Document Type : Research Paper


Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran


In recent years, researchers in their studies considered human capital as one of the most important capitals of every organization and even some of them placed it beyond this definition and introduced it as the unique factor of creating the competitive advantage in the organization. Due to the importance of human capital management, by evaluating the performance of human capital management system, managers can be aware of their organization’s status from the perspective of human capital management creation and perform corrective practices better. In this study, a method for the performance evaluation and ranking of organizational unit is presented using fuzzy DEA. Therefore in the beginning, the performance of organizational units was evaluated using fuzzy DEA and then with the use of sensitivity analysis, the most effective criteria on the efficiency of organizational units were determined. Then using the efficiency of organizational units in the best and the worst states, ranking of organizational units has been paid. Finally to examine the functionality of the proposed method, Foolad Technic Company has been chosen as a case study and the procedure has been implemented in this company.


Main Subjects

[1]    Lynham, S. and Cunningham, P. (2006). National human resource development in transitioning societies in the developing world: concept and challenges. Advances in Developing Human Resources, Vol. 8, No. 1, pp. 116-135.

[2]    Ardichvili, A., Zavyalova, E. and Minina, V. (2012). Human capital development: comparative analysis of BRICs. European Journal of Training and Development, Vol. 36, No. 2, pp. 213-233.

[3]    Nerdrum, L. and Erikson, T. (2001). Intellectual capital: a human capital perspective.

Journal of Intellectual Capital, Vol. 2, No. 2, pp. 127-135.

[4]    Harris, C. M., McMahan, G. C. and Wright, P. M. (2012). Talent and time together: The impact of human capital and overlapping tenure on unit performance. Personnel Review, Vol. 41, No. 4, pp. 408-427.

[5]    Royal, J. (2012). Evaluating human, social and cultural capital in nurse education.

Nurse Education Today, Vol. 32, No. 5, pp. e19-e22.

[6]    Bassi, L., McMurrer, D. (2007). Maximizing your return on people. Harvard Business Review, Vol. 8, No. 71, pp. 32-42.

[7]    Verkhohlyad, O. and McLean, G. N. (2012). Applying organizational commitment and human capital theories to emigration research. European Journal of Training and Development, Vol. 36, No. 2, pp. 308-328.

[8]    Griffeth, R., Hom, P. and Gaertner, S. (2000). A meta-analysis of antecedents and correlates of employees turnover: update, moderator tests, and research implications for the next millennium, Journal of Management, Vol. 26, pp. 463-88.

[9]    Jaramillo, f., Nixon, R. and Sms, P. (2005). The effect of law enforcement stress on organizational commitment. International Journal of Police Strategies and Management, Vol. 28, No. 2, pp. 321-336.

[10]    Shirouyehzad, H., HosseinzadehLotfi, F., Shahin, A., Aryanezhad, M. B. and Dabestani, R. (2012). A DEA approach for comparative analysis of service quality dimensions with a case study in hotel industry. Int. J. Services and Operations Management, Vol. 12, No. 3, pp. 289-308.



[11]    Charnes, A., Cooper, W. W. and Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, Vol. 2, No. 6, pp. 429-444.

[12]    Kacprzyk, J. (1986). Group decision making with a fuzzy linguistic majority. Fuzzy Sets and Systems, Vol. 18, No. 2 pp. 105-118.

[13]    Semih, O., Selin, S. K. and Elif, I. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Journal of Expert Systems with Applications, Vol. 36, No. 2, pp. 3887-3895.

[14]    Wang, Y. M. and Chin, K. S. (2011). Fuzzy data envelopment analysis: A fuzzy expected value approach. Expert Systems with Applications, Vol. 38, pp. 11678- 11685.

[15]    Wu, D. D., Yang, Z. and Liang, L. (2006). Efficiency analysis of cross-region bank branches using fuzzy data envelopment analysis. Applied Mathematics and Computation, Vol. 181, No. 1, pp. 271-281.

[16]    Tseng, Y. and Lee, T. (2009). Comparing appropriate decision support of human resource practices on organizational performance with DEA/AHP model. Expert Systems with Applications, Vol. 36, No. 3, pp. 6548-6558.

[17]    Carlucci, D. and Schiuma, G. (2009). Applying the analytic network process to disclose knowledge assets value creation dynamics. Expert Systems with Applications, Vol. 36, No. 4, pp. 7687-7694.

[18]    Lee, S. H. (2010). Using fuzzy AHP to develop intellectual capital evaluation model for assessing their performance contribution in a university. Expert Systems with Applications, Vol. 37, No. 7, pp. 4941-4947.

[19]    Birasnav, M., Rangnekar, S. and Dalpati, A. (2011). Transformational leadership and human capital benefits: the role of knowledge management. Leadership & Organization Development Journal, Vol. 32, No. 2, pp. 106-126.

[20]    Li, G. (2012). Output Efficiency Evaluation of University Human Resource Based on DEA. Procedia Engineering, Vol. 15, pp. 44707- 44711.

[21]    Chou, Y. C., Sun, C. C. and Yen, H. Y. (2012). Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach. Applied Soft Computing, Vol. 12, No.1, pp. 64-71.

[22]    Costa, R. (2012). Assessing Intellectual Capital efficiency and productivity: An application to the Italian yacht manufacturing sector. Expert Systems with Applications, Vol. 39, No. 8, pp. 7255-7261.

[23]    Yu, M., Chern, C. and Hsiao, B. (2013). Human resource rightsizing using centralized data envelopment analysis: Evidence from Taiwan’s Airports. Omega, Vol. 41, No. 1, pp. 119-130.

[24]    Mehralian, G., Rasekh, H. R., Akhavan. P. and RajabzadehGhatari, A. (2012). Prioritization of intellectual capital indicators in knowledge-based industries: Evidence from pharmaceutical industry. International Journal of Information Management, In Press.

[25]    Amado, C., Santos, S. P. and Marques P. M. (2012). Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment.Omega, Vol. 40, No. 11, pp. 390-403.

[26]    Kong, W. H. and Fu, T. T. (2012). Assessing the performance of business colleges in Taiwan using data envelopment analysis and student based value-added performance indicators. Omega, Vol. 40, No. 5, pp. 541-549.



[27]    Kuah, C. T., Wong, K. Y. and Wong, W. P. (2012). Monte Carlo Data Envelopment Analysis with Genetic Algorithm for Knowledge Management performance measurement. Expert Systems with Applications, Vol. 39, No. 10, pp. 9348-9358.

[28]    Saeedi, N., Alipour, A., Mirzapour, S. A. R. and MirzaeiChaboki, M. (2012). Ranking the intellectual capital components using Fuzzy TOPSIS technique (Case Study: An Iranian Company)”. Journal of Basic and Applied Scientific Research, Vol. 2, No. 10, pp. 10360-10368.

[29] Tavakoli, M. M., Nasr Esfahani A. and Shirouyehzad, H. (2012). Ranking Organizational Units with a Human Capital Management Approach using Fuzzy TOPSIS: A Case Study. International Journal of Services and Operations Management