IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-01084027.html
   My bibliography  Save this paper

Travellers’ profiles definition using statistical multivariate analysis of attitudinal variables

Author

Listed:
  • Cristina Pronello

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Cristian Camusso

    (Interuniversity Department of Regional and Urban Studies and Planning - Polito - Politecnico di Torino = Polytechnic of Turin)

Abstract

This paper aims at presenting a set of travellers' typologies using attributes characterizing people's attitude, through an Exploratory Factor Analysis (EFA), and a subsequent cluster analysis (CA), based on the obtained latent constructs. The final goal is to contribute to deepen the knowledge on market segmentation in order to define more people-oriented transport policies, focusing on a medium size Italian city, Alessandria. Six factors have been defined on which the k-means cluster analysis has been applied finding four travellers' profiles.Results confirm certain hypothesis from behavioural psychological theories. Attitude–behaviour relationships loosen when habits, consolidated in time, do intervene; moreover in small-medium urban context, as opposed to large and dense cities, insufficient transport supply does not favour the use of alternative modes to the motor vehicle, if not to the cost of a great loss in efficiency. In fact, the study shows how significant constraints such as necessity, time saving, and low transport supply (mainly designed around students going to school) are in determining a behavioural change, so that the "right general attitudes" are not sufficient to obtain a real modal shift. This leads to expect opportunistic behaviours, even within a overall positive attitude towards the environment. Actually, that overall positive attitude is not enough to prompt consistent behaviour unless a marked self-control and strong motivation are present. These two features seem to be missing in the interviewed sample of population, unlike what emerges from other studies undertaken in Northern Europe. The geographic location most likely plays a significant role in such a difference. Indeed, cultural background and the prevailing habits of the population may well explain the "slackening" of the bond between moral norms and behaviour, and the subsequent search for surrogates (e.g. the high willingness to pay for environmental protection) to justify the unwillingness to forgo the private vehicle on behalf of more sustainable modes.Finally, our study seems to prove that education could play a key role in transport policy formulation but, moreover, in social policy, as individuals more akin to modal shift are those showing higher levels of instruction.

Suggested Citation

  • Cristina Pronello & Cristian Camusso, 2011. "Travellers’ profiles definition using statistical multivariate analysis of attitudinal variables," Post-Print halshs-01084027, HAL.
  • Handle: RePEc:hal:journl:halshs-01084027
    DOI: 10.1016/j.jtrangeo.2011.06.009
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jing Yu Pan & Dothang Truong, 0. "Low cost carriers in China: passenger segmentation, controllability, and airline selection," Transportation, Springer, vol. 0, pages 1-26.
    2. Paula Vasquez-Henriquez & Eduardo Graells-Garrido & Diego Caro, 2020. "Tweets on the Go: Gender Differences in Transport Perception and Its Discussion on Social Media," Sustainability, MDPI, vol. 12(13), pages 1-21, July.
    3. Xuemei Fu & Zhicai Juan, 2017. "Accommodating preference heterogeneity in commuting mode choice: an empirical investigation in Shaoxing, China," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(4), pages 434-448, May.
    4. Timmer, Sebastian & Bösehans, Gustav & Henkel, Sven, 2023. "Behavioural norms or personal gains? – An empirical analysis of commuters‘ intention to switch to multimodal mobility behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    5. Jia, Ning & Li, Liying & Ling, Shuai & Ma, Shoufeng & Yao, Wang, 2018. "Influence of attitudinal and low-carbon factors on behavioral intention of commuting mode choice – A cross-city study in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 108-118.
    6. Jean-Baptiste Gaborieau & Cristina Pronello, 2021. "Validation of a unidimensional and probabilistic measurement scale for pro-environmental behaviour by travellers," Transportation, Springer, vol. 48(2), pages 555-593, April.
    7. Sun, Shichao & Duan, Zhengyu, 2019. "Modeling passengers’ loyalty to public transit in a two-dimensional framework: A case study in Xiamen, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 295-309.
    8. Miltos Kyriakidis & Jaka Sodnik & Kristina Stojmenova & Arnór B. Elvarsson & Cristina Pronello & Nikolas Thomopoulos, 2020. "The Role of Human Operators in Safety Perception of AV Deployment—Insights from a Large European Survey," Sustainability, MDPI, vol. 12(21), pages 1-24, November.
    9. Domokos Esztergár-Kiss, 2020. "Trip Chaining Model with Classification and Optimization Parameters," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    10. Chankrajang, Thanyaporn & Muttarak, Raya, 2017. "Green Returns to Education: Does Schooling Contribute to Pro-Environmental Behaviours? Evidence from Thailand," Ecological Economics, Elsevier, vol. 131(C), pages 434-448.
    11. Haustein, Sonja & Nielsen, Thomas A. Sick, 2016. "European mobility cultures: A survey-based cluster analysis across 28 European countries," Journal of Transport Geography, Elsevier, vol. 54(C), pages 173-180.
    12. Metcalfe, Robert & Dolan, Paul, 2012. "Behavioural economics and its implications for transport," Journal of Transport Geography, Elsevier, vol. 24(C), pages 503-511.
    13. Xuemei Fu, 2021. "A novel perspective to enhance the role of TPB in predicting green travel: the moderation of affective-cognitive congruence of attitudes," Transportation, Springer, vol. 48(6), pages 3013-3035, December.
    14. Xuemei Fu & Zhicai Juan, 2016. "Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences," Transportation, Springer, vol. 43(1), pages 37-51, January.
    15. Jing Yu Pan & Dothang Truong, 2021. "Low cost carriers in China: passenger segmentation, controllability, and airline selection," Transportation, Springer, vol. 48(4), pages 1587-1612, August.
    16. Xuemei Fu & Zhicai Juan, 2016. "Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences," Transportation, Springer, vol. 43(1), pages 37-51, January.
    17. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2019. "A Study of Tourists’ Holiday Rush-Hour Avoidance Travel Behavior Considering Psychographic Segmentation," Sustainability, MDPI, vol. 11(13), pages 1-20, July.
    18. Cristina Pronello & Jean-Baptiste Gaborieau, 2018. "Engaging in Pro-Environment Travel Behaviour Research from a Psycho-Social Perspective: A Review of Behavioural Variables and Theories," Sustainability, MDPI, vol. 10(7), pages 1-22, July.
    19. Javier Tarriño-Ortiz & Julio A. Soria-Lara & Juan Gómez & José Manuel Vassallo, 2021. "Public Acceptability of Low Emission Zones: The Case of “Madrid Central”," Sustainability, MDPI, vol. 13(6), pages 1-17, March.
    20. Wolf, Ingo & Schröder, Tobias, 2019. "Connotative meanings of sustainable mobility: A segmentation approach using cultural sentiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 259-280.
    21. Sun, Shichao & Xu, Lingyu & Yao, Yukun & Duan, Zhengyu, 2021. "Investigating the determinants to retain spurious-loyalty passengers: A data-fusion based approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 70-83.
    22. Thomas Klinger & Martin Lanzendorf, 2016. "Moving between mobility cultures: what affects the travel behavior of new residents?," Transportation, Springer, vol. 43(2), pages 243-271, March.
    23. Alonso-González, María J. & Hoogendoorn-Lanser, Sascha & van Oort, Niels & Cats, Oded & Hoogendoorn, Serge, 2020. "Drivers and barriers in adopting Mobility as a Service (MaaS) – A latent class cluster analysis of attitudes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 378-401.

    Corrections

    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:hal:journl:halshs-01084027. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.