Do transportation network companies increase or decrease transit ridership? Empirical evidence from San Francisco

Author:

Erhardt Gregory D.ORCID,Mucci Richard AlexanderORCID,Cooper DrewORCID,Sana BhargavaORCID,Chen MeiORCID,Castiglione JoeORCID

Abstract

AbstractTransportation 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.

Funder

San Francisco County Transportation Authority

Publisher

Springer Science and Business Media LLC

Subject

Transportation,Development,Civil and Structural Engineering

Reference68 articles.

1. Alemi, F., Rodier, C.: Simulation of Ridesourcing Using Agent-Based Demand and Supply Regional Models: Potential Market Demand for First-Mile Transit Travel and Reduction in Vehicle Miles Traveled in the San Francisco Bay Area. UC Davis Research Report. National Center for Sustainable Transportation: UC Davis Research Report (2017). https://escholarship.org/uc/item/3h1550wm

2. Babar, Y., Burtch, G.: Examining the heterogeneous impact of ride-hailing services on public transit use. Inf. Syst. Res. (2020). https://doi.org/10.1287/isre.2019.0917

3. BABS. n.d.: Bay Area Bike Share Open Trip Data. Accessed 13 June 2017. http://www.bayareabikeshare.com/open-data

4. BART. n.d.: BART Monthly Ridership Reports. Accessed 16 Oct 2020. https://www.bart.gov/about/reports/ridership

5. Berrebi, S.J., Watkins, K.E.: Who’s ditching the bus? Transp. Res. Part A Policy Pract. 136(June), 21–34 (2020). https://doi.org/10.1016/j.tra.2020.02.016

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3