Improvement Target Identification in Ratio-Based Data Envelopment Analysis: A Novel Methodological Approach

抄録

The DEA-R model, which integrates data envelopment analysis (DEA) with ratio analysis, allows for the evaluation of efficiency using ratio data. One main strength of DEA is its ability to provide concrete improvement targets for inefficient decision-making units (DMUs). However, identifying these targets within the DEA-R framework is particularly challenging because of the inherent characteristics of ratio data. To address this issue, this study proposes a novel approach for identifying concrete improvement targets for inputs or outputs within the DEA-R framework. Specifically, we construct the DEA-R efficient frontier based on a unique concept and develop an approach to identify improvement targets that lie explicitly on this frontier. This ensures that all the identified targets are DEA-R efficient, thereby guaranteeing their rationality and validity. Furthermore, the constructed frontier enables the setting of flexible improvement targets under various scenarios, thereby enhancing the practicality and adaptability of the proposed approach.