Impact Model of the Effectiveness of Incentive Policies for Decarbonizing Transport Based on Traveler Heterogeneity

This study evaluates the incentive policies for decarbonizing transport in the transportation sector and designs an incentive policy evaluation system and a traveler-oriented questionnaire. Based on the questionnaire data, considering individual attributes, travel characteristics, and policy intensity, a quantitative evaluation model of the effectiveness of differentiated incentive policies for decarbonizing transport is established by using a multiple linear regression (MLR) model. The results show that the full electric vehicle (FEV) purchase subsidy policy has a strong incentive effect on the car-free population. The parking preferential policy for FEV is more effective for developed urban residents. Increased fuel taxes significantly motivate frequent travelers and female travelers, and the carbon benefit reward policy is particularly effective for older individuals. The study concludes with recommendations for the implementing future decarbonizing transport incentive policies tailored to various cities and demographic groups, providing reference and support for the selection and optimization of policy tools.