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The Impact of Personal Experience on Behavior: Evidence from Video-Rental Fines

Author

Listed:
  • Michael P. Haselhuhn

    (Lubar School of Business, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53211)

  • Devin G. Pope

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

  • Maurice E. Schweitzer

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Peter Fishman

    (University of California, Berkeley, Berkeley, California 94704)

Abstract

Personal experience matters. In a field setting with longitudinal data, we disentangle the effects of learning new information from the effects of personal experience. We demonstrate that experience with a fine, controlling for the effect of learning new information, significantly boosts future compliance. We also show that experience with a large fine boosts compliance more than experience with a small fine, but that the influence of experience with both large and small fines decays sharply over time. This paper was accepted by Brad Barber, Teck Ho, and Terrance Odean, special issue editors.

Suggested Citation

  • Michael P. Haselhuhn & Devin G. Pope & Maurice E. Schweitzer & Peter Fishman, 2012. "The Impact of Personal Experience on Behavior: Evidence from Video-Rental Fines," Management Science, INFORMS, vol. 58(1), pages 52-61, January.
  • Handle: RePEc:inm:ormnsc:v:58:y:2012:i:1:p:52-61
    DOI: 10.1287/mnsc.1110.1367
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    References listed on IDEAS

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    1. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    2. Kessler, Daniel P & Levitt, Steven D, 1999. "Using Sentence Enhancements to Distinguish between Deterrence and Incapacitation," Journal of Law and Economics, University of Chicago Press, vol. 42(1), pages 343-363, April.
    3. David M. Cutler & Robert S. Huckman & Mary Beth Landrum, 2004. "The Role of Information in Medical Markets: An Analysis of Publicly Reported Outcomes in Cardiac Surgery," American Economic Review, American Economic Association, vol. 94(2), pages 342-346, May.
    4. Teck H. Ho & Xin Wang & Colin F. Camerer, 2008. "Individual Differences in EWA Learning with Partial Payoff Information," Economic Journal, Royal Economic Society, vol. 118(525), pages 37-59, January.
    5. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    6. Russo, J Edward, et al, 1986. "Nutrition Information in the Supermarket," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(1), pages 48-70, June.
    7. Joseph Lampel & Zur Shapira, 2001. "Judgmental Errors, Interactive Norms, and the Difficulty of Detecting Strategic Surprises," Organization Science, INFORMS, vol. 12(5), pages 599-611, October.
    8. Simonsohn, Uri & Karlsson, Niklas & Loewenstein, George & Ariely, Dan, 2008. "The tree of experience in the forest of information: Overweighing experienced relative to observed information," Games and Economic Behavior, Elsevier, vol. 62(1), pages 263-286, January.
    9. Ginger Zhe Jin & Phillip Leslie, 2003. "The Effect of Information on Product Quality: Evidence from Restaurant Hygiene Grade Cards," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(2), pages 409-451.
    10. Rakow, Tim & Demes, Kali A. & Newell, Ben R., 2008. "Biased samples not mode of presentation: Re-examining the apparent underweighting of rare events in experience-based choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 106(2), pages 168-179, July.
    11. repec:cup:judgdm:v:1:y:2006:i::p:159-161 is not listed on IDEAS
    12. Chu, Yun-Peng & Chu, Ruey-Ling, 1990. "The Subsidence of Preference Reversals in Simplified and Marketlike Experimental Settings: A Note," American Economic Review, American Economic Association, vol. 80(4), pages 902-911, September.
    13. Maurice E. Schweitzer & Gérard P. Cachon, 2000. "Decision Bias in the Newsvendor Problem with a Known Demand Distribution: Experimental Evidence," Management Science, INFORMS, vol. 46(3), pages 404-420, March.
    14. Sumit Agarwal & John C Driscoll & Xavier Gabaix & David Laibson, 2008. "Learning in the Credit Card Market," Levine's Working Paper Archive 122247000000002028, David K. Levine.
    15. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    16. Bo E. Honoré & Ekaterini Kyriazidou, 2000. "Panel Data Discrete Choice Models with Lagged Dependent Variables," Econometrica, Econometric Society, vol. 68(4), pages 839-874, July.
    17. TeckH. Ho & Xin Wang & ColinF. Camerer, 2008. "Individual Differences in EWA Learning with Partial Payoff Information," Economic Journal, Royal Economic Society, vol. 118(525), pages 37-59, January.
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