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Perspectives on the Ridesourcing Revolution: Surveying Individual Attitudes Toward Uber and Lyft to Inform Urban Transportation Policymaking

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Perspectives on the Ridesourcing Revolution: Surveying Individual Attitudes Toward Uber and Lyft to Inform Urban Transportation Policymaking Perspectives on the Ridesourcing Revolution: Surveying individual attitudes toward Uber and Lyft to inform urban transportation policymaking By Margo Dawes Bachelor of Science in Civil Engineering and Planning Massachusetts Institute of Technology Cambridge, MA (2015) Submitted to the Department of Urban Studies and Planning in partial fulfillment of the requirements for the degree of Master in City Planning at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2016 © 2016 Margo Dawes. All Rights Reserved The author hereby grants to MIT the permission to reproduce and to distribute publicly paper and electronic copies of the thesis document in whole or in part in any medium now known or hereafter created. Author________________________________________________________________________ Department of Urban Studies and Planning Certified by____________________________________________________________________ Assistant Professor Jinhua Zhao, Ph.D. Department of Urban Studies and Planning Thesis Supervisor Accepted by___________________________________________________________________ Associate Professor P. Christopher Zegras Chair, MCP Committee Department of Urban Studies and Planning 2 Perspectives on the Ridesourcing Revolution: Surveying individual attitudes toward Uber and Lyft to inform urban transportation policymaking By Margo Dawes Submitted to the Department of Urban Studies and Planning on May 19, 2016, in partial fulfillment of the requirements for the degree of Master in City Planning Abstract Media coverage of ridesourcing services such as Uber and Lyft has described a rivalry between new technology and the established taxi industry. Individual users and non-users of ridesourcing, however, may have more nuanced perspectives, but policymakers have little guidance on how to best represent these interests. This thesis uses a standardized questionnaire distributed across the United States by an online survey company to understand individual attitudes toward Uber, Lyft, and ridesourcing technology as a whole. It asks respondents if they identify as users or non-users of ridesourcing, why or why not, how they rank Uber and Lyft among their other travel modes, their attitudes toward the companies and toward the technology in general (on a Likert scale of 1, very negative, to 5, very positive), and their opinions on how their cities should respond, among other questions. 394 completed questionnaires from the most populous 15 metropolitan statistical areas in the U.S. reveal individuals’ use of and attitude toward ridesourcing technology along with variations across demographic groups, cities and regions, and primary travel mode. The survey returned a response rate of 27% and the spatial distribution of responses was roughly proportional to the population of each metropolitan area. The findings indicate that about 70% of respondents use some form of ridesourcing, mostly for special-purpose trips such as avoiding driving while intoxicated and getting to and from the airport. The vocal minority who don’t use Uber or Lyft for ethical reasons represent only a small subset of the sample (about 6%), but 1 in 5 respondents said the companies’ decision to treat drivers as independent contractors rather than employees made them want to use the services less. There are relationships between transportation characteristics (e.g. usage of Uber and Lyft, needing to travel for work, and having access to a car) and user identification and attitude, but demographics are the best predictor of user identification, which in turn predicts attitude, which predicts policy implications. The study suggests potential for policymakers to leverage constituent perspectives to change aspects of ridesourcing that have low public approval. Thesis supervisor: Jinhua Zhao Title: Edward H. and Joyce Linde Assistant Professor of Urban Planning 3 4 Acknowledgments My first and biggest thanks must go to my advisor, Jinhua Zhao, whose enduring enthusiasm and expert guidance helped bring this thesis to life. Jinhua’s rigorous standards and constant encouragement made this truly a learning experience, and for that I am deeply grateful. Thank you also to my readers, Onesimo Flores and Craig Kelley, who provided the invaluable, if distinct, feedback that I used to round out the beginning and end of my thesis. Thank you to everyone at JTL who had a hand in the idea formation and evaluation along the way. Hongmou, Adam, Corinna, and Jeff all provided meaningful contributions, and Nick Allen’s outsize interest and availability never went unappreciated. A big thank you also to Mira Vale and Cali Warner, who provided the technical assistance I could not ask of anyone else. I would also like to acknowledge the project managers at Qualtrics, Nate Richard and Emily Davis, who helped me prepare my survey for distribution. To my dad, Roy Dawes, who shared his expertise and aided in the transformation of my statistical analysis. And to my mom, Diane Iñiguez, for the reminder that the world still exists outside of thesis. To Carmen Castaños and Eric Benzschawel for the solidarity, and to Lindiwe Rennert for the same and for being my personal cheerleader. To Marisa Fryer for the incredulity. A heartfelt thank you to Anna Doty, for all of the love and support this year. Finally, a shout out to all of my MCP colleagues who brightened the thesis room and made my experience at DUSP what it was. 5 Contents List of Figures ................................................................................................................................ 7 List of Tables ................................................................................................................................. 8 Terms and Definitions .................................................................................................................. 9 1. Background .......................................................................................................................... 10 1.1 The Ridesourcing Phenomenon and its Roots in the So-Called Sharing Economy ....... 10 1.2 Ridesourcing Services and Regulatory Response .......................................................... 13 1.3 Study Motivation and Research Questions .................................................................... 16 2. Literature Review ................................................................................................................ 18 2.1 Regulatory History of Taxi Industry .............................................................................. 18 2.2 The Ridesourcing Debate ............................................................................................... 19 3. Data and Methodology ........................................................................................................ 21 3.1 Research Methodology and Data Acquisition ................................................................ 21 3.2 Analysis Methodology ................................................................................................... 34 4. Findings and Analysis ......................................................................................................... 35 4.1 Survey Responses and Univariate Analysis ................................................................... 35 4.2 Bivariate and Multivariate Analysis ............................................................................... 48 5. Discussion ............................................................................................................................. 58 5.1 Key Findings .................................................................................................................. 58 5.2 Discussion of Research Questions ................................................................................. 59 5.3 Policymaker Impressions ............................................................................................... 60 5.4 Limitations and Areas for Further Research .................................................................. 62 References .................................................................................................................................... 64 Appendices ................................................................................................................................... 70 Appendix 1: Survey questionnaire and recode values .............................................................. 70 Appendix 2: Correlations and regression model outputs .......................................................... 77 Appendix 3: COUHES approval ............................................................................................... 84 6 List of Figures Figure 1. Question structure shown to survey respondents for the question “Between Uber and Lyft, if you prefer one over the other, how do the following factors influence your preference?” ....................................................................................................................................................... 31 Figure 2. Question structure shown to survey respondents for the question “The following aspects of ride-hailing technology make me want to use Uber or Lyft [More, Less, or Neutral].” ....................................................................................................................................................... 33 Figure 3. Comparison of preferences between Uber and Lyft based on seven criteria. ............... 42 Figure 4: Mode choice heat map showing
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