Rider Multihoming in the United States Rideshare Market by Daniel X. Valderrama Bachelor of Science in Systems Engineering United States Military Academy, 2013 SUBMITTED TO THE SYSTEM DESIGN AND MANAGEMENT PROGRAM IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN ENGINEERING AND MANAGEMENT AT THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY MAY 2020 © 2020 Daniel X. Valderrama. All Rights Reserved. The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created. Signature of Author: ____________________________________________________________ Daniel X. Valderrama Fellow, System Design and Management Program May 15th, 2020 Certified by: __________________________________________________________________ Bruce Cameron Director, System Architecture Group Thesis Supervisor Accepted by: __________________________________________________________________ Joan S. Rubin Executive Director System Design and Management [This Page Intentionally Left Blank] 2 Rider Multihoming in the United States Rideshare Market By Daniel X. Valderrama Submitted in the System Design and Management Program on May 15th 2020 in partial fulfillment of the requirements for the degree of Master of Science in Engineering and Management ABSTRACT This thesis examines rider multihoming in the US ridesharing market. Ridesharing services experience substantial multihoming on both sides of the platform, and appear to suffer from a combination of a lack of differentiation as well as low multihoming costs. Through an informational interview, a qualitative survey, and a conjoint survey and analysis, rider preferences were able to be categorized and quantified. An adapted conjoint survey and analysis allowed for a simulation of rider decisions to accept a ride or multihome along price, time, and company attributes. With baseline thresholds, examining the prevalence of multihoming with use of several multihoming reduction strategies, have shown that network bridging strategies may have an impact in reducing the prevalence of multihoming among riders. In-App Promotions and Incentive-based strategies, meanwhile, have shown to have the opposite results, showing an increased tendency to multihome in riders that utilize them. Thesis Supervisor: Bruce Cameron Title: Director, Systems Architecture Group, MIT 3 ACKNOWLEDGEMENTS The writing of this thesis was a substantial undertaking and many people deserve credit and thanks for supporting me in my endeavor to create this work. First and foremost, I want to thank Anne Catherine Preston, for being there for me through thick and thin, keeping me motivated, and lighting a fire under me throughout this process. I also wish to thank Dr. Bruce Cameron, my advisor, who treated me like a partner, and joined in on brainstorming, shaping the problem, helping me uncover meaningful insights, and for truly guiding me through this journey. Finally, I’d like to thank the System Design and Management cohort at the Massachusetts Institute of Technology, for their continued friendship, and for allowing me to grow professionally and personally alongside them these past two years. My time at MIT has been too short, but I am grateful for the knowledge, experience, and lasting friendships that I have gained here. 4 Table of Contents ABSTRACT ................................................................................................................................... 3 ACKNOWLEDGEMENTS ......................................................................................................... 4 1.0 INTRODUCTION................................................................................................................... 7 2.0 LITERATURE REVIEW ...................................................................................................... 9 2.1 Industry Platforms .............................................................................................................. 9 2.1.1 Network Effects ............................................................................................................ 9 2.1.2 Two-sided markets ..................................................................................................... 10 2.2 Strategies for winning a platform war ............................................................................ 11 2.3 Threats to platform market dominance .......................................................................... 13 2.4 Multihoming ...................................................................................................................... 14 2.4.1 Why multihoming occurs .......................................................................................... 14 2.4.2 Costs of Multihoming ................................................................................................ 16 2.4.3 Methods to reduce Multihoming .............................................................................. 17 2.5 Ridesharing Platforms ...................................................................................................... 21 2.5.1 Platform Competition ................................................................................................ 21 2.5.2 Multihoming Tendencies ........................................................................................... 24 2.5.3 Strategies Employed to Reduce Multihoming ......................................................... 26 3.0 RESEARCH QUESTIONS .................................................................................................. 28 3.1 Factors that determine preference of service ................................................................. 28 3.2 Attributes contributing to multihoming ......................................................................... 29 3.3 Cost of multihoming ......................................................................................................... 29 4.0 RESEARCH METHODS ..................................................................................................... 30 4.1 Qualitative approach ........................................................................................................ 30 4.1.1 Rider interviews ......................................................................................................... 30 4.1.2 Rider surveys .............................................................................................................. 32 4.2 Quantitative approach ...................................................................................................... 35 4.3 Bias and limitations........................................................................................................... 40 5.0 QUALITATIVE ANALYSIS ............................................................................................... 41 5.1 Insights from interviews ................................................................................................... 41 5.2 Insights from survey ......................................................................................................... 42 5.2.1 Singlehoming Sample................................................................................................. 46 5.2.2 Multihoming Samples ................................................................................................ 56 5.2.3 Additional habits between multihoming and singlehoming users ......................... 66 5 5.3 Overview of findings and conclusions ............................................................................. 68 6.0 QUANTITATIVE ANALYSIS ............................................................................................ 71 6.1 Insights from Conjoint survey ......................................................................................... 71 6.2 Overview of findings and conclusions ............................................................................. 99 7.0 CONCLUSION ................................................................................................................... 102 7.1 Conclusions from analysis .............................................................................................. 102 7.2 Next steps ......................................................................................................................... 108 REFERENCES .......................................................................................................................... 110 Appendix A: Interview Topics/Questions ................................................................................. 115 Appendix B: A lesson in differentiation .................................................................................... 116 Appendix C: Graphs and Figures .............................................................................................. 117 6 1.0 INTRODUCTION Over the last few decades, the share of the most successful companies are increasingly platform businesses. Five of the six most valuable companies by market capitalization in the world revolve around their industry platform businesses (Yoffie, Cusumano, and Gawer 2019). Microsoft, Alphabet, Apple, Amazon, Facebook, Alibaba, etc. all are businesses that rely on their business platforms. Between 60 and 70 percent of the current and former ‘unicorns’ (companies valued at $1 billion or more) relied on a platform business model for a large