Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/4934

Robust DEA efficiency scores: A probabilistic/combinatorial approach


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Title:
Robust DEA efficiency scores: A probabilistic/combinatorial approach
Authors:
Landete Ruiz, Mercedes
Monge Ivars, Juan Francisco
Ruiz, José L.
Department:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Issue Date:
2017-05-29
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
Keywords/Subjects:
Data envelopment analysis
Model specification
Efficiency measurement
Robustness
Type of document:
application/pdf
Access rights:
info:eu-repo/semantics/openAccess
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