Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice |
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| Institution: | 1. School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing 100191, China;2. Department of Civil Engineering, University of Memphis, Memphis 38152, United States;3. Faculty Research Associate, National Center for Smart Growth Research, University of Maryland, MD 20742, United States;1. Department of Urban Planning, Tongji University, Shanghai, People’s Republic of China;2. Department of Urban Design and Planning, University of Washington, Seattle, USA;1. The Center for Modern Chinese City Studies, East China Normal University, Shanghai 200062, China;2. Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, 500 Pillsbury Drive SE, Minneapolis, MN 55455, USA;1. Northwest Land and Resources Research Center, Institute of Transport Geography and Spatial Planning, Shaanxi Normal University, China;2. Humphrey School of Public Affairs, University of Minnesota, Twin Cities, USA;3. School of Geography and Planning, Sun Yat-sen University, China;1. School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing 100191, China;2. Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing 100191, China;3. Humphrey School of Public Affairs, University of Minnesota, Twin Cities, MN 55455, United States;1. Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong;2. Department of Management, Aarhus University, Aarhus, Denmark |
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| Abstract: | Concerns over transportation energy consumption and emissions have prompted more studies into the impacts of built environment on driving-related behavior, especially on car ownership and travel mode choice. This study contributes to examine the impacts of the built environment on commuter’s driving behavior at both spatial zone and individual levels. The aim of this study is threefold. First, a multilevel integrated multinomial logit (MNL) and structural equation model (SEM) approach was employed to jointly explore the impacts of the built environment on car ownership and travel mode choice. Second, the spatial context in which individuals make the travel decisions was accommodated, and spatial heterogeneities of car ownership and travel mode choice across traffic analysis zones (TAZs) were recognized. Third, the indirect effects of the built environment on travel mode choice through the mediating variable car ownership were calculated, in other words, the intermediary nature of car ownership was considered. Using the Washington metropolitan area as the study case, the built environment measures were calculated for each TAZ, and the commuting trips were drawn from the household travel survey in this area. To estimate the model parameters, the robust maximum likelihood (MLR) method was used. Meanwhile, a comparison among different model structures was conducted. The model results suggest that application of the multilevel integrated MNL and SEM approach obtains significant improvements over other models. This study give transportation planners a better understanding on how the built environment influences car ownership and commuting mode choice, and consequently develop effective and targeted countermeasures. |
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| Keywords: | Car ownership Travel mode choice Built environment Spatial heterogeneity Mediating effect |
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