ABSTRACT
Ridesharing services such as Uber and Lyft have become an important part of the Vehicle For Hire (VFH) market, which used to be dominated by taxis. Unfortunately, ridesharing services are not required to share data like taxi services, which has made it challenging to compare the competitive dynamics of these services, or assess their impact on cities. In this paper, we comprehensively compare Uber, Lyft, and taxis with respect to key market features (supply, demand, price, and wait time) in San Francisco and New York City. Based on point pattern statistics, we develop novel statistical techniques to validate our measurement methods. Using spatial lag models, we investigate the accessibility of VFH services, and find that transportation infrastructure and socio-economic features have substantial effects on VFH market features.
- ACS. 2015. American Community Survey. (2015). http://www.census.gov/programs-surveys/acs.Google Scholar
- San Francisco Municipal Transportation Agency. 2016. Taxi Medallion by Company Statistics. (6 2016). http://www.sfmta.com/services/taxi-industry/medallions/medallion-holders.Google Scholar
- Luc Anselin. 2001. Spatial econometrics. A companion to theoretical econometrics 310330 (2001).Google Scholar
- David A Belsley. 1991. Conditioning diagnostics: Collinearity and weak data in regression. Number 519.536 B452. Wiley.Google Scholar
- California, Metropolitan Transportation Commission 2012. Communities of Concern, San Francisco Bay Area, California 2005--2009. (2012). http://purl.stanford.edu/dp294hh9321.Google Scholar
- Ryan Calo and Alex Rosenblat. 2017. The Taking Economy: Uber, Information, and Power. Columbia Law Review 117 (March 2017).Google Scholar
- Joe Castiglione, Tilly Chang, Drew Cooper, Jeff Hobson, Warren Logan, Eric Young, Billy Charlton, Christo Wilson, Alan Mislove, Le Chen, and Shan Jiang. 2016. TNCs Today: A Profile of San Francisco Transportation Network Company Activity. San Francisco County Transportation Authority (June 2016).Google Scholar
- Juan Camilo Castillo, Daniel T. Knoepfle, and E. Glen Weyl. 2017. Surge Pricing Solves the Wild Goose Chase. SSRN. (July 2017).Google Scholar
- Census. 2010. Census Block Groups. (2010). https://www.census.gov/geo/reference/gtc/gtc_bg.html.Google Scholar
- Le Chen, Alan Mislove, and Christo Wilson. 2015. Peeking Beneath the Hood of Uber. In Proc. of IMC. Google ScholarDigital Library
- M Keith Chen and Michael Sheldon. 2015. Dynamic pricing in a labor market: Surge pricing and flexible work on the Uber platform. Technical Report. UCLA.Google Scholar
- Regina R. Clewlow and Gouri Shankar Mishra. 2017. Disruptive Transportation: The Adoption, Utilization, and Impacts of Ride-Hailing in the United States. Technical Report. UC Davis, Report UCD-ITS-RR-17-07.Google Scholar
- Peter Cohen, Robert Hahn, Jonathan Hall, Steven Levitt, and Robert Metcalfe. 2016. Using big data to estimate consumer surplus: The case of uber. Technical Report. NBER.Google Scholar
- NYC Taxi & Limousine Commission. 2017. TLD Trip Record Data. (2017). http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml.Google Scholar
- Judd Cramer and Alan B. Krueger. 2016. Disruptive Change in the Taxi Business: The Case of Uber. American Economic Review 106, 5 (2016), 177--182.Google ScholarCross Ref
- San Francisco Open Data. 2012. SF Public Transportation Data. (3 2012). http://data.sfgov.org/Transportation/SFMTA-routes-and-stops-for-March-2012/f5c3--8kkj.Google Scholar
- Philip M Dixon. 2002. Ripley's K function. Encyclopedia of environmetrics (2002).Google Scholar
- Benjamin G Edelman and Damien Geradin. 2015. Efficiencies and regulatory shortcuts: How should we regulate companies like Airbnb and Uber. Stan. Tech. L. Rev. 19 (2015), 293.Google Scholar
- Benjamin G Edelman and Michael Luca. 2014. Digital discrimination: The case of Airbnb.com. (2014).Google Scholar
- Lisette Espin Noboa, Florian Lemmerich, Philipp Singer, and Markus Strohmaier. 2016. Discovering and Characterizing Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data. In Proceedings of the 25th International Conference Companion on World Wide Web (WWW '16 Companion). 537--542. Google ScholarDigital Library
- Erica Fink. 2014. Uber threatens drivers: Do not work for Lyft. CNN. (8 2014). http://money.cnn.com/2014/08/04/technology/uber-lyft/index.html.Google Scholar
- FiveThirtyEight. 2015. Uber Pickups in New York City. Kaggle. (9 2015). https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city.Google Scholar
- Yanbo Ge, Christopher R Knittel, Don MacKenzie, and Stephen Zoepf. 2016. Racial and gender discrimination in transportation network companies. Technical Report. NBER.Google Scholar
- Mareike Glöss, Moira McGregor, and Barry Brown. 2016. Designing for labour: uber and the on-demand mobile workforce. In Proc. of CHI. Google ScholarDigital Library
- André Braz Golgher and Paul R Voss. 2016. How to interpret the coefficients of spatial models: Spillovers, direct and indirect effects. Spatial Demography 4, 3 (2016), 175--205.Google ScholarCross Ref
- Suiming Guo, Yaxiao Liu, Ke Xu, and Dah Ming Chiu. 2017. Understanding passenger reaction to dynamic prices in ride-on-demand service. In Proc. of PerCom Workshops.Google Scholar
- Suiming Guo, Yaxiao Liu, Ke Xu, and Dah Ming Chiu. 2017. Understanding ride-on-demand service: Demand and dynamic pricing. In Proc. of PerCom Workshops.Google Scholar
- Jonathan V Hall and Alan B Krueger. 2016. An analysis of the labor market for Uber's driver-partners in the United States. Technical Report. NBER.Google Scholar
- Robert Cornelius Hampshire, Chris Simek, Tayo Fabusuyi, Xuan Di, and Xi Chen. 2017. Measuring the Impact of an Unanticipated Suspension of Ride-Sourcing in Austin, Texas. SSRN. (May 2017).Google ScholarCross Ref
- Aniko Hannak, Claudia Wagner, David Garcia, Alan Mislove, Markus Strohmaier, and Christo Wilson. 2017. Bias in Online Freelance Marketplaces: Evidence from TaskRabbit and Fiverr. In Proc. of CSCW. Google ScholarDigital Library
- Mike Issac. 2017. How Uber Deceives the Authorities Worldwide. New York Times. (3 2017). http://nyti.ms/2mBwTH0.Google Scholar
- Farshad Kooti, Mihajlo Grbovic, Luca Maria Aiello, Nemanja Djuric, Vladan Radosavljevic, and Kristina Lerman. 2017. Analyzing Uber's Ride-sharing Economy. In Proc. of WWW Companion. Google ScholarDigital Library
- Min Kyung Lee, Daniel Kusbit, Evan Metsky, and Laura Dabbish. 2015. Working with machines: The impact of algorithmic and data-driven management on human workers. In Proc. of CHI. Google ScholarDigital Library
- Michal Lev-Ram. 2017. How Lyft Could Defeat Uber. Fortune. (7 2017). http://fortune.com/2017/07/19/uber-vs-lyft-race/.Google Scholar
- Xi Liu, Li Gong, Yongxi Gong, and Yu Liu. 2015. Revealing travel patterns and city structure with taxi trip data. Journal of Transport Geography 43 (2015), 78 -- 90.Google ScholarCross Ref
- Moira McGregor, Barry Brown, and Mareike Glöss. 2015. Disrupting the cab: Uber, ridesharing and the taxi industry. Journal of Peer Production 6 (2015).Google Scholar
- Jared Meyer. 2016. Uber Is Not (And Will Never Be) A Monopoly. Forbes. (2 2016). https://www.forbes.com/sites/jaredmeyer/2016/02/15/uber-guardian-not-monopoly-ridesharing.Google Scholar
- Mariella Moon. 2017. Uber's 'Hell' program tracked and targeted Lyft drivers. Engadget. (4 2017). http://engt.co/2oBME0K.Google Scholar
- Benjamin Mueller. 2016. $25,000 Fine Proposed in Taxi Driver's Snub of Black Family. New York Times. (8 2016). http://nyti.ms/2yy4WVm.Google Scholar
- Anastasios Noulas, Vsevolod Salnikov, Desislava Hristova, Cecilia Mascolo, and Renaud Lambiotte. 2017. Developing and Deploying a Taxi Price Comparison Mobile App in the Wild: Insights and Challenges. arXiv preprint arXiv:1701.04208 (2017).Google Scholar
- New York City Department of Transportation. 2014. NYC Public Transportation Data. (9 2014). http://www.nyc.gov/html/dot/html/home/home.shtml.Google Scholar
- Hannah A Posen. 2015. Ridesharing in the Sharing Economy: Should Regulators Impose Uber Regulations on Uber. Iowa L. Rev. 101 (2015), 405.Google Scholar
- Associated Press. 2016. Boston wants better data from Uber, and is taking a roundabout route to try and get it. Boston Globe. (6 2016). https://www.boston.com/news/business/2016/06/28/uber-data-boston-wants.Google Scholar
- Joe Fitzgerald Rodriguez. 2016. 45,000 Uber and Lyft drivers may now operate in SF. SF Examiner. (11 2016). http://bit.ly/2gtgRsj.Google Scholar
- Brishen Rogers. 2015. The social costs of Uber. U. Chi. L. Rev. Dialogue 82 (2015), 85.Google Scholar
- Carolyn Said. 2017. SF demands data from Uber, Lyft on city trips, driver bonuses. San Francisco Chronicle. (6 2017). http://www.sfchronicle.com/business/article/SF-goes-after-Uber-Lyft-for-data-on-city-trips-11196961.php.Google Scholar
- Vsevolod Salnikov, Renaud Lambiotte, Anastasios Noulas, and Cecilia Mascolo. 2015. OpenStreetCab: exploiting taxi mobility patterns in New York City to reduce commuter costs. arXiv preprint arXiv:1503.03021 (2015).Google Scholar
- Rachel Sugar. 2017. Uber and Lyft Cars Now Outnumber Yellow Cabs in NYC 4 to 1. Curbed. (1 2017). http://ny.curbed.com/2017/1/17/14296892/yellow-taxi-nyc-uber-lyft-vianumbers.Google Scholar
- Jacob Thebault-Spieker, Loren Terveen, and Brent Hecht. 2017. Toward a Geo- graphic Understanding of the Sharing Economy: Systemic Biases in UberX and TaskRabbit. ACM Trans. Comput.-Hum. Interact. 24, 3 (April 2017), 21:1--21:40. Google ScholarDigital Library
- Uber. 2017. Uber Movement. (2017). https://movement.uber.com.Google Scholar
- Adam Vaccaro. 2015. Uber to Hand Over Trip Data to Boston. Boston. (1 2015). https://www.boston.com/news/technology/2015/01/13/uber-to-hand-over-trip-data-to-boston.Google Scholar
- Adam Vaccaro. 2016. Highly Touted Boston-Uber Partnership Has Not Lived Up to Hype So Far. Boston. (6 2016). https://www.boston.com/news/business/2016/06/16/bostons-uber-partnership-has-not-lived-up-to-promise.Google Scholar
Index Terms
- On Ridesharing Competition and Accessibility: Evidence from Uber, Lyft, and Taxi
Recommendations
Designing for Labour: Uber and the On-Demand Mobile Workforce
CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing SystemsApps allowing passengers to hail and pay for taxi service on their phone? such as Uber and Lyft-have affected the livelihood of thousands of workers worldwide. In this paper we draw on interviews with traditional taxi drivers, rideshare drivers and ...
Analyzing Uber's Ride-sharing Economy
WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web CompanionUber is a popular ride-sharing application that matches people who need a ride (or riders) with drivers who are willing to provide it using their personal vehicles. Despite its growing popularity, there exist few studies that examine large-scale Uber ...
Real-Time City-Scale Taxi Ridesharing
We proposed and developed a taxi-sharing system that accepts taxi passengers' real-time ride requests sent from smart phones and schedules proper taxis to pick up them via ride sharing, subject to time, capacity, and monetary constraints. The monetary ...
Comments