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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
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    4. 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.
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    Citations

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    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.

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