Presenting a data envelopment analysis model based on Goal programming and weight Restriction in order to evaluate the efficiency and ranking of decision-making units in Ghavamin Bank

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Industrial Management with the Field of Operational Research, Faculty of Economics and Management, Science and Research Branch, Islamic Azad University,Tehran Iran.

2 Prof., Department of Industrial Management, Faculty of Economics and Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.

3 Associate Prof., Department of Industrial Management, Faculty of Economics and Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Abstract

Objective: The purpose of this paper is to evaluate the efficiency of decision-making units using the goal programming model of data envelopment analysis with restriction weight and ranking of units with a unique method in Ghavamin Bank.
Methods: In this study, the classical CCR model was used to determine the management efficiency of provincial branches in Ghavamin Bank. To increase the discriminative power of efficient and inefficient decision-making units, a combination of goal programming models with Weight restriction was used and a new model called goal programming of data envelopment analysis with Weight restriction was presented.
Results: Based on the output values of the classical CCR model, 16 out of 32 decision-making units became efficient and 16 units became inefficient. In the next step, for more separability of the units, the goal programming model of data envelopment analysis with Weight restriction was used. The results of the first-order Euclidean norm became 7 efficient and the rest inefficient out of 32 decision-making units, and the results of the infinite Euclidean norm became 1 of 32 efficient units and the rest of the decision-making units inefficient.
Conclusion: The results showed that the goal programming model of data envelopment analysis with Weight restriction related to infinite Euclidean norm in separating and ranking efficient decision-making units from inefficient has a high discriminate power compared to the classical CCR model and the first-order Euclidean norm

Keywords

References


Ahadzadeh Namin, M., khamseh, E., Mohamadi, F. (2019). Evaluate the performance of bank branches using the control approach in analyzing the data common weight.Financial Engineering and Protfolio Management, 10(40), 1-28. (in Persian)
Allen, R., Athanassopoulos, A., Dyson, R.G., Thanassoulis, E. (1997). Weight restrictions and value judgments in data envelopment analysis: evolution, development and future directions. Annals of Operations Research, 73(1), 13-34.
Anderson, P., Petersen, N.C. (1993). A Procedure for Ranking Efficient Units in Data Envelopment Analysis. Management Science, 39(10), 1261-1264.
Andrade, R. M., Lee, S., Lee, P. T., Kwon, O.K., Chung Port, H. (2019). Efficiency Incorporating Service Measurement Variables by the BiO-MCDEA: Brazilian Case, Sustainability, 11(16), 4340. Doi: 10.3390/su11164340.
Arabmazar, A., hasani, H. (2018). Survey Performance of Iran's Banks with Network Data Envelopment Analysis Method. Quarterly Journal of Quantitative Economics, 15(2), 1-21. doi: 10.22055/jqe.2017.21388.1596. (in Persian)
Azar, A., Zarei-Mahmoudabadi, M., Moqbel-Ba'arz, A., Khadivar, A. (2014). Evaluating the Productivity of a Bank's Branches Using Network Data Envelopment Analysis Approach (Case Study: A Bank in Gilan Province). JMBR, 20(7), 285-305. (in Persian)
BOĎA, M., ZIMKOVÁ, E. (2014). Efficiency in the Slovak banking industry: a comparison of three approaches. Prague Economic Papers, 24(4), 434–452
Doyle, J., & Green, R. (1994). Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. Journal of the operational research society, 45(5), 567-578.
Eskelinen, J., Halme, M., Kallio, M. (2014). Bank branch sales evaluation using extended value efficiency analysis. European Journal of Operational Research, 232(3), 654-663.
 Jahangiri, A. (2019). Application of Data Envelopment Analysis Technique in Iran Banking System. Decisions and operation Reserarch, 3(4), 368-401. (in Persian)
Jiani Rezaei, H., Golzarianpour, S., Mahian, M. (2017). Measuring and Analysis of Bank Sepah Branch Efficiencies Using Window DEA (Case: Third Degree Branches of Mashhad City). Quarterly Journal of Islamic Finance and Banking Studies, 2(4), 37-65. (in Persian)
Khalili, M., Camanho, A.S., Portela, M., Alirezaee, M.R. (2010). The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs. European Journal of Operational Research, 203 (3) 761–770. 
 Khatami, S. M., Rajabi-Farjad, H., Chaharmahali, H. (2014). Evaluating the performance evaluation system of the employees of the organization and presenting the proposed model. Journal of Human Resource Studies (JHRS), 3(4), 129-148. (in Persian)
Li, X. B., Reeves, G. R. (1999). A multiple criteria approach to data envelopment analysis. European Journal of Operational Research, 115(1), 507–517.
Mohaqar, A., Hakak, M., Yaghoubi, H. (2014). Evaluation of the efficiency of agricultural bank currency units using the combined methods of BSC, DEA and AHP. International Journal of Industrial Engineering and Production Management, 25(2), 247-237. (in Persian)
Momeni, M., Rostamy Malkhalifeh, M., Razavi, S., Yakideh, K. (2014). Group Ranking Of Bank Units According To Data Envelopment Analysis Approach. Industrial Management Journal, 6(1), 181-196. (in Persian)
Nilchi,, M., Fadaeinejad, M., Razavi-Hajiagha, S., Badri, A. (2017). Providing New Multi-Component Data Envelopment Analysis to Evaluate Efficiency of Bank Branches. Industrial Management Studies, 15(46), 73-96. doi: 10.22054/jims.2017.7989. (in Persian)
Panahandeh khojin, G., Toloie Eshlaghy, A., Afshar Kazemi, M. (2020). Evaluate the efficiency of decision making units with classical model and goal programming data envelopment analysis and output correlation with statistical methods in Ghavamin Bank. Journal of New Researches in Mathematics.(in Persian)
Parsafard, M., shirkavand, S., Tehrani, R., Mirlohi, S. (2018). Standalone Credit Rating of the Country's Banks. Industrial Management Journal, 10(4), 575-606. 
Podinovski, V. V. (2016). Optimal weights in DEA models with weight restrictions, European Journal of Operational Research, 254(3), 916-924. 
Karimi, B., Davtalab-Olyaie, M.,Abdali, A.A.(2018). A Suitable Business Model for Bank Branches: Combining Business Model and Malmquist Productivity Index (MPI). Business and Economics Journal,9(2),348. doi: 10.4172/2151-6219.1000348.
Sadeghi Moghadam, M., Safari, H., Ahmadi Nozari, M. (2015). Measuring sustainability of service supply chain by using a multi-stage/multicast fuzzy inference system (Studied Case: Parsian Bank. Industrial Management Journal, 7(3), 533-562. (in Persian)
Sahand D, Nazila S, Fariba N. (2015). Modified Goal Programming Approach for Improving the Discrimination Power and Weights Dispersion. New Researches in Mathematics, 1(3), 5-18. 
Sahoo, B. K. Mehdiloozad, M., Tone, K. (2014). Cost, revenue and profit efficiency measurement in DEA: A directional distance function approach. European Journal of Operational Research, 237(3), 921-931. 
Salehi, S., Nikokar, G., Mohammadi, A., nataj, G. (2011). Pattern Design and Performance Evaluation of Branches of Banks and Financial Institutions (Case Study: Ghavamin Bank). Journal of Business Management, 3(1), 127-268. (in Persian)
Sexton, T.R., Silkman, R.H., Hogan, A.J. (1986). Data envelopment analysis: critique and extensions. In: Silkman, R.H. (Ed.), Measuring Efficiency: an Assessment of Data Envelopment Analysis. Jossey-Bass, San Francisco, CA, 73-105.
Shafiei, Murtaza. (2017). Evaluating the efficiency of bank branches using dynamic data envelopment analysis model with SBM approach. New Research in Mathematics (Basic Sciences of Islamic Azad University), 3(1), 5-17. (in Persian)
Shikh-hasani, D., Alifarri, M., Karimi, B. (2020). Measuring efficiency score by cross-efficiency method in data envelopment analysis and its relation to profitability and risk in banks admitted to Tehran stock exchange. Management Accounting, 13(46), 103-119. (in Persian)
Wanke, P., Azad, M.A.K., Emrouznejad, A., Antunes, J. (2019). A dynamic network DEA model for accounting and financial indicators: A case of efficiency in MENA banking. International Review of Economics and Finance. doi: https://doi.org/10.1016/j.iref.2019.01.004.
Yong, T., Christos, F. (2018). Risk, competition and efficiency in banking: Evidence from China. Global Finance Journal, 35(1) , 223–236.
Zimková, E. (2014). Technical Efficiency and Super-efficiency of the Banking Sector in Slovakia. Procedia Economics and Finance, 12(1), 780-787.
Industrial Management Journal
Volume 13, Issue 1
2021
Pages 155-169

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