Prioritizing Critical Factors for Medical Supply Hub Location under Post-Pandemic Demand Uncertainty

The COVID-19 pandemic revealed significant weaknesses in global and regional medical supply chains, particularly in the timely and efficient distribution of critical medical supplies. In response to these challenges, the strategic selection of distribution hub locations has become increasingly vital to ensure rapid response and equitable access during future health crises. However, this decision-making process is inherently complex due to high levels of uncertainty in post-pandemic demand patterns and the subjective judgments of decision-makers. This study aims to address these challenges by incorporating expert opinions under uncertainty using the Bayesian Best-Worst Method (B-BWM). B-BWM allows for a robust integration of expert preferences and uncertainty, providing probabilistic weights for each criterion rather than deterministic scores. Through consultations with experts, the study evaluates factors such as accessibility, infrastructure resilience, proximity to population centers, and scalability. Results show that "Accessibility" was identified as the most important criterion (weight = 0.208), followed by "Infrastructure Reliability" (0.157) and "Disaster Risk" (0.150). Other criteria such as Demand Flexibility (0.092), Population Coverage (0.084), Regulatory (0.091), Cost Efficiency (0.084), Scalability (0.084), and Social Acceptance (0.050) received relatively lower weights. This study offers a systematic approach to decision-making under uncertainty, contributing to the development of more resilient and responsive healthcare supply networks. The results provide practical insights for policymakers and logistics planners in designing distribution infrastructures for critical medical supplies.