Value of the stochastic efficiency in data envelopment analysis

Vincent Charles, Fabien Cornillier

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

18 Citas (Scopus)

Resumen

This article examines the potential benefits of solving a stochastic DEA model over solving a deterministic DEA model. It demonstrates that wrong decisions could be made whenever a possible stochastic DEA problem is solved when the stochastic information is either unobserved or limited to a measure of central tendency. We propose two linear models: a semi-stochastic model where the inputs of the DMU of interest are treated as random while the inputs of the other DMUs are frozen at their expected values, and a stochastic model where the inputs of all of the DMUs are treated as random. These two models can be used with any empirical distribution in a Monte Carlo sampling approach. We also define the value of the stochastic efficiency (or semi-stochastic efficiency) and the expected value of the efficiency.

Idioma originalInglés
Páginas (desde-hasta)349-357
Número de páginas9
PublicaciónExpert Systems with Applications
Volumen81
DOI
EstadoPublicada - 15 set. 2017
Publicado de forma externa

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