Will Information and Incentive Affect Traveler's Day-To-Day Departure Time Decisions?–An Empirical Study of Decision Making Evolution Process
The uncertainty and unpredictability of a transportation network roots in the dynamics of individual travel behavior, which can be revised consciously or repeated habitually depending upon the reality and personality. In this paper, we propose to study the day-to-day departure time choice behavior of the travelers, using real observation data collected from a smartphone app, "Metropia". Influenced by the information and incentives provided in the app and the comparison with the experience gained from the last trip, a transformation process of traveler's day-to-day experience on departure time from an existing habit to a new one is analyzed in this study. The analysis result in a binary choice model for the shift of departure time for each repeated morning commute trip comparing with the last one, which proves that users' experience in app engagement, previous travel time saving, habitual travel time, incentives, and commute flexibility are able to trigger day-to-day behavioral change for their morning home-to work commutes. The findings of this research provide insights on the users' adaption to a new traffic information service along with incentives, and corresponding behavior changes over a transition period. The outcomes suggest ways to improve ICT services and incentive scheme, as well as the transportation operation and demand management.
X. Hu et al., "Will Information and Incentive Affect Traveler's Day-To-Day Departure Time Decisions?–An Empirical Study of Decision Making Evolution Process," International Journal of Sustainable Transportation, Taylor & Francis Ltd., May 2019.
The definitive version is available at https://doi.org/10.1080/15568318.2019.1570402
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Departure time choice; incentive rewards; information and communication technology (ICT); smartphone based data collection; travel behavior evolution
International Standard Serial Number (ISSN)
Article - Journal
© 2019 Taylor & Francis Ltd., All rights reserved.
01 May 2019