Modeling the Transient Nature of Dynamic Pricing with Demand Learning in a Competitive Environment

  • Soulaymane Kachani
  • Georgia Perakis
  • Carine Simon
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 102)


This paper focuses on joint dynamic pricing and demand learning in an oligopolistic market. Each firm seeks to learn the price-demand relationship for itself and its competitors, and to set optimal prices, taking into account its competitors’ likely moves. We follow a closed-loop approach to capture the transient aspect of the problem, that is, pricing decisions are updated dynamically over time, using the data acquired thus far.

We formulate the problem faced at each time period by each firm as a Mathematical Program with Equilibrium Constraints (MPEC). We utilize variational inequalities to capture the game-theoretic aspect of the problem. We present computational results that provide insights on the model and illustrate the pricing policies this model gives rise to.


dynamic pricing demand learning variational inequalities game theory 


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Soulaymane Kachani
    • 1
  • Georgia Perakis
    • 2
  • Carine Simon
    • 3
  1. 1.IEOR DepartmentColumbia UniversityNew York
  2. 2.MIT Sloan School of ManagementCambridge
  3. 3.MIT Operations Research CenterCambridge

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