IDEAS home Printed from https://ideas.repec.org/a/kap/jrisku/v34y2007i2p145-154.html
   My bibliography  Save this article

Dual process theories: A key for understanding the diversification bias?

Author

Listed:
  • Christoph Kogler
  • Anton Kühberger

Abstract

The diversification bias in repeated lotteries is the finding that a majority of participants fail to select the option offering the highest probability. This phenomenon is systematic and immune to classical manipulations (e.g. monetary rewards). We apply dual process theories and argue that the diversification bias is a consequence of System 1 (automatic, intuitive, associative) triggering a matching response, which fails to be corrected by System 2 (intentional, analytic, rational). Empirically, supporting the corrective functions of System 2 through appropriate contextual cues (describing the task as a statistical test rather than as a lottery) led to a decrease of diversification. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Christoph Kogler & Anton Kühberger, 2007. "Dual process theories: A key for understanding the diversification bias?," Journal of Risk and Uncertainty, Springer, vol. 34(2), pages 145-154, April.
  • Handle: RePEc:kap:jrisku:v:34:y:2007:i:2:p:145-154
    DOI: 10.1007/s11166-007-9008-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11166-007-9008-7
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11166-007-9008-7?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rubinstein, Ariel, 2002. "Irrational diversification in multiple decision problems," European Economic Review, Elsevier, vol. 46(8), pages 1369-1378, September.
    2. Loomes, Graham, 1998. "Probabilities vs Money: A Test of Some Fundamental Assumptions about Rational Decision Making," Economic Journal, Royal Economic Society, vol. 108(447), pages 477-489, March.
    3. Arkes, Hal R. & Dawes, Robyn M. & Christensen, Caryn, 1986. "Factors influencing the use of a decision rule in a probabilistic task," Organizational Behavior and Human Decision Processes, Elsevier, vol. 37(1), pages 93-110, February.
    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. Natalie A. Obrecht & Dana L. Chesney, 2016. "Prompting deliberation increases base-rate use," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(1), pages 1-6, January.
    2. repec:cup:judgdm:v:11:y:2016:i:1:p:1-6 is not listed on IDEAS
    3. Zhou, Jing, 2024. "Does correlation matter in probability matching? A laboratory investigation," Journal of Economic Behavior & Organization, Elsevier, vol. 224(C), pages 876-894.

    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. Yaron Azrieli & Christopher P. Chambers & Paul J. Healy, 2020. "Incentives in experiments with objective lotteries," Experimental Economics, Springer;Economic Science Association, vol. 23(1), pages 1-29, March.
    2. Yaron Azrieli & Christopher P. Chambers & Paul J. Healy, 2018. "Incentives in Experiments: A Theoretical Analysis," Journal of Political Economy, University of Chicago Press, vol. 126(4), pages 1472-1503.
    3. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    4. Butler, D. J., 2000. "Do non-expected utility choice patterns spring from hazy preferences? An experimental study of choice 'errors'," Journal of Economic Behavior & Organization, Elsevier, vol. 41(3), pages 277-297, March.
    5. Vital Anderhub & Simon Gächter & Manfred Königstein, 2002. "Efficient Contracting and Fair Play in a Simple Principal-Agent Experiment," Experimental Economics, Springer;Economic Science Association, vol. 5(1), pages 5-27, June.
    6. Lawrence, Michael & Goodwin, Paul & Fildes, Robert, 2002. "Influence of user participation on DSS use and decision accuracy," Omega, Elsevier, vol. 30(5), pages 381-392, October.
    7. Janssen, Marco A. & Jager, Wander, 2000. "Preface," Ecological Economics, Elsevier, vol. 35(3), pages 307-310, December.
    8. Glen Archibald & Nathaniel Wilcox, 2002. "A New Variant of the Winner's Curse in a Coasian Contracting Game," Experimental Economics, Springer;Economic Science Association, vol. 5(2), pages 155-172, October.
    9. Christine R. Ohlert & Barbara E. Weißenberger, 2020. "Debiasing escalation of commitment: the effectiveness of decision aids to enhance de-escalation," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 30(4), pages 405-438, February.
    10. John Gathergood & Neale Mahoney & Neil Stewart & Jörg Weber, 2019. "How Do Individuals Repay Their Debt? The Balance-Matching Heuristic," American Economic Review, American Economic Association, vol. 109(3), pages 844-875, March.
    11. repec:cup:judgdm:v:9:y:2014:i:5:p:373-386 is not listed on IDEAS
    12. Glover, Steven M. & Prawitt, Douglas F. & Spilker, Brian C., 1997. "The Influence of Decision Aids on User Behavior: Implications for Knowledge Acquisition and Inappropriate Reliance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 72(2), pages 232-255, November.
    13. Hal R. Arkes & Victoria A. Shaffer & Mitchell A. Medow, 2007. "Patients Derogate Physicians Who Use a Computer-Assisted Diagnostic Aid," Medical Decision Making, , vol. 27(2), pages 189-202, March.
    14. Armstrong, J. Scott & Brodie, Roderick J., 1994. "Effects of portfolio planning methods on decision making: experimental results," MPRA Paper 81684, University Library of Munich, Germany.
    15. Glenn Boyle & Gerald Ward, 2018. "Do Better Informed Investors Always Do Better? A Buyback Puzzle," Economic Inquiry, Western Economic Association International, vol. 56(4), pages 2137-2157, October.
    16. Sofianos, Andis, 2022. "Self-reported & revealed trust: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 88(C).
    17. Kirchkamp, Oliver & Oechssler, Joerg & Sofianos, Andis, 2021. "The Binary Lottery Procedure does not induce risk neutrality in the Holt & Laury and Eckel & Grossman tasks," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 348-369.
    18. Benjamin Enke & Uri Gneezy & Brian Hall & David Martin & Vadim Nelidov & Theo Offerman & Jeroen van de Ven, 2020. "Cognitive Biases: Mistakes or Missing Stakes?," CESifo Working Paper Series 8168, CESifo.
    19. Shepherd, Dean A. & Zacharakis, Andrew, 2002. "Venture capitalists' expertise: A call for research into decision aids and cognitive feedback," Journal of Business Venturing, Elsevier, vol. 17(1), pages 1-20, January.
    20. Mark V. Pezzo & Stephanie P. Pezzo, 2006. "Physician Evaluation after Medical Errors: Does Having a Computer Decision Aid Help or Hurt in Hindsight?," Medical Decision Making, , vol. 26(1), pages 48-56, January.
    21. Dwenger, Nadja & Kübler, Dorothea & Weizsäcker, Georg, 2014. "Flipping a coin: Theory and evidence," Discussion Papers, Research Unit: Market Behavior SP II 2013-201r, WZB Berlin Social Science Center.

    More about this item

    Keywords

    Dual process theories; Diversification; Probability matching; Statistical independence; D83; D81;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    Statistics

    Access and download statistics

    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:kap:jrisku:v:34:y:2007:i:2:p:145-154. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.