DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection |
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Authors: | Jie Wu Junfei Chu Qingyuan Zhu Pengzhen Yin Liang Liang |
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Affiliation: | School of Management, University of Science and Technology of China, Hefei P.R. China |
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Abstract: | Data envelopment analysis (DEA) has been extended to cross-efficiency evaluation to provide better discrimination and ranking of decision-making units (DMUs). However, the non-uniqueness of optimal weights in the traditional DEA models (CCR and BCC models) has reduced the usefulness of the DEA cross-efficiency evaluation method. To solve this problem, we introduce the concept of the satisfaction degree of a DMU towards a set of optimal weights for another DMU. Then, a new DEA cross-efficiency evaluation approach, which contains a maxmin model and two algorithms, is proposed based on the satisfaction degrees of the DMUs. Our maxmin model and algorithm 1 can obtain for each DMU an optimal set of weights that maximises the least satisfaction degrees among all the other DMUs. Further, our algorithm 2 can then be used to guarantee the uniqueness of the optimal weights for each DMU. Finally, our approach is applied to a real-world case study of technology selection. |
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Keywords: | Data envelopment analysis (DEA) cross-efficiency evaluation satisfaction degree technology selection |
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