| This dissertation studies capacity management in a decentralized supply chain with evolving demand information. In the first part (Chapter 2), we study the tactic use of advance demand information for production planning. We develop and analyze optimal policies for finite and infinite horizon inventory control problems with capacity limit and advance demand information for both zero and positive setup costs, and conduct numerical study to quantify the value of advance demand information and capacity.; In the second part, we study the strategic interaction between two supply chain members (supplier and manufacturer) when the manufacturer can observe a private forecast update. In Chapter 3, we study the supplier's contracting problem when he has to build capacity under asymmetric forecast information. We show that the capacity reservation contract and the advance purchase contract can both achieve credible information sharing and hence enable the supplier to make a better capacity decision. We also show that the advance purchase contract combined with a pay back contract can achieve channel coordination under asymmetric information. Through a numeric study, we compare the efficiency of the capacity reservation contract and the advance purchase contract, and find them to be complementary to each other.; In Chapter 4 we study the supplier's contracting problem when he has sufficient make-to-order capacity and the manufacturer orders after the forecast update. We propose and analyze the dual purchase contract, a type of price-only contract, as an alternative to the wholesale price contract. We establish the manufacturer's optimal response to the dual purchase contract and provide necessary and sufficient condition under which the dual purchase contract achieves strict Pareto improvement. We then extend the condition to cases where the supplier is risk averse or has a minimum production quantity. Through a numerical study, we find that the variability of demand and forecast uncertainties are key factors in determining the region of strict Pareto improvement. |
