Highlights Market segmentation is useful for formulating adequate, sustainable mobility policies. Segmentation should consider individual differences in attitudes and perceptions. We identified three groups: Traditionalists, Green Conscious and All Matters. We proposed sustainable strategies considering the heterogeneities of each group.

    Abstract This paper draws attention to the need for formulating tailored, sustainable transport policies considering heterogeneity in the population regarding their preferences and attitudes. In this regard, we propose a market segmentation for incentivising sustainable transport policies. Our analysis builds from the responses of 1,041 car owners towards environmentally friendly transport alternatives in a survey issued in the five largest Colombian metropolitan areas: Bogotá, Medellín, Cali, Barranquilla, and Bucaramanga. Using the collected data, we estimated a Multiple Indicators Multiple Causes (MIMIC) model to evaluate individual attitudes towards the environment, green transport policies, car use, and technology. A cluster analysis based on the MIMIC results identified three groups: Traditionalists, Green Conscious and All Matters. Results make the contradiction between car attachment and environmental concern evident. The lower the environmental concern, the higher the attachment to the car. However, the differences between Traditionalists and All Matters are less pronounced. Finally, we proposed sustainable strategies considering the heterogeneities of each group, analysed the implications of developing custom-made actions and marketing strategies for promoting sustainable transport policies, considering the interests and characteristics of each targeted group in the population.


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    Titel :

    Market segmentation for incentivising sustainable transport policies


    Beteiligte:
    Soto, Jose J. (Autor:in) / Cantillo, Victor (Autor:in) / Arellana, Julián (Autor:in)


    Erscheinungsdatum :

    2021-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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