Tiered Pricing for Volume and Priority: Three Problems at the Intersection of Marketing and Operational Policies

This thesis addresses three problems where a focal agent's operational policies (inventory and capacity allocation) interact with marketing decisions.;The first chapter studies how wholesale all-unit discounts may lead to products being shifted from authorized retailers to discounted gray market channels. Such discounts lead to discontinuous order-costs which may induce buyers to order up to a threshold where they receive a greater discount. The buyer in this chapter is a reseller who makes purchasing decisions while taking into account inventory holding costs, how their resale price affects consumer demand and whether or not they divert inventory to the gray market. I analyze factors which determine how the reseller balances between lowering resale prices and diverting to the gray market, both of which lower costs by shortening the time inventory is held. Modelling the decisions as a Stackelberg game, the welfare of the authorized channel participants is analyzed. Of import, consumer welfare may decrease if a gray market emerges when holding costs are low.;In the latter two chapters, the supplier sells a congested service. For example, this supplier may be a courier facing stochastic buyer arrivals. Buyers vary in their value for the service and how patient they are, so the supplier may improve outcomes by providing a menu of delay levels and prices. The system is modelled as a priority queue where congestion constrains the arrival rates at each delay level.;In the first study, the supplier has aggregate market data. I model the problem as an optimization subject to incentive and congestion constraints. The novel contributions include a precise description of the optimal menu as a function of the supplier's capacity (the rate at which buyers can be served). Findings include existence of distinct capacity regions where the supplier utilizes service pooling and strategic delay.;In the final chapter the related welfare maximization problem is considered. Sufficient conditions for optimal pricing are derived which depend only on operational information: the current revenue must be equal to the best-case revenue subject to current prices and congestion constraints. An associated performance measure is shown to bound deviation from maximum welfare and is used as a heuristic within an adaptive pricing protocol. This protocol is shown to converges to near welfare maximizing outcomes.