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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.

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Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 34 (2000)
Issue (Month): 1 (January)
Pages: 1-15

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Handle: RePEc:eee:transb:v:34:y:2000:i:1:p:1-15

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  1. Goodwin, Cathy & Verhage, Bronislaw J., 1989. "Role perceptions of services: A cross-cultural comparison with behavioral implications," Journal of Economic Psychology, Elsevier, vol. 10(4), pages 543-558.
  2. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Empirical test of a constrained choice discrete model: Mode choice in São Paulo, Brazil," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 103-115, April.
  3. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," University of California Transportation Center, Working Papers qt3tb6j874, University of California Transportation Center.
  4. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Incorporating random constraints in discrete models of choice set generation," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 91-102, April.
  5. Steckel, Joel H & Vanhonacker, Wilfried R, 1988. "A Heterogeneous Conditional Logit Model of Choice," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 391-98, July.
  6. Stigler, George J & Becker, Gary S, 1977. "De Gustibus Non Est Disputandum," American Economic Review, American Economic Association, vol. 67(2), pages 76-90, March.
  7. Wagner A. Kamakura & Byung-Do Kim & Jonathan Lee, 1996. "Modeling Preference and Structural Heterogeneity in Consumer Choice," Marketing Science, INFORMS, vol. 15(2), pages 152-172.
  8. Bhat, Chandra R., 1995. "A heteroscedastic extreme value model of intercity travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 29(6), pages 471-483, December.
  9. Daly, Andrew, 1987. "Estimating "tree" logit models," Transportation Research Part B: Methodological, Elsevier, vol. 21(4), pages 251-267, August.
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Cited by:
  1. 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.
  2. Swait, Joffre & Adamowicz, Wiktor L., 1999. "Choice Environment, Market Complexity and Consumer Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into Models of Consumer Choice," Staff Paper Series 24093, University of Alberta, Department of Resource Economics and Environmental Sociology.
  3. 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.
  4. 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.
  5. Daziano, Ricardo A. & Achtnicht, Martin, 2013. "Accounting for uncertainty in willingness to pay for environmental benefits," ZEW Discussion Papers 13-059, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  6. Kjartan Sælensminde, 2002. "The Impact of Choice Inconsistencies in Stated Choice Studies," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 23(4), pages 403-420, December.
  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. 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.
  9. 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.
  10. Mark Lijesen & Peter Nijkamp & Eric Pels, 2005. "The Home Carrier Advantage in Civil Aviation," Tinbergen Institute Discussion Papers 05-011/3, Tinbergen Institute.
  11. 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.
  12. 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.

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