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Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model


  • Kamargianni, Maria
  • Dubey, Subodh
  • Polydoropoulou, Amalia
  • Bhat, Chandra


In this paper, we apply Bhat and Dubey’s (2014) new probit-kernel based Integrated Choice and Latent Variable (ICLV) model formulation to analyze children’s travel mode choice to school. The new approach offered significant advantages, as it allowed us to incorporate three latent variables with a large data sample and with 10 ordinal indicators of the latent variables, and still estimate the model without any convergence problems. The data used in the empirical analysis originates from a survey undertaken in Cyprus in 2012. The results underscore the importance of incorporating subjective attitudinal variables in school mode choice modeling. The results also emphasize the need to improve bus and walking safety, and communicate such improvements to the public, especially to girls and women and high income households. The model application also provides important information regarding the value of investing in bicycling and walking infrastructure.

Suggested Citation

  • Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
  • Handle: RePEc:eee:transa:v:78:y:2015:i:c:p:473-488
    DOI: 10.1016/j.tra.2015.06.011

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    References listed on IDEAS

    1. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    2. Lissy La Paix & Michel Bierlaire & Elisabetta Cherchi & Andrés Monzón, 2013. "How urban environment affects travel behaviour: integrated choice and latent variable model for travel schedules," Chapters,in: Choice Modelling, chapter 10, pages 211-228 Edward Elgar Publishing.
    3. McNamara, David & Caulfield, Brian, 2013. "Examining the impact of carbon price changes under a personalised carbon trading scheme for transport," Transport Policy, Elsevier, vol. 30(C), pages 238-253.
    4. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    5. Matthew Rabin, 1998. "Psychology and Economics," Journal of Economic Literature, American Economic Association, vol. 36(1), pages 11-46, March.
    6. Bhat, Chandra R., 2015. "A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 50-77.
    7. Erika Spissu & Abdul Pinjari & Chandra Bhat & Ram Pendyala & Kay Axhausen, 2009. "An analysis of weekly out-of-home discretionary activity participation and time-use behavior," Transportation, Springer, vol. 36(5), pages 483-510, September.
    8. Akshay Vij & Joan L. Walker, 2014. "Hybrid choice models: the identification problem," Chapters,in: Handbook of Choice Modelling, chapter 22, pages 519-564 Edward Elgar Publishing.
    9. Shiftan, Yoram & Outwater, Maren L. & Zhou, Yushuang, 2008. "Transit market research using structural equation modeling and attitudinal market segmentation," Transport Policy, Elsevier, vol. 15(3), pages 186-195, May.
    10. Bhat, Chandra & Lockwood, Allison, 2004. "On distinguishing between physically active and physically passive episodes and between travel and activity episodes: an analysis of weekend recreational participation in the San Francisco Bay area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(8), pages 573-592, October.
    11. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    12. Bhat, Chandra R., 2014. "The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(1), pages 1-117, July.
    13. 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.
    14. Bhat, Chandra R. & Dubey, Subodh K., 2014. "A new estimation approach to integrate latent psychological constructs in choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 68-85.
    15. Anable, Jillian, 2005. "'Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behaviour segments using attitude theory," Transport Policy, Elsevier, vol. 12(1), pages 65-78, January.
    16. repec:eee:jotrge:v:20:y:2012:i:1:p:51-61 is not listed on IDEAS
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