IDEAS home Printed from
   My bibliography  Save this paper

Socio-psychological determinants of mode choice habits


  • Bouscasse, H.
  • Bonnel, P.


This article uses structural equation modeling with latent variables to analyse the influence of socio-psychological variables on mode choice habits. Considering theories from socio-psychological research, we propose to link together environmental concern, motives for car use, public transport perceptions and mode choice habits (public transport and car). Based on a recent survey carried out by the authors in the Rhône-Alpes Region of France, we show that a high environmental concern and positive perceptions of public transport promote public transport habits. The process by which environmental concern influences public transport habits is partially mediated by perceptions of public transport. Conversely, car use habits are reduced for people with a high environmental concern. Results also suggest that car use habits are more marked to the extent that they depend on affective and symbolic motives.

Suggested Citation

  • Bouscasse, H. & Bonnel, P., 2016. "Socio-psychological determinants of mode choice habits," Working Papers 2016-05, Grenoble Applied Economics Laboratory (GAEL).
  • Handle: RePEc:gbl:wpaper:2016-05

    Download full text from publisher

    File URL:
    Download Restriction: no

    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. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    3. Jensen, Mette, 1999. "Passion and heart in transport -- a sociological analysis on transport behaviour," Transport Policy, Elsevier, vol. 6(1), pages 19-33, January.
    4. 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.
    5. Raveau, Sebastián & Yáñez, María Francisca & Ortúzar, Juan de Dios, 2012. "Practical and empirical identifiability of hybrid discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1374-1383.
    6. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    7. Shen, Weiwei & Xiao, Weizhou & Wang, Xin, 2016. "Passenger satisfaction evaluation model for Urban rail transit: A structural equation modeling based on partial least squares," Transport Policy, Elsevier, vol. 46(C), pages 20-31.
    8. Guillaume Le Borgne & Lucie Sirieix & Sandrine Costa-Migeon, 2015. "La sensibilité du consommateur au gaspillage alimentaire : proposition d’une échelle de mesure," Post-Print hal-01487360, HAL.
    9. Albert Maydeu-Olivares, 2001. "Limited information estimation and testing of Thurstonian models for paired comparison data under multiple judgment sampling," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 209-227, June.
    10. 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.
    11. Motoaki, Yutaka & Daziano, Ricardo A., 2015. "A hybrid-choice latent-class model for the analysis of the effects of weather on cycling demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 217-230.
    Full references (including those not matched with items on IDEAS)

    More about this item



    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gbl:wpaper:2016-05. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Agnès Vertier). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.