A Novel Efficiency Ranking Approach Based on Goal Programming and Data Envelopment Analysis for the Evaluation of Iranian Banks

In the Iranian economy, banks play a key role in financing and developing the capital market. Therefore, it is important to evaluate the performance of stock banks. Data Envelopment Analysis (DEA) is a wide range of mathematical models used to measure the relative efficiency for a set of homogeneous decision-making units with similar inputs and outputs. In this paper, a novel efficiency ranking approach is proposed with two flexible mixed models derived from Goal Programming Data Envelopment Analysis (GPDEA) models. To solve this mismatch, we use Gantt chart to show DMUs’ floating ranking and use another model to appoint the ranks exactly. In this paper, we analyze 18 stocks efficiency from bank industry of Tehran Exchange in 2016 using the GPDEA approach. Results demonstrate that the novel efficiency ranking approach has higher ability than the basic models in efficiency ranking.