Sustainable-resilient supplier evaluation for high-consumption drugs during COVID-19 pandemic using a data-driven decision-making approach

The recent pandemic of COVID-19 has had severe impacts on healthcare services especially the Food and Drug Administration for providing necessary medications patients. supplier selection problem in is a crucial problem. This research aims to develop data-driven model sustainable resilient evaluation. At outset, we identify related criteria based literature experts then calculate their weights using Fuzzy-Bests-Worst-Method (FBWM). Afterward, Fuzzy Inference System (FIS) method employed evaluate performance supplier. Finally, three different classification machine learning models are developed historical data every criterion also FIS output as target column. study provides 22 identified categorized into three-dimension (economic, social, environmental, resilient). results show that case managers pay more attention ‘Responsiveness’ ‘Ability’. two-stage indicate 35 records were evaluated very poor, 70 ones 98 moderate, 90 good, 57 good ones. Other companies could use same decision-making have better decision suppliers.