01629897

Component

https://doi.org/10.3141/2666-12

To contribute to existing research on the influence of various factors on household car ownership in the Netherlands, this study addressed the question whether and to what extent the influence of economic, sociodemographic, and spatial factors on the number of cars owned by households has changed over time. There seems to be an absence of studies investigating the changing influence of these factors on car ownership in recent decades, and in the Netherlands. The study used the statistical method of ordered logistic regression on household mobility data on 162,593 households, collected by the National Traffic Survey of the Netherlands in 1987, 1991, 1995, 1999, 2003, 2010, and 2014. The results show that the influence of household income, size, composition, gender, age, education, working status, and suburbanization levels on car ownership changed substantially between 1987 and 2014. The strong influence of household income on household car ownership diminished quite remarkably between 1987 and 2014, whereas the influence of household size grew significantly during the period. The results could serve as a first step toward a predictive model that endogenously estimates household car ownership levels in the Netherlands.

01648400

17-01927

English

pp 103–111

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309441926

Digital/other

Figures (2) ; References (36) ; Tables (4)

Automobile ownership; Households; Income; Socioeconomic factors; Trend (Statistics)

Netherlands

Highways; Planning and Forecasting; Society; Vehicles and Equipment

TRIS, TRB, ATRI

Dec 8 2016 10:40AM

• Analysis of Car Type Preferences Among Students Based on Seemingly Unrelated Regression
• Analysis of the Impact of Technology Use on Multimodality and Activity Travel Characteristics
• Built Environment and Walking to School: Findings from a Student Travel Behavior Survey in Massachusetts
• Digital Narratives of Place: Learning About Neighborhood Sense of Place and Travel Through Online Responses
• Exploring Daily Rhythms of Interpersonal Contacts: Time-of-Day Dynamics of Human Interactions with Latent Class Cluster Analysis
• Exploring the Role of Social Media Platforms in Informing Trip Planning: Case of Yelp.com
• Impacts of Telecommuting on Nonmandatory Activity Participation: Role of Endogeneity
• Inferring Activities from Social Media Data
• Modeling Week Activity Schedules for Travel Demand Models
• Personalization of Routing Services: User Classification as a Method to Overcome the Cold Start Problem for Personalized Models
• The Path of Least Resistance: Identifying Supporters of Public and Active Transportation Projects