Dynamic Pricing Strategies in the Presence of Demand Shifts

Manufacturing & Service Operations Management, 2014, 16(4):513-528

Columbia Business School Research Paper No. 13-67

33 Pages Posted: 16 Aug 2013 Last revised: 15 Jun 2016

See all articles by Omar Besbes

Omar Besbes

Columbia University - Columbia Business School, Decision Risk and Operations

Denis Saure

University of Chile - Industrial Engineering

Date Written: June 6, 2012

Abstract

Many factors introduce the prospect of changes in the demand environment that a firm faces, with the specifics of such changes not necessarily known in advance. If and when realized, such changes affect the delicate balance between demand and supply and thus current prices should account for these future possibilities. We study the dynamic pricing problem of a retailer facing the prospect of a change in the demand function during a finite selling season with no inventory replenishment opportunity. In particular, the time of the change and the postchange demand function are unknown upfront, and we focus on the fundamental trade-off between collecting revenues from current demand and doing so for postchange demand, with the capacity constraint introducing the main tension. We develop a formulation that allows for isolating the role of dynamic pricing in balancing inventory consumption throughout the horizon. We establish that, in many settings, optimal pricing policies follow a monotone path up to the change in demand. We show how one may compare upfront the attractiveness of pre- and postchange demand conditions and how such a comparison depends on the problem primitives. We further analyze the impact of the model inputs on the optimal policy and its structure, ranging from the impact of model parameter changes to the impact of different representations of uncertainty about future demand.

Keywords: revenue management, dynamic pricing, non-stationary demand, model uncertainty

Suggested Citation

Besbes, Omar and Saure, Denis, Dynamic Pricing Strategies in the Presence of Demand Shifts (June 6, 2012). Manufacturing & Service Operations Management, 2014, 16(4):513-528, Columbia Business School Research Paper No. 13-67, Available at SSRN: https://ssrn.com/abstract=2310786 or http://dx.doi.org/10.2139/ssrn.2310786

Omar Besbes (Contact Author)

Columbia University - Columbia Business School, Decision Risk and Operations ( email )

New York, NY
United States

Denis Saure

University of Chile - Industrial Engineering ( email )

República 701, Santiago
Chile

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