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

Author

Listed:
  • 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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    1. Kelvin Balcombe & Iain Fraser & Eugene McSorley, 2015. "Visual Attention and Attribute Attendance in Multi‐Attribute Choice Experiments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 447-467, April.
    2. Grebitus Carola & Roosen Jutta & Seitz Carolin Claudia, 2015. "Visual Attention and Choice: A Behavioral Economics Perspective on Food Decisions," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 13(1), pages 73-81, January.
    3. Sen Geng, 2016. "Decision Time, Consideration Time, And Status Quo Bias," Economic Inquiry, Western Economic Association International, vol. 54(1), pages 433-449, January.
    4. Uggeldahl, Kennet & Jacobsen, Catrine & Lundhede, Thomas Hedemark & Olsen, Søren Bøye, 2016. "Choice certainty in Discrete Choice Experiments: Will eye tracking provide useful measures?," Journal of choice modelling, Elsevier, vol. 20(C), pages 35-48.
    5. Burda, Martin & Harding, Matthew & Hausman, Jerry, 2008. "A Bayesian mixed logit-probit model for multinomial choice," Journal of Econometrics, Elsevier, vol. 147(2), pages 232-246, December.
    6. Stephane Hess & John Rose, 2012. "Can scale and coefficient heterogeneity be separated in random coefficients models?," Transportation, Springer, vol. 39(6), pages 1225-1239, November.
    7. Train, Kenneth, 2016. "Mixed logit with a flexible mixing distribution," Journal of choice modelling, Elsevier, vol. 19(C), pages 40-53.
    8. Rasch, Carsten & Louviere, Jordan J. & Teichert, Thorsten, 2015. "Using facial EMG and eye tracking to study integral affect in discrete choice experiments," Journal of choice modelling, Elsevier, vol. 14(C), pages 32-47.
    9. Krucien, Nicolas & Ryan, Mandy & Hermens, Frouke, 2017. "Visual attention in multi-attributes choices: What can eye-tracking tell us?," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 251-267.
    10. 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.
    11. Alicia Rihn & Hayk Khachatryan & Benjamin Campbell & Charles Hall & Bridget Behe, 2016. "Consumer preferences for organic production methods and origin promotions on ornamental plants: evidence from eye-tracking experiments," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 599-608, November.
    12. Kelvin Balcombe & Iain Fraser & Ben Lowe & Diogo Souza Monteiro, 2016. "Information Customization and Food Choice," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(1), pages 54-73.
    13. Van Loo, Ellen J. & Caputo, Vincenzina & Nayga, Rodolfo M. & Seo, Han-Seok & Zhang, Baoyue & Verbeke, Wim, 2015. "Sustainability labels on coffee: Consumer preferences, willingness-to-pay and visual attention to attributes," Ecological Economics, Elsevier, vol. 118(C), pages 215-225.
    14. Alicia L. Rihn & Chengyan Yue, 2016. "Visual Attention's Influence on Consumers’ Willingness‐to‐Pay for Processed Food Products," Agribusiness, John Wiley & Sons, Ltd., vol. 32(3), pages 314-328, July.
    15. Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
    16. Andrew Caplin & Daniel Martin, 2016. "The Dual-Process Drift Diffusion Model: Evidence From Response Times," Economic Inquiry, Western Economic Association International, vol. 54(2), pages 1274-1282, April.
    17. Oviedo, José L. & Caparrós, Alejandro, 2015. "Information and visual attention in contingent valuation and choice modeling: field and eye-tracking experiments applied to reforestations in Spain," Journal of Forest Economics, Elsevier, vol. 21(4), pages 185-204.
    18. Balcombe, Kelvin & Bradley, Dylan & Fraser, Iain & Hussein, Mohamud, 2016. "Consumer preferences regarding country of origin for multiple meat products," Food Policy, Elsevier, vol. 64(C), pages 49-62.
    19. Andrew Caplin, 2016. "Measuring and Modeling Attention," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 379-403, October.
    20. Michael Woodford, 2014. "Stochastic Choice: An Optimizing Neuroeconomic Model," American Economic Review, American Economic Association, vol. 104(5), pages 495-500, May.
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    More about this item

    Keywords

    Discrete choice experiment; Eye-tracking; Bayesian infinite-mixtures Logit;

    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
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other

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