Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data

Bao Jiang, Enxin Chi and Jian Li
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Bao Jiang: Department of International Trade and Economy, Ocean University of China, Qingdao 266100, China
Enxin Chi: Department of International Trade and Economy, Ocean University of China, Qingdao 266100, China
Jian Li: Department of International Trade and Economy, Ocean University of China, Qingdao 266100, China

Mathematics, 2022, vol. 10, issue 13, 1-9

Abstract: Self evaluation and peer evaluation in data envelopment analysis (DEA) are effective means to comprehensively reflect the efficiencies of decision-making units (DMUs). However, when some of the inputs and outputs of DMUs cannot be accurately observed, the traditional evaluation methods will lose their applicability. This paper attempts to treat the imprecise inputs and outputs as uncertain variables based on uncertainty theory and hence to propose a new uncertain DEA model for cross-efficiency evaluation via the evaluation of both self efficiency and peer efficiency. Moreover, the equivalent form and the proof of the new model are also presented for accurate calculation. Finally, a numerical example is given to illustrate the evaluation results.

Keywords: uncertain data envelopment analysis; uncertainty theory; cross-efficiency; self evaluation; peer evaluation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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