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

Soulaymane Kachani (), Georgia Perakis () and Carine Simon ()
Additional contact information
Soulaymane Kachani: Columbia University
Georgia Perakis: MIT Sloan School of Management
Carine Simon: MIT Operations Research Center

Chapter Chapter 11 in Network Science, Nonlinear Science and Infrastructure Systems, 2007, pp 223-267 from Springer

Abstract: Abstract 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.

Keywords: dynamic pricing; demand learning; variational inequalities; game theory (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-0-387-71134-8_11

Ordering information: This item can be ordered from
http://www.springer.com/9780387711348

DOI: 10.1007/0-387-71134-1_11

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().