GOALI: Strategic Pricing and Inventory Management of Constrained Capacity with Repeated Transactions

Columbia University, New York NY

Investigators

Abstract

This research project will explore the impact of customer learning and behavior on the optimal pricing of constrained capacity. The research team seeks to characterize instances when incorporating customer behavior will lead to strategically optimal policies that deviate significantly from tactically optimal policies that ignore customer behavior and implicitly assume a single interaction between buyer and seller. This research will provide insight into how pricing dynamics are influenced by the interplay between seller policies and customer expectations. It has the potential to lead to significant improvements in current commercial pricing policies in practice. Such improvements would lead to better capacity allocation resulting in improved economic efficiencies. The key results of this research project will be published in archival and trade journals and presented at national conferences, academic and industry seminars. In addition, the principal investigators will create and co-teach a new Ph.D. level course in revenue management and develop educational software embodying the key concepts of this rapidly developing field, thereby promoting teaching, training and learning. The problem of optimal pricing of perishable constrained capacity over time has received considerable attention. If a good perishes instantaneously and the willingness to pay for the good increases over time -- as in the case of airline seats and hotel rooms -- the problem of determining optimal prices is known as revenue management. If the willingness to pay decreases over time -- as in fashion goods and consumer electronics, the problem is known as markdown management. Revenue management has been estimated to provide $1 billion annually for large airlines while markdown management has been credited with increasing revenues by up to 7%. It is therefore not surprising that both revenue management and markdown management have been the topics of considerable academic research and substantial industry investment. Research into pricing of constrained products has generally focused on maximizing the total expected revenue (or profitability) achieved from fixed capacity. This is the goal of the EMSRb approach to airline revenue management as well as the focus of markdown management systems. This approach is appropriate when buyers and sellers will interact only once. However, if there are repeated interactions among buyers and sellers, then a seller's action today will influence the expectations (and hence the behavior) of buyers in the future. For example, a seller who offers distressed inventory at a deep discount will train some buyers to expect this in the future and change their behavior accordingly. Similarly, a seller who provides more availability of inventory to a particular market segment than the competition will train buyers to turn to him first. In both cases, sellers may achieve higher returns over time from pricing policies that incorporate the impact of customer behavior rather than simply maximizing the return from their current stock of inventory.