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68 Leaders in the transit community are grappling with the future role of products and services influenced by the rapidly advancing ICT sector. Strong differences by age and gender exist in the way in which communications devices are adopted today. These differences have implica- tions for the way in which different groups will react in the future to services and products being developed. In many cases, the predictions for transit can be optimistic: services such as advanced passenger information systems will soon provide personalized guidance within and between public modes that is not available today. In other areas, leaders in the transit community are now debating whether new services to be provided by transportation network companies (TNCs) will either help or hinder the future of public transportation. The chapter is presented in five sections: 1. Ownership of communication devices, 2. Use of and attitudes toward existing advanced communications, 3. Services from TNCs, 4. Autonomous vehicles and transit, and 5. Replacement of travel because of communications technology. Who Owns Communications Devices? According to recent Pew research (Rainie 2017), 77% of all Americans have a smartphoneâ 64% of those with incomes less than $30,000 per year and 90% or more of those with incomes greater than $75,000 per year. Rates of smartphone ownership are similar for whites, African- Americans, and Hispanics, although minorities are more likely to use a smartphone to access the Internet, which suggests they are less likely to have broadband service at home. More than 90% of urban millennials reported owning a smartphone in the Pew research. The 2016 TCRP survey found similar distributions across age groups: more than 90% of the respondents 18 to 34 years old reported owning a smartphone. The same research indicates the people who were least likely to own a smartphone were older, rural, and poor. Who Finds Communications Devices Important and How Do They Use Them? The TransitCenter survey (2014) asked respondents what device would be most difficult to live without, with a broad definition of âdeviceâ that included everything from televisions to cars. The results powerfully show the effect of increasing age on personal priorities about staying connected, as shown in Figure 25. While fully half (50%) of those between the ages of 18 and 24 say the hardest device to live without would be their phone, less than 10% of those over 65 say the same thing. The importance of the private auto has an almost inverse ratio with increasing C H A P T E R 7 Information and Communications Technology Might Change the Setting for Transit
Information and Communications Technology Might Change the Setting for Transit 69 age, with more than 45% of those over 65 stating the car would be the hardest device to live without (Figure 25). Gender is also an important factor in attitudes about mobile technology. Figure 26 reveals that women place a higher value on connected devices than men in every age group. Half of the project sample for the 2016 TCRP survey used a connected device to help with driving directions and one-quarter used a connected device to obtain real-time traffic information within the past week. A clear relationship exists between income and ageâyounger people were more likely than older people to use their device for information and navigation for auto travel, and individuals with higher incomes were more likely than individuals with lower incomes to use their device for assistance in auto travel. Overall, in the 2016 survey, 15% of the respondents had used a device to navigate transit or obtain real-time transit information in the past week. Younger people and individuals with lower incomes were more likely to use a connected device for assistance in navigating transit travel. While everyone values staying connected throughout the day, higher-income people indicated it was slightly more important for them as compared with respondents with lower incomes. People with lower incomes were slightly less (4% less) Source: TransitCenter 2014. 0 10 20 30 40 50 60 18â24 25â34 35â49 50â64 65 P er ce nt ag e R ep or tin g Age Group Cell phones (all) My car Figure 25. Percentage reporting most difficult device to live withoutâcell phone or carâby age. Source: TransitCenter 2014. P er ce nt ag e R ep or tin g 0 10 20 30 40 50 60 70 18â24 25â34 35â49 50â64 65 Male Female Millennial Gen X OlderBoomer Figure 26. Percentage reporting connected portable device most important, by age and gender.
70 Understanding Changes in Demographics, Preferences, and Markets for Public Transportation likely to agree with the statement âIt is important for me to have access to communication technology throughout the dayâ as compared with the average response to the statement. Services from Transportation Network Companies TNCs and Transit Use An established player in the set of new travel options are TNCs (e.g., Uber and Lyft) that offer âride-hailingâ services initiated, tracked, paid for, and reviewed via smartphone. A recent survey by the Pew Research Center (Smith 2016) found that 21% of urban residents nationwide have used a TNC service. In the 2016 TCRP survey, 22% of respondents indicated that they had used a TNC to make trips in the past week. Public Transportation and Ride-Hailing Younger people embrace both new means of travelâsuch as the original ride-hailing services of the TNCs. Arrangement of a ride for a single person is referred to as âprivateâ TNC service; arrangement of a ride to be shared with strangers in the same vehicle is referred to as âsharedâ TNC service. Figure 27 shows the percentage of people, by age group, who reported a transit trip or private TNC trip as the mode of travel for their most recent trip: both means of travel seem to be influenced by the age of the traveler. Seventeen percent of 18- to 24-year-old respondents reported their last trip was on transit, compared with half that (8%) for middle-aged people aged 35 to 49, and half again (4%) for those aged 65 and over. Around 6% of 18- to 34-year-old respondents reported that private TNC was used for their last trip, compared with negligible use (less than 2%) in the older age groups. According to the Pew study (Smith 2016), 10% of 18- to 29-year-old individuals living in urban areas use ride-hailing TNCs on a daily or weekly basis. However, according to the avail- able research on the types of trips made using TNCs, many trips are late-night nonwork trips. The current survey obtained the reported number of work and nonwork trips using TNCs . On average, people who reported using TNCs had used them twice in the past week. Most of these trips were for nonwork purposes. The single millennials market segment reported using a pri- vate TNC for commute purposes more than other people but used it slightly less for other types of trips. The urban commuters market segment reported using private TNC for nonwork trips more often than other groups, but less often for commuting. Source: 2016 TCRP survey. 0 2 4 6 8 10 12 14 16 18 20 18â24 P er ce nt R ep or tin g 25â34 35â49 50â64 65 Transit used on last trip Uber used on last trip Figure 27. Percentage mode share for last trip, by age group, 2016.
Information and Communications Technology Might Change the Setting for Transit 71 Both the Pew study and TCRP Research Report 188: Shared Mobility and the Transformation of Public Transit (Feigon and Murphy 2016) found that people who used ride-hailing services such as Uber and Lyft were less likely to own a personal vehicle and more likely to use public transit. The present study supports those findings. People in the 2016 TCRP survey who used TNCs were less likely to own a personal vehicle than those who did not: 79% of people who used private TNC had access to a vehicle, compared with 86% of people who did not use a TNC. However, the impact of new services on the decision to own a car (or an additional car) varied sharply by the attitudes held by the traveler: Figure 28 shows that the majority of those in the two transit-positive market segments agreed with the proposition that âBecause of new services helping me make trips, I feel less need to own a car.â By contrast, about 5% of the most car- oriented group agreed with the statement. According to the Pew study, people who use ride-hailing services are significantly more likely to use a wide range of other personal transportation options in addition to ride-hailing. Among daily or weekly ride-hailing users, 70% report that they regularly walk or ride a bike somewhere; 56% regularly take public transportation; 55% regularly use traditional taxi services; and 14% ever use bike-share services. In each instance, frequent ride-hailing users are significantly more likely than other Americans to engage in these behaviors. The 2016 survey also found that people who use ride-hailing TNCs were more likely to be transit users. About half of the sample in the survey indicated they used transit, and, of those, 40% also had used a ride-hailing TNC in the past week and 60% had not. Of all the people who reported any TNC use, 85% also reported transit use compared with 37% who did not use any TNC. The interrelationship of auto ownership, new services, and transit use is revealed repeatedly in the survey data. As noted, TNC users were also more likely to use public transit and own fewer cars. In addition, the survey supports research that found that people who have access to carshare services (car2go or Zipcar, for instance) were less likely to own a vehicle. Just 2% of the overall sample said they had regular access to a carshare programâtoo small to break out the vehicle ownership by cluster. However, about half of the percentage of people with access to a carshare program owned a vehicle (40%) compared with those without such access (85%). A sharp variation exists in attitudes about the extent to which new services will lower the need for the car; significant differences are shown by market segment in Figure 28. Source: 2016 TCRP survey. %5 16% 56% 62% 26% 0 10 20 30 40 50 60 70 Car LoversOccasional Transit Users Single Millennials Urban Commuters Total Market Segment A gr ee m en t w ith S ta te m en t ( % ) Figure 28. Agreement in 2016 with the statement: âBecause of new services helping me make trips, I feel less need to own a car.â
72 Understanding Changes in Demographics, Preferences, and Markets for Public Transportation More Direct Competition with Fixed Route and Schedule Transit? The Slow Emergence of Shared Services While most of the professional literature does not currently focus on new shared service that could compete directly with transit, the emergence of new kinds of shared services is discussed in Special Report 319: Between Public and Private Mobility: Examining the Rise of Technology- Enabled Transportation Services (Transportation Research Board 2016, p. 2): To date, the most rapidly growing forms of shared mobility entail sequential sharing of vehicles, with each user in turn having exclusive use of a motor vehicle or bicycle. Potentially more consequential, but still in its infancy, is concurrent sharing of vehicles among strangers. By increasing vehicle occupancy, this form of shared services may collectively have greater effectsâin terms of affordable personal mobility, vehicle use, energy consumption, traffic congestion, and environmental benefitsârelative to todayâs most popular new sequential mobility options. Considerably less is known about these spin-offs from ride-hailing services, described in this report as âshared TNCâ services. Ford Motor Companyâs Chariot, Via, Lyft Shuttle and uberPOOL are offering services similar to those pioneered by Bridj. These services share a similar concept that certain routes can be operated in smaller vehicles, carrying multiple parties with some common origins and destinations, based on last-minute pairing though mobile devices. The extent to which these specialized bus services can or cannot be integrated into (or coordinated with) existing networks is the subject of much debate in the international transit community at this point. Autonomous Vehicles and Transit Some future technologies could completely disrupt current patterns of travel behavior. While private TNC services provide a platform to connect drivers and people wanting rides, in practice it is like a taxi service, and thus not the same market as most transit. On the other hand, a more disruptive technology, autonomous vehicles, will likely be used for mobility in the future, with direct impact on transit ridership patternsâbut how will autonomous vehicles be used? Recent research points to three possibilities (Correia 2016): â¢ A taxi fleet available throughout urban areas, â¢ Autonomous cars replacing familiesâ privately-owned cars, and â¢ Public transport vehicles substituting for buses and trams. The reality will probably be a combination of all three. In the 2016 survey, the respondentsâ thoughts about how autonomous cars would affect their transit use varied starkly by market segment. A sharp difference was seen between the urban commuters, who had less than mean propensity to agree that âIn a world with driverless cars, I would not see much of a role for buses and subways anymore,â and the single millennials, who strongly agreed with the statement. Importantly, younger people (millennials) tended to imagine a world where autonomous cars would replace transit, while older respondents (and âoccasional transit usersâ) did not. The mix of future services and their relationship to fixed route and schedule transit is a matter of some concern for the transit industry. Currently, TNCs are most frequently used for social trips between 10:00 p.m. and 4:00 a.m., times when public transit runs infrequently or is not available; however, the data showed that single millennials were starting to use TNCs as part of their commute options. TNCs may currently substitute more for automobile trips than public transit trips, but as TNCs encourage people to own fewer vehicles and depend more on shared servicesâand, more importantly, as those services develop and change in response to market forcesâthey may compete directly with transit. Young people believe that autonomous cars would change their trip-making behavior, and males believe this somewhat more than the females (Figure 29).
Information and Communications Technology Might Change the Setting for Transit 73 Are Trips Being Replaced by Information Technology? Variation in Telecommuting, by Age Predicting how evolving information technology will affect the total number of trips taken in the future is highly challenging. Perhaps the simplest form of substitution occurs when the employer encourages the worker to work a part of the week outside of the established office. This pattern is not the same as the decision to base oneâs work at home, which was reported in Chapter 3 in the discussion of journey-to-work data. The propensity to base work at home rises directly with increasing age. The propensity to report telecommuting decreases directly with increasing age, as shown in Figure 30. Thus, given the observed fact that the younger cohort is used to working remotely more often, a reasonable forecast is that this trend will not be good for daily transit ridership to work: if this trend is a cohort-based pattern, higher overall telecommuting rates will result; if it is an age-based pattern, some decrease over time would be expected. Source: Coogan et al. 2016. 15 20 25 30 35 40 45 50 18â24 25â34 35â44 45â65 >65 Age Group A gr ee m en t w ith S ta te m en t ( % ) Male Female Figure 29. Effect of age and gender on agreement that autonomous cars would alter present travel behavior. Figure 30. Effect of age on telecommuting at least once per week, 2016. Source: 2016 TCRP Survey. 0 5 10 15 20 25 30 18â24 25â34 35â49 50â64 Age Group T el ec om m ut in g (% )
74 Understanding Changes in Demographics, Preferences, and Markets for Public Transportation When Are Trips Substituted? The effect of information technology on travel is most apparent in two areas: 1. When the technology supports travel choices that include applications and tools such as real-time travel information, mapping, and car- or ride-share services, the new technology complements travel. 2. When information provides a more attractive method for completing a task, then it substitutes for travel. This is evident in activities such as shopping or banking, for which smart devices have enabled activities without travel to the location. The classic model developed by Circella and Mokhtarian (2010) also includes ICT as an inspiration to travel and the impact of ICT in freeing resources (time or money) that can be shifted to more travel. Demonstrably, a complex interrelationship exists that will potentially affect the way people go about their daily lives, including how, when, and why they travel. In a major study undertaken in Germany and the United Kingdom, ICT and Physical Mobility, Pawlak et al. (2015) concluded that the naÃ¯ve expectation that ICT is serving to replace physical mobility is unsupported by either theory or the empirical evidence in the public domain. Leading scholars demonstrate that, depending on oneâs interpretation, the results are either indeterminate in their conclusions or tend to, on balance, refute this âreplacement hypothesis.â Changes in Retail Travel Patterns? If fewer total trips are going to be made to brick-and-mortar stores, then transit ridership will decline for those trips. Online retail options are growing, and the effect on land use is apparent: large trip generators such as record stores, book stores, and electronic stores have disappeared from malls and retail centers. However, new behaviors, such as showrooming (i.e., going to a retail shop to examine something before purchasing online) and looking at choices online before buying from a brick-and-mortar shop, demonstrate that the effect of ICT on travel is complicated and largely unknown. In addition, the theory of the travel time budget suggests time not spent shopping and doing errands will be replaced by other travel. Additionally, there is another way to look at the issue. The 2009 NHTS showed that adults (ages 16â65) spent more time at homeâan average addition of 1 hour and 15 minutes a weekâ than they did in 1995, and menâs time at home changed more than womenâs. Men spent about 2 hours more time at home per week than they did in 1995, and women spent 30 minutes more time at home per week. In keeping with the analysis presented so far, the youngest cohort showed the greatest change. What can be keeping young men at home? The American Time Use Survey indicates a growth in time spent in leisure activities at home (comparing 2003 and 2014 data), including gaming. In addition, new streaming options for entertainment, more online social and communication options, and the overall greater diversity of activities accomplished online may also contribute. The implications here are complicated, but, to some extent, improved information technology may have a role in lowering the total number of trips rather than in replacing them.