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Using cooperative game theory to contribute to strategy research
Author(s) -
Ross David Gaddis
Publication year - 2018
Publication title -
strategic management journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 11.035
H-Index - 286
eISSN - 1097-0266
pISSN - 0143-2095
DOI - 10.1002/smj.2936
Subject(s) - cooperative game theory , game theory , computer science , management science , theory , value (mathematics) , formal description , mathematical economics , economics , machine learning , programming language
Research Summary A growing literature uses cooperative game theory to develop formal strategy theories of value creation and value capture. In a recent review, Gans and Ryall ([Gans, J., 2017]) provide an introduction to this literature in which they emphasize the biform modeling framework of Brandenburger and Stuart ([Brandenburger, A. M., 1996], [Brandenburger, A. M., 2007]). The purpose of this article is to extend the work of Gans and Ryall ([Gans, J., 2017]) by (a) discussing the many ways that cooperative game theory and allied models can contribute to strategy research beyond the biform framework itself, and (b) offering recommendations for choosing among formal modeling options, both cooperative and noncooperative. Managerial Summary Growing numbers of strategy scholars are using cooperative game theory to study strategic interaction and develop practical tools for managers, because it offers the mathematical precision of traditional formal modeling techniques while imposing fewer constraints on the actions of firms and managers. Gans and Ryall ([Gans, J., 2017]) review cooperative game theory, with a particular focus on a version developed by Brandenburger and Stuart ([Brandenburger, A. M., 1996], [Brandenburger, A. M., 2007]). This article extends Gans and Ryall ([Gans, J., 2017]) by discussing the many additional ways that cooperative game theory can contribute to strategy research and how to choose between cooperative game theory and other formal modeling methods.

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