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| Tekkaya, A. Erman |
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| Förster, Peter |
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| Mudimu, George T. |
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| Shibata, Lillian Marie |
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| Talabbeydokhti, Nasser |
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| Laffite, Ernesto Dante Rodriguez |
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| Schöpke, Benito |
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| Gobis, Anna |
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| Alfares, Hesham K. |
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| Münzel, Thomas |
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| Joy, Gemini Velleringatt |
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| Oubahman, Laila |
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| Filali, Youssef |
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| Philippi, Paula |
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| George, Alinda |
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| Lucia, Caterina De |
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| Avril, Ludovic |
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| Belachew, Zigyalew Gashaw |
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| Kassens-Noor, Eva | Darmstadt |
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| Cho, Seongchul |
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| Tonne, Cathryn |
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| Hosseinlou, Farhad |
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| Ganvit, Harsh |
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| Schmitt, Konrad Erich Kork |
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| Grimm, Daniel |
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Circella, Giovanni
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (21/21 displayed)
- 2023Combining disparate surveys across time to study satisfaction with life: the effects of study context, sampling method, and transport attributescitations
- 2023Changes in Active Travel During the COVID-19 Pandemiccitations
- 2023Conclusion: Reflections and Lessons from the Pandemic
- 2023Adoption of Telecommuting and Changes in Travel Behavior in Southern California During the COVID-19 Pandemiccitations
- 2022Adoption of telecommuting and changes in travel behavior in Southern California during the COVID-19 pandemiccitations
- 2021Who doesn’t mind waiting? Examining the relationships between waiting attitudes and person- and travel-related attributescitations
- 2021Glimpse of the future : simulating life with personally owned autonomous vehicles and their implications on travel behaviorscitations
- 2021What drives the gap? Applying the Blinder–Oaxaca decomposition method to examine generational differences in transportation-related attitudescitations
- 2021Do millennials value travel time differently because of productive multitasking? A revealed-preference study of Northern California commuterscitations
- 2020Will autonomous vehicles change residential location and vehicle ownership? Glimpses from Georgiacitations
- 2020Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in Californiacitations
- 2019Identifying latent mode-use propensity segments in an all-AV eracitations
- 2019Who doesn’t mind waiting? Examining the relationships between waiting attitudes and person- and travel-related attributescitations
- 2019It’s not all fun and games : an investigation of the reported benefits and disadvantages of conducting activities while commutingcitations
- 2019How do activities conducted while commuting influence mode choice? Using revealed preference models to inform public transportation advantage and autonomous vehicle scenarioscitations
- 2019Millennials in cities : comparing travel behaviour trends across six case study regionscitations
- 2018Transport policy in the era of ridehailing and other disruptive transportation technologiescitations
- 2018Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experimentcitations
- 2018Projecting travelers into a world of self-driving vehicles : estimating travel behavior implications via a naturalistic experimentcitations
- 2015The estimation of changes in rail ridership through an onboard survey: did free Wi-Fi make a difference to Amtrak’s Capitol Corridor service?citations
- 2006Smart Technologies for Environmental Safety and Knowledge Enhancement in Intermodal Transport
Places of action
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booksection
Transport policy in the era of ridehailing and other disruptive transportation technologies
Abstract
Transportation is changing at an unprecedented pace. New transportation options provided by shared mobility providers are expanding the set of travel alternatives and they account for an increasing percentage of total trips. In particular, ridehailing services, such as those provided by Uber and Lyft, have become a popular option for trips in cities and metropolitan areas of North America. Understanding the impacts of these mobility services on the use of other travel modes and other components of travel behavior is not easy. In this chapter, we analyze the use of ridehailing using data from the California Millennials Dataset, a rich dataset that contains information on individual attitudes, residential location, vehicle ownership, travel behavior and the adoption of emerging transportation services from approximately 2000 millennials and members of the preceding Generation X in California. We find that users of ridehailing are predominantly well-educated independent millennials or young Gen Xers, who do not have children and live in urban neighborhoods. These travelers also tend to use ridehailing more frequently. Suburban residents who live with their families are less likely to use Uber/Lyft frequently, though their likelihood of using ridehailing increases if they make long-distance trips by plane. We find that single-user ridehailing replaces the use of public transit, walking and bicycling, and, to some extent, the use of a private vehicle. Only a minority of travelers increases public transportation use, e.g., through using ridehailing for first-/last-mile access to public transportation terminals. Based on the results from this research, we urge planners and policy makers to regulate these services to maximize societal benefits through a combination of pricing and other policies that lead to the integration of ridehailing with other transportation options, expand travel options for those that do not own a car, increase the shared used of vehicles, and support the use of public transportation and active ...
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