Conceptualising A Supply And Demand Resilience Methodology: A Hybrid Dematel-Topsis-Possibilistic Multi-Objective Optimization Approach

COMPUTERS & INDUSTRIAL ENGINEERING(2021)

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摘要
Due to the growing globalisation and strategic sourcing, supply chains (SCs) are confronted with potential dis-ruptions. 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 SCR. Also, organisations require resilience 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 SCR. 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 ef-ficiency; and (2) elevate the company's resilience 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 inves-tigation. Furthermore, the suppliers' assessment output was validated by using two sensitivity analysis ap-proaches including criteria weight variation and other multi-attribute decision making (MADM) approaches.
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关键词
COVID-19 disruption, Resilient sourcing, Supply chain resilience, Multi-objective programming, MCDM
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