A real-option approach to mitigate disruption risk in the supply chain

We study the optimal ordering decision policy for a retailer who is exposed to supply disruptions along with correlated demand and price uncertainty. A new modeling approach to optimize inventory planning in a two-stage supply chain is proposed in order to choose an optimal order quantity that maximizes the expected terminal profit. With the aid of real-option pricing methodology, we derive an explicit form of the profit function and adopt a dual sourcing strategy that allows for disruption risk mitigation. Then we drive a solution to the given problem, facilitated by the use of an actuarial technique. This study reveals that when demand and price are assumed to be stochastic, the objective function features four terms that resemble the pay-off of real-options, corresponding to risks of shortage and write-off. Therefore, the optimization problem can be reduced to determining the fair value of those options. The model is contextualized using an example from the Chinese dairy market. Sensitivity experiments are performed to demonstrate the robustness of the developed approach. The results can be used by managers to decide on ordering quantities at the beginning of each period, which maximizes the expected profit, while also considering the disruption risk of the primary supplier and correlated demand and price uncertainty.