Some managers are better than others. Nevertheless, although numerous studies have modeled heterogeneous consumers on a variety of dimensions, management heterogeneity is rarely examined. This is not for a lack of models of strategic heterogeneity. For example, Camerer, Ho, and Chong (2004) develop a “cognitive hierarchy” model (hereinafter, CH) of heterogeneous strategic thinking in which players differ in how deeply they consider competitor choices. In the current article, the authors develop the first structural nonlaboratory estimate of management heterogeneity based on the CH model and apply it to the decisions of 2233 Internet service providers (ISPs) to provide 56K modem technology to their customers. In particular, on the basis of evidence from laboratory experiments, the authors build an empirical model in which players differ in their ability to conjecture the behavior of their competitors. Then, the authors explore the consequences of a change in this ability for ISPs and for modem manufacturers.
The authors operationalize the CH framework by modeling a Type 0 ISP to act as if it is the only player in the market. A Type 1 ISP acts as if it believes that all other ISPs act as if they are the only player in the market. Finally, a Type k ISP acts as if all other players are distributed between Type 0 and Type (k – 1). This structure enables the authors to develop a prediction of behavior for players of different types. A useful consequence of this model is that the solution is unique because each firm believes that it knows what its competitors are doing.
The context for estimating this model is the 1997 decision by ISPs whether to offer customers a higher speed of service (56K bps [bits per second] over 33K bps) and, if so, which technology to provide. As Augereau, Greenstein, and Rysman (2006) discuss, firms faced a clear, reasonably well-defined technology choice game of not upgrading, upgrading to Rockwell Semiconductor’s K56Flex modem, upgrading to USRobotics’ X2 modem, or upgrading to both. The authors find that strategic thinking slowed the distribution and diffusion of the new technology; that ISPs that were estimated to be more likely to be strategic using 1997 data were more likely to have survived through April 2007; and that firms behaved more strategically if they competed in larger cities, if they competed in markets with more educated populations, and if they competed with more firms. Thus, even though the estimate of strategic thinking is associated with increased competition, the ISPs with higher levels of strategic thinking were more likely to survive. More broadly, the results provide external validity to the current laboratory research on the CH model: In addition to the finding on survival, the estimate of the parameter that measures the distribution of strategic ability across the population is at the high end of the range found by Camerer, Ho, and Chong (2004).
Overall, the CH model helps explain the variation in managerial decision making in a useful way. The combination of behavioral game theory with the structural methods of new empirical industrial organization provides a new framework for understanding variation in the decisions of managers who face similar choices.
Biography
Avi Goldfarb is Associate Professor of Marketing in the Rotman School of Management at the University of Toronto. He received his PhD from Northwestern University and his BA from Queen’s University. His research has explored brand value; behavioral modeling in industrial organization; and the impact of information technology on marketing, on universities, and on the economy. Professor Goldfarb has published more than 25 articles in a variety of outlets, including American Economic Review, Marketing Science, Management Science, Journal of International Economics, Journal of Economics and Management Strategy, and Quantitative Marketing and Economics. He is coeditor at Journal of Economics and Management Strategy and an associate editor of Information Economics and Policy.
Botao Yang is a doctoral student in Marketing in the Rotman School of Management at the University of Toronto. He holds an MA in Economics from Peking University and a BA in Economics from Renmin University. His research focuses on structural models of technology adoption using dynamic discrete choice models and behavioral game theory as tools.
Journal Marketing Research, Volume 46, Number 5, October 2009
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