Research on the impact of new energy vehicle purchase intention considering the tail number restriction policy

To analyze the impact of car restriction policies on the willingness to purchase new energy vehicles, analyze the influencing factors and mechanisms of car purchase intention, quantify the impact of different factors, and propose a Structural Equation Model of planned behavior theory situational perceived risk. Firstly, based on the theory of planned behavior, situational factors, perceived value variables, and return risk variables were introduced to establish an adaptation model. A Likert 7-level scale was designed to conduct questionnaire surveys and statistics. After data processing, hypothesis testing and path analysis were conducted on the model, and a case study was conducted on a restricted bridge in Chongqing. The results showed that, in terms of influencing factors, Situational Factor (0.38), New-Energy Vehicle Attitude (0.35), and Subjective Norm (0.30) are the most important influencing factors on the willingness to purchase new energy vehicles. Among situational factors, Demand Management (0.18) have a greater impact; Gender and Acceptable Prices of New Energy Vehicles have a moderating effect. Women are more susceptible to subjective norms, while men are more concerned about the environmental and safety performance of new energy vehicles. Low budget groups are more affected by policies and advertising, while high budget groups are more concerned about the safety, economy, and fast charging performance of vehicles; From the implementation of bridge traffic restrictions before and after, the proportion of new energy vehicles in restricted bridges has shown a significant increase, which is consistent with the evaluation results of the structural equation model. The research conclusion can provide support for the formulation of urban car restriction policies, promotion of new energy vehicles, and enterprise marketing strategies.

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Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1145/3745238.3745415
Primary Topic
Electric Vehicles and Infrastructure
Type
article
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Research on the impact of new energy vehicle purchase intention considering the tail number restriction policy

X.B. Li, Hao Wu, Yabo Hu, Tao Xu et al.
Electric Vehicles and Infrastructure
article

Research on the impact of new energy vehicle purchase intention considering the tail number restriction policy

X.B. Li, Hao Wu, Yabo Hu, Tao Xu, Leong Jin Cheng
article en

Abstract

To analyze the impact of car restriction policies on the willingness to purchase new energy vehicles, analyze the influencing factors and mechanisms of car purchase intention, quantify the impact of different factors, and propose a Structural Equation Model of planned behavior theory situational perceived risk. Firstly, based on the theory of planned behavior, situational factors, perceived value variables, and return risk variables were introduced to establish an adaptation model. A Likert 7-level scale was designed to conduct questionnaire surveys and statistics. After data processing, hypothesis testing and path analysis were conducted on the model, and a case study was conducted on a restricted bridge in Chongqing. The results showed that, in terms of influencing factors, Situational Factor (0.38), New-Energy Vehicle Attitude (0.35), and Subjective Norm (0.30) are the most important influencing factors on the willingness to purchase new energy vehicles. Among situational factors, Demand Management (0.18) have a greater impact; Gender and Acceptable Prices of New Energy Vehicles have a moderating effect. Women are more susceptible to subjective norms, while men are more concerned about the environmental and safety performance of new energy vehicles. Low budget groups are more affected by policies and advertising, while high budget groups are more concerned about the safety, economy, and fast charging performance of vehicles; From the implementation of bridge traffic restrictions before and after, the proportion of new energy vehicles in restricted bridges has shown a significant increase, which is consistent with the evaluation results of the structural equation model. The research conclusion can provide support for the formulation of urban car restriction policies, promotion of new energy vehicles, and enterprise marketing strategies.

Chongqing Jiaotong University (CN)
Affordable and clean energy
Openalex Percentile: Top 83%
Electric Vehicles and Infrastructure
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Research on the impact of new energy vehicle purchase intention considering the tail number restriction policy — X.B. Li, Hao Wu, et al. · (2025) | TGRS Research Map | TGRS