Nonlinear effects of residential and workplace built environment on car dependence |
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| Affiliation: | 1. College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China;2. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China;3. Mobilities and Urban Policy Lab, Graduate School of Advanced Science and Engineering, Graduate School for International Development and Cooperation, Hiroshima University, Higashi Hiroshima 739-8529, Japan;4. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China;1. College of Urban and Environmental Sciences, Peking University, No.5 Yiheyuan Road, Beijing 100871, China;2. Institute of Beijing Studies, Beijing Union University, 197 Bei-Tu-Cheng West Road, Beijing 100191, China;1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing, China;2. College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China;1. Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 211189, China;2. School of Automobile, Chang’an University, Xi’an, 710064, China. |
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| Abstract: | The relationships between the built environment (BE) and car dependence have been thoroughly evaluated, with a primary focus on the residential BE; however, the effects of the BE at workplaces have remained largely unexplored. Little is known about the potential nonlinear effects of the BE at both locations. Using data from a household travel survey in Changchun, China, we aimed to reveal the nonlinear effects of the residential and workplace BE on car dependence by building a gradient boosting decision trees model. The results show that the BE at both locations has strong explanatory power for car ownership and car purchasing intention. With relative contributions values of 17.90% and 18.13%, respectively, the BE at workplaces contributes less to explaining the two dependent variables than the BE at residences. All BE attributes show nonlinear effects on car ownership, and car purchasing intention and the effects differ between residential and workplace locations. |
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