Quantitative Marketing and Economics

, Volume 10, Issue 1, pp 27–62 | Cite as

An empirical analysis of individual level casino gambling behavior

  • Sridhar Narayanan
  • Puneet Manchanda


Gambling and gaming is a very large industry in the United States with about one-third of all adults participating in it on a regular basis. Using novel and unique behavioral data from a panel of casino gamblers, this paper investigates three aspects of consumer behavior in this domain. The first is that consumers are addicted to gambling, the second that they act on “irrational” beliefs, and the third that they are influenced by marketing activity that attempts to influence their gambling behavior. We use the interrelated consumer decisions to play (gamble) and the amount bet in a casino setting to focus on addiction using the standard economic definition of addiction. We test for two irrational behaviors, the “gambler’s fallacy” and the “hot hand myth”—our research represents the first test for these behaviors using disaggregate data in a real (as opposed to a laboratory) setting. Finally, we look at the effect of marketing instruments on the both the decision to play and the amount bet. Using hierarchical Bayesian methods to pin down individual-level parameters, we find that about 8% of the consumers in our sample can be classified as addicted. We find support in our data for the gambler’s fallacy, but not for the hot hand myth. We find that marketing instruments positively affect gambling behavior, and that consumers who are more addicted are also affected by marketing to a greater extent. Specifically, the long-run marketing response is about twice as high for the more addicted consumers.


Gambling behavior Addiction Selection models Casino gaming and gambling Slots Hierarchical Bayes methods 

JEL Classification

M31 M37 D03 C33 C11 



The authors are grateful to Wes Hartmann, Harikesh Nair, Subrata Sen, Katherine Burson, Scott Rick, seminar participants at Dartmouth’s Tuck School, Duke University, London Business School, National University of Singapore, Rotterdam School of Management, Texas A&M University, University of British Columbia, University of Guelph, University of Iowa, University of Maryland, University of Michigan, University of Notre Dame, University of Texas at Austin, University of Toronto, University of Wisconsin at Madison and Yale School of Management, and the participants of the 2006 Summer Institute of Competitive Strategy and the 2009 Marketing Science Conference for comments and feedback and an anonymous company for providing the data and institutional insights. Manchanda would like to acknowledge the Kilts Center for Marketing and the True North Faculty Fund at the University of Chicago, and Narayanan would like to acknowledge the Coulter Family fellowship for providing research support.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Graduate School of BusinessStanford UniversityStanfordUSA
  2. 2.Ross School of BusinessUniversity of MichiganAnn ArborUSA

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