Research on the comprehensive measurement of car dependence and its influencing factors
HE Mingwei
DENG Peiyao
LI Jianbo
LEI Jiayou
LIU Jie
Abstract：To address the issues of existing methods for measuring car dependence,including their single-dimensional focus and lack of clarity regarding influencing mechanisms,this study conducts a comprehensive analysis of car dependence and its influencing factors,using travel survey data collected from car users in Kunming.Incorporating three dimensions,which are objective dependence,subjec-tive dependence,and car usage conditions,the study employs a second-order structural equation model to comprehensively measure car dependence and analyze group-level differences.Subsequently,the Gradient Boosting Decision Tree(GBDT)model and the Shapley Additive exPlanations(SHAP)model are applied to explore the influence mechanisms of socio-economic attributes and built environ-ment on car dependence.The results indicate that the loading coefficients for objective dependence,subjective dependence,and car usage conditions are 0.725,0.242,and 0.852,respectively.Car de-pendence is constrained by car usage conditions,with objective dependence proving stronger than sub-jective factors,and varying significantly across demographic groups.The objective built environment accounts for 62.48%of the variance in car dependence,higher than 29.87%for socio-economic attri-butes and just 7.46%for the perceived built environment with a relatively low influence.The influence of the built environment on car dependence also exhibits nonlinear relationships and threshold effects.These findings present a novel framework for measuring car dependence and provide valuable insights for developing targeted strategies to reduce car dependence.
Keywords：transportation planning and managementcar dependencemeasurement methodGBDTbuilt environment
Publication Date：2025-02-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 128-135 )