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Dynamic Pricing in Competitive Markets

  • Paresh Nakhe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10660)

Abstract

Dynamic pricing of goods in a competitive environment to maximize revenue is a natural objective and has been a subject of research over the years. In this paper, we focus on a class of markets exhibiting the substitutes property with sellers having divisible and replenishable goods. Depending on the prices chosen, each seller observes a certain demand which is satisfied subject to the supply constraint. The goal of the seller is to price her good dynamically so as to maximize her revenue. For the static market case, when the consumer utility satisfies the gross substitutes CES property, we give a \(O(\sqrt{T})\) regret bound on the maximum loss in revenue of a seller using a modified version of the celebrated Online Gradient Descent algorithm by Zinkevich [17]. For a more specialized set of consumer utilities satisfying the iso-elasticity condition, we show that when each seller uses a regret-minimizing algorithm satisfying a certain technical property, the regret with respect to \((1-\alpha )\) times optimal revenue is bounded as \(O(T^{1/4} / \sqrt{\alpha })\). We extend this result to markets with dynamic supplies and prove a corresponding dynamic regret bound, whose guarantee deteriorates smoothly with the inherent instability of the market. As a side-result, we also extend the previously known convergence results of these algorithms in a general game to the dynamic setting.

Keywords

Dynamic pricing Online convex optimization 

Notes

Acknowledgements

I would like to thank Martin Hoefer and Yun Kuen Cheung for the helpful discussions that helped shape this paper. I would also like to thank the anonymous reviewers for their helpful comments.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Institute of Computer ScienceGoethe UniversityFrankfurt (Main)Germany

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