Risk management of supply chain disruptions: An epidemic modeling approach

Abstract

Quality issues in supply networks can adversely affect the performance of suppliers and their downstream customers. Since suppliers might fail to comply with quality guidelines, decentralized quality controls by each firm in a supply network may be insufficient; thus, a complete network perspective on risk management could help to minimize supply disruptions. Here, we develop a novel modeling framework drawing on epidemiology, to demonstrate how network structure impacts the propagation of quality issues—akin to the spread of an infectious disease. We formulate an SIS model in which nodes represent individual suppliers while directed edges represent the movement of goods between suppliers; these nodes can be either susceptible (S) to or infected (I) by a disruption. Applying the model to 21 real-world networks, we find that a quality issue’s magnitude depends strongly on its origin node and the network archetype. The network’s maximum Authority value—based on the relationship between relevant authoritative nodes and hub nodes— is highly correlated with the extent of a supply disruption in our simulation. We examine different network-level strategies for containing an outbreak and find that improving quality control at critical nodes—those characterized by a high Authority value or customer proximity—is an effective measure. Adjusting the network structure by focusing on an upstream-centric flow of goods, thereby reducing the maximum Authority value, decreases vulnerability to quality issues. Managers can reduce the impact of quality disruptions through a combination of conventional firm-level strategies and novel network risk management strategies.