IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v25y2014i3p511-527.html
   My bibliography  Save this article

Online Gambling Behavior: The Impacts of Cumulative Outcomes, Recent Outcomes, and Prior Use

Author

Listed:
  • Xiao Ma

    (Department of Information Systems, Sam M. Walton College of Business, University of Arkansas, Fayettleville, Arkansas 72701)

  • Seung Hyun Kim

    (School of Business, Yonsei University, Seoul 120-479, Korea; and Department of Information Systems, National University of Singapore, Singapore 117417)

  • Sung S. Kim

    (Department of Operations and Information Management, Wisconsin School of Business, University of Wisconsin–Madison, Madison, Wisconsin 53706)

Abstract

The objective of this work is to examine various psychological forces underlying the behavior of people’s online gambling, an increasingly popular form of entertainment in the gaming industry. Drawing on extant theories, we first developed a model of how cumulative outcomes, recent outcomes, and prior use affect online gambling behavior differently. We empirically tested the model using longitudinal panel data collected over eight months from 22,304 actual users of a gambling website. The results of a multilevel panel data analysis strongly supported our hypotheses. First, consistent with gambling theory, individuals' online gambling was found to increase with any increase in a cumulative net gain or cumulative net loss. Second, as the availability heuristic prescribes, a recent loss reduced online gambling, whereas a recent gain increased it. Third, consistent with the literature on repeated behavior, regular use and extended use moderated the relationship between current and subsequent gambling. Taken together, the present study clarifies how people react differently to immediate and cumulative outcomes and also how regular use and extended use facilitate routine behavior in the context of online gambling. In general, our findings suggest that the three perspectives, i.e., gambling theory, the availability heuristic, and repeated behavior, should be taken into account to understand online gambling, which is in essence a series of risk-taking attempts with the potential of eventually becoming routine behavior. This study is expected to offer valuable insights into other types of online games that could engage people in risking real or cyber money and, at the same time, could be easily enmeshed with everyday life (e.g., fantasy sports, online virtual worlds).

Suggested Citation

  • Xiao Ma & Seung Hyun Kim & Sung S. Kim, 2014. "Online Gambling Behavior: The Impacts of Cumulative Outcomes, Recent Outcomes, and Prior Use," Information Systems Research, INFORMS, vol. 25(3), pages 511-527, September.
  • Handle: RePEc:inm:orisre:v:25:y:2014:i:3:p:511-527
    DOI: 10.1287/isre.2014.0517
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2014.0517
    Download Restriction: no

    File URL: https://libkey.io/10.1287/isre.2014.0517?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Shlomo Benartzi & Richard H. Thaler, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 73-92.
    2. Rachel Croson & James Sundali, 2005. "The Gambler’s Fallacy and the Hot Hand: Empirical Data from Casinos," Journal of Risk and Uncertainty, Springer, vol. 30(3), pages 195-209, May.
    3. Charles T. Clotfelter & Philip J. Cook, 1989. "Selling Hope: State Lotteries in America," NBER Books, National Bureau of Economic Research, Inc, number clot89-1, March.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    5. Venkatesh, Viswanath & Morris, Michael G. & Ackerman, Phillip L., 2000. "A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(1), pages 33-60, September.
    6. Keasey, Kevin & Moon, Philip, 1996. "Gambling with the house money in capital expenditure decisions: An experimental analysis," Economics Letters, Elsevier, vol. 50(1), pages 105-110, January.
    7. Cook, Philip J & Clotfelter, Charles T, 1993. "The Peculiar Scale Economies of Lotto," American Economic Review, American Economic Association, vol. 83(3), pages 634-643, June.
    8. Richard H. Thaler & Eric J. Johnson, 1990. "Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice," Management Science, INFORMS, vol. 36(6), pages 643-660, June.
    9. Clyde W. Holsapple & Jiming Wu, 2008. "Building effective online game websites with knowledge-based trust," Information Systems Frontiers, Springer, vol. 10(1), pages 47-60, March.
    10. Sridhar Narayanan & Puneet Manchanda, 2012. "An empirical analysis of individual level casino gambling behavior," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 27-62, March.
    11. Shaffer, H.J. & Hall, M.N. & Vander Bilt, J., 1999. "Estimating the prevalence of disordered gambling behavior in the United States and Canada: A research synthesis," American Journal of Public Health, American Public Health Association, vol. 89(9), pages 1369-1376.
    12. Terrance Odean, 1998. "Are Investors Reluctant to Realize Their Losses?," Journal of Finance, American Finance Association, vol. 53(5), pages 1775-1798, October.
    13. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    14. Sung S. Kim & Naresh K. Malhotra, 2005. "A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Postadoption Phenomena," Management Science, INFORMS, vol. 51(5), pages 741-755, May.
    15. Adwait Khare & J. Jeffrey Inman, 2006. "Habitual Behavior in American Eating Patterns: The Role of Meal Occasions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(4), pages 567-575, March.
    16. Nicole DeHoratius & Ananth Raman, 2008. "Inventory Record Inaccuracy: An Empirical Analysis," Management Science, INFORMS, vol. 54(4), pages 627-641, April.
    17. Soon Ang & Sandra Slaughter & Kok Yee Ng, 2002. "Human Capital and Institutional Determinants of Information Technology Compensation: Modeling Multilevel and Cross-Level Interactions," Management Science, INFORMS, vol. 48(11), pages 1427-1445, November.
    18. Randolph B. Cooper & Robert W. Zmud, 1990. "Information Technology Implementation Research: A Technological Diffusion Approach," Management Science, INFORMS, vol. 36(2), pages 123-139, February.
    19. Desmond Lam & Richard Mizerski, 2009. "An investigation into gambling purchases using the NBD and NBD–Dirichlet models," Marketing Letters, Springer, vol. 20(3), pages 263-276, September.
    20. Sung S. Kim & Naresh K. Malhotra & Sridhar Narasimhan, 2005. "Research Note—Two Competing Perspectives on Automatic Use: A Theoretical and Empirical Comparison," Information Systems Research, INFORMS, vol. 16(4), pages 418-432, December.
    21. Massimo Massa & Andrei Simonov, 2005. "Behavioral Biases and Investment," Review of Finance, Springer, vol. 9(4), pages 483-507, December.
    22. June Cotte & Kathryn A. Latour, 2009. "Blackjack in the Kitchen: Understanding Online versus Casino Gambling," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(5), pages 742-758, September.
    23. Robert Kraut & Tridas Mukhopadhyay & Janusz Szczypula & Sara Kiesler & Bill Scherlis, 1999. "Information and Communication: Alternative Uses of the Internet in Households," Information Systems Research, INFORMS, vol. 10(4), pages 287-303, December.
    24. Jonathan Guryan & Melissa S. Kearney, 2008. "Gambling at Lucky Stores: Empirical Evidence from State Lottery Sales," American Economic Review, American Economic Association, vol. 98(1), pages 458-473, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sandra Schneider & Sandra Kauffman & Andrea Ranieri, 2016. "The effects of surrounding positive and negative experiences on risk taking," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(5), pages 424-440, September.
    2. Maggie Rong Hu & Xiaoyang Li & Yang Shi & Xiaoquan (Michael) Zhang, 2023. "Numerological Heuristics and Credit Risk in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 34(4), pages 1744-1760, December.
    3. Shan, Wei & Qiao, Tong & Zhang, Mingli, 2020. "Getting more resources for better performance: The effect of user-owned resources on the value of user-generated content," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Mamonov, Stanislav & Benbunan-Fich, Raquel, 2017. "Exploring factors affecting social e-commerce service adoption: The case of Facebook Gifts," International Journal of Information Management, Elsevier, vol. 37(6), pages 590-600.
    5. Martin Adam & Konstantin Roethke & Alexander Benlian, 2022. "Gamblified digital product offerings: an experimental study of loot box menu designs," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 971-986, June.
    6. repec:cup:judgdm:v:11:y:2016:i:5:p:424-440 is not listed on IDEAS

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mattos, Fabio & Garcia, Philip & Pennings, Joost M.E., 2008. "Probability weighting and loss aversion in futures hedging," Journal of Financial Markets, Elsevier, vol. 11(4), pages 433-452, November.
    2. Darren Duxbury & Robert Hudson & Kevin Keasey & Zhishu Yang & Songyao Yao, 2013. "How prior realized outcomes affect portfolio decisions," Review of Quantitative Finance and Accounting, Springer, vol. 41(4), pages 611-629, November.
    3. Maximilian Rüdisser & Raphael Flepp & Egon Franck, 2017. "Do casinos pay their customers to become risk-averse? Revising the house money effect in a field experiment," Experimental Economics, Springer;Economic Science Association, vol. 20(3), pages 736-754, September.
    4. Maximilian Rüdisser & Raphael Flepp & Egon Franck, 2017. "When do reference points update? A field analysis of the effect of prior gains and losses on risk-taking over time," Working Papers 369, University of Zurich, Department of Business Administration (IBW).
    5. Mattos, Fabio & Garcia, Philip, 2009. "The Effect of Prior Gains and Losses on Current Risk-Taking Using Quantile Regression," 2009 Conference, April 20-21, 2009, St. Louis, Missouri 53035, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    6. Fenghua Wen & Zhifang He & Xu Gong & Aiming Liu, 2014. "Investors’ Risk Preference Characteristics Based on Different Reference Point," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-9, April.
    7. Lin Jia & Xiuwei Song & Dianne Hall, 2022. "Influence of Habits on Mobile Payment Acceptance: An Ecosystem Perspective," Information Systems Frontiers, Springer, vol. 24(1), pages 247-266, February.
    8. Hopfensitz, Astrid, 2009. "Previous outcomes and reference dependence: A meta study of repeated investment tasks with and without restricted feedback," MPRA Paper 16096, University Library of Munich, Germany.
    9. Francisco Gomes & Michael Haliassos & Tarun Ramadorai, 2021. "Household Finance," Journal of Economic Literature, American Economic Association, vol. 59(3), pages 919-1000, September.
    10. Hee Mok Park & Joseph Pancras, 2022. "Social and Spatiotemporal Impacts of Casino Jackpot Events," Marketing Science, INFORMS, vol. 41(3), pages 575-592, May.
    11. Andrey Kudryavtsev & Gil Cohen & Shlomit Hon-Snir, 2013. "“Rational” or “Intuitive”: Are Behavioral Biases Correlated Across Stock Market Investors?," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 7(2), June.
    12. Enrico Giorgi & Thorsten Hens, 2006. "Making prospect theory fit for finance," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 20(3), pages 339-360, September.
    13. Haven, Emmanuel & Khrennikova, Polina, 2018. "A quantum-probabilistic paradigm: Non-consequential reasoning and state dependence in investment choice," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 186-197.
    14. Rieger, Marc O. & Wang, Mei & Phan, Thuy Chung & Gong, Yujing, 2022. "Trend following or reversal: Does culture affect predictions and trading behavior?," Global Finance Journal, Elsevier, vol. 54(C).
    15. Martin Adam & Konstantin Roethke & Alexander Benlian, 2022. "Gamblified digital product offerings: an experimental study of loot box menu designs," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 971-986, June.
    16. Wang, Huijun & Yan, Jinghua & Yu, Jianfeng, 2017. "Reference-dependent preferences and the risk–return trade-off," Journal of Financial Economics, Elsevier, vol. 123(2), pages 395-414.
    17. Li An & Huijun Wang & Jian Wang & Jianfeng Yu, 2020. "Lottery-Related Anomalies: The Role of Reference-Dependent Preferences," Management Science, INFORMS, vol. 66(1), pages 473-501, January.
    18. Ormos, Mihály & Joó, István, 2011. "Diszpozíciós hatás a magyar tőkepiacon [Disposition effect in the Hungarian capital market]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 743-758.
    19. Joshua B. Miller & Adam Sanjurjo, 2014. "A Cold Shower for the Hot Hand Fallacy," Working Papers 518, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    20. David Johnstone, 2002. "Behavioral and Prescriptive Explanations of a Reverse Sunk Cost Effect," Theory and Decision, Springer, vol. 53(3), pages 209-242, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:25:y:2014:i:3:p:511-527. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.