Evaluating the Performance of a Safe Insulin Supply Chain Using the AHP-TOPSIS Approach

Abstract

People with type 1 diabetes require insulin, a lifesaving and essential medication, to maintain their blood sugar levels below dangerous levels. Unfortunately, the insulin industry faces supply and affordability issues, and patients and their families face an enormous burden. As a result of high prices and lack of availability, individuals are turning to other options for purchasing insulin, such as online pharmacies, which may or may not be legitimate. Despite the necessity of safe insulin for diabetics in the legitimate Pharmaceutical Supply Chain (PSC), few researchers have considered implementing strategies to maximize patient safety for purchasing insulin. Therefore, the current research seeks to bridge this gap and provide cohesive information on overcoming this challenge and maximizing insulin safety. This study employs a Multi-Criteria Decision-Making (MCDM) model that combines Supply Chain Operations Reference (SCOR) metrics, Analytic Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a model that can prioritize and select the best criteria for maximizing insulin safety and achieving the study objective. A comparison of two insulin supply chain scenarios was performed. As a result of this research, adding a traceability technology to the insulin supply chain, specifically blockchain (T42) in scenario 2 provides the best results to the supply chain for maximizing and ensuring the safety of insulin, as compared to scenario 1, where the final score achieved almost 71%. This research provides a useful tool for assessing the safety of other critical goods that customers value in strategic and complex decision-making. Academics, professionals, and decision-makers can benefit from this research using a rigorous scientific decision-support system.