Conceptualising a supply and demand resilience methodology: A hybrid DEMATEL-TOPSIS-possibilistic multi-objective optimization approach

A. Mohammed*, B. Naghshineh, V. Spiegler, H. Carvalho

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Due to the growing globalisation and strategic sourcing, supply chains (SCs) are confronted with potential disruptions. Companies need to make further efforts and investments to improve their supply chain resilience (SCR) in becoming more prepared to minimise disruption risks. Sourcing is one of the main, strategic, key factors towards SC resilience. Also, organisations require resiliency in demand fulfilment to handle volatile marketplaces. This paper presents a methodology towards SCR to both supply and demand variations motivated by a real case study of a manufacturing company that works to improve its SC resilience. To this end, a hybrid integrated multi-attribute decision making-possibilistic bi-objective programming model (MADM-PBOPM) was developed. First, a new framework presenting pillars to assess suppliers’ resilience was developed based on a thorough literature review and decision makers’ input. Then, a DEMATEL-TOPSIS approach was proposed to quantify existing suppliers’ resilience and assess its performance. It also helped in categorising resilience pillars (RPs) as causes and effects. Thereafter, the obtained weights of suppliers and pillars were integrated into the developed PBOPM. The latter helps the purchasing team to (1) order materials from suppliers based on their resilience and performance efficiency; and (2) elevate the company's resiliency to uncertain demands fulfilment. Therefore, the developed methodology can potentially be used by the purchasing teams to build up SCs that are resilient to supply disruption and demand uncertainty. This MADM-PBOPM model was validated as part of the case study investigation. Furthermore, the suppliers’ assessment output was validated by using two sensitivity analysis approaches including criteria weight variation and other MADM approaches.

Original languageEnglish
Article number107589
Number of pages19
JournalComputers and Industrial Engineering
Volume160
Early online date3 Aug 2021
DOIs
Publication statusPublished - Oct 2021

Bibliographical note

Funding Information:
The authors would like to thank the Editor in Chief and Gest Editors and the anonymous referees whose thorough reviews and insightful comments made a valuable contribution to this work. The research leading to these results has received Research Project Funding from The Minister of Higher Education, Research, and Innovation of the Sultanate of Oman, under Commissioned Research Program, Contract NO. TRC/CRP/MU/COVID-19/20/15. Naghshineh and Carvalho acknowledge Fundação para a Ciência e a Tecnologia (FCT - MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI).

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

  • COVID-19 disruption
  • MCDM
  • Multi-objective programming
  • Resilient sourcing
  • Supply chain resilience

ASJC Scopus subject areas

  • General Computer Science
  • General Engineering

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