The Influence of CCR/BCC Models and DEA Approach in Finding Branch Efficiency A Case Study: EN-Bank

Abstract

The purpose of this study was to illustrate a Data Envelopment Analysis (DEA) approach to assessing EN Bank branch network performance. In the present paper, we focused on deploying the DEA model to analyze bank branches’ performance and which criteria could be selected as an input or output in developing the DEA model; of course, we concentrated on the suitable DEA models in Bank branch performance analysis. This paper used a two-stage Data Envelopment Analysis approach to simultaneously benchmark the bank branch’s performance. After that, inputs and outputs were analyzed with CCR and BCC models to find branch efficiency. After analyzing the data, it can be concluded that BCC models are more optimistic. The average efficiency score and the number of efficient branches in BCC models for both approaches are more than the CCR model. The findings also indicated that the variation within branches in the intermediary model is more than the profitability model. This indicated that branches are more homogeneous in the profitability approach than the intermediary model. According to overall scores and ranking, we can compare the current EN bank score for each branch by its DEA overall score, and of course, their rank based on these scores can be supplied. Comparing them can lead the reader to find the compatibility of the current system by DEA ranking of branches.