Profit Efficiency Evaluation: A composed Approach of DEA and multi- objective programming

Subject Areas : Operation Research

Soheila Seyedboveir ^{1 *} , Fatemeh Mehregan ² , Mahnaz Maghbouli ³

1 - Department of Statistics and Mathematics, Arvand International Branch, Islamic Azad University, Abadan, Iran
2 - Department of Statistics and Mathematics, Arvand International Branch, Islamic Azad University, Abadan, Iran
3 - Department of Mathematics, Aras Branch, Islamic Azad University, Jolfa, Iran

Received: 2025-02-09 Accepted : 2025-06-08 Published : 2025-01-13

Keywords: Data Envelopment Analysis, Profit Efficiency, Multi-objective Programming,

Abstract :

Data envelopment analysis (DEA) is a nonparametric method for evaluating the relative efficiency of decision making units (DMUs) described by multiple inputs and multiple outputs. The issue of measuring the cost, revenue and profit efficiency in manufacturing and economic systems is one of the most important issues for managers. In this research, using Data envelopment analysis and multi-objective programming an attempt is made to provide a model for evaluating profit efficiency of banking industry. We apply data envelopment analysis (DEA) and multi-objective programming (MOP) models to measure profit efficiency as cost and revenue scores are as close as possible to their best scores and as far away as possible to their worst scores. The results showed that composing these two models, can directly affect the result and also findings of research distinguished the differences between the efficient DMUs from the point of view of DEA. In this study, Profit efficiency score has been obtained from a fairer perspective than the previous models. A numerical example of Iranian banking industry is used to illustrate the proposed model.

References:

[1] AMIRTEIMOORI, A., KORDROSTAMI, S. & RABETIEZER, A. (2006). An improvement to the cost efficiency interval: A DEA based approach. Applied mathematics and computation, 81,775-781.

[2] APARICIO, J. BORRAS, F. &, PASTOR, J.T., VIDAL, F. (2013). Accounting for slacks to Measure and decompose revenue efficiency in the Spanish Designation of Origin wines with DEA European Journal of Operational Research, 231,443-451.

[3] CAMANHO, A.S. & DYSON, R.G. (2005). Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments. European journal of operational Research, 161,432-446.

[4] FARELL, M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society (Series A) 129, 253-351.


[5] FARE, R., GROSSKOPF.S. & LOVELL, C.A.K. (1985). The measurement of efficiency of Production. Boston: Kluwer Publication.

[6] FARE, R., GROSSKOPF.S. & LOVELL, C.A.K (1994). Production Frontiers. Cambridge University Press. Southern Illinois university, Carbondale.

[7] FARE, R., GROSSKOPF.S. & WEBER, W. (2004). The effect of Risk-based capital requirements on profit efficiency in banking. Applied Economics, 36, 1731-1743.


[8] FUKUYAMA, H., & MATOUSEK, R. (2017). Modeling bank performance: A network DEA approach. European Journal of Operational Research, 259, pp 721-732.

[9] FUKUYAMA H. & WEBER, W. L. (2008). Profit inefficiency of Japanese securities firms. Journal of Applied Economics, 11, 281-303.

[10] JAHANSHAHLOO, G.R. INAATEEOT- HEEEOAD, M., MOSTAFAEE, A. (2008). A simplified version of the DEA cost efficiency model. European Journal of Operational Research. 184, 814-815.

[11] JAHANSHAHLOO, G.R. ETRHADREO, S.M., VAKILI.J. (2011). an interpretation of the cost model in Data Envelopment Analysis. Journal of Applied Sciences, 11(2), 389-392.

[12] MOGHADDAS, Z & VAEZ GHASEMI, M. (2022). Revenue Efficiency Evaluation in a Two-stage Network with Nonlinear Prices in Data Envelopment Analysis. Journal of Decisions and operations Research, 6, 1–9.

[13] PARK, K.S.M., & ODN J.W. (2011). Pro-efficiency: Data speak more than technical efficiency. European Journal of Operational Research, 215, 301-308.

[14] PORTELA, M.C.A.S. &, THANASSOULIS, E. (2007). Developing a decomposable measure of profit efficiency using DEA. Journal of the Operational Research Society, 58, 481-490.

[15] SEYEDBOVEIR, S. KORDROSTAMI, S. DANESHIAN. (2018). Revenue-Profit Measurement in Data Envelopment Analysis with Dynamic Network Structures: A Relational Model. Int. J. Industrial Mathematics, 10.

[16] TOLOO, M. & ERTAY, T. (2014). The most cost efficient automotive vendor with price uncertainty: A new DEA approach. Measurement, 52,135-144.