This thesis investigates two issues in operations management. The first one is the dynamic pricing and inventory control problem of a retailer in the presence of strategic consumers with reference effects, and the second one is the performance analysis and optimal control of spectrum sharing networks.

In the first part, we consider a retailer that sells the same or different versions of the product season after season. At the beginning of each season (stage 1), the retailer places an order and sells the product at the full price. As the sales unfold, the retailer has an opportunity to mark down the price (stage 2) to match supply with demand. However, the retailer’s markdown strategies in past seasons give strategic consumers an incentive to time their purchases in future seaso...[ Read more ]

This thesis investigates two issues in operations management. The first one is the dynamic pricing and inventory control problem of a retailer in the presence of strategic consumers with reference effects, and the second one is the performance analysis and optimal control of spectrum sharing networks.

In the first part, we consider a retailer that sells the same or different versions of the product season after season. At the beginning of each season (stage 1), the retailer places an order and sells the product at the full price. As the sales unfold, the retailer has an opportunity to mark down the price (stage 2) to match supply with demand. However, the retailer’s markdown strategies in past seasons give strategic consumers an incentive to time their purchases in future seasons. Specifically, consumers learn from the retailer’s past practice and form their expectation or reference on the markdown prices which will influence their purchasing decisions in future seasons. We characterize the properties of the optimal ordering and markdown decisions and show that markdowns, if adopted appropriately, do not necessarily destroy the stability of a business even in the presence of strategic consumers and learning the reference is enough for strategic consumers to time their purchases. Furthermore, consumers’ reference should fluctuate around a “mean”, referred to as mean-reverting, under certain conditions. We conduct numerical studies to investigate the impact of consumer learning about reference price in the presence of strategic consumers and various system parameters on the retailer’s optimal strategies and profitability.

In the second part, we consider a bandwidth of electromagnetic spectrum with a number of identical channels shared by both licensed and unlicensed users. Such a network differs from most many-server, two-class queues in service systems including call centers due to the restrictions imposed on the unlicensed users when in service and waiting in order to limit interference to the licensed users. We first approximate the key performance indicators, the throughput rate of the system and delay probability of the licensed users under the heavy traffic regime, which requires the analysis of both scaled and un-scaled processes simultaneously using the averaging principle. Our analysis reveals some distinctive properties of the system performances compared with most service systems. For example, sharing does not affect the service of the licensed users under heavy traffic even when the system is critically loaded. We then study the optimal control of the system to maximize the system throughput rate while maintaining the delay probability of the licensed users below a certain level when the system is overloaded. Finally, we extend our study to systems with uncertain or time-varying arrival rates.