Abstract

While public acceptance is a major obstacle to policy implementation, the factors affecting the acceptance of anti-congestion policies such as congestion pricing remain unclear. Few studies investigate whether public acceptance varies across neighborhoods of variant built environment features and with perceived air pollution levels which people are exposed to. In this article we developed a generalized multilevel structural equation model (GMSEM) with latent class variables to investigate the direct effects and mediation effects among built environment, air pollution perception, satisfaction with existing driving restriction policies, and public acceptance of congestion pricing strategies. We draw on a questionnaire survey of about 1300 residents from 26 neighborhoods in Beijing, where driving restriction policies have been implemented and congestion pricing policies under consideration. This research reveals that residents living in neighborhoods with high population density and low diversity of land uses and those proximity to transit service and in the central urban areas tend to more strongly support the congestion pricing policy. Residents who perceive serious air pollution and who believe in the policy effectiveness are more supportive to the pricing policy; they may pay more attention to the level of air pollution caused by congestion caused by driving. These findings demonstrate the importance of recognizing neighborhood variations in policy acceptance and provide policy implications for incorporating appropriate land use planning and promotion strategies.

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