Do transportation network companies increase or decrease transit ridership? Empirical evidence from San Francisco
Transportation network companies (TNCs), such as Uber and Lyft, have been hypothesized to both complement and compete with public transit. Existing research on the topic is limited by a lack of detailed data on the timing and location of TNC trips. This study overcomes that limitation by using data scraped from the Application Programming Interfaces of two TNCs, combined with Automated Passenger Count data on transit use and other supporting data. Using a panel data model of the change in bus ridership in San Francisco between 2010 and 2015, and confirming the result with a separate time-series model, we find that TNCs are responsible for a net ridership decline of about 10%, offsetting net gains from other factors such as service increases and population growth. We do not find a statistically significant effect on light rail ridership. Cities and transit agencies should recognize the transit-competitive nature of TNCs as they plan, regulate and operate their transportation systems.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00494488
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Supplemental Notes:
- Copyright © 2022, Springer Nature. The contents of this paper reflect the views of the author[s] and do not necessarily reflect the official views or policies of the Transportation Research Board or the National Academy of Sciences.
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Authors:
- Erhardt, Gregory D
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0000-0001-8133-3381
- Mucci, Richard Alexander
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0000-0002-7217-6836
- Cooper, Drew
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0000-0002-7240-1845
- Sana, Bhargava
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0000-0003-1502-5991
- Chen, Mei
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0000-0002-7737-2895
- Castiglione, Joe
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0000-0002-3931-6286
- Publication Date: 2021-3
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: 313–342
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Serial:
- Transportation
- Volume: 49
- Issue Number: 2
- Publisher: Springer
- ISSN: 0049-4488
- EISSN: 1572-9435
- Serial URL: http://link.springer.com/journal/11116
Subject/Index Terms
- TRT Terms: Mobility; Public transit; Ridership; Ridesharing; Ridesourcing
- Identifier Terms: Lyft; Uber
- Subject Areas: Highways; Public Transportation; Safety and Human Factors;
Filing Info
- Accession Number: 01847265
- Record Type: Publication
- Files: TRIS
- Created Date: May 25 2022 9:40AM