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

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