Report Release: “Fare Choices” on Ride-Hailing in Metro Boston

On February 6, MAPC released “Fare Choices,” a survey of ride-hailing passengers in Metro Boston.

The ride-hailing industry, led by Uber and Lyft, has seen explosive growth in recent years. As more and more travelers choose these on-demand mobility services, they have the potential to transform regional travel patterns. These transformations may become even more profound if widespread adoption of autonomous vehicles makes on-demand mobility even less expensive and more efficient. Either way, it is likely that the use of ride-hailing today is but the tip of the iceberg, with an even greater expansion of these services to come.

This transformation in personal mobility is likely to bring a host of changes: some positive, others less so. For public agencies, planning for that transformation is made difficult by the paucity of information about ride-hailing trips. Conventional transportation surveys have been slow to measure the change in behavior; and transportation network companies see their data as a valuable commodity and are unwilling to provide it to transportation planners.

MEdia Coverage

Feb.5 – Boston Globe: Adam Vaccaro, Uber and Lyft are pulling people off public transit and putting them in traffic, study says

Feb. 6 – CommonWealth Magazine: Uber vs. the T

Feb. 6 – WBUR: Zeninjor Enwemeka, Report: Uber and Lyft are Adding to Boston-Area Traffic

Feb. 6 – WBUR: Benjamin Swasey, In 2017, Greater Boston Drivers Spent An Average of 60 Hours of Traffic During Peak Times

Feb. 6 – WCVB: Lyft, Uber rides adding to Boston-area traffic congestion, report finds

Feb. 6 – WHDH: Study: Uber, Lyft rides contributing to heavy traffic in Boston area

Feb. 7 – The Drive: Uber and Lyft are Making Boston Traffic Worse

Feb. 8 – The Daily Free Press: Editorial: Improving Public Transit Efficiency is Necessary to Alleviate Traffic on Boston’s Roads

Feb. 8 – Streetsblog USA: Evidence from Boston that Uber is Making Traffic Worse

Feb. 9 – Boston Globe: You’re not paying enough for Uber

Feb. 15 – Daily Hampshire Gazette: Autonomous vehicles may be on Mass. roads soon

Feb. 22 – eCommerce Times: Uber’s New Express Pool: Walk and Wait

Feb. 22 – The Radical Urbanist: The ride-hailing war isn’t stabilizing – it’s just getting started

Feb. 22 – The Ringer: Taking the High Road

Feb. 25 – AP (republished by ABC News, Fox 25, Washington Post): Studies are increasingly clear: Uber, Lyft congest cities

Feb. 26 – Futurism (also published in NewsCaf): Ride-Hailing Services Aimed at Cutting Traffic are Having the Opposite Effect

Feb. 27 – Boston Magazine: Massachusetts Drives Don’t Want to Pay Higher Tolls, Admit Infrastructure is Failing

Read the Full Report Here!

Main Takeaways

Public sector access to these data is essential. Only with a better understanding of this new mode of transportation can analysts develop better forecasts of travel behavior and infrastructure needs, measure the region’s progress toward a more sustainable future, and establish more efficient operations and management practices for existing roadways.

In an effort to begin filling those gaps in our understanding of the ride-hailing industry and its users, MAPC surveyed nearly 1,000 ride-hailing passengers in late 2017 and asked about their demographics, the nature of their trip, and why they chose ride-hailing over other modes of transportation.

A man is lit by the light of his phone screen as he stands on a busy city street.
Photo via Lyft

The results confirmed many common assumptions about ride-hailing users; they also provided striking new insight into the ways that the services are changing travel behavior and affecting our existing transportation system. Not surprisingly, the survey found that most ride-hailing users are under the age of 35, that most of them use the service on a weekly basis, and that most don’t own a car. Less predictably, we found that reported rider incomes are similar to the region overall, and a substantial number of trips are made by people from households earning less than $38,000 per year. (And no, they’re not all students; most of those lower-income riders are in the workforce.)

The survey results also provide some hard data about the types of trips made via ride-hailing. Most trips start or end at home, but nearly one-third (31%) are from one non-home location to another. Ride-hailing usage is distributed throughout the day; the evening hours from 7:00 P.M. to midnight see the greatest frequency of trips, but about 40% of weekday trips take place during the morning or afternoon commute periods. People also like to travel by themselves: only one-fifth of customers opt for a truly shared ride (e.g., UberPOOL), and the majority of travel is for a single passenger. Riders are willing to pay a substantial premium for the convenience and predictability of ride-hailing. Nearly two thirds of trips cost more than $10, and one in five costs more than $20.

While the services are justifiably popular, their growing use may result in negative outcomes for traffic congestion, transit use, and active transportation. When asked how they would have made their current trip if ride-hailing hadn’t been an option, 12% said they would have walked or biked, and over two-fifths (42%) of respondents said they would have otherwise taken transit. Some of this “transit substitution” takes place during rush hours. Indeed, we estimate that 12% of all ride-hailing trips are substituting for a transit trip during the morning or afternoon commute periods; an additional 3% of riders during these times would have otherwise walked or biked. Overall, 15% of ride-hailing trips are adding cars to the region’s roadways during the morning or afternoon rush hours.

Notably, we found that this “transit substitution” is more frequent among riders with a weekly or monthly transit pass. Those who ride transit more often are more likely to drop it for ride hailing, even while doing so at a huge cost differential, and even when they have already paid for the transit.

Riders without a transit pass opting for ride-hailing, on the other hand, means less fare revenue for the MBTA. After accounting for transit pass availability and substitution options, we estimate that the average ride-hailing trip represents 35 cents of lost fare revenue for the MBTA. This lost revenue exceeds the amount of the legislatively mandated 20 cent surcharge on each ride. That surcharge itself represents a remarkably small fraction of trip costs. When compared to reported fares, the surcharge amounts to less than 2% of the cost for most rides. Because it is a fixed fee, long and expensive rides that may have the greatest impact on traffic congestion and air quality pay 1% or less.

A car mirror reflects traffic at sunset or sunrise; several cars with their lights on are seen
Photo by Anty Diluvian

These findings begin to provide a better understanding of this evolving mobility option that will undoubtedly continue to change the way people travel around the region. Our results raise concerns about how users are becoming accustomed to on-demand mobility, and what that means for the future of the region’s transportation system. Even if future ride-hailing vehicles were fully electric and autonomous, the region’s roadways could not accommodate unchecked growth in single-occupant vehicle travel. It is essential to ensure that the region has a reliable and effective transit system that—from the rider’s perspective—is competitive with and complementary to on-demand mobility services. For transit to thrive, it must change, perhaps by incorporating the types of on-demand response and real-time information that riders value.

Meanwhile, there is a great need to understand the effects of ride hailing and to ensure a balance of benefits and costs resulting from these commercial services. Ride hailing is already having substantial impacts on congestion and transit revenue, the costs of which are not recouped by the small surcharge. A higher fee would provide more resources to mitigate the negative effects of ride hailing without substantially affecting rider costs. Even more preferable would be a fee structure proportional to the impacts of each ride on the transportation system. To the extent possible, such fees should also be structured to incentivize shared trips, thereby reducing overall impacts on the transportation system while also accommodating ride-hailing preferences. Of course, effective policy requires better data about when, where, and why ride-hailing trips are taking place. Only by understanding the current adoption of ride-hailing and on-demand mobility can we plan for its successful and sustainable future.