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Inclusion of latent variables in Mixed Logit models: Modelling and forecasting

Author

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  • Yáñez, M.F.
  • Raveau, S.
  • Ortúzar, J. de D.

Abstract

Travel demand models typically use mainly objective modal attributes as explanatory variables. Nevertheless, it has been well known for many years that attitudes and perceptions also influence users' behaviour. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of subjective factors. We estimated hybrid models in a short-survey panel context for data among many alternatives. The paper analyses the results of applying these models to a real urban case study, and also proposes an approach to forecasting using these models. Our results show that hybrid models are clearly superior to even highly flexible traditional models that ignore the effect of subjective attitudes and perceptions.

Suggested Citation

  • Yáñez, M.F. & Raveau, S. & Ortúzar, J. de D., 2010. "Inclusion of latent variables in Mixed Logit models: Modelling and forecasting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 744-753, November.
  • Handle: RePEc:eee:transa:v:44:y:2010:i:9:p:744-753
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    References listed on IDEAS

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    1. María Yáñez & Patricio Mansilla & Juan de Ortúzar, 2010. "The Santiago Panel: measuring the effects of implementing Transantiago," Transportation, Springer, vol. 37(1), pages 125-149, January.
    2. Mokhtarian, Patricia L. & Salomon, Ilan, 1997. "Modeling the desire to telecommute: The importance of attitudinal factors in behavioral models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(1), pages 35-50, January.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, December.
    4. Daniel McFadden, 1986. "The Choice Theory Approach to Market Research," Marketing Science, INFORMS, vol. 5(4), pages 275-297.
    5. Francisco Amador & Rosa González & Juan Ortúzar, 2005. "Preference Heterogeneity and Willingness to Pay for Travel Time Savings," Transportation, Springer, vol. 32(6), pages 627-647, November.
    6. Anders Skrondal & Sophia Rabe-Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745.
    7. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.
    8. Fujii, Satoshi & Gärling, Tommy, 2003. "Application of attitude theory for improved predictive accuracy of stated preference methods in travel demand analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(4), pages 389-402, May.
    9. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2005. "Latent Variables in a Travel Mode Choice Model: Attitudinal and Behavioural Indicator Variables," Working Paper Series 2005:5, Uppsala University, Department of Economics.
    10. Mauricio Sillano & Juan de Dios Ortúzar, 2005. "Willingness-to-pay estimation with mixed logit models: some new evidence," Environment and Planning A, Pion Ltd, London, vol. 37(3), pages 525-550, March.
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