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dc.contributor.authorMehdizadeh, S.
dc.contributor.authorAmirteimoori, A.
dc.contributor.authorVincent, Charles
dc.contributor.authorBehzadi, M.H.
dc.contributor.authorKordrostami, S.
dc.date.accessioned2020-01-16T14:20:38Z
dc.date.available2020-01-16T14:20:38Z
dc.date.issued2020
dc.identifier.citationMehdizadeh S, Amirteimoori A, Vincent C et al (2020) Measuring the efficiency of two stage network processes: a satisficing DEA approach. Journal of the Operational Research Society. Accepted for Publication.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17577
dc.descriptionNoen_US
dc.description.abstractRegular Network Data Envelopment Analysis (NDEA) models deal with evaluating the performance of a set of decision-making units (DMUs) with a two-stage construction in the context of a deterministic data set. In the real world, however, observations may display a stochastic behavior. To the best of our knowledge, despite the existing research done with different data types, studies on two-stage processes with stochastic data are still very limited. This paper proposes a two-stage network DEA model with stochastic data. The stochastic two-stage network DEA model is formulated based on the satisficing DEA models of chance-constrained programming and the leader-follower concepts. According to the probability distribution properties and under the assumption of the single random factor of the data, the probabilistic form of the model is transformed into its equivalent deterministic linear programming model. In addition, the relationship between the two stages as the leader and the follower, respectively, at different confidence levels and under different aspiration levels, is discussed. The proposed model is further applied to a real case concerning 16 commercial banks in China in order to confirm the applicability of the proposed approach at different confidence levels and under different aspiration levels.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1080/01605682.2019.1671151
dc.subjectStochastic DEAen_US
dc.subjectSatisficing DEAen_US
dc.subjectChance constrained modelen_US
dc.subjectTwo stage systemen_US
dc.subjectPerformance evaluationen_US
dc.subjectEfficiencyen_US
dc.titleMeasuring the efficiency of two stage network processes: a satisficing DEA approachen_US
dc.status.refereedYesen_US
dc.date.Accepted2019-08-29
dc.date.application2020-03-24
dc.typeArticleen_US
dc.type.versionNo full-text in the repositoryen_US


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