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Performance Evaluation of Commercial Bank Branches Using Data Envelopment Analysis
Considerable research has been devoted to using multiple criteria to measure the performance of business units such as bank branches. However, bank managers continue to use traditional methods to evaluate their branch offices. In general, subjective weights for various criteria are used to arrive at a weighted average score to measure the performance of a bank branch. Potential deficiencies in an existing set of weights include bias and inconsistency with organizational objectives. This paper employs Data Envelopment Analysis (DEA) to evaluate the operational performance of a bank branch relative to the performance of its peer branches. Utilizing data from 31 branches of a major bank located in Southern California, the use of DEA yields the following: 1) rankings of bank branches using efficiency scores, 2) identification of areas of deficiency and 3) establishment of the reference group against which a branch is evaluated. Twenty-two of the 31 branches were found to be in need of improvements in various areas. In addition to identifying best-practice branches and those that are out-of-line with the best practice branches, DEA also points to the specific changes that must be made in the less productive branches in order for them to catch up with their best-practice peer group. The findings of this study should help management in identifying the strengths and weaknesses of their bank branches.
(ProQuest-CSA LLC: ... denotes formula omitted.)
This study introduces and applies a framework for evaluating the operational performance of a bank branch network to assist bank managers in appraising bank branches. This framework is a linear-programming-based method called Data Envelopment Analysis (DEA) (Charnes, Cooper, Huang, Sx Sun, 1990). DEA is a nonparametric method that can serve as a

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