Green supply chains and performance evaluation: A multiplier network analytics model with common set of weights

Elnaz Azadi, Zohreh Moghaddas, Reza Farzipoor Saen*, Abbas Mardani, Majid Azadi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Supply chains (SCs) are considered complicated systems consisting of many interactions, components, and flows. Green SCs have forced policymakers and managers to pay more attention to the environment rather than only focus on the economic aspect. Performance evaluation of complex systems, including green SCs is a critical issue in organizations. Most of the current models are unable to evaluate the performance of green SCs in an integrated framework. To address this issue in organizations, in this paper, our objective is to propose a powerful network data envelopment analysis (NDEA) to evaluate green SCs. The NDEA method is considered an effective approach to deal with complex settings including SCs. Our multiplier NDEA model for cost efficiency evaluation is presented based on the cost production possibility set (PPS). A common set of weight model based on cost PPS is formulated. The proposed model maximizes the cost-efficiency of all decision making units (DMUs), simultaneously. In our model, the common set of weights and cost efficiency of each stage and the overall cost are obtained. Finally, the developed model for assessing the sustainably of SCs in the wire and cable industry is applied. The results show how well our developed model, based on common set of weights, can evaluate the performance of green SCs compared to the classic models.

Original languageEnglish
Article number137377
JournalJournal of Cleaner Production
Publication statusPublished - Jul 20 2023


  • Common set of weights
  • Green supply chain
  • Network data envelopment analysis (NDEA)

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Environmental Science(all)
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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