Developing a new chance constrained NDEA model to measure performance of sustainable supply chains

Izadikhah, M; Azadi, E; Azadi, M; Farzipoor Saen, R; Toloo, M

Developing a new chance constrained NDEA model to measure performance of sustainable supply chains

Izadikhah, M Azadi, E Azadi, M Farzipoor Saen, R Toloo, M

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Annals of Operations Research, 2022, 316, (2), pp. 1319-1347
Issue Date:: 2022-01-01

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Field	Value	Language
dc.contributor.author	Izadikhah, M
dc.contributor.author	Azadi, E
dc.contributor.author	Azadi, M
dc.contributor.author	Farzipoor Saen, R
dc.contributor.author	Toloo, M
dc.date.accessioned	2023-03-22T00:35:16Z
dc.date.available	2023-03-22T00:35:16Z
dc.date.issued	2022-01-01
dc.identifier.citation	Annals of Operations Research, 2022, 316, (2), pp. 1319-1347
dc.identifier.issn	0254-5330
dc.identifier.issn	1572-9338
dc.identifier.uri	http://hdl.handle.net/10453/168020
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.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Annals of Operations Research
dc.relation.isbasedon	10.1007/s10479-020-03765-8
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	01 Mathematical Sciences, 08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services
dc.subject.classification	Operations Research
dc.title	Developing a new chance constrained NDEA model to measure performance of sustainable supply chains
dc.type	Journal Article
utslib.citation.volume	316
utslib.for	01 Mathematical Sciences
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2023-03-22T00:35:15Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	316
utslib.citation.issue	2

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.

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http://hdl.handle.net/10453/168020