A novel network data envelopment analysis model for evaluating green supply chain management

Seyed Mostafa Mirhedayatian, Majid Azadi, Reza Farzipoor Saen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

214 Citations (Scopus)

Abstract

Green supply chain management (GSCM) has become a method to improve environmental performance. Under stakeholder pressures, forces and regulations, companies need to improve the GSCM practice, which are effected by practices such as green purchasing, green design, product recovery, and collaboration with patrons and suppliers. As companies promote the GSCM, their economic performance and environmental performance will be enhanced. Hence, GSCM evaluation is very important for any company. One of the techniques that can be used for evaluating GSCM is data envelopment analysis (DEA). Traditional models of data envelopment analysis (DEA) are based upon thinking about production as a "black box". One of the drawbacks of these models is to omit linking activities. The objective of this paper is to propose a novel network DEA model for evaluating the GSCM in the presence of dual-role factors, undesirable outputs, and fuzzy data. A case study demonstrates the application of the proposed model. A case study demonstrates the applicability of the proposed model.

Original languageEnglish
Pages (from-to)544-554
Number of pages11
JournalInternational Journal of Production Economics
Volume147
Issue numberPART B
DOIs
Publication statusPublished - Jan 2014

Keywords

  • Dual-role factors
  • Fuzzy set
  • Green supply chain management (GSCM)
  • Network data envelopment analysis (NDEA)
  • Undesirable outputs

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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