Assessing sustainability of supply chains by chance-constrained two-stage DEA model in the presence of undesirable factors

Mohammad Izadikhah, Reza Farzipoor Saen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)


Sustainable supply chain is recognized as a key component of corporate responsibility. Despite conventional data envelopment analysis (DEA) models that view decision making units (DMUs) as black boxes, two-stage DEA models take into account intermediate measures within a DMU. However, there might be stochastic data. Objective of this paper is to present a new stochastic two-stage DEA model in the presence of undesirable data. We present some linear models that obtain lower and upper bounds of efficiencies of stages 1 and 2. Also, we propose a linear model that calculates overall efficiency of DMUs. Meanwhile, we extend our proposed model for dealing with stochastic data in the presence of undesirable data. A case study demonstrates applicability of our approach.

Original languageEnglish
Pages (from-to)343-367
Number of pages25
JournalComputers and Operations Research
Publication statusPublished - Dec 2018


  • Chance-constrained data envelopment analysis (DEA)
  • Efficiency
  • Intermediate products
  • Stochastic data
  • Sustainability of supply chain
  • Two-stage DEA model
  • Undesirable data

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research

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