Price competition under mixed multinomial logit demand functions

Margaret Aksoy-Pierson, Gad Allon, Awi Federgruen

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


In this paper, we postulate a general class of price competition models with mixed multinomial logit demand functions under affine cost functions. In these models, the market is partitioned into a finite set of market segments. We characterize the equilibrium behavior of this class of models in the case where each product in the market is sold by a separate, independent firm. We identify a simple and very broadly satisfied condition under which a pure Nash equilibrium exists and the set of Nash equilibria coincides with the solutions of the system of first-order-condition equations, a property of essential importance to empirical studies. This condition specifies that in every market segment, each firm captures less than 50% of the potential customer population when pricing at a specific level that, under the condition, is an upper bound for a rational price choice for the firm irrespective of the competitors' prices. We show that under a somewhat stronger, but still broadly satisfied, version of the above condition, a unique equilibrium exists. We complete the picture by establishing the existence of a Nash equilibrium, indeed a unique Nash equilibrium, for markets with an arbitrary degree of concentration, under sufficiently tight price bounds. We discuss how our results extend to a continuum of customer types. A discussion of the multiproduct case is included. The paper concludes with a discussion of implications for structural estimation methods.

Original languageEnglish (US)
Pages (from-to)1817-1835
Number of pages19
JournalManagement Science
Issue number8
StatePublished - Aug 2013


  • Competitive strategy
  • Marketing
  • Pricing

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research


Dive into the research topics of 'Price competition under mixed multinomial logit demand functions'. Together they form a unique fingerprint.

Cite this