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dc.contributor.authorLandete, Mercedes-
dc.contributor.authorMonge Ivars, Juan Francisco-
dc.contributor.authorRuiz, José L.-
dc.contributor.otherDepartamentos de la UMH::Estadística, Matemáticas e Informáticaes
dc.date.accessioned2018-12-13T10:08:40Z-
dc.date.available2018-12-13T10:08:40Z-
dc.date.created2017-05-29-
dc.date.issued2018-12-13-
dc.identifier.issn0957-4174-
dc.identifier.urihttp://hdl.handle.net/11000/4934-
dc.description.abstractIn 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 playerses
dc.description.sponsorshipThis research has been partly supported by the Spanish Ministerio de Economía y Competitividad , through grant MTM2013-43903-P-
dc.description.sponsorshipThis research has been partly supported by the Spanish Ministerio de Economía y Competitividad , through grant MTM2015-68097-P-
dc.description.sponsorshipThis research has been partly supported by the Spanish Ministerio de Economía y Competitividad , through grant MTM2016- 76530-R (AEI/FEDER, UE).-
dc.formatapplication/pdfes
dc.format.extent10es
dc.language.isoenges
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.subjectData envelopment analysises
dc.subjectModel specificationes
dc.subjectEfficiency measurementes
dc.subjectRobustnesses
dc.subject.other517 - Análisises
dc.titleRobust DEA efficiency scores: A probabilistic/combinatorial approaches
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1016/j.eswa.2017.05.072-
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.eswa.2017.05.072-
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