How the norm activation model explains the individuals’ response to Tradable Credit Schemes and reducing car use

Abstract

This study explores how individuals respond to the Tradable Credits Scheme (TCS), a cap-and-trade approach aiming to reduce congestion, by introducing the norm activation model (NAM). The research utilized questionnaire data from 544 Chinese participants. First, we analyzed the credit proportion thresholds for shifting travel mode and the distribution of participants corresponding to five thresholds. Second, we developed the latent and explicit variable model, revealing that NAM could explain acceptability of TCS, with personal norms being crucial; specifically, personal norms could positively predict perceived effectiveness, attitude towards TCS, and behavior intention. Finally, we performed a moderated-mediation analysis, for which the findings suggested TCS's potential in promoting sustainable travel, with driving licenses and the frequency of weekly trips as significant behavior moderators. People with driving licenses and having less travels per week would be more likely to intensify their behavior intention by enhancing their recognition on TCS. This work contributes to understanding TCS as an innovative congestion policy and its influence on sustainable travel behaviors.