查看文章

" Soft" travel demand management policies are gaining attention as they have shown cost-effective results compared to traditional “hard” strategies. Although there is a good body of research on the effect of incentive-based demand management strategies and their relation with socio-demographic groups as one of the most successful" soft" strategies, there is a need for additional evidence on the impacts of such schemes on traveler behavior over longer periods of time and also cross-market validation. In this study using Metropia app, an incentive-based behavior change framework, the authors present useful descriptive statistics for the usage of the app such as trip type, number of trips, and differences between cities that it has been implemented in. Moreover, the authors estimate an Ordered Logit model to see if there are correlations between trip characteristics and the propensity to earn more points and therefore peak spread. The findings indicate that, despite many similarities, reaction of users in different cities differ significantly to the long-term incentive scheme. While travelers consider duration and congestion level of their routes for deciding how to react to the amount of incentive they plan to receive, seasonality affect the general trend of the response.