An ex-post evaluation of the public acceptance of a license plate-based restriction policy: A case study of Xi'an, China

Over the last decade, there has been a steady increase in the number of cities in China and around the world adopting License Plate-based Restriction (LPR) policies, whereby vehicles are permitted to enter a defined road or area on the basis of a specific digit on the registration, license or number plate, to help mitigate traffic congestion and its associated impacts. Although the costs and benefits of implementing a LPR policy have been recognized, the public acceptance of a LPR policy has been less well studied. To better understand the factors affecting the public acceptance of a LPR policy, we improved the theoretical model by adding two factors related to attitude and new supposed deeper level effects between different factors. Accordingly, the theoretical model on exploring the factors affecting the public acceptance of such a scheme were explored in a questionnaire completed by 619 local residents in Xi'an, China and analyzed using a partial least square structural equation model (PLS-SEM). In addition, we carried out heterogeneity analysis to compare the differences between residents with various socio-economic attributes in factors with respect to affecting the acceptance of a LPR policy. The results show that problem perception, perceived effectiveness, perceived value and social norms exert a significant direct and indirect impact on the acceptance of a LPR policy. Important aims to reach can only indirectly affect the acceptance of a LPR policy by perceived effectiveness and perceived value, while policy cognition, attribution of responsibility have no significant influence on the acceptance of a LPR policy. Important aims and perceived effectiveness directly and direct affect the acceptance of a LPR policy by residents who are young, high-income and car-owning. The findings of this study can assist policy makers to design a more acceptable policy to further mitigate congestion situations.