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Long distance mode choice and distributions of values of travel time savings in three European countries

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  • de Lapparent, M.,
  • Axhausen , K.W.
  • Frei, A.

Abstract

The study presented in this paper uses Stated Preferences (SP) data on mode choice collected as part of a recent survey on long distance travel undertaken in three European countries. The purpose of this article is twofold. It aims at exploring the impacts of the choice of mixing probability distributions while accounting for unobserved taste heterogeneity and it aims at focusing on the derived estimation of the distributions of values of travel time savings (VTTS). We compare eleven distributions, each having particular properties in terms of domain, location, scale, and shape. Due to the repetitive nature of the SP experiments, we estimate mixtures of Multinomial Logit (MNL) models for panel data. The results show that the mixing distributions differ from one country to another, suggesting existence of European disparities as it regards long-distance mode choice. The results also show that long-distance travellers pay a lot more attention to access and egress travel times to and from the main mode than to total travel time with the main mode.

Suggested Citation

  • de Lapparent, M., & Axhausen , K.W. & Frei, A., 2013. "Long distance mode choice and distributions of values of travel time savings in three European countries," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 53, pages 1-7.
  • Handle: RePEc:sot:journl:y:2013:i:53:p:1
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    File URL: https://www.openstarts.units.it/dspace/handle/10077/8687
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    References listed on IDEAS

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    1. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(03), pages 437-483, June.
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    3. Fosgerau, Mogens & Hess, Stephane, 2008. "Competing methods for representing random taste heterogeneity in discrete choice models," MPRA Paper 10038, University Library of Munich, Germany.
    4. Kenneth Train ., 2000. "Halton Sequences for Mixed Logit," Economics Working Papers E00-278, University of California at Berkeley.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, December.
    6. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    7. Fosgerau, Mogens, 2006. "Investigating the distribution of the value of travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 688-707, September.
    8. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    9. Hess, Stephane, 2007. "Posterior analysis of random taste coefficients in air travel behaviour modelling," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 203-212.
    10. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
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    Cited by:

    1. Arbués, Pelayo & Baños, José F. & Mayor, Matías & Suárez, Patricia, 2016. "Determinants of ground transport modal choice in long-distance trips in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 131-143.

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