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

Mohammad Izadikhah; Elnaz Azadi; Majid Azadi; Reza Farzipoor Saen; Mehdi Toloo

doi:10.1007/s10479-020-03765-8

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

Mohammad Izadikhah, Elnaz Azadi, Majid Azadi, Reza Farzipoor Saen^*, Mehdi Toloo

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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	https://doi.org/10.1007/s10479-020-03765-8
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.

Keywords

Data envelopment analysis (DEA)
Network DEA (NDEA)
Performance measurement
Stochastic network DEA
Sustainable supply chain management (SSCM)

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10.1007/s10479-020-03765-8

Cite this

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title = "Developing a new chance constrained NDEA model to measure performance of sustainable supply chains",

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.",

keywords = "Data envelopment analysis (DEA), Network DEA (NDEA), Performance measurement, Stochastic network DEA, Sustainable supply chain management (SSCM)",

author = "Mohammad Izadikhah and Elnaz Azadi and Majid Azadi and {Farzipoor Saen}, Reza and Mehdi Toloo",

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 (GA{\v C}R 19-13946S) for the supports. ",

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AU - Izadikhah, Mohammad

AU - Azadi, Elnaz

AU - Azadi, Majid

AU - Farzipoor Saen, Reza

AU - Toloo, Mehdi

N1 - 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.

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N2 - 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.

AB - 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.

KW - Data envelopment analysis (DEA)

KW - Network DEA (NDEA)

KW - Performance measurement

KW - Stochastic network DEA

KW - Sustainable supply chain management (SSCM)

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UR - https://link.springer.com/article/10.1007/s10479-020-03765-8

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JO - Annals of Operations Research

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IS - 2

ER -

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

Abstract

Bibliographical note

Keywords

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