Researchers have extensively investigated car dependency and its drivers, given the significant role of private vehicles as a transport mode and the various adverse effects associated with their use. In this research, we examine the topic at the level of global metropolitan areas. By utilising time series data available on two editions of the Mobility in Cities Database and conducting a longitudinal analysis through the Least Square Dummy Variable model, relevant variables' contribution to the evolution of car dependency is studied in 38 metropolitan areas worldwide. As a consequence, a combination of built environment, public transport and cost of travel variables were detected to influence car dependency over time. Additionally, a comparison is made between the outcome of the current analysis and the results of an earlier cross-sectional research on car dependency in metropolitan areas, that exhibits resemblances and disparities on variables affecting car dependency. Resemblances are observed in categories of determinant variables in both studies that primarily include built environment, public transport and cost of travel. Concerning disparities, different attributes of variables are found to play a part that are density of metropolitan areas and public transport fleet size per million inhabitants for this study but density of the urbanised area of metropolitan areas and public transport kilometres of service and journeys per capita for the earlier cross-sectional study.

中文翻译：

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全球大都市地区随时间推移的汽车依赖性贡献者


鉴于私家车作为交通方式的重要作用以及与使用它们相关的各种不利影响，研究人员广泛调查了对汽车的依赖性及其驾驶员。在这项研究中，我们在全球大都市地区层面研究了这个话题。通过利用两个版本的城市流动性数据库中提供的时间序列数据，并通过最小二乘虚拟变量模型进行纵向分析，研究了全球 38 个大都市地区相关变量对汽车依赖性演变的贡献。因此，检测到建筑环境、公共交通和旅行成本变量的组合会随着时间的推移影响汽车依赖性。此外，将当前分析的结果与早期关于大都市地区汽车依赖性的横断面研究的结果进行了比较，该研究在影响汽车依赖性的变量上表现出相似之处和差异。在这两项研究中，在决定因素变量的类别中都观察到相似之处，主要包括建筑环境、公共交通和旅行成本。关于差异，发现变量的不同属性起着一定的作用，即本研究的大都市区密度和每百万居民的公共交通车队规模，但早期横断面研究的大都市区城市化面积密度和公共交通公里数的服务和人均出行次数。