Sustainably resilient supply chains evaluation in public transport: A fuzzy chance-constrained two-stage DEA approach

Mohammad Izadikhah, Majid Azadi, Mehdi Toloo*, Farookh Khadeer Hussain

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

Owing to today's highly competitive market environments, substantial attention has been focused on sustainably resilient supply chains (SCs) over the last few years. Nevertheless, very few studies have focused on the efficiency evaluation analysis of the sustainability and resilience of SCs as an inevitable essential in any profitable business. This study aims to address this issue by proposing a novel fuzzy chance-constrained two-stage data envelopment analysis (DEA) model as an advanced and rigorous approach in the performance evaluation of sustainably resilient SCs. To the best of our knowledge, the current study is pioneering as it introduces a new fuzzy chance-constrained two-stage method that can be used to undertake the deterministic non-fuzzy programming of the proposed model. The proposed approach is validated and applied to evaluate a real case study including 21 major public transport providers in three megacities. The results demonstrate the advantages of the proposed approach in comparison to the existing approaches in the literature.

Original languageEnglish
Article number107879
JournalApplied Soft Computing
Volume113
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Data envelopment analysis
  • Fuzzy chance-constrained two-stage DEA
  • Performance evaluation and analysis
  • Public transport
  • Sustainably resilient supply chains

ASJC Scopus subject areas

  • Software

Cite this