Intertemporal Price Discrimination: Structure and Computation of Optimal Policies
Columbia Business School - Decision Risk and Operations
New York University (NYU)
August 6, 2014
Management Science, Vol. 61, No. 1, January 2015, pp. 92–110.
Columbia Business School Research Paper No. 12/46
We study a firm's optimal pricing policy under price commitment. The firm's objective is to maximize its long-term average revenue given a steady arrival of strategic customers. In particular, customers arrive over time, are strategic in timing their purchases and are heterogeneous along two dimensions: their valuation for the firm's product and their willingness to wait before purchasing or leaving. The customers' patience and valuation may be correlated in an arbitrary fashion. For this general formulation, we prove that the firm may restrict attention to cyclic pricing policies, which have length at most twice the maximum willingness to wait of the customer population. To efficiently compute optimal policies, we develop a dynamic programming approach which uses a novel state space which is general, enabling to handle arbitrary problem primitives, and that generalizes to finite horizon problems with non-stationary parameters. We analyze the class of monotone pricing policies and establish their suboptimality in general. Optimal policies are, in a typical scenario, characterized by nested sales, where the firm offers partial discounts throughout each cycle, offers a significant discount halfway through the cycle, with the largest discount offered at the end of the cycle. We further establish a form of equivalence between the problem of pricing for a stream of heterogeneous strategic customers and pricing for a pool of heterogeneous customers who may stockpile units of the product.
Number of Pages in PDF File: 45
Keywords: pricing, optimization, intertemporal pricing, price discrimination, strategic consumers, stockpiling
Date posted: August 8, 2012 ; Last revised: February 17, 2015
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo5 in 0.516 seconds