Examining public pre-acceptance of license plate restriction policy cancellation using structural equation modeling: Evidence from Hangzhou

Abstract

To better understand the factors influencing the pre-acceptance of canceling the License Plate Restriction (LPR) policy among Hangzhou residents, a questionnaire survey was conducted with 958 residents, and two analytical methods were applied. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to examine the complex relationships between psychological factors. Meanwhile, ordinal logistic regression was employed to analyze the influence of socio-economic attributes, such as gender, family life cycle, commuting time, and vehicle ownership, on policy pre-acceptance. The results indicate that the acceptance of alternative measures, perceived infringement, social norms, post-acceptance of the LPR policy, perceived effectiveness, perceived cost-benefit, and fairness significantly influence the public's pre-acceptance of canceling the LPR policy. Through the analysis of socio-economic attributes, it was found that families with children, groups with higher travel demands, and those with fewer vehicles are more likely to support canceling the LPR policy. Among these, males show a greater willingness to cancel the LPR policy compared to females. This study provides valuable insights for policymakers, offering evidence-based recommendations for optimizing Traffic Demand Management (TDM) strategies, particularly as the effectiveness of the LPR policy declines over time. The findings are significant as they contribute to the understanding of public attitudes toward policy change and can inform future traffic management reforms.