Chasing Demand: Learning and Earning in a Changing Environment

N. Bora Keskin () and Assaf Zeevi ()
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N. Bora Keskin: Fuqua School of Business, Duke University, Durham, North Carolina 27708
Assaf Zeevi: Graduate School of Business, Columbia University, New York, New York 10027

Mathematics of Operations Research, 2017, vol. 42, issue 2, 277-307

Abstract: We consider a dynamic pricing problem in which a seller faces an unknown demand model that can change over time. The amount of change over a time horizon of T periods is measured using a variation metric that allows for a broad spectrum of temporal behavior. Given a finite variation “budget,” we first derive a lower bound on the expected performance gap between any pricing policy and a clairvoyant who knows a priori the temporal evolution of the underlying demand model, and then we design families of near-optimal pricing policies, the revenue performance of which asymptotically matches said lower bound. We also show that the seller can achieve a substantially better revenue performance in demand environments that change in “bursts” than in demand environments that change “smoothly,” among other things quantifying the net effect of the “volatility” in the demand environment on the seller’s revenue performance.

Keywords: revenue management; pricing; model uncertainty; changing environment; sequential estimation; exploration–exploitation; regret (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormoor:v:42:y:2017:i:2:p:277-307

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