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Distinguishing taste variation from error structure in discrete choice data

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  • Swait, Joffre
  • Bernardino, Adriana

Abstract

We propose as a practice that researchers investigate other sources of heterogeneity besides taste variation in the search for parsimonious recommendations about new product development and marketing program design. Some evidence exists that regularities in choice processes may be more common than previously thought (Louviere and Swait, 1996, Louviere et al., 1999; see also Stigler and Becker, 1977). In fact, it may be that taste homogeneity is more prevalent than expected, if we recognize other sources of heterogeneity properly. In this paper we show how discrete choice models confound taste heterogeneity and differences in error structure. We then illustrate the use of the Tree Extreme Value (TEV) model to investigate taste homogeneity in three trans-oceanic air travel markets, while controlling for error structure heterogeneity. We conclude that partial taste homogeneity exists across the markets, despite accentuated cultural differences; in addition, two of the routes exhibit a much higher degree of taste homogeneity, despite a significant difference in trip length.

Suggested Citation

  • Swait, Joffre & Bernardino, Adriana, 2000. "Distinguishing taste variation from error structure in discrete choice data," Transportation Research Part B: Methodological, Elsevier, vol. 34(1), pages 1-15, January.
  • Handle: RePEc:eee:transb:v:34:y:2000:i:1:p:1-15
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    References listed on IDEAS

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    2. Elisabetta Cherchi & Juan Dios Ortúzar, 2008. "Empirical Identification in the Mixed Logit Model: Analysing the Effect of Data Richness," Networks and Spatial Economics, Springer, vol. 8(2), pages 109-124, September.
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    4. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    5. Iain Embrey, 2017. "States of Nature and States of Mind: A Generalised Theory of Decision-Making, evaluated by application to Human Capital Development," Working Papers 209919485, Lancaster University Management School, Economics Department.
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    7. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2004. "Decomposing Unobserved Choice Variability In The Presence Of Consumers' Taste Heterogeneity," 2004 Annual meeting, August 1-4, Denver, CO 19954, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Stephen Harrison & Suh, J., 2005. "A Test for the Presence of Genuine or Pure Altruistic Motives in Non-Market Valuation: A Case Study Using Choice Modeling," Discussion Papers Series 338, School of Economics, University of Queensland, Australia.
    9. Börjesson, Maria & Fosgerau, Mogens, 2015. "Response time patterns in a stated choice experiment," Journal of choice modelling, Elsevier, vol. 14(C), pages 48-58.
    10. Joffre Swait & Rick L. Andrews, 2003. "Enriching Scanner Panel Models with Choice Experiments," Marketing Science, INFORMS, vol. 22(4), pages 442-460, September.
    11. Swait, Joffre & Adamowicz, Wiktor, 2001. "Choice Environment, Market Complexity, and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 86(2), pages 141-167, November.
    12. Bennett, Michael & Provencher, Bill & Bishop, Richard, 2004. "Experience, Expectations and Hindsight: Evidence of a Cognitive Wedge in Stated Preference Retrospectives," Staff Paper Series 468, University of Wisconsin, Agricultural and Applied Economics.
    13. Lee, Backjin & Timmermans, Harry J.P., 2007. "A latent class accelerated hazard model of activity episode durations," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 426-447, May.
    14. Koppelman, Frank S. & Sethi, Vaneet & Wen, Chieh-hua, 2001. "Alternative nested logit models: a response to comments by Andrew Daly on an earlier paper of Frank Koppelman and Chieh-hua Wen," Transportation Research Part B: Methodological, Elsevier, vol. 35(8), pages 725-729, September.
    15. Daziano, Ricardo A. & Achtnicht, Martin, 2014. "Accounting for uncertainty in willingness to pay for environmental benefits," Energy Economics, Elsevier, vol. 44(C), pages 166-177.
    16. Kjartan Sælensminde, 2002. "The Impact of Choice Inconsistencies in Stated Choice Studies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 403-420, December.
    17. Habib, Khandker M. Nurul & Swait, Joffre & Salem, Sarah, 2014. "Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 110-126.
    18. Díaz, Federico & Cantillo, Víctor & Arellana, Julian & Ortúzar, Juan de Dios, 2015. "Accounting for stochastic variables in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 222-237.
    19. Hess, Stephane & Stathopoulos, Amanda, 2013. "Linking response quality to survey engagement: A combined random scale and latent variable approach," Journal of choice modelling, Elsevier, vol. 7(C), pages 1-12.
    20. Beck, Matthew J. & Rose, John M. & Hensher, David A., 2013. "Consistently inconsistent: The role of certainty, acceptability and scale in choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 81-93.

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