Ranking via composite weighting schemes under a DEA cross-evaluation framework

•Suggests a new perspective for ranking under DEA cross efficiency settings.•Exploits the existence of separate weighting schemes in DEA cross evaluation to build composite value systems.•Combines cross-efficiency, weighting schemes and OWA operators to provide a full ranking of DMUs.•Illustrates an...

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Bibliographic Details
Published in:Computers & industrial engineering 2018-03, Vol.117, p.217-224
Main Author: Oukil, Amar
Format: Article
Language:English
Subjects:
Composite value system
Cross-efficiency
Data envelopment analysis
Ranking
Weighting scheme
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Summary:•Suggests a new perspective for ranking under DEA cross efficiency settings.•Exploits the existence of separate weighting schemes in DEA cross evaluation to build composite value systems.•Combines cross-efficiency, weighting schemes and OWA operators to provide a full ranking of DMUs.•Illustrates an application of the proposed method in ranking 15 baseball players. Data envelopment analysis (DEA) is one of the most powerful tools for ranking decision making units (DMUs). In this paper, we present a new perspective for ranking DMUs under a DEA peer-evaluation framework. We exploit the property of multiple weighting schemes generated over the cross evaluation process in developing a methodology that yields not only robust ranking patterns but also more realistic sets of weights for the DMUs. The robustness of the proposed methodology is evaluated using OWA combinations involving different minimax disparity models and different levels of optimism of the decision maker. We show that discrimination is boosted at each stage of the decision process. As an illustration, our approach is applied for ranking a sample of baseball players.
ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2018.01.022