An In-Depth Analysis of Contingent Sourcing Strategy for Handling Supply Disruptions

In this paper, we consider a make-to-stock producti-on-inventory system where a manufacturer's production may be entirely interrupted due to a supply disruption. Customers react dynamically to the subsequent inventory shortage, depending on factors including market condition, customer characteristic, and behavioral interaction. The manufacturer can adopt contingent sourcing to manage the disruption. Consequently, the postdisruption demand and inventory exhibit complicated dynamics in terms of customer behavior, demand recovery, and the adoption of contingent sources. We first model and forecast the postdisruption customer behavior. Customers are classified into two types based on brand loyalty and the interaction is captured as "demand learning" within each type. Using differential models, we analytically characterize customers' postdisruption behavior in five possible scenarios, depending on customers' constitution, transient reaction, brand loyalty, and competition intensity. Next, we propose dynamic contingent sourcing strategies to mitigate the supply disruption, and the optimal sourcing time is derived. Finally, by conducting numerical analysis, we obtain further managerial insights on how to adapt dynamic contingent sourcing strategies according to various contributing factors.