Abstract Determining the likelihood of consumers purchasing automated vehicles (AVs) is extremely important for policymakers, researchers, and automobile manufacturers. Successful penetration of AVs into the market depends on the end-user’s perception and their affinity towards these vehicles. In this study, a comprehensive state-wide data has been used to determine the factors affecting the purchase likelihood of AVs. A wide range of potential factors are evaluated, including attributes related to safety and consumer’s perception, socio-economic and demographic factors, carsharing and ridesharing habits, types of housing and parking, types of owned and future vehicles, consumers’ preferences for buying or leasing a vehicle, and their residential region. A random parameters logit model with three outcomes of consumer’s affinity (i.e., agree, neither agree nor disagree, disagree) towards purchasing either partially (Levels 3 and 4) or fully (Level 5) AVs is considered. Moreover, to account for different layers of unobserved heterogeneity and to obtain a better statistical fit, the means and variances of random parameters are allowed to vary across the observations. The estimations results reveal significant differences between the determinants of consumer’s affinity towards partially and fully AVs. For partially AVs, the effect of certain variables related to the status of owing hybrid vehicles, education level, parking type, gender, and consumer’s opinion about the future of carsharing and ridesharing programs represented significant degrees of heterogeneity. For fully AVs, however, variables related to education level, parking type, housing type, and ethnicity were found to produce random parameters. The findings from this study can be used to estimate AV penetration and promote AV adoption.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Determinants of purchase likelihood for partially and fully automated vehicles: Insights from mixed logit model with heterogeneity in means and variances


    Beteiligte:


    Erscheinungsdatum :

    2022-03-11


    Format / Umfang :

    21 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch