A Mathematical Model for Analyzing Medicine Supply Chains’ System Interactive Risks Using Bayesian Belief Networks

Risk and failure in the supply chain can have a significant and negative effect on the short-term and long-term performance of the participants in the chain. Therefore, this research has an innovative look for a mathematical model for analyzing the interactive risks of the supply chain system using Bayesian belief networks. The study is descriptive in terms of purpose and has descriptive nature. The research community is classified into the two categories of academic experts and operational experts. In this research, information on the drug supply chain of the Imam Reza Hospital of Mashhad was obtained and analyzed using the bayesian belief network modeling process. The findings of this study show that Bayesian belief networks are much better than traditional risk analysis methods, because it can analyze basic risk analysis, including risk ranking and scenario analysis, and other essentials. BBN can also display different uncertainties in the language of probabilities with an appropriate visual form and provide more comprehensive view of the supply chain conditions and its risks