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Does eye-tracking have an effect on economic behavior?

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  • Jennifer Kee
  • Melinda Knuth
  • Joanna N Lahey
  • Marco A Palma

Abstract

Eye-tracking is becoming an increasingly popular tool for understanding the underlying behavior driving human decisions. However, an important unanswered methodological question is whether the use of an eye-tracking device itself induces changes in participants’ behavior. We study this question using eight popular games in experimental economics chosen for their varying levels of theorized susceptibility to social desirability bias. We implement a simple between-subject design where participants are randomly assigned to either a control or an eye-tracking treatment. In seven of the eight games, eye-tracking did not produce different outcomes. In the Holt and Laury risk assessment (HL), subjects with multiple calibration attempts demonstrated more risk averse behavior in eye-tracking conditions. However, this effect only appeared during the first five (of ten) rounds. Because calibration difficulty is correlated with eye-tracking data quality, the standard practice of removing participants with low eye-tracking data quality resulted in no difference between the treatment and control groups in HL. Our results suggest that experiments may incorporate eye-tracking equipment without inducing changes in the economic behavior of participants, particularly after observations with low quality eye-tracking data are removed.

Suggested Citation

  • Jennifer Kee & Melinda Knuth & Joanna N Lahey & Marco A Palma, 2021. "Does eye-tracking have an effect on economic behavior?," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-25, August.
    • Handle: RePEc:plo:pone00:0254867
    DOI: 10.1371/journal.pone.0254867
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    References listed on IDEAS

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    1. Daniel T. Knoepfle & Joseph Tao-yi Wang & Colin F. Camerer, 2009. "Studying Learning in Games Using Eye-Tracking," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 388-398, 04-05.
    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. Elena Reutskaja & Rosemarie Nagel & Colin F. Camerer & Antonio Rangel, 2011. "Search Dynamics in Consumer Choice under Time Pressure: An Eye-Tracking Study," American Economic Review, American Economic Association, vol. 101(2), pages 900-926, April.
    4. Joanna N. Lahey & Douglas Oxley, 2016. "The Power of Eye Tracking in Economics Experiments," American Economic Review, American Economic Association, vol. 106(5), pages 309-313, May.
    5. Joseph Tao-yi Wang & Michael Spezio & Colin F. Camerer, 2010. "Pinocchio's Pupil: Using Eyetracking and Pupil Dilation to Understand Truth Telling and Deception in Sender-Receiver Games," American Economic Review, American Economic Association, vol. 100(3), pages 984-1007, June.
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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. Bigné, Enrique & Ruiz-Mafé, Carla & Badenes-Rocha, Alberto, 2023. "The influence of negative emotions on brand trust and intention to share cause-related posts: A neuroscientific study," Journal of Business Research, Elsevier, vol. 157(C).
    3. Fischbacher, Urs & Hausfeld, Jan & Renerte, Baiba, 2022. "Strategic incentives undermine gaze as a signal of prosocial motives," Games and Economic Behavior, Elsevier, vol. 136(C), pages 63-91.

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    More about this item

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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