Ranking of bank branches with undesirable and fuzzy data: A DEA-based approach

Subject Areas : Data Envelopment Analysis

Sohrab Kordrostami ¹ , Alireza Amirteimoori ² , Monireh Jahani Sayyad Noveiri ³

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Received: 2016-08-09 Accepted : 2016-10-26 Published : 2016-12-01

Keywords: Data Envelopment Analysis (DEA), Ranking, undesirable data, bank branches performance, fuzzy data,

Abstract :

Banks are one of the most important financial sectors in order to the economic development of each country. Certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. Sometimes the performance of banks must be measured in the presence of undesirable and vague factors. For these reasons in the current paper a procedure based on data envelopment analysis (DEA) is introduced for evaluating the efficiency and complete ranking of decision making units (DMUs) where undesirable and fuzzy measures exist. To illustrate, in the presence of undesirable and fuzzy measures, DMUs are evaluated by using a fuzzy expected value approach and DMUs with similar efficiency scores are ranked by using constraints and the Maximal Balance Index based on the optimal shadow prices. Afterwards, the efficiency scores of 25 branches of an Iranian commercial bank are evaluated using the proposed method. Also, a complete ranking of bank branches is presented to discriminate branches.

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