Impacts of negative congestion experiences on acceptance of tradable credits schemes: Integration of NAM and TPB

Abstract

Prior negative congestion experiences can influence public acceptance of congestion charging policies; however, this area remains underexplored in both academic and practical contexts. This study investigates this issue by integrating the norm activation model (NAM) and the theory of planned behavior (TPB), focusing on public acceptance of tradable credits schemes (TCS). Specifically, acceptance is measured via attitudes toward TCS and behavioral intentions to reduce car use under TCS. Using latent profile analysis, 426 participants were categorized into three distinct groups based on their prior negative congestion experiences. The findings indicate that those with high reactions exhibit stronger behavioral intentions to reduce car use. Chain mediation analysis demonstrates that prior negative congestion experiences causally impact these behavioral intentions. Moderated mediation analysis further reveals that such experiences (e.g., anxiety and bodily reactions) moderate behavioral intentions under TCS. High levels of anxiety and bodily reactions weaken the impact of personal norms on attitudes toward TCS, suggesting that individuals with intense reactions to congestion are more likely to directly support TCS. Conversely, enhancing personal norms among individuals with lower anxiety or bodily reactions tend to increase their support for TCS. Furthermore, personal norms are found to be more influential than social norms, offering greater explanatory power.