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Intellectual capital in high-tech firms
Intellectual capital in high-tech firms
The case of Spain Gregorio Martı´n de Castro and Pedro Lo´pez Sa´ez
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Departamento de Organizacio´n de Empresas, Facultad de Ciencias Econo´micas y Empresariales, Universidad Complutense de Madrid, Madrid, Spain Abstract Purpose – The literature shows several intellectual capital models. Nevertheless, there is little empirical evidence about the building blocks that form intellectual capital in practice. The purpose of this paper is to test the widespread categorization of human capital, structural capital, and relational capital with a survey applied to high-technology firms from Spain. Design/methodology/approach – Factor analysis was conducted with a sample of 49 firms (larger than 50 employees). Findings – The results indeed demonstrate the existence of three main components of intellectual capital that, in general, fit the dominant structure proposed by other authors. Research limitations/implications – Before moving into an internationally accepted system for classification and measurement of intellectual capital, future research should seek a geographical and industrial agreement about the main components of this construct. In that direction, our empirical evidence provides only the experience of Spanish high-tech firms; this experience could be different in other countries or industries. Practical implications – In this paper, managers interested in the field can find a useful guidance for structuring an intellectual capital balance sheet, taking the three proposed components as main dimensions, and the items of the survey as a measurement tool for analyzing the intellectual strengths and weaknesses of their firms. Originality/value – Academics can also benefit from this research, taking it as a basis for replication studies about intellectual capital in other countries and/or industries. This article presents one of the first empirical tests of the theoretically accepted components of intellectual capital. Keywords Intangible assets, Intellectual capital, Human capital Paper type Research paper
1. Introduction More than a decade has passed since the publication of the first proposals about the concept and measurement of intellectual capital. So far the literature has provided several intellectual capital models (see Brooking, 1996; Bueno-Campos, 1998; CIC, 2003; Edvinsson and Malone, 1997; Kaplan and Norton, 1992, among others). Nevertheless, the need to adapt theoretical and empirical models to new social and economic trends justifies an effort in improving previous proposals. Empirical evidence is still necessary and empirically supported models for classification and measurement of intellectual capital are not very common. At international level it is accepted that there are three basic components of intellectual capital:
Journal of Intellectual Capital Vol. 9 No. 1, 2008 pp. 25-36 q Emerald Group Publishing Limited 1469-1930 DOI 10.1108/14691930810845786
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(1) human capital; (2) structural capital; and (3) relational capital. In a wide sense, these represent all expressions of a firm’s knowledge stocks. This triple nature of intellectual assets has been revisited by different lines of research are trying to reconcile the concept of intellectual capital (CIC, 2003). In our research, based on the dominant stream, we adopt these basic three components of intellectual capital: (1) human capital, which includes values and attitudes, aptitudes and know-how; (2) structural capital, that contains both organizational and technological elements that pursue integration and coordination within the firm; and (3) relational capital, which gathers the value of the relationships that the firm maintains with external agents (business activity close by or with other more distant social agents). 2. Background: main components of intellectual capital and competitive advantage Although for a long time it has been recognized that economic wealth comes from knowledge assets – i.e. intellectual capital – and its useful application (Teece, 1998), the emphasis on it is relatively new. Managing the intellectual capital of the firm has become one of the main tasks on the executive agenda. Nevertheless, this work is especially difficult because of the problems involved in its identification, measurement and strategic assessment. In this situation, the models of intellectual capital become highly relevant, because they not only allow us to understand the nature of these assets, but also to carry out their measurement. The term “intellectual capital” has been used as a synonym for intangible or knowledge assets since the work of Stewart (1991). The fact of calling it “capital” makes reference to its economic roots, because it was described in 1969 by the economist Galbraith as a process of value creation and as a bundle of assets at the same time. The definition by Bueno-Campos (1998, p. 221) – i.e. “basic competencies of intangible character that allow to create and maintain competitive advantage” – argues how we can tie intellectual capital to the resource-based view (RBV). A joint perspective for intellectual capital (understood as strategic resources and capabilities) led to us to raise its assessment in order to state its own consistency. The different types of intellectual capital represent different types of intangible resources and capabilities. Nevertheless, in spite of their strategic nature, all of these assets would not have the same value for the firm, as suggested by the works of Hall (1992, 1993), Itami and Roehl (1987), Aaker (1989), or Prahalad and Hamel (1990) which emphasize the importance of certain intangibles. Setting this kind of difference can be considered as useful help for strategic management. Such differences can help in making decisions about the actions that the firm must perform and about the implementation of programs that allow protection, maintenance or development of those more valuable intangible assets. Nevertheless, in order to explore the relation between any specific kind of intellectual asset and competitive advantage, a clear identification of the main components of intellectual capital is required.
Several contributions have provided different frameworks for classifying the different components of intellectual capital, as well as for establishing series of indicators for intellectual capital measurement. Thus, according to most theoretical proposals, in a first step, three main components can be found: (1) human capital; (2) structural capital; and (3) customer or relational capital (Kaplan and Norton, 1992; Saint-Onge, 1996; Sveiby, 1997; Edvinsson and Malone, 1997). Nevertheless, a more detailed classification is needed in order to reach a better understanding. In this sense, Brooking (1996) highlights the differences between intellectual property assets (i.e. focused on technological knowledge) and infrastructure assets (focus on organizational knowledge) and gives a broader concept of market assets (which include customer assets). Other intellectual capital proposals, such as CIC (2003), include five components: (1) human capital – makes reference to the tacit or explicit knowledge which people possess, as well as their ability to generate it, which is useful for the mission of the organization and includes values and attitudes, aptitudes and know-how); (2) technological capital – refers to the combination of knowledge directly linked to the development of the activities and functions of the technical system of the organization, responsible for obtaining products and services; (3) organizational capital – the combination of explicit and implicit, formal and informal knowledge which in an effective and efficient way structure and develop the organizational activity of the firm, that includes culture (implicit and informal knowledge), structure (explicit and formal knowledge) and organizational learning (implicit and explicit, formal and informal renewal knowledge processes); (4) business capital – refers to the value to the organization of the relationships which it maintains with the main agents connected with its basic business processes (customers, suppliers, allies, etc.); and (5) 5) social capital – the value to the organization of the relationships which it maintains with other social agents and its surroundings). As can be seen, due to its heterogeneous nature, structural capital is divided into technological and organizational capital. In the same way, relational capital is divided into business and social capital. This more detailed classification allows a better understanding of these types of organizational factors. The Intellectus Model (CIC, 2003) is a good example that theoretical proposals about intellectual capital are becoming more complex and detailed every day. This encourages analytical reflection among managers and chief knowledge officers, but it can also be seen as too extensive a proliferation of criteria and categories of intangible assets. Empirical evidence is thus needed in order to determine the level of aggregation that intellectual capital components must adopt in practice. This is the purpose of this work: to determine the main components or building blocks of an intellectual capital balance sheet. Bearing this aim in mind, we take the three most common components of
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intellectual capital (human capital, structural capital, and relational capital) and test empirically whether this grouping of intangible assets is supported by the evidence obtained from a sample of high-technology firms. 3. Sample and method Taking into account our theoretical proposal, we empirically test the presented simple model of intellectual capital in high-technology firms. With this purpose, we have carried out a survey in firms operating within NAICS 334 (Computer and Electronic Product Manufacturing), 516 (Internet Publishing and Broadcasting), 517 (Telecommunications) and 518 (Internet Service Providers, Web Search Portals, and Data Processing Services) from Spain during 2005. The selection of industries was guided by the purpose of using a homogeneous sample (Rouse and Daellenbach, 1999). From a population of 408 firms, finally 49 firms took part in our survey, so we reached a response rate of 12.09 percent (see Table I for a general description of the fieldwork). Based on previous empirical works (Huselid, 1995; Youndt et al., 2004; Carmeli and Tishler, 2004; Youndt and Snell, 2004; Warn, 2005; Subramanian and Youndt, 2005), the questionnaire employed for the survey included 12 items for measuring different intellectual capital aspects according to the three main constructs that it involves. Four items were devoted to report human capital (HC), three addressed structural capital (SC), and five tried to analyze relational capital (RC). Firms had to answer on a seven-point Likert-type scale, showing their level of agreement about the sentences present in the survey. The 12 items employed in the questionnaire were taken from general insights about the pre-defined components of intellectual capital taken into account (see Table II). The items were ungrouped in the questionnaire, and one of them was reverse coded (“Our relations with suppliers are sporadic and punctual”). These facts ensured attention and sense-making on the part of the respondents. 4. Results A factor analysis was developed in order to identify the main dimensions of intellectual capital for these type of industries as well as their main elements and variables, although in the following paragraphs, as a preliminary approach to the data analysis performed after data gathering, a comment on the descriptive statistics regarding the Research focus
Intellectual capital blocks
Criteria defining sample
High-technology firms From industries NAICS 334, 516, 517 and 518 Located in Spain 50 employees or more Included in the SABI Database 408 firms 12.09 percent (49 firms) Survey Ordinary mail Follow up by telephone Backup with second ordinary mail, FAX, webpage and e-mail SPSS 13.0S for Windows (version 13.0.1)
Sample Response rate Method for data gathering Process for data gathering Table I. Research resume´
Statistical software used
Questionnaire items HC2. Our employees are among the most experienced in the industry HC1. Our employees develop new ideas and knowledge HC3. Our employees do team work HC4. Our employees have a long experience in the firm RC5. Our firm is recognized by external agents (customers, suppliers, competitors, and the general public) as one of the best firms in the industry RC2. Our customers are highly loyal to our firm RC4. Our collaboration agreements are held during long periods of time SC1. Our efforts in creating and sustaining an organizational culture are among the highest in our industry SC2. Our firm develops more ideas and products than any other firm in our industry SC3. We perform a lot of actions to spread our corporate values and beliefs RC3. Our relations with suppliers are sporadic and punctual (R) RC1. Our firm devotes an important part of its budget to funding community and green actions
Mean
SD
5.98 5.76 5.67 5.60
1.089 1.090 1.148 1.286
Intellectual capital in high-tech firms 29
5.52 5.40 5.15
1.355 1.321 1.424
4.98
1.725
4.89 3.91 3.78
1.674 1.756 1.387
2.64
1.844
Notes: R, reverse coded item. Un-reversed mean would be 4.19. Standard deviation remains the same
items of the questionnaire is provided. This analysis allows us to detect the most and less common aspects of intellectual capital that firms possess (see Table II). As can be seen, the items related to human capital show higher means (close to 6 on a scale with 7 as the maximum value). This shows that firms operating in the chosen industries are highly focused on having strong human capital. This data is quite robust, as the low standard deviation figures show. Almost every firm values its human capital as strongly. Employees with high experience in the industry, the ability to develop new ideas and knowledge, as well as experience within the firm and involvement in teamwork appear to be key assets for competing in the industries analysed. The surveyed firms agreed considerably (reduced standard deviations) about recognizing as the next most important in the list of intellectual strengths and assets renown among customers, suppliers, competitors and the general public, effective customer loyalty, and long-lasting collaboration agreements sealed by the firm. All of these issues are tied to relational capital in the fashion of reputation-based and operationally based relationships with the environment. The item “Our relations with suppliers are sporadic and punctual” (RC3) deserves special attention. Its correct mean places it as an intermediate power asset. This is consistent with the literature, which confers less relevance to relations with the suppliers in respect to other external agents such as customers or allies. This is backed by the results obtained, because the items devoted to these agents show higher values as firm strengths than relations with suppliers. When firms assessed their intellectual capital positions, issues tied to structural capital ranked among the less common elements. Organizational culture emerges as the most employed element of internal coherence, but firms differ considerably regarding this issue (see the standard deviation figure). The effective flow of ideas and products delivered to the market is a slightly common asset, but we must take into
Table II. Intellectual capital elements: descriptive statistics
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account that it has been posed in industrial-competition terms. Finally, the relevance of actions for spreading and reinforcing corporate values and beliefs differ considerably for each particular firm (see standard deviations in Table II). In order to end this preliminary descriptive analysis of our results, we must highlight that there are very few firms in the industries studied investing in community and green actions. Funding these actions was posed as an indicator for relational capital focused on community, social and green care agents. The average position in this kind of relation is actually low. After the descriptive statistics, an exploratory factor analysis was carried out in order to identify the factors or latent phenomena that lie in the data about intellectual capital provided by the firms studied. To decide whether factor analysis is an appropriate technique in this case, several preliminary tests are needed: analysis of correlations and communalities, the Bartlett test, and the Kaiser-Meyer-Olkin (KMO) test. Tables III-V show the results of these tests for the set of items contained in the questionnaire employed in the research. As can be seen in Tables III-V, the tests advise performing factor analysis, rejecting the null hypothesis that the correlation matrix is an identity matrix (there are several correlations among the considered variables). Also, the KMO index is above 0.6, so it can be considered acceptable for exploratory studies (such as this one), and factor analysis becomes appropriate. From the factor analysis we obtained four components of intellectual capital. Jointly they explained almost 63 percent of the total variance contained in the original data (see Table VI). The first component found was labeled “experienced and innovative human capital” because it gathered all the items originally developed for measuring this construct, as well as one of the elements initially designed for relational capital. The five items included in this component explained 26 percent of the total intellectual capital of the firm. The element that better characterizes “human capital” is the experience in the industry that employees hold. Nevertheless, experience within the firm also has an important factorial weight. Also, this component of intellectual capital includes the abilities of the employees to develop ideas and new knowledge, and for team-working, as well as the recognition as a leading firm by the external agents (see Table VII for factorial loadings). The second component found in the factor analysis represents 22 percent of the intellectual capital of the firm and includes three elements. It includes the development of new ideas and products as well as organizational efforts in creating and sustaining an organizational culture and corporate social responsibility. These items clearly represent structural capital, and because this component of intellectual capital includes two of the three items originally designed for structural capital, it was named “structural capital”. The third component of intellectual capital found weighted 15 percent of the total variance contained in the original data and was shaped by three items. The strongest of these represented collaboration agreements, showing content clearly tied to relational capital. In this vein, this component also included relations with customers, as well as relations with suppliers. The factorial loadings of three relational capital items in this component, as well as the clear dominance of one of them, led us to label it simply “relational capital”, although it also contained one of the items originally
Sig. (unilaterat)
Correlation
CO1 CR1 CO2 CR2 CR3 CR4 CH1 CH2 CH3 CH4 CR5 CO1 CR1 CO2 CR2 CR3 CR4 CH1 CH2 CH3 CH4 CR5 0.002 0.000 0.270 0.245 0.263 0.354 0.008 0.014 0.004 0.045
1.000 0.415 0.592 0.094 0.105 2 0.097 0.057 0.355 0.329 0.395 0.256
CO1
0.000 0.267 0.449 0.387 0.113 0.439 0.153 0.069 0.135
0.415 1.000 0.714 0.096 2 0.020 0.044 2 0.186 2 0.024 0.158 0.227 0.170 0.002
CR1
0.055 0.463 0.243 0.379 0.196 0.053 0.010 0.035
0.592 0.714 1.000 0.241 0.014 0.106 20.047 0.131 0.244 0.346 0.272 0.000 0.000
CO2
0.055 0.008 0.034 0.138 0.140 0.004 0.010
0.094 0.096 0.241 1.000 0.242 0.359 0.275 0.166 0.165 0.391 0.348 0.270 0.267 0.055
CR2
0.067 0.420 0.273 0.316 0.295 0.368
0.105 2 0.020 0.014 0.242 1.000 0.242 0.033 0.099 2 0.078 0.088 0.055 0.245 0.449 0.463 0.055
CR3
0.055 0.162 0.228 0.246 0.048
2 0.097 0.044 0.106 0.359 0.242 1.000 0.253 0.158 0.119 0.110 0.263 0.263 0.387 0.243 0.008 0.067
CR4
0.000 0.109 0.017 0.000
0.057 20.186 20.047 0.275 0.033 0.253 1.000 0.595 0.188 0.318 0.641 0.354 0.113 0.379 0.034 0.420 0.055
CH1
0.001 0.003 0.000
0.355 20.024 0.131 0.166 0.099 0.158 0.595 1.000 0.453 0.403 0.622 0.008 0.439 0.196 0.138 0.273 0.162 0.000
CH2
0.041 0.002
0.329 0.158 0.244 0.165 20.078 0.119 0.188 0.453 1.000 0.262 0.426 0.014 0.153 0.053 0.140 0.316 0.228 0.109 0.001
CH3
0.256 0.170 0.272 0.348 0.055 0.263 0.641 0.622 0.426 0.519 1.000 0.045 0.135 0.035 0.010 0.368 0.048 0.000 0.000 0.002 0.000
0.395 0.227 0.346 0.391 0.088 0.110 0.318 0.403 0.262 1.000 0.519 0.004 0.069 0.010 0.004 0.295 0.246 0.017 0.003 0.041 0.000
CR5
CH4
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Table III. Correlation matrix (determinant ¼ 0:015)
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SC1 RC1 SC2 RC2 RC3 RC4 HC1 HC2 HC3 HC4 RC5
Kaiser-Meyer-Olkin index Bartlett test Table V. KMO and Bartlett tests
Initial
Extraction
1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
0.634 0.738 0.818 0.585 0.445 0.556 0.732 0.733 0.441 0.505 0.750
Approximate x 2 FD Significance
0.719 131.409 55 0.000
designed for structural capital (see the composition of this component through the factorial loadings shown in Table VII). 5. Discussion and conclusion We want to highlight the contribution of our research to the field of intellectual capital, where empirical works are very scarce. This way, although several proposals about intellectual capital classification, identification and measurement can be found in the literature, this work provides an evidence-driven classification and configuration of intangible assets. Thus, according to the data obtained, the average balance sheet of intellectual capital that could be found in a firm in the high-technology industries of computer and electronic product manufacturing, internet publishing and broadcasting, telecommunications, and internet service providers, web search portals, and data processing services operating in Spain at the beginning of 2005 would show something similar to Figure 1. In this configuration of intellectual capital, human capital appears as the most influential component. It includes the experience, creativity and teamwork of the employees, but when the firm holds a strong position in these areas, an image of a leading firm is projected towards external agents (customers, suppliers, competitors, and the general public) present in the environmental setting. Thus, the quality of the workforce seems to be the main indicator of leadership in the industry. Probably, due to the important knowledge-base of the industries studied, the role of key engineers or experts could determine that “the best people make the best firm”. Structural capital represents the second block of the intellectual capital of a typical firm. The purpose of structural capital is to provide an appropriate context for communication, cooperation, adhesion and identity (Kogut and Zander, 1996). Issues related to innovative behaviors, as well as organizational culture, values and beliefs are
3.550 2.014 1.374 0.923 0.799 0.677 0.470 0.450 0.289 0.233 0.221
32.274 18.312 12.489 8.390 7.265 6.151 4.275 4.091 2.628 2.120 2.005
32.274 50.586 63.075 71.465 78.729 84.881 89.156 93.247 95.875 97.995 100.000
Note: Extraction method: main components analysis
1 2 3 4 5 6 7 8 9 10 11
Component Total
Initial autovalues Percentage of Cumulative variance percentage 3.550 2.014 1.374
32.274 18.312 12.489
32.274 50.586 63.075
Sum of saturation at extraction squared Percentage of Cumulative Total variance percentage 2.873 2.408 1.657
26.116 21.895 15.065
26.116 48.010 63.075
Sum of saturation at rotation squared Percentage of Cumulative Total variance percentage
Intellectual capital in high-tech firms 33
Table VI. Variance explained
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Table VII. Rotated components matrixa
1 HC2 RC5 HC1 HC3 HC4 SC2 RC1 SC1 SC4 RC2 RC3
Component 2
3
0.855 0.819 0.790 0.585 0.544 0.890 0.853 0.724 0.728 0.703 0.662
Notes: Extraction method: main components analysis; rotation method: Varimax normalization with Kaiser; arotation converged after five iterations
Figure 1. Components of intellectual capital obtained from the empirical research
gathered within the label of structural capital, although we have found that investments in green care or community initiatives hold a strong relation to corporate culture and structural capital. This is nothing strange, because when a positive mission and values are stated for the company, probably the best way to legitimize them is with subsequent actions which reinforce the declared principles. Respect for the natural environment and active involvement in the community life are two of the most common aspects that can be included in documents about organizational mission, vision and values, and this explains the configuration obtained for structural capital. Nevertheless, one of the most appealing findings of this research has been the importance of alliances (and its time duration) in the configuration of relational capital, when in others previous proposals “customer capital” was pre-eminent. This shows that certain collaboration agreements deserve special interest. The presence of strategic partners could make the management and nature of this component considerably different from the management of the rest of the relations with environmental agents. Although we have taken into account firms from different industries, or even from different sectors, there are common patterns regarding the possible interactions with key partners. Thus, firms born in a certain industry can learn to operate in another one with the help of an appropriate ally, or simply form alliance networks (Kogut, 2000) to reinforce their competitive position.
We must highlight that the empirically driven model for classifying intellectual capital that has been obtained in this research (see Figure 1) does not differ very much from the three main components that have been defended traditionally and theoretically. Strategic alliances emerge as an important component of the relational capital component, probably due to their relevance in the industries of the sample. References Aaker, D. (1989), “Managing assets and skills: the key to a sustainable competitive advantage”, California Management Review, Vol. 31, pp. 91-106. Brooking, A. (1996), Intellectual Capital. Core Asset for the Third Millennium Enterprise, International Thomson Business Press, London. Bueno-Campos, E. (1998), “El capital intangible como clave estrate´gica en la competencia actual”, Boletı´n de Estudios Econo´micos, Vol. 53, pp. 207-29. Carmeli, A. and Tishler, A. (2004), “The relationships between intangible organizational elements and organizational performance”, Strategic Management Journal, Vol. 25, pp. 1257-78. CIC (2003), Modelo Intellectus: Medicio´n y Gestio´n del Capital Intelectual, Centro de Investigacio´n sobre la Sociedad del Conocimiento (CIC), Madrid. Edvinsson, L. and Malone, M. (1997), Intellectual Capital. Realizing your Company’s True Value by Finding its Hidden Brainpower, HarperCollins, New York, NY. Hall, R. (1992), “The strategic analysis of intangible resources”, Strategic Management Journal, Vol. 13, pp. 135-44. Hall, R. (1993), “A framework linking intangible resources and capabilities to sustainable competitive advantage”, Strategic Management Journal, Vol. 14, pp. 607-18. Huselid, M. (1995), “The impact of human resource management practices on turnover, productivity, and corporate financial performance”, Academy of Management Journal, Vol. 38, pp. 635-72. Itami, H. and Roehl, T. (1987), Mobilizing Invisible Assets, Harvard University Press, Cambridge, MA. Kaplan, R. and Norton, D. (1992), “The Balanced Scorecard – measures that drive performance”, Harvard Business Review, Vol. 70, pp. 71-9. Kogut, B. (2000), “The network as knowledge: generative rules and emergence of structure”, Strategic Management Journal, Vol. 21, pp. 405-25. Kogut, B. and Zander, U. (1996), “What firms do? Coordination, identity, and learning”, Organization Science, Vol. 7, pp. 502-18. Prahalad, C. and Hamel, G. (1990), “The core competence of the corporation”, Harvard Business Review, Vol. 90, pp. 79-91. Rouse, M.J. and Daellenbach, U.S. (1999), “Rethinking research methods for the resource-based perspective: isolating sources of sustainable competitive advantage”, Strategic Management Journal, Vol. 20, pp. 487-94. Saint-Onge, H. (1996), “Tacit knowledge: the key to the strategic alignment of intellectual capital”, Strategy & Leadership, Vol. 24, pp. 10-14. Stewart, T. (1991), “Brainpower”, Fortune, Vol. 123, pp. 44-50. Subramanian, M. and Youndt, M. (2005), “The influence of intellectual capital on the types of innovative capabilities”, Academy of Management Journal, Vol. 48, pp. 450-63. Sveiby, K. (1997), The New Organizational Wealth, Berrett-Koeheler, San Francisco, CA.
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Teece, D. (1998), “Capturing value from knowledge assets: the new economy, markets for know-how, and intangible assets”, California Management Review, Vol. 40, pp. 55-79. Warn, J. (2005), “Intangibles in commercialization: the case of air navigation services in the South Pacific”, Journal of Intellectual Capital, Vol. 6, pp. 72-88. Youndt, M. and Snell, S. (2004), “Human resource configurations, intellectual capital and organizational performance”, Journal of Managerial Issues, Vol. 16, pp. 337-60. Youndt, M., Subramanian, M. and Snell, S. (2004), “Intellectual capital profiles: an examination of investments and returns”, Journal of Management Studies, Vol. 42, pp. 335-61. About the authors Gregorio Martı´n de Castro is Assistant Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain). He has several years of research experience at the CIC Spanish Knowledge Society Research Centre, he holds an Expert Diploma in Intellectual Capital and Knowledge Management by INSEAD (France), and was Post-Doctoral Research Fellow at RCC, Harvard University during 2004-2005. He is the author or co-author of several papers concerning the resource-based view, intellectual capital and knowledge management. Gregorio Martı´n de Castro is the corresponding author and can be contacted at:
[email protected] Pedro Lo´pez Sa´ez is Assistant Professor at the Business Administration Department in Universidad Complutense de Madrid (Spain) and was a Research Fellow at RCC, Harvard University during 2004-2005. He has several years of research experience at the CIC Spanish Knowledge Society Research Centre, and is the author or co-author of several papers concerning the resource-based view, intellectual capital and knowledge management.
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