Decision Tree Analysis for Selection of Factors in DEA: An Application to Banks in India

Abstract

The body of research assessing the technical efficiency of decision-making units (DMUs) with a special reference to Indian banking sector suggests that a majority of these studies have employed data envelopment analysis (DEA) for measuring technical efficiency with two-input/two-output or three-input/three-output or models with several combinations of various input and output factors. In almost all the cases, the choice of input and output factors was based on the judgement of the researchers. They lack the rigorous justification pertaining to the appropriateness of or the efficacy of such input– output factors to measure the true technical efficiency of the DMUs. This study evaluates 11 select DEA models representing the intermediary approach with various input–output factors and investigates the relationship between the computed efficiency scores and a single performance measure of DMUs by using decision tree (DT) analysis. The objective is to find a better criterion using a scientific method of input–output selection to effectively assess the true efficiency of the DMUs. The article analyzes the relative efficiency scores of 57 DMUs (representing private, public and foreign scheduled commercial banks) from 11 different variable returns to scale (VRS) DEA models with input orientation. The results indicate that 2 out of the 11 models are the most appropriate to measure relative efficiency when intermediary approach is considered to evaluate the banks. This leads to the conclusion that the management of the banks in our study should focus their efforts and resources on the input–output factors from these two models to improve efficiency and increase profitability.