The Efficiency Analysis and Ranking Employing Data Envelopment Analysis and Multi-Criteria Decision Analysis: Incorporating Cumulative Prospect Theory

This study proposes an integrated methodology for evaluating and ranking decision-making units (DMUs) characterized by multiple inputs and outputs by combining data envelopment analysis (DEA) and multi-criteria decision analysis (MCDA) with cumulative prospect theory (CPT), a behavioral decision-making framework. Recognizing that decision-making is often influenced by risk perception and behavioral biases, the proposed approach incorporates CPT to capture the psychological preferences of decision-makers under uncertainty by establishing prospect intervals for each input and output (or criterion) based on pessimistic and optimistic reference points. These prospect interval values are then aggregated and utilized for the efficiency evaluation and ranking of DMUs. Given that traditional DEA models frequently assign an efficiency score of one to several DMUs, posing challenges in their differentiation and ranking, the study introduces a hybrid approach that integrates DEA with the Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) method. By benchmarking DMUs against ideal and anti-ideal solutions, MARCOS facilitates a more nuanced and comprehensive ranking process. The proposed framework is empirically validated using data from 30 assets listed in the Nifty 50 index, illustrating its effectiveness in providing a robust, behaviorally informed evaluation of DMUs. Additionally, a comparative analysis is conducted to assess the differences between the rankings generated by the two MCDA methods.