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https://hdl.handle.net/11000/4934
Robust DEA efficiency scores: A probabilistic/combinatorial approach
Title: Robust DEA efficiency scores: A probabilistic/combinatorial approach |
Authors: Landete, Mercedes Monge Ivars, Juan Francisco Ruiz, José L. |
Department: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Issue Date: 2017-05-29 |
URI: http://hdl.handle.net/11000/4934 |
Abstract:
In this paper we propose robust efficiency scores for the scenario in which the specification of the in- puts/outputs to be included in the DEA model is modelled with a probability distribution. This probabilis- tic approach allows us to obtain three different robust efficiency scores: the Conditional Expected Score, the Unconditional Expected Score and the Expected score under the assumption of Maximum Entropy principle. The calculation of the three efficiency scores involves the resolution of an exponential num- ber of linear problems. The algorithm presented in this paper allows to solve over 200 millions of linear problems in an affordable time when considering up 20 inputs/outputs and 200 DMUs. The approach proposed is illustrated with an application to the assessment of professional tennis players
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Keywords/Subjects: Data envelopment analysis Model specification Efficiency measurement Robustness |
Knowledge area: Análisis |
Type of document: application/pdf |
Access rights: info:eu-repo/semantics/openAccess |
DOI: http://dx.doi.org/10.1016/j.eswa.2017.05.072 |
Appears in Collections: Artículos Estadística, Matemáticas e Informática
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