Understanding factors influencing user engagement in incentive-based travel demand management program

Songhua Hu, Chenfeng Xiong, Ya Ji, Xin Wu, Kailun Liu and Paul Schonfeld

Transportation Research Part A: Policy and Practice, 2024, vol. 186, issue C

Abstract: Incentive-based travel demand management (IBTDM) has proven effective in mitigating traffic congestion. However, a comprehensive understanding of factors influencing user engagement in IBTDM is lacking due to limited empirical evidence from real-world applications. This study bridges this research gap by examining data from over 4,000 users in an actual IBTDM program, incenTrip, in the Washington, D.C.-Baltimore region. Employing Poisson-Tweedie generalized additive models to account for excess zeros and nonlinear relations, the study examines how home and work-related factors influence users’ enrollment and engagement, measured by the number of registrations, generated trips, and earned incentives at a census block group level. Results reveal that: 1) Urban areas with high population densities and low incomes attract more users and encourage more green travel. 2) Initial enrollment is higher among young, female, Asian, and highly-educated residents, although their subsequent engagement may not be sustained. 3) Workers in educational institutions and retail trades exhibit higher enrollment and maintain stronger engagement than other workers. 4) Well-developed transportation facilities and a higher density of points of interest near the users’ homes or workplaces substantially enhance program attractiveness. 5) Nonlinearities, particularly threshold effects, are observed across various relations analyzed. These findings have valuable policy implications for optimizing ongoing IBTDM programs and informing future initiatives. Policy recommendations include implementing targeted and progressive incentives, adopting combined TDM strategies, prioritizing user-friendly designs, fostering collaboration with employers, and employing nuanced policymaking.

Keywords: Incentive; Economics; User profiles; Travel demand management; Poisson-Tweedie generalized additive model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tra.2024.104145

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