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Motivation and affective processing biases in risky decision making: A counter-regulation account

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  • Schwager, Susanne
  • Rothermund, Klaus

Abstract

We hypothesized that framing possible outcomes of decisions in terms of gains vs. losses should increase the salience of information that is incongruent in valence (counter-regulation principle: gain frame – negativity bias, loss frame – positivity bias). These incongruent attentional biases in the processing of positive and negative outcomes of risky options can explain why people tend to avoid risky options in a gain frame but tend to choose risky options in a loss frame. In line with our expectations, Experiment 1 revealed incongruent effects of framing on attentional biases for positive vs. negative stimuli in an evaluation task. In addition, valence bias predicted risk-seeking vs. risk-averse decisions and mediated the effect of framing on decision making. Two additional experiments investigated effects of valence biases on risky decision making by manipulating affective processing directly with an attention training task. Inducing a positivity (negativity) bias produced risk-seeking (risk-averse) decision behavior by enhancing the salience of win- or loss-related information in a gambling task with ambivalent color stimuli (Experiment 2) and by enhancing the impact of gain or loss outcomes on decision making in a coin toss (Experiment 3).

Suggested Citation

  • Schwager, Susanne & Rothermund, Klaus, 2013. "Motivation and affective processing biases in risky decision making: A counter-regulation account," Journal of Economic Psychology, Elsevier, vol. 38(C), pages 111-126.
    • Handle: RePEc:eee:joepsy:v:38:y:2013:i:c:p:111-126
    DOI: 10.1016/j.joep.2012.08.005
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    References listed on IDEAS

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    1. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    2. 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..
    3. Isen, Alice M. & Geva, Nehemia, 1987. "The influence of positive affect on acceptable level of risk: The person with a large canoe has a large worry," Organizational Behavior and Human Decision Processes, Elsevier, vol. 39(2), pages 145-154, April.
    4. Levine, John M. & Higgins, E. Tory & Choi, Hoon-Seok, 2000. "Development of Strategic Norms in Groups," Organizational Behavior and Human Decision Processes, Elsevier, vol. 82(1), pages 88-101, May.
    5. Levin, Irwin P. & Schneider, Sandra L. & Gaeth, Gary J., 1998. "All Frames Are Not Created Equal: A Typology and Critical Analysis of Framing Effects," Organizational Behavior and Human Decision Processes, Elsevier, vol. 76(2), pages 149-188, November.
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    Cited by:

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    3. Uparna, Jayaram & Bingham, Chris, 2022. "Breaking “Bad”: Negativity’s benefit for entrepreneurial funding," Journal of Business Research, Elsevier, vol. 139(C), pages 1353-1365.

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    More about this item

    Keywords

    2300; 2340; 2346; 2360; Framing effect; Risk; Counter-regulation; Valence bias; Prospect theory; Regulatory focus theory; Query theory;
    All these keywords.

    JEL classification:

    • D - Microeconomics
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics

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