Abstract
Previous studies have explored the relationships between an individual's use of information and communication technology (ICT) and their travel. However, these studies often focus on one specific type of travel and have not considered new forms of mobility, such as ride-hailing, that are enabled by greater ICT penetration. This paper focuses on how ICT use impacts an individual's self-reported travel behavior—including total number of trips, personal miles traveled (PMT), and vehicle miles traveled (VMT) in a typical travel day—and ride-hailing use in the past month. Specifically, we investigate whether substitution or complementarity dominates the relationships between ICT use and an individual's net travel; how ICT impacts individual ride-hailing adoption and frequency of use; and how ride-hailing use is associated with an individual's overall travel behavior. Using data from the 2017 U.S. National Household Travel Survey (NHTS), we estimate a structural equation model that includes a robust set of individual, household, built environment, and travel characteristics, frequency of ICT use, and a hurdle model (two-part regression) of the adoption and frequency of ride-hailing use. Results reveal that greater ICT is not significantly related to the total number of trips that an individual takes, but it does significantly predict higher PMT and VMT. Greater ICT use is positively and substantively correlated with whether or not the individual has used ride-hailing in the past 30 days, but has no significant relationship with the frequency of ride-hailing use with this bounded outcome being controlled for. We further find that an individual's ride-hailing use has a small negative correlation with their PMT and VMT after controlling for other common factors. Our results indicate the importance of future research examining the mechanisms by which ICT use increases the distance individuals travel and the role that new ICT-enabled modes, such as ride-hailing, play in changing these mechanisms at both the individual and system levels.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-15 |
| Number of pages | 15 |
| Journal | Transportation Research Part A: Policy and Practice |
| Volume | 141 |
| DOIs | |
| State | Published - Nov 2020 |
Bibliographical note
Funding Information:The research is supported by the National Research Foundation , the CREATE programme from the Singapore Prime Minister’s Office, and the Singapore-MIT Alliance for Research and Technology Future Urban Mobility Interdisciplinary Research Group . The authors would like to thank their colleague Nathaniel Bailey for comments on the paper. The authors would also like to thank the editor and anonymous reviewers who provided constructive comments that helped to improve this work.
Funding Information:
The research is supported by the National Research Foundation, the CREATE programme from the Singapore Prime Minister's Office, and the Singapore-MIT Alliance for Research and Technology Future Urban Mobility Interdisciplinary Research Group. The authors would like to thank their colleague Nathaniel Bailey for comments on the paper. The authors would also like to thank the editor and anonymous reviewers who provided constructive comments that helped to improve this work.
Publisher Copyright:
© 2020 Elsevier Ltd
Keywords
- Hurdle model
- ICT
- Individual travel
- Ride-hailing use