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.

先前的研究已经探索了个人对信息和通信技术（ICT）的使用与其旅行之间的关系。但是，这些研究通常只关注一种特定类型的旅行，而没有考虑通过ICT的广泛普及而实现的新型出行方式，例如乘车游览。本文着重探讨ICT的使用如何影响个人的自我报告出行行为，包括典型的出行日的出行总数，个人行驶里程（PMT）和车辆行驶里程（VMT）以及过去的乘车使用月。具体来说，我们调查替代或互补是否主导了ICT使用与个人净旅行之间的关系；ICT如何影响个人叫车的采用和使用频率；以及如何将打车服务与个人的整体出行行为联系起来。使用2017年美国全国家庭旅行调查（NHTS）的数据，我们估算出一个结构方程模型，其中包括一组稳健的个人，家庭，建筑环境和旅行特征，ICT使用频率以及障碍模型（分为两部分）乘车使用的频率和频率）。结果表明，较高的ICT与个人出行的总数没有显着相关，但确实可以预测较高的PMT和VMT。ICT的大量使用与个人在过去30天内是否曾使用过叫车服务有正向和实质上的相关性，但在控制此有限结果的情况下，与使用打车服务的频率没有显着关系。我们还发现，在控制了其他共同因素之后，个人的乘车使用与他们的PMT和VMT负相关性较小。我们的结果表明，未来研究的重要性很重要，即研究使用ICT来增加个人出行距离的机制，以及新的ICT支持模式（如叫车服务）在改变个人和系统级别的这些机制中所扮演的角色。