| Issue |
RAIRO-Oper. Res.
Volume 55, 2021
Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
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|---|---|---|
| Page(s) | S21 - S49 | |
| DOI | https://doi.org/10.1051/ro/2019059 | |
| Published online | 09 February 2021 | |
Recommending investment opportunities given congestion by adaptive network data envelopment analysis model: Assessing sustainability of supply chains
1
Department of Operations Research, Faculty of Management and Accounting, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
2
Young Researchers and Elite Club, Karaj Branch, Islamic Azad University, Karaj, Iran.
3
Faculty of Business, Sohar University, Sohar, Oman.
* Corresponding author: farzipour@yahoo.com
Received:
7
November
2018
Accepted:
27
May
2019
Nowadays, forward-thinking companies move beyond conventional structures of organizations and consider all parties of the supply chain. The objective of this paper is to present an adaptive network data envelopment analysis (DEA) model to evaluate overall and divisional efficiency of sustainable supply chains in the presence of desirable and undesirable outputs. Our adaptive network DEA model can assess overall and divisional efficiency of supply chains given managerial and natural disposability. Also, it suggests new investment opportunity given congestion type. A case study is presented.
Mathematics Subject Classification: 90C08
Key words: Network data envelopment analysis (NDEA) / congestion / Sustainable supply chain management (SSCM) / Range-adjusted measure (RAM) / sustainable investment / undesirable outputs
© EDP Sciences, ROADEF, SMAI 2021
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