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A cross-inefficiency approach based on the deviation variables framework
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DOI：10.1016/j.omega.2022.102668.png)
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This paper presents a solution to the problem of ranking efficient decision-making units (DMUs) in data envelopment analysis (DEA). We develop a cross-inefficiency approach for the deviation variables framework based on a pair of epsilon-based benevolent and aggressive models for both constant and variable returns-to-scale technologies. The new method improves the discriminating power of DEA, solves the non-uniqueness of ranking solutions, and avoids the negative efficiency scores associated with current models in the deviation variables framework. We illustrate the performance of the approach using a real life case study. Not only does the research improve the discriminating power, but it also encourages the first step towards integrating the deviation variables framework in the context of decision-making uncertainty. (c) 2022 Published by Elsevier Ltd.
Keyword:
Data envelopment analysis
Deviation variables
Cross-inefficiency
Ranking
Discriminating power
Negative efficiency score
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