The built environment and travel behavior in urban China: A literature review

Wang, Donggen; Zhou, Meng

doi:10.1016/j.trd.2016.10.031

Cited by 187 publications

(78 citation statements)

References 62 publications

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“…For instance, the results indicate that higher household income and bigger household size is significantly related to a higher probability of owning cars, which is consistent with most prior studies [32]. It has been well-studied that household income closely linked with car maintenance and daily use [21]. Moreover, bigger household size means that there are more children and elder people in the family so it might generate more driving demands for education and healthcare purposes.…”

Section: Car Ownership Modelsupporting

confidence: 87%

“…Besides the growth of income, other socio-demographic characteristics including gender, age, education, and household structure have been found to have significant influences on car ownership and use in China [57][58][59]. In addition, there are some factors that should be taken into consideration to differentiate China from other developed countries, especially in small and mid-sized cities in China, such as the Hukou and housing sources [21]. Hukou is a special system to control the population movement from rural area to cities [60].…”

Section: Determinants Of Car Ownership and Use In Chinamentioning

confidence: 99%

“…Therefore, studies on the determiners and how they influence the car ownership and use have gained wide interests among transportation researchers [7][8][9][10]. To address the challenges, it is widely acknowledged that a solution to reduce car dependency by promoting urban development patterns [11][12][13][14][15][16][17][18][19][20], in which built environment plays an important role [21]. Moreover, the built environment could change with rapid urbanization in China, which also provides a good opportunity for understanding the link between the built environment and car dependency.…”

Section: Introductionmentioning

confidence: 99%

“…However, there are several major gaps that need to be filled. First, although many studies have explored these impacts in developed countries, little is known about the relationship in urban China, especially in the context of small or mid-sized cities, in which car ownership and use is still increasing rapidly [21,25]. With rapid urbanization, many Chinese cities are reshaping their spatial forms and the number of car ownership is still growing constantly, which is significantly different from western cities.…”

Section: Introductionmentioning

confidence: 99%

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Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

et al. 2018

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Concerns about transportation energy consumption and emissions force urban planners and policy makers to pay more attention to the effects of car ownership and use on the environment in China. However, few studies have investigated the relationship between the built environment and car ownership and use in China, especially in mid-sized and small cities. This study uses Changchun, China as a case study and examines the potential impacts of the built environment and socio-demographics on car ownership and use for commuting simultaneously using Bayesian multilevel binary logistic models. Furthermore, the spatial autocorrelation of car ownership and use is recognized across traffic analysis zones (TAZs), which are specifically represented by the conditional autoregressive (CAR) model. The estimated results indicate that socio-demographic characteristics have significant effects on car ownership and use. Moreover, the built environment measured at the TAZ level still shows a significant association with other factors controlled. Specifically, it suggests that denser residential density, compact land use, better transit services and street connectivity can reduce car dependency more effectively. This study provides new insights into how the built environment influences the car ownership and use, which can be useful for urban planners and policy makers to develop strategies for reducing car dependency.

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Section: Car Ownership Modelsupporting

confidence: 87%

Section: Determinants Of Car Ownership and Use In Chinamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

et al. 2018

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“…At an aggregate level, the proliferation of active travel modes has the potential to help foster greater levels of physical activity, social interaction, and overall 'healthier' lifestyles, for example with respect to nutritional intake (Thompson and Taylor, 2017). These outcomes are conditional on a supportive built environment, whose relationship with travel behavior is well-studied (Wang and Zhou, 2017;Mokhtarian and Cao, 2008;Handy, Cao, and Mokhtarian, 2005). Thus, there is sufficient evidence in the literature indicating the critical influence of both land use patterns and infrastructure availability on human movement, especially regarding active transportation.…”

Section: Introductionmentioning

confidence: 99%

Where does active travel fit within local community narratives of mobility space and place?

Biehl

Chen

Sanabria-Véaz³

et al. 2019

Transportation Research Part A: Policy and Practice

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Encouraging sustainable mobility patterns is at the forefront of policymaking at all scales of governance as the collective consciousness surrounding climate change continues to expand. Not every community, however, possesses the necessary economic or socio-cultural capital to encourage modal shifts away from private motorized vehicles towards active modes. The current literature on 'soft' policy emphasizes the importance of tailoring behavior change campaigns to individual or geographic context. Yet, there is a lack of insight and appropriate tools to promote active mobility and overcome transport disadvantage from the local community perspective. The current study investigates the promotion of walking and cycling adoption using a series of focus groups with local residents in two geographic communities, namely Chicago's (1) Humboldt Park neighborhood and (2) suburb of Evanston. The research approach combines traditional qualitative discourse analysis with quantitative text-mining tools, namely topic modeling and sentiment analysis. The aim of the analysis is to uncover the local mobility culture, embedded norms and values associated with acceptance of active travel modes in different communities. The analysis uncovers that underserved populations within diverse communities view active mobility simultaneously as a necessity and as a symbol of privilege that is sometimes at odds with the local culture. Thereby, this research expands on the walking and cycling literature by providing novel insights regarding the perceived benefits of, and barriers to, equitable promotion of these modes. The mixed methods approach to analyzing community member discourses is translated into policy findings that are either tailored to local context or broadly applicable to curbing automobile dominance. Overall, residents of both Humboldt Park and Evanston envision a society in which multimodalism replaces car-centrism, but differences in the local physical and social environments would and should influence the manner in which overarching policy objectives are met.

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Self-Organisation Process, Accessibility and Principles of Justice

Lau

2020

Self-Organisation Shapes Travel Behaviours and Social Exclusion in Deprived Urban Neighbourhoods of China

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The built environment and travel behavior in urban China: A literature review

Cited by 187 publications

References 62 publications

Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

Where does active travel fit within local community narratives of mobility space and place?

Self-Organisation Process, Accessibility and Principles of Justice

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