A fuzzy expected value approach under generalized data envelopment analysis

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dc.cclicenceN/Aen
dc.contributor.authorGhasemi, M. R.en
dc.contributor.authorIgnatius, J.en
dc.contributor.authorLozano, S.en
dc.contributor.authorEmrouznejad, A.en
dc.contributor.authorHatami-Marbini, A.en
dc.date.accessioned2017-02-27T10:18:03Z
dc.date.available2017-02-27T10:18:03Z
dc.date.issued2015-07-09
dc.description.abstractFuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models – fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models – and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.en
dc.funderN/Aen
dc.identifier.citationGhasemi, M. R. et al. (2015) A fuzzy expected value approach under generalized data envelopment analysis. Knowledge-Based Systems, 89, pp. 148-159en
dc.identifier.doihttps://doi.org/10.1016/j.knosys.2015.06.025
dc.identifier.urihttp://hdl.handle.net/2086/13330
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherElsevieren
dc.researchinstituteCentre for Enterprise and Innovation (CEI)en
dc.subjectData envelopment analysisen
dc.subjectGeneralized data envelopment analysisen
dc.subjectFuzzy expected valueen
dc.subjectSuper-efficiencyen
dc.subjectSymmetric and asymmetric fuzzy numbersen
dc.titleA fuzzy expected value approach under generalized data envelopment analysisen
dc.typeArticleen

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