2018
DOI: 10.3390/su10020484
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Application of Bayesian Multilevel Models Using Small and Medium Size City in China: The Case of Changchun

Abstract: 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 f… Show more

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Cited by 20 publications
(14 citation statements)
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“…It is found that household size has no significant influence on commuting mode choice. What's more, commuting distance is positively associated with the probability of car commuting, which is consistent with the previous study [23].…”
Section: Determinants Of Car Usesupporting
confidence: 92%
See 2 more Smart Citations
“…It is found that household size has no significant influence on commuting mode choice. What's more, commuting distance is positively associated with the probability of car commuting, which is consistent with the previous study [23].…”
Section: Determinants Of Car Usesupporting
confidence: 92%
“…Built environment consists of some measurements, including diversity, density, distance to transit, and destination accessibility, which have been summarized as "D variables". Land use mixture is a key component representing diversity, which has received much attention [23][24][25]. For instance, Acker and Witlox [25] treated car ownership as a mediating variable between built environment and car use and confirmed that land use mixture had a significant influence on car use at the significance level of 99% (Coeff.…”
Section: The Impacts Of Built Environment On Travel Behaviormentioning
confidence: 96%
See 1 more Smart Citation
“…Older adults with lower incomes, those who drive frequently, and those who live closer to downtown are more likely to have benefited from Oakville's free bus program [32]. Better transit services and street connectivity can reduce car dependency more effectively in mid-sized and small cities [33]. A preliminary exploratory analysis sheds light on the differences in activity participation, trip chaining, time-of-day preferences for trip departure, and transportation mode selection by non-workers in Bangalore city [34].…”
Section: Literature Reviewmentioning
confidence: 99%
“…In particular, we expected that a group of pilgrims over the age of 48 may have more time for pilgrimage, and may, therefore, show different mobility patterns when compared to people under 48 years old. Most previous studies in this field have included overall income as a variable explaining mode choice instead of personal disposable income, which has higher accuracy [33]. To this end, the multinomial logit model developed in this study was complemented with a multilevel model extension.…”
Section: Literature Reviewmentioning
confidence: 99%