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Eye-tracking and economic theories of choice under risk

Author

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  • Glenn W. Harrison

    (Georgia State University
    University of Cape Town)

  • J. Todd Swarthout

    (Georgia State University)

Abstract

We examine the ability of eye movement data to help understand the determinants of decision-making over risky prospects. We start with structural models of choice under risk, and use that structure to inform what we identify from the use of process data in addition to choice data. We find that information on eye movements does significantly affect the extent and nature of probability weighting behavior. Our structural model allows us to show the pathway of the effect, rather than simply identifying a reduced form effect. This insight should be of importance for the normative design of choice mechanisms for risky products. We also show that decision-response duration is no substitute for the richer information provided by eye-tracking.

Suggested Citation

  • Glenn W. Harrison & J. Todd Swarthout, 2019. "Eye-tracking and economic theories of choice under risk," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 26-37, August.
    • Handle: RePEc:spr:jesaex:v:5:y:2019:i:1:d:10.1007_s40881-019-00063-3
    DOI: 10.1007/s40881-019-00063-3
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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.
    2. Amos Arieli & Yaniv Ben-Ami & Ariel Rubinstein, 2011. "Tracking Decision Makers under Uncertainty," American Economic Journal: Microeconomics, American Economic Association, vol. 3(4), pages 68-76, November.
    3. Glenn W. Harrison & Jia Min Ng, 2016. "Evaluating The Expected Welfare Gain From Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 91-120, January.
    4. A. Marley, 1981. "Multivariate stochastic processes compatible with “aspect” models of similarity and choice," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 421-428, December.
    5. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    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. Glenn Harrison & E. Rutström, 2009. "Expected utility theory and prospect theory: one wedding and a decent funeral," Experimental Economics, Springer;Economic Science Association, vol. 12(2), pages 133-158, June.
    8. Harrison, Glenn W., 2008. "Neuroeconomics: A Critical Reconsideration," Economics and Philosophy, Cambridge University Press, vol. 24(3), pages 303-344, November.
    9. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    10. Glenn W. Harrison & Don Ross, 2018. "Varieties of paternalism and the heterogeneity of utility structures," Journal of Economic Methodology, Taylor & Francis Journals, vol. 25(1), pages 42-67, January.
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    Cited by:

    1. Segovia, Michelle & Palma, Marco & Lusk, Jayson L. & Drichoutis, Andreas, 2022. "Visual formats in risk preference elicitation: What catches the eye?," MPRA Paper 115572, University Library of Munich, Germany.
    2. Fiedler, Susann & Hillenbrand, Adrian, 2020. "Gain-loss framing in interdependent choice," Games and Economic Behavior, Elsevier, vol. 121(C), pages 232-251.
    3. Konstantinos Georgalos & Nathan Nabil, 2023. "Heuristics Unveiled," Working Papers 400814162, Lancaster University Management School, Economics Department.
    4. David J. Cooper & Ian Krajbich & Charles N. Noussair, 2019. "Choice-Process Data in Experimental Economics," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 5(1), pages 1-13, August.
    5. Filip-Mihai Toma & Cosmin-Octavian Cepoi & Matei Nicolae Kubinschi & Makoto Miyakoshi, 2023. "Gazing through the bubble: an experimental investigation into financial risk-taking using eye-tracking," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.

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    More about this item

    Keywords

    Risk; Individual decision making; Choice; Visual attention; Eye tracking; Experiment;
    All these keywords.

    JEL classification:

    • 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
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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