Abstract
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.
| Original language | English (US) |
|---|---|
| Journal | International Journal of Sustainable Transportation |
| DOIs | |
| State | Published - Jan 1 2019 |
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Keywords
- Departure time choice
- incentive rewards
- information and communication technology (ICT)
- smartphone based data collection
- travel behavior evolution
ASJC Scopus subject areas
- Environmental Engineering
- Civil and Structural Engineering
- Geography, Planning and Development
- Renewable Energy, Sustainability and the Environment
- Automotive Engineering
- Transportation
Cite this
Will information and incentive affect traveler’s day-to-day departure time decisions?—An empirical study of decision making evolution process. / Hu, Xianbiao; Zhu, Xiaoyu; Chiu, Yi-Chang; Tang, Qing.
In: International Journal of Sustainable Transportation, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Will information and incentive affect traveler’s day-to-day departure time decisions?—An empirical study of decision making evolution process
AU - Hu, Xianbiao
AU - Zhu, Xiaoyu
AU - Chiu, Yi-Chang
AU - Tang, Qing
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - Departure time choice
KW - incentive rewards
KW - information and communication technology (ICT)
KW - smartphone based data collection
KW - travel behavior evolution
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UR - http://www.scopus.com/inward/citedby.url?scp=85065802620&partnerID=8YFLogxK
U2 - 10.1080/15568318.2019.1570402
DO - 10.1080/15568318.2019.1570402
M3 - Article
JO - International Journal of Sustainable Transportation
JF - International Journal of Sustainable Transportation
SN - 1556-8318
ER -