Sustainability assessment of supply chains by inverse network dynamic data envelopment analysis

M. Kalantary*, R. Farzipoor Saen, A. Toloie Eshlaghy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


This paper focuses on assessing sustainability of supply chains. This paper, at first, proposes network dynamic Range Adjusted Measure (RAM) model. Then, an inverse version of network dynamic RAM model is proposed. The proposed inverse network dynamic Data Envelopment Analysis (DEA) model changes both inputs and outputs of Decision-Making Units (DMUs) so that existing efficiency scores of DMUs remain unchanged. We change inputs and outputs without any modification in efficiency score of DMU under evaluation, while inputs and outputs may have a large range. A case study shows the efficacy of the proposed model.

Original languageEnglish
Pages (from-to)3723-3743
Number of pages21
JournalScientia Iranica
Issue number6E
Publication statusPublished - Nov 1 2018


  • Data Envelopment Analysis (DEA)
  • Dynamic DEA.
  • Inverse data envelopment analysis
  • Network DEA
  • Range Adjusted Measure (RAM)
  • Sustainable Supply Chain Management (SSCM)

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Chemistry (miscellaneous)
  • Civil and Structural Engineering
  • Materials Science (miscellaneous)
  • General Engineering
  • Mechanical Engineering
  • Physics and Astronomy (miscellaneous)
  • Industrial and Manufacturing Engineering

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