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Implementing no free disposability in data envelopment analysis
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AI
DOI：10.1016/j.ejor.2024.11.029.png)
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Abstract
En 中文
Data envelopment analysis (DEA) relies on two main postulates of convexity and inefficiency (free disposability). No free disposability postulate is suggested to address undesirable measures. In this study, we demonstrate how no-disposability assumption can be correctly integrated into the DEA framework. We propose the appropriate constraints that should be used in the absence of the free disposability postulate in a DEA model. The additional constraints bound the previously unbounded feasible region (production technology) rather than altering the strongly efficient frontier. We also discuss that treating an undesirable output (input) as a desirable input (output) does not affect the corresponding efficient frontier of a dataset, but misrepresents its corresponding production technology in the presence of free disposability postulate. We provide numerical examples to clarify the concerns in treating an undesirable measure as a desirable measure. A real-life example of United States' electric power plants is also discussed.
Keywords:
Data envelopment analysis
Free disposability
Convexity
Production frontier
Undesirable measures
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W