Dynamic competitive pricing strategies

Anne T. Coughlan; Murali K. Mantrala

doi:10.1016/0167-8116(92)90031-F

Dynamic competitive pricing strategies

Anne T. Coughlan^*, Murali K. Mantrala

^*Corresponding author for this work

Marketing

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Pricing decisions have long been of interest to researchers in the competitive strategy area. Static game theory models of competitive pricing commonly assume that rivals act with full information and full rationality. Such models imply that rivals immediately reach a Nash equilibrium. This implication is consistent neither with experimental research results nor with casual observation of real markets. We therefore relax the assumption of full information to investigate how competitors learn and update their marketing strategies over time, as well as to identify the ultimate equilibrium they reach. This dual focus on the learning process as well as its outcome is important to understanding how rivals compete over time. We find that the ultimate equilibrium takes some time to reach, and is neither the standard Nash solution nor a collusive one. These differences from the usual static game solutions suggest the value of models that better capture the incomplete information facing a firm in a competitive marketplace.

Original language	English (US)
Pages (from-to)	91-108
Number of pages	18
Journal	International Journal of Research in Marketing
Volume	9
Issue number	1
DOIs	https://doi.org/10.1016/0167-8116(92)90031-F
State	Published - Mar 1992

ASJC Scopus subject areas

Marketing

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10.1016/0167-8116(92)90031-F

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@article{055b7411865446a795cedc1f92671637,

title = "Dynamic competitive pricing strategies",

abstract = "Pricing decisions have long been of interest to researchers in the competitive strategy area. Static game theory models of competitive pricing commonly assume that rivals act with full information and full rationality. Such models imply that rivals immediately reach a Nash equilibrium. This implication is consistent neither with experimental research results nor with casual observation of real markets. We therefore relax the assumption of full information to investigate how competitors learn and update their marketing strategies over time, as well as to identify the ultimate equilibrium they reach. This dual focus on the learning process as well as its outcome is important to understanding how rivals compete over time. We find that the ultimate equilibrium takes some time to reach, and is neither the standard Nash solution nor a collusive one. These differences from the usual static game solutions suggest the value of models that better capture the incomplete information facing a firm in a competitive marketplace.",

author = "Coughlan, {Anne T.} and Mantrala, {Murali K.}",

note = "Funding Information: The authors thank John Hauser, James Jeck, Richard Staelin, Birger Wernerfelt, the reviewers. and especially Barton Weitz for comments on this paper. Responsibility for any errors of course rests with the authors. Anne T. Coughlan thanks the Brunswick Foundation for research support in this work. The order in which the authors are listed is alphabetical. Both authors contributed equally to this work.",

year = "1992",

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doi = "10.1016/0167-8116(92)90031-F",

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AU - Coughlan, Anne T.

AU - Mantrala, Murali K.

N1 - Funding Information: The authors thank John Hauser, James Jeck, Richard Staelin, Birger Wernerfelt, the reviewers. and especially Barton Weitz for comments on this paper. Responsibility for any errors of course rests with the authors. Anne T. Coughlan thanks the Brunswick Foundation for research support in this work. The order in which the authors are listed is alphabetical. Both authors contributed equally to this work.

PY - 1992/3

Y1 - 1992/3

N2 - Pricing decisions have long been of interest to researchers in the competitive strategy area. Static game theory models of competitive pricing commonly assume that rivals act with full information and full rationality. Such models imply that rivals immediately reach a Nash equilibrium. This implication is consistent neither with experimental research results nor with casual observation of real markets. We therefore relax the assumption of full information to investigate how competitors learn and update their marketing strategies over time, as well as to identify the ultimate equilibrium they reach. This dual focus on the learning process as well as its outcome is important to understanding how rivals compete over time. We find that the ultimate equilibrium takes some time to reach, and is neither the standard Nash solution nor a collusive one. These differences from the usual static game solutions suggest the value of models that better capture the incomplete information facing a firm in a competitive marketplace.

AB - Pricing decisions have long been of interest to researchers in the competitive strategy area. Static game theory models of competitive pricing commonly assume that rivals act with full information and full rationality. Such models imply that rivals immediately reach a Nash equilibrium. This implication is consistent neither with experimental research results nor with casual observation of real markets. We therefore relax the assumption of full information to investigate how competitors learn and update their marketing strategies over time, as well as to identify the ultimate equilibrium they reach. This dual focus on the learning process as well as its outcome is important to understanding how rivals compete over time. We find that the ultimate equilibrium takes some time to reach, and is neither the standard Nash solution nor a collusive one. These differences from the usual static game solutions suggest the value of models that better capture the incomplete information facing a firm in a competitive marketplace.

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Dynamic competitive pricing strategies

Abstract

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