Modelling flexible decisions about sustainable supplier selection in multitier sustainable supply chain management

Li Cui, Hao Wu, Jing Dai

Research output: Journal PublicationArticlepeer-review

16 Citations (Scopus)

Abstract

Supplier selection is crucial decision for buying companies to develop sustainable supply chain strategy. Not only first-tier suppliers but also lower-tier suppliers would influence the buyer’s sustainability performance. Thus, buying companies need to consider extending their sustainable supply chain plan to multitier suppliers, and develop multitier sustainable supply chain management (MT-SSCM). Sustainable supplier selection (SSS), as an important SSCM practice, can effectively enhance the sustainable competitiveness of supply chains. However, there are few theoretical studies on SSS under MT-SSCM, which affects the decision-making efficiency of organisations. In general, there are three multitier supply chain (MTSC) structures: open MTSC, closed MTSC and transitional MTSC structures. Because some traditional decision models cannot deal with a variety of structures at the same time, this study proposes a hybrid model that integrates fuzzy set theory, stepwise weight assessment ratio analysis and a Bayesian network to evaluate the critical SSS criteria in three MTSC structures. Finally, a case of a Chinese buying company is used to verify the flexibility and applicability of the proposed model, and some suggestions are provided for the practitioners to select sustainable suppliers in different MTSC structures.

Original languageEnglish
Pages (from-to)4603-4624
Number of pages22
JournalInternational Journal of Production Research
Volume61
Issue number14
DOIs
Publication statusPublished Online - 19 May 2021

Keywords

  • Bayesian network
  • Multitier sustainable supply chain management
  • SWARA
  • flexible decisions
  • fuzzy set theory
  • sustainable supplier selection

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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