Fuzzy Approach to Ranking the Impact of Intellectual Capital Components on the Performance of a University

Subject Areas : Business Management

Abdolnaser Shojaei ¹ , Tooraj Beygi ² , Mohamad Hassan Fotros ³

1 - PhD Student, Faculty Member of Islamic Azad University, Sanandaj Branch
2 - PhD student of Economics, Islamic Azad University, Science and Research Branch
3 - Associate Professor of Bu-Ali Sina University, Hamedan, Iran

Received: 2011-05-04 Accepted : 2011-12-09 Published : 2011-12-22

Keywords: Intellectual Capital, Performance, University, fuzzy hierarchical analysis,

Abstract :

Intangible assets represent all assets that are not reflected in the balance sheet but are considered a source for creating value that leads to sustainable competitive advantages. In the modern economy, intellectual capital is described as an intellectual asset that can be used as a source for sustainable competitive advantage so much so that the leading organizations in modern economy are those that create value by relying on intellectual capital. On the other hand, universities face the same challenges, and increasing the performance of universities is one of the major goals of every country to achieve sustainable growth and development. In this study, we have applied fuzzy hierarchical analysis to the ranking of the effect of each intellectual capital component on the performance of universies. In the first step, a questionnaire consisting of 7 tables was set by 9 successful managers and top university researchers, and the hierarchical fuzzy analysis was carried out on the basis of Chang method. The results of fuzzy ranking indicate that the degree of the influence of intellectual capital components on the organizational performance is determined by the number and rank of the academic staff, relation with the market and industry, IT infrastructures, relation with government, staff, and physical infrastructures, respectively.  

References:

Bontis, N. (1997), “Intellectual Capital Questionnaire”, Institute for Intellectual Capital Research, Hamilton, Canada.

 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. 5/6/7/8, pp. 433-462.

Bontis, N., Keow, W.C. and Richardson, S. (2000), “Intellectual Capital and Business Performance in Malaysian Industries”, Journal of Intellectual Capital, Vol. 1, No. 1, pp. 85-100.

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.

Bozbura, F. T., & Beskese, A. (2007), Prioritization of organizational capital measurement indicators using fuzzy AHP international. Journal of Approximate Reasoning, 44, 124–147.

Casper, C. A., & Henry, M. S. (2001), Developing performance-oriented models for university resource allocation. Research in Higher Education, 42(3), 353–376.

Castro, G. M., & Sáez, P. L. (2008), Intellectual capital in high-tech firms. Journal of Intellectual Capital, 9(1), 25–36.

Chang, D. Y. (1996), Applications of extent analysis method on fuzzy AHP. European Journal of Operational Research,95,649–655.

Cheng, C. H. (1996), evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational Research, 96, 343–350.

Chen, J., Zhu, Z. and Xie, H.Y. (2004), “Measuring Intellectual Capital: a New Model and Empirical Study”, Journal of Intellectual Capital, Vol. 5, No. 1, pp. 195-212.

Chen, C.T. (2000), Extensions of TOPSIS for group decision-making under fuzzy environment.Fuzzy sets and systems. 114. 1-9.

Cheng, Ch (2001), the function and the client’s attitude in developing of e-banking, Honk Kongh University Publisher.

Cheng, C.H. (1999), evaluating weapon systems using ranking fuzzy numbers. Fuzzy sets and systems.107, 25-35.

Csutora,R., & Buckley,J.L.(2001), Fuzzy hierarchical analysis: the Lambda-Max method. Fuzzy sets and systems, 120,181-195.

Drucker, P. (1993), Post capitalist society. New York: Harper Business.

Eckstein, C. (2004), the measurement and recognition of intangible assets: Then and now. Accounting Forum, 28, 139–158.

Edvinsson, L., & Malone, S. M. (1997), Intellectual capital: Realizing your firm’s true value by finding its hidden brainpower. New York: Harper Collins Publishers.

Edvinsson, L., & Sullivan, P. (1996), developing a model for managing intellectual capital. European Management Journal, 14(4), 356–364.

Ferrier, F. and McKenzie, P. (1999), “Looking Ahead: An Enterprise Information and Self-Evaluation Kit”, International Symposium on Measuring and Reporting Intellectual Capital: Experiences, Issues, and Prospects, OECD, Amsterdam.

Fruin, W. M. (1997), Knowledge works: Managing intellectual capital at Toshiba. New York: Oxford University Press.

Han, D., & Han, I. (2004), Prioritization and selection of intellectual capital measurement indicators using analytic hierarchy process for the mobile telecommunications industry. Expert Systems with Applications, 26, 519–527.

Huang, W.Y and Chang, C. (2005), “Intellectual Capital and Performance in Causal Models: Evidence from the Information Technology Industry in Taiwan”, Journal of Intellectual Capital, Vol. 6, No. 2, pp. 222-236.

Khorshid, S., & Ghane, H. (2009). Ranking the Challenges of Electronic Banking from the Point of View of Banking Customers and Managers Using the Fuzzy Analytical Hierarchy Process. Quarterly Journal of Industrial Management, 4(9), 89 -106, (In Persian).

Leitner, K. H. (2004), Intellectual capital reporting for universities: Conceptual background and application for Austrian universities. Research Evaluation, 13(2), 129–140.

Mavridis, D.G. (2004), “The Intellectual Capital Performance of the Japanese Banking Sector”, Journal of Intellectual Capital, Vol. 5, No. 1, pp. 92-115.

Pulic, A. (1997), “The Physical and Intellectual Capital of Austrian Banks”, available at: http://irc.mcmaster.ca (accessed 11 June 2004).

Seetharaman, H. and Saravanan, A. (2002), “Intellectual Capital Accounting and Reporting in the Knowledge Economy”, Journal of Intellectual Capital, Vol. 3, No. 2, pp. 128-148.

Skandia, (1996), “Power of Innovation”, Skandia’s 1996 Interim Report, Skandia, Stockholm.

Sullivan J, P, H. and Sullivan S, P, H. (2000), “Valuing Intangible Companies: an Intellectual Capital Approach”, Journal of Intellectual capital, Vol. 1, No. 4, pp. 328-340.

Shojaei, A. N., & Baghbaniyan, M. (2009). Investigating the Relationship between Intellectual Capital and Organizational Performance of Banking Industry in Iran: A Case Study of Kurdistan Province. Quarterly Journal of Industrial Management, 4(9), 107-118, (In Persian).

Shyh-Hwang, L.(2010),” Using fuzzy AHP to develop intellectual capital evaluation model for assessing their performance contribution “Expert Systems with Applications 37, 4941–4947.

Wang, W.Y and Chang, C. (2005), “Intellectual Capital and Performance in Causal Models: Evidence from the Information Technology Industry in Taiwan”, Journal of Intellectual Capital, Vol. 6, No. 2, pp. 222-236.

Wiig, K.M. (1997), “Integrating Intellectual Capital and Knowledge Management”, Long Range Planning, Vol. 30, No. 3, pp. 399-405.

Williams, S.M. (2001), “Are Intellectual Capital Performance and Disclosure Practices Related?” Journal of Intellectual Capital, Vol. 2, No. 3, pp. 192-203.

Youndt, M.A., Subramanian, M. and Snell, S.A. (2004), “Intellectual Capital Profiles: An Examination of Investments and Returns”, Journal of Management Studies, Vol. 41, No. 2, pp. 335-361.

Zadeh, L.A. (1965), Fuzzy sets. Information and control,8,338-353.