查看文章

There is a continued ownership of private cars, although the concern for the negative environmental impacts of private car use is growing. Emerging modes, such as cargo bikes, and mobility solutions, such as shared mobility services, are envisioned to reduce private car-ownership. However, to the best of authors' knowledge, a comprehensive analysis on private car-ownership (covering a large set of variables and dealing with emerging mobility solutions, different cities and multiple modelling levels) is still missing in the pertinent literature. Therefore, this study aims to fill this gap by developing disaggregate multinomial logit and aggregate linear regression models for private car-ownership, focusing on the cities of Madrid, Leuven and Regensburg. The novelty of this study lies in the methodological framework combining multiple data sources from multiple cities to perform analysis at multiple levels. The estimation results show the influence of (i) socio-demographic characteristics (age, gender, nationality, education, employment status, mobility restriction, household income, household size and household vehicle-ownership),(ii) mobility patterns (mobility rate, possession of public transport pass and license, and frequency of use of conventional modes),(iii) transport supply (public parking supply and fleet size of car-sharing and bike-sharing systems) and (iv) urban characteristics (population density). Based on the common influential factors across the three cities, generic car-ownership models have also been estimated to support application in other cities. Discussions are included on behavioural, policy and modelling insights. The contributions …