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

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

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 44 (2010)
    Issue (Month): 9 (November)
    Pages: 744-753

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    Handle: RePEc:eee:transa:v:44:y:2010:i:9:p:744-753

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    Related research

    Keywords: Latent variables Discrete choice models Mixed Logit Forecasting;

    References

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    1. 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.
    2. 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.
    3. 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.
    4. Mauricio Sillano & Juan de Dios Ort�zar, 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.
    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. 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.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    8. 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.
    9. 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.
    10. Daniel McFadden, 1986. "The Choice Theory Approach to Market Research," Marketing Science, INFORMS, vol. 5(4), pages 275-297.
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    Citations

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    Cited by:
    1. Björklund, Gunilla & Mortazavi , Reza, 2013. "Influences of infrastructure and attitudes to health on value of travel time savings in bicycle journeys," Working papers in Transport Economics 2013:35, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    2. Marcel Paulssen & Dirk Temme & Akshay Vij & Joan Walker, 2014. "Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice," Transportation, Springer, vol. 41(4), pages 873-888, July.
    3. Glerum, Aurélie & Atasoy, Bilge & Bierlaire, Michel, 2014. "Using semi-open questions to integrate perceptions in choice models," Journal of choice modelling, Elsevier, vol. 10(C), pages 11-33.
    4. Bergantino, Angela S. & Bierlaire, Michel & Catalano, Mario & Migliore, Marco & Amoroso, Salvatore, 2013. "Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators," Transport Policy, Elsevier, vol. 30(C), pages 77-91.
    5. Andrew Daly & Stephane Hess & Bhanu Patruni & Dimitris Potoglou & Charlene Rohr, 2012. "Using ordered attitudinal indicators in a latent variable choice model: a study of the impact of security on rail travel behaviour," Transportation, Springer, vol. 39(2), pages 267-297, March.
    6. Brey, Raúl & Walker, Joan L., 2011. "Latent temporal preferences: An application to airline travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 880-895, November.
    7. Rungie, Cam M. & Coote, Leonard V. & Louviere, Jordan J., 2012. "Latent variables in discrete choice experiments," Journal of choice modelling, Elsevier, vol. 5(3), pages 145-156.
    8. Stephane Hess & Nesha Beharry-Borg, 2012. "Accounting for Latent Attitudes in Willingness-to-Pay Studies: The Case of Coastal Water Quality Improvements in Tobago," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 52(1), pages 109-131, May.
    9. Di Ciommo, Floridea & Monzón, Andrés & Fernandez-Heredia, Alvaro, 2013. "Improving the analysis of road pricing acceptability surveys by using hybrid models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 302-316.

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