Evaluating and Selecting a Supplier in a Healthcare Supply Chain Using the Technique for Order Performance by Similarity to Ideal Solution Under Intuitionistic Fuzzy Environment

Supplier selection is an important aspect of effective supply chain management (SCM) and has implications in risk mitigation, profitability, and cultivating robust supplier-buyer relationships.In this dynamic and competitive landscape, it is essential to implement multi-criteria decisionmaking (MCDM) methods.Therefore, we employ the technique for order performance by similarity to ideal solution (TOPSIS), an MCDM technique, to evaluate the best supplier.Our approach incorporates fuzzy intuitionistic data and leverages the insights of decision-makers.Seven essential criteria, namely, supplier relationships, patient demand, quality, profitability, delivery time, post-delivery service, and patient cost, are integral to this assessment.This methodology is particularly valuable in situations that require swift supplier selection and those that cater to the urgent supplier needs of pharmacists.While our focus was on a specific context, the adaptability of this approach enables researchers to customize it for their respective fields by incorporating pertinent criteria based on expert inputs.Supplier evaluation within the healthcare sector, focusing on sector-specific metrics such as antibiotic drug selection, remains a relatively unexplored area.To address this issue, we present a comprehensive framework to select antibiotic drug suppliers.