Dynamic pricing in the newsvendor problem with yield risks

Nowadays supply chains are facing challenges in managing risk issues. Supply of raw materials may exhibit a random yield due to technical failure of production resources or supply disruption after a natural disaster. In case supply has a random yield, one way to reduce supply chain loss is by introducing a dynamic pricing policy, with the aim of manipulating demand in the market while inducing the customer to buy substitute products temporarily. This paper investigates newsvendor problem with random demand and random yields, in which the price decision will be postponed and determined upon recognition of random yield and prior to realising demand uncertainties. With the objective of maximising expected profits, we develop the optimal price and ordering decisions in the system, while comparing the system's performances with dynamic and fixed pricing policies. Further, we investigate the conditions of adapting dynamic pricing policy. An interesting finding shows that such a policy brings increase in benefit when demand uncertainty is small. The outcome of this research provides alternative solutions in designing a robust supply chain.