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.
| Original language | English |
|---|---|
| Pages (from-to) | 1319-1347 |
| Number of pages | 29 |
| Journal | Annals of Operations Research |
| Volume | 316 |
| Issue number | 2 |
| Early online date | 27 Aug 2020 |
| DOIs | |
| Publication status | Published - Sept 2022 |
Bibliographical note
Funding Information:The authors would like to thank two anonymous Reviewers for their insightful and constructive comments and suggestions. Furthermore, the fifth author would like to appreciate Czech Science Foundation (GAČR 19-13946S) for the supports.
Funding
The authors would like to thank two anonymous Reviewers for their insightful and constructive comments and suggestions. Furthermore, the fifth author would like to appreciate Czech Science Foundation (GAČR 19-13946S) for the supports.
Keywords
- Data envelopment analysis (DEA)
- Network DEA (NDEA)
- Performance measurement
- Stochastic network DEA
- Sustainable supply chain management (SSCM)