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IGT's impacts on ride-hailing use and individual travel

机译:IGT对乘车使用和个人旅行的影响

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摘要

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.
机译:以前的研究探索了个人使用信息和通信技术(ICT)和旅行之间的关系。然而,这些研究往往专注于一种特定类型的旅行,并且没有考虑通过更大ICT渗透的乘坐骑行性的新形式的移动性,例如骑行。本文重点介绍了ICT使用如何影响个人的自我报告的旅行行为 - 包括旅行的总数,旅行的个人里程(PMT),以及在典型的旅行日旅行(VMT)的车辆里程 - 以及过去的骑行使用月。具体而言,我们调查替代或互补性是否占据ICT使用与个人净旅行之间的关系; ICT如何影响个人乘车的采用和使用频率;如何与个人的整体旅行行为相关联。使用2017年美国国家家庭旅游调查(NHTS)的数据,我们估计了一个结构方程模型,包括一套强大的个人,家庭,建筑环境和旅行特征,ICT使用频率和障碍模型(两部分回归)采用和频率的骑行使用。结果表明,更大的ICT与个人所需的旅行总数没有显着相关,但它确实可以显着预测更高的PMT和VMT。更大的ICT使用与过去30天在过去30天内使用乘车骑行,而是与被控制的这种有界结果的频率无关的关系。我们进一步发现,在控制其他常见因素后,个人的乘车使用与他们的PMT和VMT具有小的负相关性。我们的结果表明,未来研究的重要性检查ICT使用的机制可以增加距离个体旅行以及启用新的ICT模式,如乘车样式,如骑行方式,在个人和系统级别改变这些机制时发挥作用。

著录项

  • 来源
    《Transportation Research 》 |2020年第11期| 1-15| 共15页
  • 作者单位

    Singapore MIT Alliance Res & Technol Ctr SMART Singapore 138602 Singapore|MIT Dept Urban Studies & Planning Cambridge MA 02139 USA;

    MIT Mobil Syst Ctr Energy Initiat 77 Massachusetts Ave Cambridge MA 02139 USA;

    MIT Dept Urban Studies & Planning Cambridge MA 02139 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ICT; Ride-hailing use; Individual travel; Hurdle model;

    机译:ICT;骑行使用;个人旅行;障碍模型;

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