IDEAS home Printed from https://ideas.repec.org/p/mpg/wpaper/2008_42.html
   My bibliography  Save this paper

Information Processing in Decisions under Risk: Evidence for Compensatory Strategies based on Automatic Processes

Author

Listed:
  • Andreas Glöckner

    (Max Planck Institute for Research on Collective Goods, Bonn)

  • Ann-Katrin Herbold

    (University Hospital, Bonn)

Abstract

Many everyday decisions have to be made under risk and can be interpreted as choices between gambles with different outcomes that are realized with specific probabilities. The underlying cognitive processes were investigated by testing six sets of hypotheses concerning choices, decision times, and information search derived from cumulative prospect theory, decision field theory, priority heuristic and parallel constraint satisfaction models. Our participants completed forty decision tasks of two gambles with two non-negative outcomes each. Information search was recorded using eye-tracking technology. Results for all dependent measures conflict with the prediction of the non-compensatory priority heuristic and indicate that individuals use compensatory strategies. Choice proportions are well predicted by a cumulative prospect theory. Process measures, however, indicate that individuals do not rely on deliberate calculations of weighted sums. Information integration processes seem to be better explained by models that partially rely on automatic processes such as decision field theory or parallel constraint satisfaction models.

Suggested Citation

  • Andreas Glöckner & Ann-Katrin Herbold, 2008. "Information Processing in Decisions under Risk: Evidence for Compensatory Strategies based on Automatic Processes," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2008_42, Max Planck Institute for Research on Collective Goods.
  • Handle: RePEc:mpg:wpaper:2008_42
    as

    Download full text from publisher

    File URL: http://www.coll.mpg.de/pdf_dat/2008_42online.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:cup:judgdm:v:3:y:2008:i::p:304-316 is not listed on IDEAS
    2. Lohse, Gerald L. & Johnson, Eric J., 1996. "A Comparison of Two Process Tracing Methods for Choice Tasks," Organizational Behavior and Human Decision Processes, Elsevier, vol. 68(1), pages 28-43, October.
    3. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    4. repec:cup:judgdm:v:3:y:2008:i:6:p:457-462 is not listed on IDEAS
    5. Birnbaum, Michael H. & LaCroix, Adam R., 2008. "Dimension integration: Testing models without trade-offs," Organizational Behavior and Human Decision Processes, Elsevier, vol. 105(1), pages 122-133, January.
    6. 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..
    7. Andreas Glöckner & Tilmann Betsch, 2008. "Modeling Option and Strategy Choices with Connectionist Networks: Towards an Integrative Model of Automatic and Deliberate Decision Making," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2008_02, Max Planck Institute for Research on Collective Goods.
    8. Andreas Glöckner & Tilmann Betsch, 2008. "Multiple-Reason Decision Making Based on Automatic Processing," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2008_12, Max Planck Institute for Research on Collective Goods.
    9. 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..
    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. Andreas Glöckner, 2009. "Investigating intuitive and deliberate processes statistically: The multiple-measure maximum likelihood strategy classification method," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(3), pages 186-199, April.
    2. Nina Horstmann & Andrea Ahlgrimm & Andreas Glöckner, 2009. "How distinct are intuition and deliberation? An eye-tracking analysis of instruction-induced decision modes," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(5), pages 335-354, August.
    3. repec:cup:judgdm:v:4:y:2009:i:5:p:335-354 is not listed on IDEAS
    4. Traxler, Christian, 2012. "Majority voting and the welfare implications of tax avoidance," Journal of Public Economics, Elsevier, vol. 96(1), pages 1-9.
    5. Nina Horstmann & Andrea Ahlgrimm & Andreas Glöckner, 2009. "How Distinct are Intuition and Deliberation? An Eye-Tracking Analysis of Instruction-Induced Decision Modes," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2009_10, Max Planck Institute for Research on Collective Goods.
    6. repec:cup:judgdm:v:4:y:2009:i:3:p:186-199 is not listed on IDEAS
    7. Hakenes, Hendrik & Schnabel, Isabel, 2010. "Credit risk transfer and bank competition," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 308-332, July.

    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. Glöckner, Andreas & Betsch, Tilmann, 2008. "Do people make decisions under risk based on ignorance? An empirical test of the priority heuristic against cumulative prospect theory," Organizational Behavior and Human Decision Processes, Elsevier, vol. 107(1), pages 75-95, September.
    2. repec:cup:judgdm:v:6:y:2011:i:8:p:711-721 is not listed on IDEAS
    3. Andreas Glockner & Tilmann Betsch, 2011. "The Empirical content of theories in judgment and decision making: Shortcomings and remedies," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(8), pages 711-721, December.
    4. Moshe Glickman & Orian Sharoni & Dino J Levy & Ernst Niebur & Veit Stuphorn & Marius Usher, 2019. "The formation of preference in risky choice," PLOS Computational Biology, Public Library of Science, vol. 15(8), pages 1-25, August.
    5. Michael H. Birnbaum & Daniel Navarro-Martinez & Christoph Ungemach & Neil Stewart & Edika G. Quispe-Torreblanca, 2016. "Risky Decision making: Testing for violations of transitivity predicted by an editing mechanism," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(1), pages 75-91, January.
    6. repec:cup:judgdm:v:16:y:2021:i:6:p:1324-1369 is not listed on IDEAS
    7. Hao‐Che Wu & Michael K. Lindell & Carla S. Prater, 2015. "Process Tracing Analysis of Hurricane Information Displays," Risk Analysis, John Wiley & Sons, vol. 35(12), pages 2202-2220, December.
    8. Andreas Glöckner & Tilmann Betsch, 2008. "Do People Make Decisions Under Risk Based on Ignorance? An Empirical Test of the Priority Heuristic against Cumulative Prospect Theory," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2008_05, Max Planck Institute for Research on Collective Goods.
    9. Sudeep Bhatia & Graham Loomes & Daniel Read, 2021. "Establishing the laws of preferential choice behavior," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(6), pages 1324-1369, November.
    10. repec:cup:judgdm:v:11:y:2016:i:1:p:75-91 is not listed on IDEAS
    11. González-Vallejo, Claudia & Harman, Jason L. & Mullet, Etienne & Muñoz Sastre, Maria T., 2012. "An examination of the proportional difference model to describe and predict health decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 118(1), pages 82-97.
    12. van den Bergh, J.C.J.M. & Botzen, W.J.W., 2015. "Monetary valuation of the social cost of CO2 emissions: A critical survey," Ecological Economics, Elsevier, vol. 114(C), pages 33-46.
    13. Shoji, Isao & Kanehiro, Sumei, 2016. "Disposition effect as a behavioral trading activity elicited by investors' different risk preferences," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 104-112.
    14. Jonathan Meng & Feng Fu, 2020. "Understanding Gambling Behavior and Risk Attitudes Using Cryptocurrency-based Casino Blockchain Data," Papers 2008.05653, arXiv.org, revised Aug 2020.
    15. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    16. Boone, Jan & Sadrieh, Abdolkarim & van Ours, Jan C., 2009. "Experiments on unemployment benefit sanctions and job search behavior," European Economic Review, Elsevier, vol. 53(8), pages 937-951, November.
    17. Castro, Luciano de & Galvao, Antonio F. & Kim, Jeong Yeol & Montes-Rojas, Gabriel & Olmo, Jose, 2022. "Experiments on portfolio selection: A comparison between quantile preferences and expected utility decision models," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    18. Jos'e Cl'audio do Nascimento, 2019. "Behavioral Biases and Nonadditive Dynamics in Risk Taking: An Experimental Investigation," Papers 1908.01709, arXiv.org, revised Apr 2023.
    19. Francesco GUALA, 2017. "Preferences: Neither Behavioural nor Mental," Departmental Working Papers 2017-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    20. Bin Zou, 2017. "Optimal Investment In Hedge Funds Under Loss Aversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    21. Itzhak Gilboa & Andrew Postlewaite & Larry Samuelson & David Schmeidler, 2019. "What are axiomatizations good for?," Theory and Decision, Springer, vol. 86(3), pages 339-359, May.
    22. Wiafe, Osei K. & Basu, Anup K. & Chen, En Te, 2020. "Portfolio choice after retirement: Should self-annuitisation strategies hold more equities?," Economic Analysis and Policy, Elsevier, vol. 65(C), pages 241-255.
    23. Nicholas Barberis, 2012. "A Model of Casino Gambling," Management Science, INFORMS, vol. 58(1), pages 35-51, January.

    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:mpg:wpaper:2008_42. 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: Marc Martin (email available below). General contact details of provider: https://edirc.repec.org/data/mppggde.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.