Barrier Analysis for Supply Chain Coordination in Auto-Parts Manufacturing During Pandemic Disruption

Abstract The COVID-19 outbreak negatively affected global markets and disrupted supply chains, particularly in manufacturing industries. Pandemic diseases can be classified as disruption risks because they can significantly affect supply chain structures and operations. In such situations, the side effects of COVID-19 create numerous barriers, hindering the correct functioning of supply chain sectors. Therefore, the first and most crucial step is to identify these barriers and then prioritise their resolution based on their importance. This paper aims to propose a decision-making approach that can address this problem. First, we use the Material, Management, Operation, Guidelines, Logistics, and Evaluation (MMOG/LE) model to identify the barriers that emerged from the COVID-19 outbreak in a supply chain. Next, the fuzzy Best–Worst Method (BWM) is applied to rank and prioritise barriers for managerial intervention based on their weights. We apply the proposed approach to an auto-parts manufacturing case study to validate and illustrate its applicability. The study's results indicate that MMOG/LE has identified 10 barriers, with demand forecasting being the top priority and non-agreed safety regulations being the lowest priority when it comes to fuzzy BWM results.