Capacity management is challenging. Many decisions regarding capacity are made before full information is known, often requiring large and irrevocable expenditures. Moreover, the consequences of wrong capacity decisions critically affect the firm’s bottom line. In recent years, the capacity decision has become of particular interest, reflecting two principal trends. First, advances in information technology that provide huge amounts of data about operations and demand offer firms potential to utilize this big data in making capacity decisions. Second, although supply chains today are highly decentralized with complex topologies, many buying firms and suppliers aim to maintain tight relationships with initiatives such as supplier development, among which capacity investment is an important strategic decision. Corresponding to the two streams, we analyze a firm’s capacity management decision, how much capacity a firm should have and why, at both intra-firm and inter-firm levels. At the intra-firm level, we investigate how a firm should learn demand information and leverage the information in capacity decisions. In Chapter II, we formulate a firm’s capacity adjustment plan when the demand distribution is unknown as a stochastic dynamic program, and derive the optimal policy and date-driven heuristics. At the inter-firm level, using game theory, we examine how a firm should manage its capacity at a shared supplier given two contractual constraints: exclusive, where other firms cannot access the leftover, and first-priority, where they can. In Chapter III where firms compete and the capacity cost consists of a fixed and a variable portion, we find that firms tend to invest more aggressively under the exclusive contract. Therefore, sometimes the firm may benefit from letting a competitor free-ride on the invested capacity. In Chapter IV where firms may or may not compete and the capacity cost has a variable portion, we characterize two equilibria: a prisoner’s dilemma, where both firms choose the exclusive capacity which is not Pareto-optimal, and a free-rider equilibrium, where one firm chooses the first-priority capacity and allows the other with exclusive capacity to free ride. Both equilibria can be sustained when the firms serve independent markets, but not when they compete in a Cournot market.
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Capacity Management:Intra-Firm and Inter-Firm Perspectives.