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

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

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


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 & Industrial Engineering
Publication statusPublished - Oct 2021


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


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