A new two-stage data envelopment analysis (DEA) model for evaluating the branch performance of banks

Abstract

The purpose of this paper is to provide a framework for evaluating the overall performance of bank branches in terms of profitability efficiency and effectiveness by means of a two stage data envelopment analysis (DEA) model. DEA is a linear programming problem approach for evaluating efficiency of decision making units (DMU) that have multiple inputs and outputs. In this paper, we use a two stage DEA model for efficiency evaluation of DMUs. In the two stage model all the outputs from the first stage are the only inputs to the second stage, in addition to the inputs to the first stage and the outputs from the second stage. The outputs from the first stage to the second stage are called intermediate measures. Many papers have regressed non parametric estimate of efficiency in the two stage DEA procedure. All of these studies have several problems in the benchmark or projection unit and present the DMU with relative efficiency. Most of these papers do not present an efficient benchmark unit and cannot evaluate the relative efficiency unit. In this paper we review these studies and then create a two stage model that does not have these problems. Our model presents the efficient benchmark unit and also presents DMU with relative efficiency. In the next step we apply our two stage model in bank branches of a large commercial bank in Iran. This study aggregates profitability efficiency and effectiveness into the overall performance. Some relations between profitability efficiency and effectiveness are very important. Without these relations we cannot obtain superior insight about overall performance. So we assume that profitability efficiency and effectiveness are dependent, and with this assumption we design a two stage DEA model. This study shows the importance of profitability efficiency and effectiveness in the overall performance in bank branches in Iran. Key words: Banking, process efficiency, organizational effectiveness, data envelopment analysis (DEA), banks, banks performance.