On Policies for Single-Leg Revenue Management with Limited Demand Information

Will Ma (), David Simchi-Levi () and Chung-Piaw Teo ()
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Will Ma: Graduate School of Business, Columbia University, New York, New York 10027
David Simchi-Levi: Institute for Data, Systems, and Society, Department of Civil and Environmental Engineering, and Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
Chung-Piaw Teo: Business School, National University of Singapore, Singapore 119245

Operations Research, 2021, vol. 69, issue 1, 207-226

Abstract: In this paper, we study the single-item revenue management problem, with no information given about the demand trajectory over time. When the item is sold through accepting/rejecting different fare classes, the tight competitive ratio for this problem has been established by Ball and Queyranne through booking limit policies, which raise the acceptance threshold as the remaining inventory dwindles. However, when the item is sold through dynamic pricing instead, there is the additional challenge that offering a low price may entice high-paying customers to substitute down. We show that despite this challenge, the same competitive ratio can still be achieved using a randomized dynamic pricing policy. Our policy incorporates the price-skimming technique originated by Eren and Maglaras, but importantly we show how the randomized price distribution should be stochastically increased as the remaining inventory dwindles. A key technical ingredient in our policy is a new “Valuation Tracking” subroutine, which tracks the possible values for the optimum, and follows the most “inventory-conservative” control, which maintains the desired competitive ratio. Finally, we demonstrate the empirical effectiveness of our policy in simulations, where its average-case performance surpasses all naive modifications of the existing policies.

Keywords: online algorithms; competitive ratio; revenue management; dynamic pricing (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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