Between Public and Private Mobility: Examining the Rise of Technology-Enabled Transportation Services (2016)

8 Equity and Access

Many of the public policy debates over the rise of new technology-enabled mobility services concern matters of fairness and equity. For example, is the taxi industry being treated fairly vis-à-vis the new transportation network companies (TNCs)? Are those without smartphones unfairly excluded from these new services? Are TNC drivers treated fairly as workers?

Transportation access is an issue of particular concern, as it is central to nearly all aspects of economic and social life. Many segments of the population have limited access to jobs, goods, services, health care, recreation, and social interaction because of a lack of transportation options. The reasons behind this limited access are varied, including physical disabilities, low incomes, and discrimination, among others. The innovative mobility options discussed in this report have the potential to increase the accessibility of transportation for many Americans, including these disadvantaged populations. But they may also leave people who are already transportation-disadvantaged further behind, either because they will not be able to take advantage of these new services (making them relatively worse off) or because the rise of these new services could reduce some existing services (making them absolutely worse off).

This chapter examines both the potential challenges and opportunities related to equity and access presented by the burgeoning innovative mobility services in the United States. It begins by proposing a framework for thinking about the dimensions of equity with respect to these new services. The chapter then considers issues of equity and access for various disadvantaged groups, including

racial and ethnic minorities, people with disabilities, low-income households, “unbanked” populations,¹ people without smartphones, and rural residents.

Dimensions of Equity

Because the new technology-enabled services are provided primarily by the private sector and because they are evolving so rapidly, issues of fairness and equity raised by these services and the established modes with which they often compete are complex, multidimensional, and sometimes conflicting. The dimensions of these issues can be characterized in terms of

• Firms, markets, and competition;
• Regulations, subsidies, and social services;
• Geographies and jurisdictions; and
• Stakeholder groups (see Table 8-1).

This section addresses each of these dimensions in turn.

Firms, Markets, and Competition

Most of the new and emerging mobility services discussed in this report are financed privately, with little in the way of direct public subsidy. They typically compete for customers on price and service quality, both of which can depend significantly on the firms’ economies of scope and scale. Large firms are better able to provide service over wide geographic areas and around the clock, which can give them a competitive advantage over smaller rivals, and a substantial market share can give them leverage with drivers and suppliers that enables them to hold costs down. But the emergence of dominant players in private markets also can lead to market-cornering behaviors, efforts to convince public officials to erect barriers to market entry so as to squelch competition, and the “regulatory capture” of public agencies that may succumb to especially dominant firms. Thus the public policy equity challenge with respect to firms and

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¹ The term “unbanked” refers to people who lack credit or bank accounts.

Table 8-1 Four Dimensions of Equity in Public Policy Debates over Technology-Enabled Mobility Services

competition in these private markets is to ensure fair, open, and competitive markets among new and yet-to-emerge private service providers. In addition, because these services do not receive direct public subsidies, and most also do not benefit from public regulations that restrict competition, one of the main tools local governments use to advance equity agendas—conditioning a subsidy to or privilege for a firm on that firm’s performing some redistributive function—may not be available.

Regulations, Subsidies, and Social Services

Nearly all of the new services examined in this report are, or likely will be, regulated in some manner in the interests of safety, public health, worker protections, and other public concerns. And many of these regulations, such as those imposed on TNCs and the taxi industry, entail different sets of rules applied to very different, competing new and long-established industries. Further, some of these new services, such as car- and especially bikeshare services, entail varying degrees of public collaboration with or subsidy of some private firms but not others. Finally, some of these new services compete with existing firms that provide both private, for-profit services and social service transportation—such as mandated wheelchair-equipped door-to-door services provided by taxi operators. Ensuring fair regulatory

treatment across industries, transparent treatment of firms engaged in public–private partnerships, and continuation of current social service transportation thus poses significant challenges for public officials in a rapidly evolving mobility service environment.

Geographies and Jurisdictions

Almost by definition, many of the newly emerging technology-enabled mobility services defy traditional geographies of service provision. Most (though not all) of the new services entail door-to-door or station-to-station travel that adheres to neither fixed routes nor fixed schedules. Further, as private, primarily for-profit enterprises, these new firms tend to arise and propagate where customer demand is greatest: generally in the largest metropolitan areas, in the most densely settled parts of cities, and in more affluent areas with large numbers of potential customers who have the disposable income to pay for the services. If these services are viewed largely as the product of private transactions between willing buyers and sellers, then the boundary crossing and geographic concentration of these services is not necessarily a public concern. But if carshare, bikeshare, microtransit, TNC, and other services rise in scope and scale to become important components of urban transportation systems, cross jurisdictional regulatory regimes, or provide quality service in lucrative (and affluent) areas but not in others, they become important matters for public policy.

Stakeholder Groups

Federal laws prohibit discrimination on the basis of race or ethnicity and require that accommodations be made for those with disabilities. Such rules, for example, significantly affect the provision of public transit services in ways that both ensure justice and often raise the costs of service provision. Other classes of travelers may not enjoy such explicit federal protections, but nonetheless warrant consideration of treatment on fairness grounds. They include, among others, (1) people who, because of income limitations or disability, are unable to have or fully use smartphones; (2) workers in

existing industries (such as the taxi industry) who may be displaced by these new services; and (3) “unbanked” travelers unable to make use of most of these new cashless services.

With the rise of mobility services in general and TNCs in particular, equity dimensions are in play for all of the above groups. The next section examines equity issues related to the subgroups of stakeholders whose interests may be furthered or harmed depending on how the urban mobility services evolve in the coming years.

Intergroup Equity Issues

Racial and Ethnic Minorities

The extent to which different racial and ethnic groups use and have access to technology-enabled mobility services may have implications under Title VI of the Civil Rights Act of 1964. While the use of these services across various racial–ethnic groups has not been well studied, the limited data available suggest that they tend to be used disproportionately by whites. With respect to carsharing, a 2005 study that examined carsharing in 13 U.S. cities found that 87 percent of the carshare users surveyed were white (Millard-Ball et al. 2005). Likewise a study of bikesharing in Washington, D.C., found that about 80 percent of the members were white and less than 4 percent were African American (Buck et al. 2013), as compared with a city population that was 43 percent white and 50 percent African American (U.S. Census Bureau 2014). Surveys of bikeshare members in four North American cities (Washington, Minneapolis, Toronto, and Montreal) found that 79 percent were white (Shaheen et al. 2012b). The reasons for generally low rates of usage of these services among nonwhites are not clear, although they may relate to some combination of the geographic availability of the services, differences in average income levels across racial or ethnic groups, and differences in modal preferences and demands across groups.

There has been much debate in the popular media concerning TNCs and race and ethnicity. Some journalists, based mainly on personal experience, have suggested that TNCs may provide racial or ethnic minorities with more frequent service than taxis with fewer trip rejections (Wortham 2015). Critics have long complained about

(and documented) racial and ethnic discrimination in the taxi industry: in many cities, racial and ethnic minorities have difficulty getting taxi rides, and neighborhoods that are disproportionately minority have traditionally been underserved. A recent poll of Chicago residents, for example, which was funded by Uber, found that 66 percent of African Americans surveyed believe that taxis deliberately avoid serving them; 55 percent have experienced a refusal by a taxi company to serve their community; and 48 percent believe that if they tried to hail a cab, it would pass them by (Brilliant Corners 2015). This same poll showed that a plurality of white citizens of Chicago agree that cabs deliberately avoid serving African American citizens.

The technology used by TNCs could conceivably help counter such abuses (Rogers 2015) because, for example, TNC drivers must accept a ride request without knowing in advance either the destination or the race or ethnicity of the passenger. Officials with Uber have asserted that its drivers serve diverse communities often underserved by taxis (MacDonald 2014). On the other hand, systems that rely on user-generated ratings and shared profiles are susceptible to bias and possible abuse (Harman 2014; Rogers 2015). One study found that African American hosts of Airbnb properties in New York City received lower rental prices, even after controlling for other factors; the authors concluded that discrimination occurred via the online profiles (Edelman and Luca 2014). Many TNCs, however, do not show the driver either the photo or profile of the passenger or the destination when a ride is requested, reducing the possibility of discrimination against riders. Yet anecdotal accounts in the popular press indicate that bias may be exercised through the rating systems that come into play after the ride takes place—both by the driver toward the passenger and by the passenger toward the driver (see, for example, Barrie 2015; Hern 2014; and Weissmann 2014). While few data are currently available from TNCs with which to examine these questions, research in other fields has documented racial bias in hiring processes based on both photographs and names (Bertrand and Mullainathan 2003; Pager and Western 2012). It is possible that a TNC could refuse to accept ride requests from passengers with ethnic-sounding names, although frequent declinations can put TNC drivers at risk of probation for failing to meet the TNC’s take-up

mandate. Because of a lack of data on TNC services, users, and drivers, it is not possible to assess these arguments.

People with Disabilities

Roughly 10 percent of the U.S. population (30.6 million) has a physical limitation of some kind; among those with such limitations, 3.6 million use a wheelchair, and another 11.6 million use a cane, crutches, or a walker (U.S. Census Bureau 2012). Access to car-for-hire services for those with disabilities has been an issue in the taxi and limousine industries for many years. While some jurisdictions, such as New York City, have seen success in expanding the supply and availability of wheelchair-accessible cabs, many other areas have struggled to expand their accessible vehicle fleets. The primary obstacles involve the cost of acquiring and operating accessible vehicles, including fuel and maintenance expenses, higher insurance premiums, the need for special driver training, and lower productivity due to the extra time involved in serving customers in wheelchairs.

Some cities have imposed fees on taxi permit holders or on all passengers to subsidize the higher capital and operating costs of serving passengers with disabilities. Such fees include a 30-cent-per-trip fee added to fares in New York and a $100 annual fee imposed on Chicago medallion owners who do not operate an accessible vehicle. Although the funds are used to help offset the added expenses incurred by owners and drivers of accessible vehicles, such financing mechanisms raise equity questions of their own by singling out a particular group, such as other taxi passengers, rather than taxpayers more broadly to underwrite the costs of a social service (accessible door-to-door transportation) widely viewed as both socially desirable and mandated by federal law.²

Aside from tradition, there is no inherent logic in having taxi riders, rather than taxpayers more broadly, subsidize the accessible rides of people with disabilities. This is the case particularly because taxi riders tend to be either highly educated (and affluent) or quite poor.

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² The city of Portland, Oregon, is testing the use of a service performance standard tied to response times and service requests that would apply to both taxis and TNCs, instead of relying on fleet vehicle requirements for taxis (PBOT 2015).

Low-income households use taxis more often than middle-income households and at about the same rate as high-income households (Pucher and Renne 2003; Renne and Bennett 2014). Although fewer than 1 percent of trips made by low-income households are in taxis, more than 40 percent of all taxi users in urban areas are from households with incomes under $20,000 (which account for only 22 percent of all households) (Renne and Bennett 2014). On the other hand, only about 28 percent of people with severe disabilities are poor. So under schemes to impose per ride fees to increase access for people with disabilities, low-income taxi riders would pay disproportionately high per trip and per mile fees to subsidize people in wheelchairs who might well be more affluent than they are.

In some jurisdictions, then, a per ride fee that finances accessible vehicles may well be regressive. Given that it is in the interest of all Americans to provide mobility for people with disabilities, it may be wiser to finance these subsidies with a broader tax instrument. Moreover, basic public finance principles suggest that redistribution should be accomplished through broad tax instruments at high levels of government. In the absence of intergovernmental help, cities may be justified on equity grounds in using general fund revenues to pay for such programs.

There is also debate over how well, and to what extent, TNCs should be obligated to serve the needs of people with disabilities. If TNCs are viewed primarily as ridematching and payment processing services that link people driving their own cars with willing customers, the obligations of these drivers to accommodate the special needs of particular passengers are unclear. But if these services are viewed as a central new component of public and private urban transportation systems, the requirements of the Americans with Disabilities Act (ADA) may need to apply to TNCs—a question that has yet to be settled. It is not certain what role, if any, TNCs might play in helping transit agencies with ADA paratransit. TNC representatives claim that they are not providing public accommodations and therefore need not comply with the ADA accessibility provisions. For the reporting year 2013, the Federal Transportation Administration’s National Transit Database (NTD) shows that almost 10 percent of the approximately 850 urban transit agencies use taxis for their demand

response mode, which is mostly paratransit. To the extent that TNC competition hurts the taxi industry, the public transit industry loses or at least has a very diminished and weakened resource that many transit agencies use to help meet their ADA paratransit requirements (KFH Group, Inc. 2015).

TNC apps may facilitate automobile access for the blind; for example, they provide voice options, allowing easy vehicle requests from a smartphone without the need to see a passing taxi and hail it on the street. Cashless transactions eliminate the question of what change a taxi driver has provided, and the driver is not aware that the passenger is sight-impaired before accepting the ride. And an Uber black car competitor has added features to make its service more accessible to the blind (Alba 2015). At the same time, however, accommodating guide dogs in TNCs has become an issue. A lawsuit filed in San Francisco by the National Federation of the Blind alleged that Uber discriminated against blind passengers with service dogs (Bay City News 2014). Disability rights advocates also have filed lawsuits against TNCs in Texas and California regarding access for passengers with wheelchairs (Rosenthal 2014; Wieczner 2015). The Department of Justice issued a “Statement of Interest” in the San Francisco case, supporting the application of the ADA to Uber services and indicating that “Plaintiffs do not need to show that Defendants are public accommodations or operate a place of public accommodation to succeed on their ADA claim” (Gupta v. U.S. Department of Justice 2015). As of this writing, the case is pending.

As courts continue to deliberate whether ADA rules apply to TNCs, there is a related potential consequence of TNCs for access by people with disabilities: as mentioned in Chapter 3, the rise of TNCs could result in a net loss of wheelchair-accessible vehicles if other services operating these vehicles are reduced or driven out of business by TNCs. The cities and other jurisdictions that typically regulate taxis have provided various incentives for both taxi companies and drivers to operate them, which have met with varying degrees of success. But as TNCs have grown and, in some places, taken a substantial share of taxi business, these incentives may no longer be effective. In San Francisco, for example, the Metropolitan Transportation Authority reported in 2014 that a quarter of the city’s accessible taxis

were idle because no drivers with proper training were available to operate them. Also reported was a significant decline in the number of wheelchair trips made in cabs over the same period (Kwong 2014). Data provided by the San Francisco Municipal Transportation Agency indicate a 43 percent decline in wheelchair-accessible taxi trips between fiscal years 2012 and 2014.

For both taxis and TNCs, moreover, serving the needs of patrons who use wheelchairs by having accessible vehicles on hand is only one aspect of providing access for people with disabilities; having the vehicles does not equate to having service. Some cities, such as New York and Washington, D.C., have mandated having a central dispatching mechanism for accessible cabs so as to reduce response times, as well as having drivers properly trained and motivated to serve the unique needs of these customers (see Appendix B).

As the largest operators in the TNC industry, Uber and Lyft are likely to play central roles in addressing issues of access for people with disabilities. Uber approached the City and County of San Francisco, for example, to take over the city’s paratransit services for the elderly and those with disabilities (Rodriguez 2015). Because of unresolved insurance issues, however, those talks did not culminate in an Uber–San Francisco agreement (Kwong 2014). Uber also has created a variation of its service, known as UberWAV, that provides wheelchair-accessible vehicles (WAVs) as a specific request option. UberWAV connects riders with wheelchair-accessible “boro taxis” in the outer boroughs of New York City. Payment is not made through the Uber app; instead, it is made to the driver as in traditional taxi transactions (Uber.com 2014). In mid-2015, Uber introduced UberAssist in Los Angeles, a service that offers drivers with special training and vehicles capable of handling wheelchairs, walkers, and scooters (Alba 2015). Similarly, Lyft allows users to enable an “Access Mode.” Both of these services dispatch vehicles that are specially outfitted to accommodate wheelchairs, typically at a cost that compares with that of limousine or UberBlack service.

Low-Income Households

While the cost burden of vehicle ownership is significant for lower-income households (Blumenberg and Manville 2004; Deka 2002),

studies have shown that ownership of private vehicles substantially increases accessibility, which helps people acquire and keep better jobs (Blumenberg and Ong 2001; Grengs 2010; Shen 2001; Taylor and Ong 1995). In this context, innovative mobility services have the potential to provide enhanced accessibility without the cost burden of vehicle ownership.

Carsharing can reduce household transportation costs, often through reduced vehicle ownership costs (Lane 2005; Martin et al. 2010). However, some surveys of carsharing members have found low participation rates among lower-income households (Martin and Shaheen 2011; Martin et al. 2010; Millard-Ball et al. 2005). Similarly, surveys of bikeshare members have found that the services tend to attract disproportionately customers with moderate and higher incomes (Buck et al. 2013; Shaheen et al. 2012a). Identified barriers to participation in shared vehicle services by low-income individuals include a dearth of stations in low-income neighborhoods; transactionally complicated rules of membership and use; requirements to hold credit cards and have Internet access; high prices; lack of information about the new services; and cultural factors, including distrust of authority or discomfort with shared mobility systems (Kodransky and Lewenstein 2014). Nonetheless, many low-income households may participate in informal sharing of cars within their community (Giuliano and Moore 2000; Blumenberg and Smart 2013; Roy et al. 2004).

Car- and bikesharing providers locate vehicle stations largely on the basis of demand. In addition, for-profit providers and those relying on advertising revenues may be influenced by neighborhood income levels in locating stations. The same observations could apply to the boundaries of a floating or one-way carsharing system.

The evidence on this issue related to carshare stations is not conclusive. An analysis of carsharing stations in 13 cities found that income levels around the stations were not noticeably different from those for the region, although there were “substantial variations from city to city” (Millard-Ball et al. 2005). The share of households with incomes over $100,000 was positively correlated with the level of carsharing service (as measured by the number of vehicles

available) in one city and negatively correlated in three others. The study did find that stations were more likely to be in neighborhoods with smaller households, higher education levels, lower vehicle ownership rates, more transit use, and higher density. In contrast, however, an analysis of carshare stations in a single city did not find that neighborhood income was a significant factor in predicting use (Stillwater et al. 2009).

There are ways to overcome the barriers to participation in vehicle sharing among low-income individuals. Nonprofit carsharing services, such as Buffalo CarShare in Buffalo, New York, target services to lower-income households and neighborhoods. In contrast to many other systems, about half of Buffalo CarShare members were found to have incomes of $25,000 or less (Randall 2011). The City of Denver’s regulation allowing carsharing vehicles to have dedicated on-street parking spaces requires operators to locate at least two vehicles in higher-poverty neighborhoods (City and County of Denver 2013). Similarly, Washington, D.C., requires providers to locate vehicles in low-income neighborhoods (Shaheen et al. 2010). And officials with the California Air Resources Board are planning to fund pilot carsharing projects in disadvantaged communities using funds from the state’s Cap-and-Trade program (California Air Resources Board 2015).

Peer-to-peer (P2P) carsharing has the potential to increase low-income people’s access to carsharing vehicles, since the vehicles can be located anywhere a willing owner lives (Dill et al. 2014), although little research has evaluated this potential (Ballus-Armet et al. 2014; Shaheen et al. 2012a). One early study of renters signing up for a P2P service in Portland, Oregon, found that about 40 percent of those surveyed had incomes under $35,000, only slightly higher than the city average overall. However, lower-income adults aged 35 or older were the most frequent users of the system (Dill et al. 2015).

Bikeshare operators also have been criticized for not placing stations in low-income communities (Kodransky and Lewenstein 2014). However, several bikesharing programs are offering reduced memberships for low-income users and programs targeting the unbanked population (Kodransky and Lewenstein 2014), and the

Better Bike Share Partnership is using grant funding to increase access for low-income users in Philadelphia and other cities.³ The effectiveness of these efforts in increasing bikesharing among low-income individuals has yet to be proven. Some early efforts, such as discounted and free memberships in Denver, were not as successful as hoped, pointing to the need for more comprehensive approaches that also address cultural and other barriers beyond cost (Kodransky and Lewenstein 2014).

Very little research to date has examined low-income individuals’ access to TNCs. In a study of 380 TNC passengers in San Francisco, Rayle and colleagues (2015) found that users generally were younger and more highly educated than the city average (84 percent had a bachelor’s degree or higher). As noted earlier, however, taxi use is relatively high among low-income households (Renne and Bennett 2014). Thus, taxi riders tend to be either highly educated (and affluent) or quite poor. As already noted, low-income households use taxis more often than middle-income households and at about the same rate as high-income households (Pucher and Renne 2003; Renne and Bennett 2014).

Renne and Bennett (2014) also found that taxi trips by the lowest-income households in urban areas are the shortest compared with those of other income groups, averaging just 4.3 miles. To the extent that TNCs provide services similar to those of taxis for people without automobile access but at a lower cost, TNC services could meaningfully increase accessibility for low-income individuals. However, some of the barriers faced by low-income individuals with respect to vehicle sharing, such as lower levels of access to credit, the Internet, and smartphones, would similarly apply to TNCs.

Despite the frequent use of cabs among lower-income travelers, taxi regulators have long contended with cab companies over the level and quality of taxi service provided in low-income communities (Gilbert and Samuels 1982). With the rise of TNCs, those concerned about equity have suggested that TNC service in low-income communities is not monitored as carefully as it tends to be for taxis.

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³ See http://www.peopleforbikes.org/pages/better-bike-share-partnership.

At least one carefully designed study comparing TNC and taxi service and prices in Los Angeles suggests that TNCs may provide residents in low-income neighborhoods who have smartphones and credit cards with a faster and more economical transportation option relative to taxis (BOTEC Analysis Corporation 2015). In the study, pairs of riders were recruited to simultaneously call for taxi service and use a mobile app to call for an UberX car along routes preplanned for the study. Initial findings showed that the average total wait time for UberX was almost 8 minutes from the time of a ride request until a driver arrived for pickup, compared with a total wait time for taxi service of almost 19 minutes. The average cost of an UberX ride, $7.26, was less than half that of a taxi, which cost an average of $17.09. The researchers then conducted a series of followup tests to check the validity of the initial findings and data management procedures, such as the exclusion of outlier wait times that were exceptionally long and could have skewed the results; the follow-up tests produced similar results. The findings of this study thus suggest both that TNCs (in this case Uber) do serve low-income neighborhoods in the absence of regulation requiring them to do so and that the prices for their service (at least in Los Angeles) are consistently lower than those for taxi service.

This study, it should be noted, was funded by Uber Technologies, Inc., and requires independent replication in other cities and in different types of low-income neighborhoods to produce generalizable findings about the relative geography, service quality, and price of TNC and taxi service. For example, the neighborhoods in the study had average incomes of $50,000 or less (a definition of low-income that is used by the Los Angeles Housing Authority and is less than 80 percent of the Los Angeles median income for a family of three), but the neighborhoods selected were not those with the highest crime rates. If the study findings hold, low-income travelers who are more likely than those in higher-income households to have limited or no private vehicle access may benefit significantly from faster and more affordable door-to-door service offered by TNCs relative to taxis. But because the findings are from a sample of low-income neighborhoods in just one large city, they should be viewed as preliminary and not definitive.

Unbanked Populations

A sizable number of Americans currently do not have access to many of the technology-enabled mobility services examined in this report because of their lack of revolving credit or bank accounts. The Federal Deposit Insurance Corporation (FDIC) has done extensive research on the so-called “underbanked” and “unbanked” populations, whom they collectively term the “underserved” (FDIC 2014). The FDIC estimates that 17 million people (8 percent of U.S. households) are unbanked in that they do not have a bank account. The percentage of unbanked households has remained fairly steady since 2009 (7.6 percent in 2009, 8.2 percent in 2011, and 7.7 percent in 2013), suggesting that this rate is likely to remain consistent (FDIC 2014), at least in the near term. The reasons for a lack of banking services are related to both income (insufficient funds and costly services for low-balance customers) and attitude (lack of trust in institutions and privacy concerns) (FDIC 2014).

If the burgeoning new technology-enabled mobility services are to be available to all passengers willing to pay, alternative payment options for those without credit or bank accounts will be needed.⁴ To date, however, TNCs appear to have made little effort to address the financially underserved, although Uber is conducting a pilot in India to test cash payment (Kona 2015). Carsharing services also have limited experience with alternative payment arrangements, instead focusing on other equity issues, such as geography and cost. Upstate New York carshare has done the most to offer such alternatives: Buffalo Carshare accepted money orders in lieu of credit cards, while Ithaca Carshare has always offered cash payment as an option (Carney and Jaffe 2012; Ithaca Carshare 2015).

Public transit agencies and bikeshare operators could serve as a model for how alternative payment options might work. As public transit agencies around the United States have modernized their fare collection systems to be “all electronic” and upgraded to smart-

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⁴ While such policies may aim to increase access for the unbanked, they could inadvertently undermine safety aspects of TNCs for drivers if not implemented with care. The current TNC credit card requirement eliminates passenger anonymity, thereby increasing safety. If passengers were permitted to use anonymous prepaid debit cards on a prepaid cell phone, their identity could be lost should problems arise.

card payment systems and mobile apps, they have had to consider alternatives to bank accounts for their underserved customers as part of that transition. These alternatives include accepting prepaid debit cards, working with nonbanking institutions such as check cashing services, or continuing to offer cash as an alternative payment. Since 2011, for example, Greyhound has partnered successfully with PayNearMe—a private electronic cash payment service that allows members to pay for their membership using cash by going to a local convenience store instead of using a credit card online—and 7-Eleven to provide an option that entails cash payment and online purchase with applicable Internet discounts (Greyhound.com 2011). Relative to most other private shared mobility services, bikeshare services have a more extensive record of supporting financial alternatives to address equity concerns, perhaps as a result of their typically closer partnerships with public agencies. About one-third of the 19 technology-based bikeshare operators in North America offer debit cards as an option to encourage use by the underserved (Shaheen et al. 2012b). More recently, BikeArlington in Arlington County, Virginia, and Indego, Philadelphia’s new bikeshare system, have been offering cash payment options (BikeArlington 2015; Corbin 2015). Indego offers a monthly cash membership using PayNearMe (Indego 2015).

People Without Smartphones

As discussed previously, many innovative mobility services are app-based and operate exclusively through smartphones. In many cases, then, not having a smartphone means not having access to technology-enabled mobility services.

Currently, 64 percent of Americans own smartphones (Pew Research Center 2015b), a percentage that reflects rapid growth (from 35 percent in 2011) across all common demographic categories (income, gender, age, and race) (Pew Research Center 2015b). Among those earning less than $30,000, 50 percent owned a smartphone in 2015, compared with 43 percent in 2013. Smartphone access, on average, varies more by age than by income: just 27 percent of adults over age 65 have a smartphone, compared with 18 percent in 2013. Smartphone use among this age group lags that among all other demographic categories, at

about half the level of the next-lowest category (Pew Research Center 2015b). In 2015, for example, two-thirds of teens in low-income families owned a smartphone; ownership among African American teens (85 percent) is higher than that among either white or Hispanic teens (both 71 percent) (Pew Research Center 2015a).

Rural Residents

Because their average trip distances tend to be long and trip origins and destinations spatially dispersed, rural residents rely more heavily on private vehicles relative to urban or suburban residents. In rural areas, residents who cannot drive, such as some elderly people, may find their travel significantly restricted. According to the 2009 National Household Transportation Survey (NHTS), nearly all (97 percent) of households in rural areas have at least one motorized vehicle, and 92 percent of adults are drivers, compared with, respectively, 90 percent and 86 percent in urban areas. In rural areas, however, 22 percent of adults aged 65 and over have a medical condition making it difficult for them to travel, and 36 percent of these individuals have given up driving (NHTS 2009 data). Transit is available to only about 13 percent of the rural population and to 37 percent of people living in small urban areas (NCTR 2014).

Some shared mobility services, particularly carsharing and bikesharing, generally do not exist in rural areas outside of selected university campuses. Both of these services rely on the relatively high land use densities of cities and inner-ring suburbs. On the other hand, TNCs can provide rides anywhere drivers with cars are willing to operate, and thus could increase mobility options for people living in rural areas, where public transit and taxi services often are less available. In very low-density areas, the TNC model could be more cost-effective than current demand-response services. The latter services are the most common form of public transit available in rural areas, and the average operating cost per ride is high—$18.86 in 2012 (NCTR 2014).

While the extent to which for-profit TNCs are operating in rural areas is unclear at this stage, at least one nonprofit mobility service is entering this market. The Independent Transportation Network

(ITN), a nonprofit focused on older adults, has introduced ITNEverywhere, a service whereby members can earn credits by sharing rides or earn rides by trading a car they no longer drive (ITNAmerica 2015). As of early 2015, this service was operating in 18 areas in the United States. Programs with volunteer drivers for older adults exist in other communities, such as those run by individual organizations in large urban areas (an example is TRIP, which began in Riverside, California), but there are no data on the overall scale or impact of these efforts. TNC drivers are not likely to expand service to rural residents because drivers are incentivized to operate in densely populated areas for earnings that a rural market typically will not support (Hall and Krueger 2015, Figure 4). As a result, the provision of ride services to rural areas by TNCs may require some form of subsidy.

Conclusion

This chapter has considered four dimensions of equity issues related to new technology-enabled mobility services: (1) firms, markets, and competition; (2) regulations, subsidies, and social services; (3) geographies and jurisdictions; and (4) stakeholder groups. Innovative mobility services have the potential to enhance mobility for many disadvantaged groups, including racial and ethnic minorities, people with disabilities, low-income households, unbanked populations, people without smartphones, and rural residents. These services also may be easier to use than other mobility services for people with some disabilities, and they may reduce some forms of discrimination and provide alternatives to traditional public transit and taxi services where the availability of the latter services is limited. Absent sufficient data on usage, however, it is unclear whether discrimination may occur more or less often with these services than with other existing transportation services. Moreover, there are barriers to use of these new services for some people, particularly the 8 percent of households made up of unbanked individuals (who are more likely than other groups to be poor), the 36 percent of the population without smartphones, and people in wheelchairs.

Equity issues related to being unbanked and to smartphone ownership are quite different. Lack of access to banking services can

serve as a barrier to the use of innovative mobility services for underserved populations. Public transit agencies and bikeshare operators could provide models for alternative financial services for these populations, including the use of third-party electronic cash payment systems. TNCs in particular may have to find ways to accommodate the un- and underbanked if they want to continue their global expansion. TNCs, for example, will need to find alternative financial solutions in countries where personal banking is less ubiquitous than is the case in the United States. With respect to smartphone ownership, the digital divide for smartphones is based less on income and more on age. Those over age 65 are potentially the most excluded, a problem that is certain to diminish with time.

Of particular concern is a potential reduction in accessible taxis because of TNC competition, especially in areas where taxi companies also provide ADA paratransit services. Whether and how TNCs, and perhaps other innovative services, will be expected or required to provide accessible services is an open question. However, if the increased popularity of TNCs reduces taxi fleets significantly without provisions being made for accessibility for all people with disabilities, the mobility options for these people could be negatively affected. The ultimate resolution of this issue could have a significant impact on TNCs. It could affect the pace of their growth, their productivity, and the impacts associated with their services. For example, the resolution of accessibility issues could influence vehicle sizes, energy efficiency, emissions, user costs, utilization levels, and the subsequent impact on mobility.

In the short term, public agencies and regulatory authorities will likely need to address barriers to use of the new mobility services among people with disabilities and those who are unbanked if the potential for these services to enhance the mobility options of these groups is to be realized. On the other hand, should these services continue to expand over larger and larger geographic areas, they may increase considerably the opportunities for relatively affordable door-to-door motor vehicle access for those who, because of age, income, or disability, cannot own or drive a car, increasing mobility for transportation-disadvantaged groups in the process. Achieving these goals, however, may require deliberate public policies.

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