Interval network data envelopment analysis model for classification of investment companies in the presence of uncertain data

Document Type : conference paper


School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran


This paper proposes the interval network data envelopment analysis (INDEA) approach under constant return to scale (CRS) and variable return to scale (VRS) assumptions which can assess the performance of investment companies (ICs) by considering uncertainty and internal structure. The presented approach of the paper is capable to model two-stage efficiency with intermediate measures in a single implementation. Finally, a real-life case study from Tehran stock exchange (TSE) is implemented to demonstrate applicability and exhibit the efficiency and effectiveness of the presented INDEA approach for performance measurement, ranking and classification of ICs in the presence of uncertain data.


Main Subjects

Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Chen, Y., & Zhu, J. (2004). Measuring information technology's indirect impact on firm performance. Information Technology and Management5(1), 9-22.
Despotis, D. K., & Smirlis, Y. G. (2002). Data envelopment analysis with imprecise data. European Journal of Operational Research140(1), 24-36.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
Kao, C. (2014). Network data envelopment analysis: A review. European Journal of Operational Research, 239(1), 1-16.
Galagedera, D. U., Watson, J., Premachandra, I. M., & Chen, Y. (2016). Modeling leakage in two-stage DEA models: An application to US mutual fund families. Omega61, 62-77.
Premachandra, I. M., Zhu, J., Watson, J., & Galagedera, D. U. (2016). Mutual Fund Industry Performance: A Network Data Envelopment Analysis Approach. In Data Envelopment Analysis (pp. 165-228). Springer US.
Premachandra, I. M., Zhu, J., Watson, J., & Galagedera, D. U. (2012). Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition. Journal of Banking & Finance, 36(12), 3302-3317.
Sadjadi, S., & Omrani, H. (2008). Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies. Energy Policy, 36(11), 4247-4254.
Zohdi, M., Marjani, A. B., Najafabadi, A. M., Alvani, J., &Dalvand, M. R. (2012). Data envelopment analysis (DEA) based performance evaluation system for investment companies: Case study of Tehran Stock Exchange. African Journal of Business Management, 6(16), 5573.