis, N. (2002), “National intellectual capital index: intellectual capital development in the Arab region”, United Nations Development Program Research Initiative, New York, NY, available at: www.bontis.com/research.htm (accessed 11 March 2003). Bounfour, A. (1995), “Immate´riel et strate´gies compe´titives, e´le´ments de proble´matique”, paper presented at the AIMS Fourth Confe´rence, Paris, 2-4 May. Bounfour, A. (1998a), Le management des ressources immate´rielles, maıˆtriser les nouveaux leviers de l’avantage compe´titif, Dunod, Paris. Bounfour, A. (1998b), “Accounting for intangibles and value setting”, paper presented at the 21st Congress of European Accounting Association, Antwerp, 6-8 April. Bounfour, A. (1998c), “Outsourcing of intangibles and corporate performance: some strategic and accounting issues”, paper presented at the 21st Congress of European Accounting Association, Antwerp, 6-8 April.

Bounfour, A. (2000), “Competitiveness and intangible resources: towards a dynamic view of corporate performance”, in Buigues, P., Jacquemin, A. and Marchipont, J-F. (Eds), Competitiveness and the Value of Intangibles, Edward Elgar Publishing Ltd, Paris. Bounfour, A. (2002a), “Measuring intellectual capital’s dynamic value”, Research Monograph, Universite´ Marne La Valle´e. Bounfour, A. (2002b), The Management of Intangibles: The Organisation’s Most Valuable Assets, Routledge, London. Brooking, A. (1996), Intellectual Capital, ITP Press, London. Dierickx, I. and Cool, K. (1989), “Asset stock accumulation and sustainability of competitive advantage”, Management Science, Vol. 35, pp. 1504-13. Edvinsson, L. and Malone, M.S. (1997), Intellectual Capital, Realizing your company’s True Value by Finding its Hidden Brainpower, HarperBusiness, New York, NY. Grant, R.M. (1991), “The resource-based theory of competitive advantage: implications for strategy formulation”, California Management Review, Spring, pp. 114-35. Grant, R.M. (1996), “Toward a knowledge-based theory of the firm”, Strategic Management Journal, Vol. 17, pp. 109-22. Hall, R. (1993), “A framework linking intangible resources and capabilities to sustainable competitive advantage”, Strategic Management Journal, Vol. 14, pp. 607-18. International Federation of Accountants (1998), The Measurement and Management of Intellectual Capital. An Induction, IFAC, New York, NY. Itami, H. (1989), “Mobilising invisible assets: the key for successful corporate strategy”, in Punset, E. and Sweeney, G. (Eds), Information Resources and Corporate Growth, Pinter Publishers, New York, NY. Itami, H. and Roehl, T. (1987), Mobilizing Invisible Assets, Harvard University Press, Boston, MA. Kaplan, R.S. and Norton, D.P. (1992), “The balanced score-card – measures that drive performance”, Harvard Business Review, January-February, pp. 71-9. Kaplan, R.S. and Norton, D.P. (1993), “Putting the balanced score-card to work”, Harvard Business Review, September-October, pp. 134-47. Kaplan, R.S. and Norton, D.P. (1996a), “Using the balanced score-card as a strategic management system”, Harvard Business Review, January-February, pp. 75-9. Kaplan, R.S. and Norton, D.P. (1996b), The Balanced Score-card, Harvard Business School Press, Boston, MA. Nelson, R.R. and Winter, S.G. (1982), An Evolutionary Theory of Economic Change, Belknap Press, Boston, MA. Nonaka, I. (1994), “Dynamic theory of organizational knowledge creation”, Organization Science, Vol. 5 No. 1, pp. 14-37. Nonaka, I. and Takeuchi, H. (1995), The Knowledge-Creating Company, Oxford University Press, London. Penrose, E. (1959), The Theory of the Growth of the Firm, Wiley, New York, NY. Peteraf, M.A. (1993), “The corner-stones of competitive advantage: a resource-based view”, Strategic Management Journal, Vol. 14 No. 3, pp. 179-92. PIMS Associates (1994), Building Business for Europe: Evidence from Europe and North America on “Intangible” Factors behind Growth, Competitiveness and Jobs, PIMS, Paris. Porter, M. (1980), Competitive Strategy, Free Press, New York, NY. Porter, M. (1985), Competitive Advantage, Free Press, New York, NY.

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Porter, M. (1990), Competitive Advantage of Nations, Free Press, New York, NY. Prahalad, C.K. and Hamel, G. (1990), “The core competence of the corporation”, Harvard Business Review, May-June, pp. 79-81. Quinn, J.B. (1992), Intelligent Enterprise, Free Press, New York, NY. Stewart, T.A. (1997), Intellectual Capital: The New Wealth of Organizations, Nicholas Brealey Publishing, New York, NY. Sveiby, K.E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-based Assets, Berrett-Koehler Publishers, New York, NY. Teece, D.J., Pisano, G. and Shuen, A. (1997), “Dynamic capabilities and strategic management”, Strategic Management Journal, Vol. 18 No. 7, pp. 509-33. Wernerfelt, B. (1984), “A resource-based view of the firm”, Strategic Management Journal, Vol. 5, pp. 171-80. Wernerfelt, B. (1989), “From critical resources to corporate strategy”, Journal of General Management, Vol. 14 No. 3, pp. 4-12. Further reading Bounfour, A. (1999), “Is outsourcing of intangibles a real source of competitive advantage?”, International Journal of Applied Quality Management, Vol. 2 No. 2, pp. 1-25. Business Intelligence (1998), Creating the Knowledge-based Business, BI Press, London. Clement, W., Hammerer, G. and Schwarz, K. (1998), Measuring Intangible Investment: Intangible Investment from an Evolutionary Perspective, OECD, Paris. Collis, D. (1991), “A resource-based analysis of global competition: the case of the bearings industry”, Strategic Management Journal, Vol. 12, pp. 49-68. Danish Agency for Trade and Industry (1999), Developing Intellectual Capital Accounts, Experiences from 19 Companies, Ministry of Industry and Trade, Copenhagen. Dosi, G. and Teece, D. (1993), “Organisational competencies and the boundaries of the firm”, CCC Working Paper, No 93, Center for Research in Management, University of California Berkeley, Berkeley, CA. Ducharme, L.M. (1998), Measuring Intangible Investments: Introduction, Main Theories and Concepts, OECD, Paris. Lev, B. (2001), “Can corporate knowledge (intangibles) be measured?”, paper presented at the 4th Intangibles Conference, NYU Stern, New York, NY. Porter, M. et al. (1994), “Towards a dynamic theory of strategy”, in Rumelt, R. et al. (Eds), Fundamental Issues in Strategy, Harvard Business School Press, Boston, MA. RCS Conseil (1998), Intangible Investments, The Single Market Review Services, Office for Publications of the European Communities, Luxembourg. Winter, S. (1987), “Knowledge and competence as strategic assets”, in Teece, D. (Ed.), The Competitive Challenge, Harper & Row, New York, NY.

Literati Club

Awards for Excellence Jason Hurwitz, Stephen LinesBill Montgomery and Jeffrey Schmidt Towers Perrin, New York, USA

are the recipients of the Journal’s Outstanding Paper Award for Excellence for their paper

‘‘The linkage between management practices, intangibles performance and stock returns’’ which appeared in Journal of Intellectual Capital, Vol. 3 No. 1, 2002 Jason A. Hurwitz, a senior consultant in Towers Perrin’s New York office, is a member of the firm’s Corporate Innovation function, where he develops analytical tools for measuring intangible assets in corporations. Earlier, he was part of the firm’s Strategy and Organization practice, where he collaborated with leading university research professors to develop intellectual capital derived from intangible asset valuation models, leading to the formation of a joint venture. His client work includes analyzing the competition to derive an R&D strategy for a telecommunications component manufacturer and detailing alternatives for a non-profit organization to create a profitable Internet start-up subsidiary. He holds an MBA in management and finance with honours form Columbia University Business School. His BS in mathematics is from Lafayette College in Pennsylvania, and he studied probability and statistics in Russian at Moscow State University in Russia. Stephen Lines, a Senior Practitioner at Towers Perrin, has over 20 years’ consulting experience for a wide range of industries. His areas of expertise include market and competitive assessment, economic modeling, competitive cost analysis, market entry, growth, cost reduction strategies, and development of acquisition and divestiture strategies. Currently, he is engaged in the development of performance management and investment decision systems for intangible assets. He has consulted for a wide range of industries spanning consumer products, financial institutions, consumer and industrial services and commodity industrial products. He has advised investor groups on long-term economic viability, asset valuation, and potential growth, acquisition and divestiture strategies. In addition, he has built economic models incorporating relative cost positions for systems of manufacturing facilities, quantification of local market trends, and scenarios of existing and expected competitive actions. He received his MBA from the Harvard Business School.

William R. Montgomery, Towers Perrin’s former Energy Practice Leader, now manages the firm’s Oil and Gas sub-practice. His senior executive management experience spanned 14 years of consulting to the energy industry, including responsibilities as Vice President of Global Marine. Additionally, he is past president, North American operations, Gaffney Cline & Associates, the worldwide energy technical consulting firm. He was the first president of Sterling Consulting Group, a Houston-based energy performance measurement consultancy. His consulting has covered upstream performance measurement assignments, business strategy, project feasibility, acquisition analyses and related management issues. Among his US-based consulting assignments are Amoco, ARCO International Oil & Gas Company and Phillips Petroleum Company. Internationally, he consulted for many Australian and Canadian energy companies as well as Japex in Japan, Mobil International and Unocal International. He received an Honours degree in Economics from the University of Michigan and holds an MBA from the Harvard Business School. Jeffrey A. Schmidt is currently the Managing Director for Innovation at Towers Perrin. During his 25 years of consulting and research, he also served on the firm’s Board of Directors, Executive Committee and Leadership Council. Earlier he was Managing Director, Strategy and Organization consulting division. In addition to his work on human capital, he has consulted in business and people strategy, organization design and capabilities, human resource effectiveness, cost reduction/profitability improvement and holistic risk management. He holds a BS in engineering management with honours from USMA, West Point, and an MBA from Harvard University. He has served as an instructor for the Institute of Management Consultants, and has been a member of the Committee on Corporate Development of the Graduate School of Business of the University of Chicago. The primary author and general editor of Making Mergers Work: The Strategic Importance of People, he has published over 24 articles on business performance, and he is a sought-after keynote speaker at many management conferences.

The Edvinsson-Saint-Onge Best Student Paper Award Amount: US$2,000 Theme: Regional or national intellectual capital development Description

Important dates

Much of the extant literature on intellectual capital has focused on the firm level of analysis. However, a burgeoning area of interest poses an important research question: How can we identify, measure and leverage the intellectual capital of nations or regions? Many of the same constructs within firm-level research (e.g. financial capital, human capital and structural capital) have similar conceptualizations for countries. Some nations (e.g. Sweden, Croatia, Israel, Denmark) and regions (e.g. Arab Region) have already ventured forward into this field of research. Although great strides have been made, there is much more opportunity left. For this particular award, submitted papers can be conceptual, theoretical, empirical, experimental, or case studies and will be adjudicated by the five members of the awards committee:

July 31, 2003 – Abstracts due, send via e-mail to [email protected] August 31, 2003 – Invitation of full submission October 1, 2003 – Full paper due – send via e-mail to [email protected] November 1, 2003 – Notification of winner January 14, 2004 – Presentation at World Congress on Intellectual Capital

Dr Nick Bontis, McMaster University, Associate Editor, JIC Hubert Saint-Onge, , Chief Executive Officer Leif Edvinsson, UNIC, Editorial Advisory Board, JIC Rory Chase, Teleos, Editor, JIC Dr Christopher Bart, McMaster University, Chairperson, World Congress on Intellectual Capital

Only students registered in university programs are eligible.

Abstract submission criteria (July 31, 2003) English, 8.5" by 11", 350 words maximum, MS Word attachment (please scan attachment for viruses before sending), include cover sheet (author’s name, affiliation, full address, phone number, fax number, e-mail, title of paper) http://worldcongress.mcmaster.ca

Call for papers 25th McMaster World Congress Hamilton Convention Centre, Ontario, Canada January 14-16, 2004 http://worldcongress.mcmaster.ca Topics include:

1998, 1999, 2000, 2002 and 2003 attracted approximately 3,000 delegates (practitioners, academics and PhD students) from over 40 countries. This year we are planning an even larger event which will include a KM technology expo, a PhD recruiting fair, a CKO forum, a knowledge cafe´, and a special government and non-for-profit stream of best practices. Submissions can be conceptual, theoretical, empirical, experimental, or case studies. All accepted papers will be published in full or in abstract form in a CD of proceedings. Prizes will be awarded for the best conference papers. Selected papers will be published in a Special Issue of the Journal of Intellectual Capital.

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intellectual capital;

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knowledge management;

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corporate governance;

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innovation management;

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intangible assets;

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organizational learning;

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management of new technology;

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human capital;

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corporate portals; and

Instructions

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knowledge behaviours.

Abstracts are due on July 31, 2003 – send via e-mail to [email protected]; Full paper submission due on October 1, 2003: Abstracts must be in English, 8.5" by 11", 350 words maximum, MS Word attachment (please scan attachment for viruses before sending), include cover sheet (first author’s name, affiliation, full address, phone number, fax number, e-mail, co-author’s name/s and e-mail, title of paper and, indicate if the paper is suitable for oral presentation or poster presentation or eligible for both. See conference Web site for further information:

The 25th McMaster World Congress is sponsored by the Management of Innovation and New Technology Research Centre at McMaster University (widely recognized as Canada’s most innovative university!). This international conference is recognized globally as the largest and most prestigious event on intellectual capital. It brings both academic researchers and professional practitioners together to present, discuss and review the latest issues and trends in the field. Last year’s event was covered by several international newspapers, TV and magazine media outlets from over ten countries. The first six events in 1996,

http://worldcongress.mcmaster.ca Academic Program Director, Dr Nick Bontis, www.bontis.com