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Can Ridehailing Deliver Equity? Lessons for New Mobility Planning

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Anne Brown, University of Oregon

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Can Ridehailing Deliver Equity? Lessons for New Mobility Planning

  1. 1. Can Ride-hailing Deliver Equity? Lessons for New Mobility Planning May 31, 2019 – Portland State University Friday Transportation Seminar Anne Brown Assistant Professor University of Oregon abrown33@uoregon.edu
  2. 2. OVERVIEW • Taxis and ridehail access
  3. 3. OVERVIEW • Taxis and ridehail access • In Los Angeles
  4. 4. OVERVIEW • Taxis and ridehail access • In Los Angeles • In a nutshell • Extends car access to nearly every neighborhood in LA
  5. 5. OVERVIEW • Taxis and ridehail access • In Los Angeles • In a nutshell • Extends car access to nearly every neighborhood in LA • Most heavily used in areas with less personal car access
  6. 6. OVERVIEW • Taxis and ridehail access • In Los Angeles • In a nutshell • Extends car access to nearly every neighborhood in LA • Most heavily used in areas with less personal car access • Ridehailing narrows but does not erase differences between riders
  7. 7. The need for occasional car access Sources: Ralph 2015, U.S. Census 2015, NHTS 2009, Garasky Fletcher and Jensen 2006
  8. 8. Taxis
  9. 9. Taxi Discrimination • Poor / no service in low-income neighborhoods and communities of color Taxis
  10. 10. Taxi Discrimination • Poor / no service in low-income neighborhoods and communities of color • Discrimination against individuals Taxis
  11. 11. Ride-hailing Taxis A new chapter in car access?
  12. 12. Ride-hail travel & equity in Los Angeles
  13. 13. Where are Lyft trips?
  14. 14. Where are Lyft trips? What factors are associated with individual Lyft use?
  15. 15. Where are Lyft trips? What factors are associated with individual Lyft use? Is there evidence of discrimination in the ridehail and taxi industries?
  16. 16. Where are Lyft trips? What factors are associated with individual Lyft use? Is there evidence of discrimination in the ridehail and taxi industries?
  17. 17. Where are Lyft trips? What factors are associated with individual Lyft use? Is there evidence of discrimination in the ridehail and taxi industries? 6.3 million Lyft trips taken in Los Angeles County
  18. 18. LOS ANGELES COUNTY
  19. 19. WHERE AREN’T LYFT TRIPS?
  20. 20. WHERE ARE LYFT TRIPS?
  21. 21. WHERE ARE LYFT TRIPS?
  22. 22. WHERE ARE LYFT TRIPS? + Density Young residents (15-34) Majority black Majority white Zero car households
  23. 23. WHERE ARE LYFT TRIPS? + Density Young residents (15-34) Majority black Majority white Zero car households - Majority Asian Majority Hispanic
  24. 24. 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% <1 trip/month About 1 trip/month 2-3 trips/month 1-2 trips/week 3+ trips/week ShareofUsers Lyft Use Frequency
  25. 25. WHERE DO LYFT USERS LIVE?
  26. 26. WHERE DO LYFT USERS LIVE?
  27. 27. WHAT FACTORS ARE ASSOCIATED WITH INDIVIDUAL LYFT USE?
  28. 28. + Density Low-income Majority black Majority white Young residents (15-34) Zero car households WHAT FACTORS ARE ASSOCIATED WITH INDIVIDUAL LYFT USE?
  29. 29. + Density Low-income Majority black Majority white Young residents (15-34) Zero car households - High-income Majority Asian Majority Hispanic WHAT FACTORS ARE ASSOCIATED WITH INDIVIDUAL LYFT USE?
  30. 30. Where are Lyft trips? What factors are associated with individual Lyft use? Is there evidence of discrimination in the ridehail and taxi industries?
  31. 31. Where are Lyft trips? What factors are associated with individual Lyft use? Is there evidence of discrimination in the ridehail and taxi industries?
  32. 32. Where are Lyft trips? What factors are associated with individual Lyft use? Is there evidence of discrimination in the ridehail and taxi industries? Audit study: 1,704 Lyft, Uber, and taxi trips
  33. 33. • Wait times • Cancellation rates • Driver characteristics Site 1 Site 2
  34. 34. FINDINGS 1. General patterns of service 2. Differences across rider characteristics
  35. 35. CANCELLATIONS 4.3% 3.5% 19.5% Lyft Uber Taxis Share of rides with request cancellations
  36. 36. 4.3% 3.5% 19.5% Lyft Uber Taxis Share of rides with request cancellations 99.4% 100% 81.5% Lyft Uber Taxis Share of riders who got picked up CANCELLATIONS
  37. 37. 0% 10% 20% 30% 40% 50% 60% <5 5 - 9 10 - 14 15 - 19 20 - 24 25 - 29 30 - 34 35 - 39 40 - 44 45 - 49 50 - 54 55 - 60 ShareofTrips Arrival Wait Time (minutes) Lyft Uber Taxi ARRIVALTIMES
  38. 38. -0.40 0.00 0.40 0.80 Difference in wait times (minutes) Taxis Uber Lyft -10% -5% 0% 5% 10% 15% 20% 25% Men riders relative to women riders Black riders relative to white riders Asian/Hispanic riders relative to white riders Percentage Point Change in Probability of Cancellation Cancellation Rates • No differences between white, Asian, and Hispanic riders CANCELLATIONS
  39. 39. -0.40 0.00 0.40 0.80 Difference in wait times (minutes) Taxis Uber Lyft -10% -5% 0% 5% 10% 15% 20% 25% Men riders relative to women riders Black riders relative to white riders Asian/Hispanic riders relative to white riders Percentage Point Change in Probability of Cancellation Cancellation Rates • No differences between men and women CANCELLATIONS
  40. 40. -0.40 0.00 0.40 0.80 Difference in wait times (minutes) Taxis Uber Lyft -10% -5% 0% 5% 10% 15% 20% 25% Men riders relative to women riders Black riders relative to white riders Asian/Hispanic riders relative to white riders Percentage Point Change in Probability of Cancellation Cancellation Rates • 26% of taxi trips hailed by black riders were cancelled CANCELLATIONS
  41. 41. -0.40 0.00 0.40 0.80 Difference in wait times (minutes) Taxis Uber Lyft -10% -5% 0% 5% 10% 15% 20% 25% Men riders relative to women riders Black riders relative to white riders Asian/Hispanic riders relative to white riders Percentage Point Change in Probability of Cancellation Cancellation Rates • 26% of taxi trips hailed by black riders were cancelled • vs. 15% of taxi trips by white riders • vs. 20% of taxi trips by Asian/Hispanic riders CANCELLATIONS
  42. 42. -0.40 0.00 0.40 0.80 Difference in wait times (minutes) Taxis Uber Lyft -10% -5% 0% 5% 10% 15% 20% 25% Men riders relative to women riders Black riders relative to white riders Asian/Hispanic riders relative to white riders Percentage Point Change in Probability of Cancellation Cancellation Rates • 26% of taxi trips hailed by black riders were cancelled • vs. 15% of taxi trips by white riders • vs. 20% of taxi trips by Asian/Hispanic riders • Black riders were 73% more likely to have a taxi cancel on them vs. white riders CANCELLATIONS
  43. 43. -0.40 0.00 0.40 0.80 Difference in wait times (minutes) Taxis Uber Lyft -10% -5% 0% 5% 10% 15% 20% 25% Men riders relative to women riders Black riders relative to white riders Asian/Hispanic riders relative to white riders Percentage Point Change in Probability of Cancellation Cancellation Rates • 26% of taxi trips hailed by black riders were cancelled • vs. 15% of taxi trips by white riders • vs. 20% of taxi trips by Asian/Hispanic riders • Black riders were 73% more likely to have a taxi cancel on them vs. white riders • On Uber and Lyft, was about a 4 percentage point difference CANCELLATIONS
  44. 44. 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  45. 45. • No differences between white, Asian, and Hispanic riders 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  46. 46. • No differences between white, Asian, and Hispanic riders • No differences between men and women 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  47. 47. • Black vs. white riders à black riders wait, on average: 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  48. 48. • Black vs. white riders à black riders wait, on average: • Taxi: 6 min 47 sec to 14 min 47 sec longer 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  49. 49. • Black vs. white riders à black riders wait, on average: • Taxi: 6 min 47 sec to 14 min 47 sec longer • Lyft: 32 sec – 1 min 43 sec longer 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  50. 50. • Black vs. white riders à black riders wait, on average: • Taxi: 6 min 47 sec to 14 min 47 sec longer • Lyft: 32 sec – 1 min 43 sec longer • Uber 11 sec to 1 min 30 sec longer 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Lyft 0 5 10 15 20 25 30 35 Black Asian/ Hispanic White Uber 0 5 10 15 20 25 30 35 Black Asian/… White Total Wait Time, minutes Taxi TOTAL WAIT TIMES
  51. 51. Technology isn’t a clean slate.
  52. 52. What should policymakers do? • Policies to ensure access
  53. 53. What should policymakers do? • Policies to ensure access • Policies to reduce discrimination
  54. 54. Ensuring access for all • Banking and smartphone access remain critical barriers to shared mobility access • Lessons from ride-hail pilots & bike share
  55. 55. Ensuring access for all • Banking and smartphone access remain critical barriers to shared mobility access • Lessons from ride-hail pilots & bike share • Even for those with technology; barriers remain
  56. 56. Ensuring access for all • Banking and smartphone access remain critical barriers to shared mobility access • Lessons from ride-hail pilots & bike share • Even for those with technology; barriers remain • Language
  57. 57. Ensuring access for all • Banking and smartphone access remain critical barriers to shared mobility access • Lessons from ride-hail pilots & bike share • Even for those with technology; barriers remain • Language • Accessible vehicles
  58. 58. Tackling discrimination • Platform-level
  59. 59. Tackling discrimination • Platform-level • Policymakers: audits and enforcement
  60. 60. A need for metrics and data • Equity-first goals needed to deliver equitable access to new mobility
  61. 61. A need for metrics and data • Equity-first goals needed to deliver equitable access to new mobility. • Clear metrics & data linked to these goals
  62. 62. A need for metrics and data • Equity-first goals needed to deliver equitable access to new mobility. • Clear metrics & data linked to these goals • Equity at the neighborhood and individual level
  63. 63. A need for metrics and data • Equity-first goals needed to deliver equitable access to new mobility. • Clear metrics & data linked to these goals • Equity at the neighborhood and individual level • Data of users and non-users
  64. 64. Can Ride-hailing Deliver Equity? Lessons for New Mobility Planning May 31, 2019 – Portland State University Friday Transportation Seminar Anne Brown Assistant Professor University of Oregon abrown33@uoregon.edu

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