Design of a Hybrid Mathematical AHP-DEA Model for Evaluating Branch Performance

Performance evaluation is the process of assessing and measuring the current situation and determining how to achieve a desired state based on specific criteria over a given period, with the aim of continuously improving organizational performance. Data Envelopment Analysis (DEA) is one of the most efficient and popular methods for evaluating efficiency. The basic DEA model does not provide a complete ranking and only classifies options into two groups: efficient and inefficient. Nevertheless, over the past decade, many efforts have been made to achieve complete ranking of options using the DEA concept. This research is another attempt to use the DEA concept for full ranking of options by employing one of the common multi-criteria decision-making methods, the Analytic Hierarchy Process (AHP). The AHP/DEA model examined in this study consists of two stages. In this research, using Data Envelopment Analysis, the criteria are first compared with each other, and the pairwise comparison matrix is obtained. Then, using the Analytic Hierarchy Process, the most efficient branch is determined. Branch performance evaluation is conducted based on the input and output values. In this study, 4 input criteria (movable property costs, human resource costs, administrative costs, and number of branch personnel) and 3 output criteria (deposits, granted facilities, and branch profit) were used to evaluate the efficiency of bank branches during the period from November 2025 to January 2026 for 16 branches of Bank Mellat in Yazd Province, Iran. The AHP/DEA model was implemented using WinQSB and Expert Choice software. The results showed that the Alavi, Markazi, and Joushkar branches had the highest rank weights, respectively. Furthermore, the results indicated that the AHP/DEA method is efficient in calculating efficiency and can improve the shortcomings of the traditional DEA method.