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Examining the relationship between visual attention and stated preferences: A discrete choice experiment using eye-tracking

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  • Balcombe, Kelvin
  • Fraser, Iain
  • Williams, Louis
  • McSorley, Eugene

Abstract

We examine the relationship between visual attention and stated preferences derived from a discrete choice experiment. Focussing on consumer preferences regarding country of origin food labels, we employ a Bayesian infinite mixture Logit to derive results that reveal patterns of respondent heterogeneity that would not be captured assuming that random parameters take a specific distributional form. Our results reveal weak relationships between the eye-tracking data, our stated preference results and various attribute use questions. Although respondents with higher levels of visual attendance value specific attributes more highly, the strength of the relationship is fairly weak. Therefore, whilst we maintain that eye-tracking is useful, we argue that there needs to be greater clarity about the aims and purpose of using eye-tracking in stated preference research.

Suggested Citation

  • Balcombe, Kelvin & Fraser, Iain & Williams, Louis & McSorley, Eugene, 2017. "Examining the relationship between visual attention and stated preferences: A discrete choice experiment using eye-tracking," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 238-257.
    • Handle: RePEc:eee:jeborg:v:144:y:2017:i:c:p:238-257
    DOI: 10.1016/j.jebo.2017.09.023
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jeffrey E. Harris & Mariana Gerstenblüth & Patricia Triunfo, 2018. "Smokers’ Rational Lexicographic Preferences for Cigarette Package Warnings: A Discrete Choice Experiment with Eye Tracking," Documentos de Trabajo (working papers) 0218, Department of Economics - dECON.
    2. Dudinskaya, Emilia Cubero & Naspetti, Simona & Zanoli, Raffaele, 2020. "Using eye-tracking as an aid to design on-screen choice experiments," Journal of choice modelling, Elsevier, vol. 36(C).
    3. Edenbrandt, Anna Kristina & Lagerkvist, Carl-Johan & Lüken, Malte & Orquin, Jacob L., 2022. "Seen but not considered? Awareness and consideration in choice analysis," Journal of choice modelling, Elsevier, vol. 45(C).
    4. Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
    5. Huseynov, Samir & Krajbich, Ian & Palma, Marco A., 2018. "No Time to Think: Food Decision-Making under Time Pressure," 2018 Annual Meeting, August 5-7, Washington, D.C. 274135, Agricultural and Applied Economics Association.
    6. Ellen J Van Loo & Carola Grebitus & Rodolfo M Nayga & Wim Verbeke & Jutta Roosen, 2018. "On the Measurement of Consumer Preferences and Food Choice Behavior: The Relation Between Visual Attention and Choices," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 40(4), pages 538-562, December.
    7. Welling, Malte & Sagebiel, Julian & Rommel, Jens, 2023. "Information processing in stated preference surveys," Journal of Environmental Economics and Management, Elsevier, vol. 119(C).
    8. Fiedler, Susann & Hillenbrand, Adrian, 2020. "Gain-loss framing in interdependent choice," Games and Economic Behavior, Elsevier, vol. 121(C), pages 232-251.
    9. Fraser, Iain & Balcombe, Kelvin & Williams, Louis & McSorley, Eugene, 2021. "Preference stability in discrete choice experiments. Some evidence using eye-tracking," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    10. Carola Grebitus & Ellen J. Van Loo, 2022. "Relationship between cognitive and affective processes, and willingness to pay for pesticide‐free and GMO‐free labeling," Agricultural Economics, International Association of Agricultural Economists, vol. 53(3), pages 407-421, May.

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    More about this item

    Keywords

    Discrete choice experiment; Eye-tracking; Bayesian infinite-mixtures Logit;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other

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