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DEA cross-efficiency evaluation based on satisfaction degree: an application to technology selection.
- Source :
- International Journal of Production Research; Oct2016, Vol. 54 Issue 20, p5990-6007, 18p, 8 Charts
- Publication Year :
- 2016
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00207543
- Volume :
- 54
- Issue :
- 20
- Database :
- Complementary Index
- Journal :
- International Journal of Production Research
- Publication Type :
- Academic Journal
- Accession number :
- 117807841
- Full Text :
- https://doi.org/10.1080/00207543.2016.1148278