A fuzzy rough network data envelopment analysis approach for evaluating the sustainability of supply chains: a case study in the pasta industry

Seyed Amir Hossein Sadeghi, Reza Farzipoor Saen*, Abbas Toloie Eshlaghy, Mahmoud Modiri

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Evaluation of the sustainability of supply chains is a complex decision-making problem. One of the techniques, which are used for assessing the sustainability of supply chains is data envelopment analysis (DEA). Conventional DEA models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration the internal interactions of DMUs. Also, they assume inputs and outputs are crisp. In this research, the network DEA (NDEA) model for assessing the sustainability of supply chains in the presence of fuzzy rough data is developed. The main contribution of this paper is to develop a novel NDEA model in the existence of internal and external uncertainties. To validate the proposed model, a case study for evaluating the sustainability of the supply chain in the pasta industry is presented.

Original languageEnglish
JournalJournal of Decision Systems
Publication statusPublished - Mar 23 2023


  • Data envelopment analysis (DEA)
  • fuzzy rough data
  • network data envelopment analysis (NDEA)
  • sustainable supply chain management

ASJC Scopus subject areas

  • Management Information Systems
  • Library and Information Sciences

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