Optimal sampling policies in a centralised supply chain with demands affected by product quality

We address a quality control problem frequently encountered in multi-stage pharmaceutical supply chains transporting drugs from a producer to a wholesaler and eventually to retailers (pharmacies). Depending on the transportation modes and storage methods used, the stages may expose the drugs to hostile environments, such as extreme temperatures, which may impact the quality. To study the performance of such a supply chain, we incorporate the effect of quality on demand with the Neyman–Pearson statistical framework. We show that in a centralised supply chain the optimal inspection strategies for the parties depend on parameters, which signify the relative importance of price and the impact of quality on demand. In particular, we find that the ratio between the customer demand under perfect product quality and the customer sensitivity to quality plays a critical role in selecting optimal inspection policies.