Abstract

Carpooling is one of the travel demand management strategies to mitigate road congestion. Incentive-Based Travel Demand Management (IBTDM) strategies are pivotal for carpool promotion by providing incentives to address inconveniences and privacy apprehensions, yet their efficacy lacks validation. Considering the constraints of incentive budget as well as the penetration rate, it is important to assess the long-term impact of incentives on carpooling, improve the programs in term of information feedback and identify the individuals who are most inclined to carpool. To achieve the goals, we conducted a laboratory experiment through WeChat applet platform focused on carpooling and departure time choices. 194 participants successfully completed the entire experiment. The experiment emphasizes several crucial elements, including long term (participants making daily travel choices in one month), the interactivity and information feedback mechanisms, instruments enhancing participant engagement (redeeming incentives at the end of the experiment, etc.), exit questionnaire to collect travelers' behavioral strategies. The findings elucidate several key insights: 1) Incentives have a significant long-term influence on encouraging travelers to carpool, and compensatory mechanisms for unsuccessful carpool matches further amplify travelers' impetus. 2) IBTDM administrations can promote carpooling by improving feedback information according to travelers' learning effect in each round, such as introducing real-time displays of the numbers of carpool drivers and passengers. 3) Drawing from the analysis of travelers’ participation, behavioral compliance and psychological strategies of carpooling, it can be inferred that individuals with higher incomes, fewer commuting days who have a solid grasp of the experimental mechanism, constitute prospective candidates for carpooling programs. This work contributes to helping IBTDM administrations clarify the target participants and develop a more reasonable carpooling program. The behavioral data collection approach based on our laboratory experiment is portable for future studies.

Full Text
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