Data envelopment analysis (DEA) is a powerful approach for evaluating the relative efficiency of decision-making units with multiple inputs and outputs. Integrating DEA with ratio analysis has become essential because of the increasing prevalence of ratio data (e.g., return on assets) in practical applications. This study develops a novel DEA-R model and the RAM-R model, which combines the well-established range-adjusted measure (RAM) with ratio analysis. The model effectively handles ratio data, accommodates negative values, and accounts large variations across indicators, thereby enhancing flexibility and robustness in efficiency evaluation. A case study of 93 Japanese banks compares the RAM-R model with the RAM and another slacks-based DEA-R (the slacks-based measure-R and SBM-R) models using ratio data to demonstrate its effectiveness in evaluating efficiency.
Wang et al. (Mon,) studied this question.
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