Modeling Shock Propagation on Supply Chain Networks: A Stochastic Logistic-Type Approach

Supply Chains have been more and suffering from unexpected industrial, natural events, or epidemics that might disrupt the normal flow of materials, information, money. The recent pandemic triggered by outbreak new COVID-19 has pointed out increasing vulnerability supply chain networks, prompting companies (and governments) to implement specific policies actions control reduce spread disease across network, cope with exogenous shocks. In this paper, we present a stochastic Susceptible-Infected-Susceptible (SIS) framework model different distribution networks determine social distancing/treatment in case local global networks. We highlight relevance adaptability flexibility decisions unstable unpredictable scenarios.