Innovative Simulation Model for Analyzing the Effects of Supplier Disruptions on Supply Chain Distributors

Abstract

In the current business landscape, supply chain disruptions, have become increasingly prevalent, impacting operational efficiency and profitability. These disruptions have resulted in significant ripple effects throughout the supply chain, resulting in increased delivery times and lost sales that, in extreme cases, can reach Statistics up to 76,169 units. Despite the growing recognition of the importance of managing these disruptions, comprehensive models that quantitatively assess their propagation and impact on downstream distributors are lacking. This study aims to address this gap by developing a discrete-time Markov chain model integrated with a Baye.sian network to analyze the ripple effects of supplier disruptions on distributors. The research focuses on key metrics such as lead times and lost sales, revealing that disruptions can increase lost sales by up to 44% in definite scenarios. By employing this dynamic modeling approach, the study illustrates the pathways through which disruptions propagate, identifies critical risk factors, and evaluates supplier vulnerabilities. The findings underscore the necessity for robust supply chain strategies to mitigate the effects of disruptions, providing valuable insights for managers to make informed decisions regarding supplier selection and inventory management. The scientific implications of this research contribute to the evolution of more comprehensive frameworks for disruption management in multi-tier supply chains, paving the way for future studies to expand on these insights and enhance supply chain resilience.