dc.contributor.author | Izadikhah, Mohammad | |
dc.contributor.author | Azadi, Elnaz | |
dc.contributor.author | Azadi, Majid | |
dc.contributor.author | Saen, Reza Farzipoor | |
dc.contributor.author | Toloo, Mehdi | |
dc.date.accessioned | 2020-10-14T14:55:51Z | |
dc.date.available | 2020-10-14T14:55:51Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Annals of Operations Research. 2020. | cs |
dc.identifier.issn | 0254-5330 | |
dc.identifier.issn | 1572-9338 | |
dc.identifier.uri | http://hdl.handle.net/10084/142322 | |
dc.description.abstract | Owing 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.iso | en | cs |
dc.publisher | Springer Nature | cs |
dc.relation.ispartofseries | Annals of Operations Research | cs |
dc.relation.uri | http://doi.org/10.1007/s10479-020-03765-8 | cs |
dc.rights | Copyright © 2020, Springer Nature | cs |
dc.subject | performance measurement | cs |
dc.subject | sustainable supply chain management (SSCM) | cs |
dc.subject | data envelopment analysis (DEA) | cs |
dc.subject | network DEA (NDEA) | cs |
dc.subject | stochastic network DEA | cs |
dc.title | Developing a new chance constrained NDEA model to measure performance of sustainable supply chains | cs |
dc.type | article | cs |
dc.identifier.doi | 10.1007/s10479-020-03765-8 | |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.identifier.wos | 000562937200001 | |