Revenue management at the interface of economics and marketing

This dissertation consists of the following three self-contained parts on Revenue Management at the interface of Economics and Marketing.; Dynamic pricing and leadtime quotation for a multi-class make-to-order queue. We consider a profit maximizing make-to-order manufacturer that offers multiple products to a market of price and delay sensitive users, using a model that captures three aspects of particular interest: first, the joint use of dynamic pricing and leadtime quotation controls to manage demand; second, the presence of a dual sourcing mode that can expedite orders at a cost; and third, the interaction of the aforementioned demand controls with the operational decisions of sequencing and expediting that the firm must employ to optimize revenues and satisfy the quoted leadtimes. Using an approximating diffusion control problem we derive near-optimal dynamic pricing, leadtime quotation, sequencing, and expediting policies that provide structural insights and lead to practically implementable recommendations. A set of numerical results illustrates the value of joint pricing and leadtime control policies.; Revenue management with costly price adjustments. We consider a novel variant of the perishable inventory profit management problem faced by a firm which sells a fixed inventory over a finite horizon in the presence of price adjustment costs. In economics literature, such price adjustment costs are widely studied and are typically assumed to include a fixed component (e.g., advertising costs), an inventory-dependent component (e.g., inventory re-labeling costs), as well as a component that depends on the magnitude of the price adjustment (e.g., cognitive and coordination managerial costs).; We formulate the firm's profit management problem as a finite-horizon dynamic program in which the state of the system is described by both the inventory level as well as the current price level. We derive first-order properties of the optimal value function and give a complete characterization of optimal policies for the case of ample inventory and for the case of a single batch of inventory over a set of two predetermined price levels. Through a set of examples we demonstrate the complex and counter-intuitive nature of optimal price adjustment policies. Consequently, we develop and solve a fluid model based on the original stochastic dynamics and propose three fluid-based heuristic policies. We derive expressions for the expected profit generated by each one of these heuristics when applied to the stochastic problem and derive sufficient conditions for the asymptotic optimality of the policies when the initial inventory levels and planning horizons are proportionally scaled tip. Finally, we test the performance of the heuristics in a numerical study and demonstrate a robust, near-optimal performance of one of the heuristics (which we call the 'Fluid Time' heuristic) for a wide range of problem parameters.; Optimal timing of revealing sales information for two products under herding. Online retailers have recently started to reveal sales information regarding a group of products belonging to the same category by announcing the sales ratio of each product in addition to posting online customer reviews. In this chapter we investigate the optimal timing of such information revelations by combining existing models in economics and marketing literatures. We introduce a novel innovation diffusion model for two competing products that incorporates into the demand dynamics herding effects resulting from the revelations of past sales fractions. For a direct and very intuitive form of herding, we obtain the corresponding demand dynamics for two products in closed-form. Based on this result, we present the terminal market shares for each product explicitly. We characterize in closed-form the optimal information revelation time that maximizes total discounted profits. In addition, we derive necessary and sufficient conditions for the optimal inf...