Evaluating the performance of bank branches using fuzzy network data envelopment analysis model with optional input-undesirable output

Subject Areas : Financial engineering

Hasan Amini Javid` ¹ , Mohammad Ebrahim Mohammadpoor Zarandi ² , Mirfeiz fallahshams ³ , naghi shoja ⁴

1 - PhD student in Industrial Management, Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran,( Visiting Professor of Science and Research Branch)
3 - Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran, ,( Visiting Professor of Science and Research Branch)
4 - Department of Mathematic, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran,( Visiting Professor of Science and Research Branch)

Received: 2022-07-30 Accepted : 2022-11-03 Published : 2023-09-23

Keywords: Performance Evaluation, Bank Branches, Undesirable output, fuzzy network data coverage analysis, optional input,

Abstract :

The purpose of this research is to provide a model for evaluating the performance of bank branches using the network coverage analysis model using fuzzy data. In this research, an attempt was made to use a model based on the traditional model of data envelopment analysis, taking into account factors such as the network nature and internal relationships of each decision-making unit, undesirable output, non-optional input, and the variables having a fuzzy nature. which is more consistent with the actual conditions related to the decision-making units and calculates the efficiency in a more accurate way.After presenting the research model, first, based on the studies conducted in the past researches and field studies and obtaining opinions from experts in this industry, indicators were considered as input and output. After identifying the indicators, fuzzy Delphi method was used for initial screening of the indicators. In the following, confirmatory factor analysis technique was used to finalize the screened indicators. At the end of the research, the developed model was solved using the data collected from the studied branches, by Gams software and with the alpha cutting approach. The results indicate that among the 34 investigated branches, 8 are efficient and 26 are ineffective.