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dc.contributor.authorIzadikhah, Mohammad
dc.contributor.authorAzadi, Elnaz
dc.contributor.authorAzadi, Majid
dc.contributor.authorSaen, Reza Farzipoor
dc.contributor.authorToloo, Mehdi
dc.date.accessioned2020-10-14T14:55:51Z
dc.date.available2020-10-14T14:55:51Z
dc.date.issued2020
dc.identifier.citationAnnals of Operations Research. 2020.cs
dc.identifier.issn0254-5330
dc.identifier.issn1572-9338
dc.identifier.urihttp://hdl.handle.net/10084/142322
dc.description.abstractOwing to the increasing importance of sustainable supply chain management (SSCM), it has received much attention from both corporate and academic over the past decade. SSCM performance evaluation plays a crucial role in organizations success. One of the practical techniques that can be used for SSCM performance assessment is network data envelopment analysis (NDEA). This paper develops a new NDEA for performance evaluation of SSCM in the presence of stochastic data. The proposed model can evaluate the efficiency of SSCM under uncertain conditions. A case study in the soft drinks industry is presented to demonstrate the efficacy of the proposed method.cs
dc.language.isoencs
dc.publisherSpringer Naturecs
dc.relation.ispartofseriesAnnals of Operations Researchcs
dc.relation.urihttp://doi.org/10.1007/s10479-020-03765-8cs
dc.rightsCopyright © 2020, Springer Naturecs
dc.subjectperformance measurementcs
dc.subjectsustainable supply chain management (SSCM)cs
dc.subjectdata envelopment analysis (DEA)cs
dc.subjectnetwork DEA (NDEA)cs
dc.subjectstochastic network DEAcs
dc.titleDeveloping a new chance constrained NDEA model to measure performance of sustainable supply chainscs
dc.typearticlecs
dc.identifier.doi10.1007/s10479-020-03765-8
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.identifier.wos000562937200001


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