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Transit and Micromobility (2021)

Chapter: Chapter 3 - Micromobility Users and Utilization

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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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Suggested Citation:"Chapter 3 - Micromobility Users and Utilization." National Academies of Sciences, Engineering, and Medicine. 2021. Transit and Micromobility. Washington, DC: The National Academies Press. doi: 10.17226/26386.
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44 This chapter discusses a variety of characteristics of micromobility users, as well as the nature of micromobility’s use in a variety of urban environments (including large and small metro areas), with an emphasis on understanding micromobility’s interaction with public transit systems. The analysis utilizes two datasets gathered by Populus Technologies, Inc. (one of the author organizations). First, to understand user characteristics and contrast them with those of non-users, this analysis incorporates Populus Groundtruth data collected through regional surveys. Conducted in 2019 in 18 metropolitan areas with representative sampling, these surveys assess transpor- tation choices. Akin to regional travel surveys typically conducted once a decade, this opt-in data-gathering effort captures basic demographic data, household characteristics, vehicle owner- ship, and key transportation decisions, including the adoption and use of new mobility services. Here, the focus is on a subset of the data related to micromobility adoption, comparing micro- mobility users and non-users. Second, to illuminate patterns of micromobility usage in space and time, Populus has also leveraged relationships with cities and operators to use select micromobility vehicle and trip data from docked and dockless systems, both to observe how the introduction of dockless micromobility may have changed docked system use and to evaluate dockless micromobility use around transit stops. More information on the methodology behind these two data sources is provided in Appendix A. The research team acquired permission from several cities and operators to share the data included in this report. Grouping of Metro Areas by Density and Transit Use Populus’ 2019 Groundtruth survey resulted in over 15,000 responses across 18 metro areas. To identify common patterns across different metro area types, the researchers grouped the regions into subsets with common population and transit characteristics, using population, population density, housing unit density, gross domestic product (GDP) per capita, and transit ridership per capita. Survey responses are presented according to these groupings throughout this study. Figure 14 displays the metro groupings in terms of population density (persons per square mile) and transit use (unlinked passenger trips per capita). User Characteristics Micromobility Adoption Rates Among survey respondents, nearly 20% had some experience using a shared bike or scooter (together considered “micromobility adoption”), as shown in Figure 15. About half as many had used a shared scooter alone. C H A P T E R 3 Micromobility Users and Utilization

Micromobility Users and Utilization 45   Notes: Only two of five factors used in the clustering are shown in the figure. MSA = metropolitan statistical area. Figure 14. Result of metro grouping analysis (top) and location map (bottom).

46 Transit and Micromobility Higher Scooter Adoption Rates Are Associated with Lower Levels of Regulation Among the cities where scooters were available at the time of the survey, most had scooter adoption percentages near the 10% range, with San Jose, San Diego, and Austin having signifi- cantly higher rates (Figure 16). This is likely explained in part by the lightly regulated nature of scooters in those cities. While many cities restrict the number of vehicles that can be deployed, the cities with significantly higher adoption rates had higher fleet caps (or none at all) at the time of the survey. This pattern is also visible in micromobility users as a whole (Figure 16a). The New York City, Chicago, Boston (except Brookline), Seattle, and Houston metros did not permit, or severely restricted, shared scooters at the time of surveying, but several of them had docked bikeshare systems. This is reflected in the much lower scooter adoption rates in these metros compared with their micromobility adoption overall (with the scooter figures in those cities likely reflect- ing experience with shared scooters in other markets). Demographics Age Scooter Adopters Tend to Be Younger Than the Typical Residents of Their Metros, with Peak Use in Those Under 35 and Few Users Above Age 55. The average respondent age was 43, while the average age of scooter adopters was 31 years old. Figure 17 shows the age distribution of respondents. In general, scooter users and micromobility users tended to be younger than non-users. The greatest micromobility use was among people under 35, with usage tapering off in older cohorts. Only a few users of scooters or micromobility generally were age 55 or older. Gender Micromobility Users Were Split About Evenly Between Males and Females, in Contrast to Scooters Alone, in Which Females Were Overrepresented. Similar to previous studies (Clewlow 2019a), the survey shows a gender gap between how people have adopted micromobility Figure 15. Micromobility (shared bikes and scooters) adoption (left); adoption of scooters alone (right). Note: “Yes” indicates the respondent had ridden a shared bike or scooter before. Source: Populus Groundtruth survey 2019.

Figure 16. Micromobility adoption by metro area (a, top); scooter-only adoption by metro area (b, bottom). Source: Populus Groundtruth survey 2019. Note: Some bar lengths vary from percentages due to rounding. (b) (a)

Source: Populus Groundtruth survey 2019. Note: Some bar lengths vary from percentages due to rounding. Figure 17. Age distribution for scooter-only users (red), all micromobility users (green), and all respondents (gray) across all metro areas.

Micromobility Users and Utilization 49   generally versus scooters alone (Figure 18). Combining bikeshare and scooter services, 48% of users identify as female versus 51% as male. The gender gap for scooter-only adoption is the inverse, favoring women, and slightly larger, with 54% of users identifying as female and 46% as male. Race and Ethnicity More Non-White People Were Users of Micromobility and Scooters. The rates of micro- mobility and scooter use by race and ethnicity differed from those for the overall population of respondents (Figure 19). A smaller proportion of both groups was white (42% to 43% versus 52% among all respondents), with Hispanic and Asian people seeing greater representation among both micromobility generally and scooter-only users. The data do not suggest a significant difference in micromobility or scooter adoption by Black people. Income People of all Income Levels Used Scooters and Micromobility, with Only a Small Variation from the General Population Across Income Levels. Adoption rates did rise with income to some degree, with the highest income brackets somewhat overrepresented among scooter and micromobility users (Figure 20). Compared to micromobility generally, in which higher income brackets contained somewhat more users, scooter use appears to be more equitably distributed. For all groups, the most users came from households in the middle of the income spectrum Source: Populus Groundtruth survey 2019. Figure 18. Gender distribution for scooter-only users (red), all micromobility users (green), and all respondents (gray) across all metro areas.

50 Transit and Micromobility ($50,000 to $99,000). Some 42% of scooter users had an annual household income under $50,000, about the same as the general population, compared to 37% for micromobility generally. Use of Other Transportation To better understand how shared mobility options fit into broader travel decisions, Populus’ regional travel surveys gather data on traditional transportation behavior, including com- mute mode, vehicle ownership, and mode shift. This section presents analysis based on data gathered in 2019, with a focus on assessing how scooter adoption fits into broader travel decisions. Commute Mode Scooter Users Were Less Likely to Have Solo Car Commutes and More Likely to Use Ride Hailing, but Use of Transit and Carpools Varied by Region. Scooter users made different commute choices than the general population, with slightly lower rates of solo driving and notably higher rates of ride-hail commuting (double or more) across all metro types, suggesting Source: Populus Groundtruth survey 2019. Note: Some bar lengths vary from percentages due to rounding. Figure 19. Race and ethnicity distribution for scooter-only users (red), all micromobility users (green), and all respondents (gray) across all metro areas.

Micromobility Users and Utilization 51   Source: Populus Groundtruth 2019. Note: Some bar lengths vary from percentages due to rounding. Figure 20. Household income distribution of scooter users (red), all micromobility users, (green) and all respondents (gray). that they are people who are already comfortable with using shared mobility. In the high-transit- use metros (Figure 21a), scooter users commuted by transit at lower rates, and carpooled at higher rates, than the general population. The inverse was true of the low-transit-use metros (Figure 21b): scooter users were somewhat more likely to be transit commuters, and less likely to carpool. Given that the average scooter trip is approximately 1 mile, commutes by scooter (assessed only among scooter adopters) represent only a fraction of respondents’ primary commute mode. That being said, this figure reached 1% in the high-transit-use metro areas (Figure 21a), which is surprisingly large given that scooters are a new entrant to the transportation mix and that commuting by bike even in higher-use cities is below 3%. Given that a substantial proportion of frequent scooter users said that their last scooter trip was for commuting, a number of first-/ last-mile trips may not be being picked up by a question focused on a single commute mode. Commuting patterns more generally appear to be mostly driven by urban context. Survey respondents in the medium- and high-transit-use metro areas had the highest share of public transit use for commuting (15% and 24%, respectively) and the lowest shares of driving alone (64% and 55%), regardless of scooter use. Both low-transit-use metro groups were dominated by solo driving as the primary commute mode (74% to 76%), with only 6% of the population relying on public transit. (Note that medium-density, medium-transit and medium-density, low-transit metros are not shown in the figure.)

52 Transit and Micromobility (a). Commute mode for high-density, high-transit-use metro areas for all respondents (top) and scooter users (bottom). (b). Commute mode for low-density, low-transit-use metro areas for all respondents (top) and scooter users (bottom). Source: Populus Groundtruth survey 2019. Figure 21. Respondent commute modes.

Micromobility Users and Utilization 53   Note that these figures simply describe the differences in the commuting habits of scooter adopters compared with non-adopters across metro types; they do not represent causal relation- ships or tell us anything about non-commute trips. Household Vehicle Ownership Scooter Users Live in Households with More Cars Than Non-Adopters Do. Across all user groups and metro types, respondents were consistently most likely to live in one- or two-vehicle households (Figure 22). But scooter users had a larger share of households with three or more vehicles than the general population—consistent with scooter users tending to have higher incomes, but also possibly pointing to younger people living in group households with several roommates. Given that many scooter users have multiple household vehicles, there may be greater opportunity for personal vehicle shedding due to increased micro- mobility options. How and Why People Use Scooters The Populus Groundtruth survey also asked scooter users how frequently they rode shared scooters, as well as safety-related questions and how scooters fit into their overall transporta- tion mix. This section highlights several key findings based on those questions; the findings are broken out by the metro clusters described previously. Results are weighted by frequency of scooter use; the weighting method is described in Appendix A. Trip Purpose: People Use Scooters for a Variety of Reasons Commuting in the More-Dense Places, Socializing in the Less Dense. There was high variability in the reasons that people use scooters across metropolitan areas, as shown in Figure 23. In higher-density regions with greater transit service and usage, shared-scooter use was primarily associated with commutes to/from work (38% in the medium- and high-transit metros). This contrasts with low-density, low-transit regions, where less than 14% of trips were for commuting and the majority of trips were for social activity (51%). Since less than 1% of respondents said that scooters were their primary commute mode (see previous section), many of the commute trips here may represent first-/last-mile trips connecting to other modes. Although they are not shown here, the unweighted results find social activities as the most common trip purposes across all metro types. But since the frequency-weighted results place commutes in the top position in denser metros, this suggests that repeat users are those who find ways to incorporate scooters into their travel in more utilitarian ways. Reasons for Choosing Scooters Fun Is Key Almost Everywhere, but Utility Is Central in the Densest Metros. Competitive Prices Are Also Important. Mirroring the results for trip purpose, the reasons that people chose scooters over other transportation options also varied significantly by metro type (Figure 24). In higher-density, high-transit regions, scooters were chosen over other alternatives for utili- tarian reasons the majority of the time, especially because they are the fastest and most reliable option (33%) and because of the difficulty of parking at their destination (22%). In medium-density and low-density metropolitan areas, scooters were chosen as a mode “just for fun” more than a third of the time, likely including “joyrides” and trips made to get to or from social activities. While it was nowhere the top reason, scooters’ low price compared to other modes was a key rationale 11% to 15% of the time in every metro type.

54 Transit and Micromobility (a). Number of household vehicles, high-density, high-transit use. (b). Number of household vehicles, medium-density, medium-transit use. (c). Number of household vehicles, medium-density, low-transit use. (d). Number of household vehicles, low-density, low-transit use. Source: Populus Groundtruth survey 2019. Notes: “Yes” (red) bars represent scooter use; left axis is vehicles per household. Figure 22. Number of household vehicles owned, by metro type.

Micromobility Users and Utilization 55   Together, the trip purpose and reasoning results suggest that shared scooters were more likely to be used for utilitarian purposes in high-density, transit-oriented areas, as compared with lower-density regions where they were used less frequently and primarily for social trips. Scooters’ low prices also appear to remain an important selling point for a significant minority of users. Modes Replaced by Scooters Similar to other recent reports, this national, statistically based sample of data suggests that scooter trips replaced a significant number of automobile trips, although mode substitution also varies by region (Figure 25). Most Scooter Trips Replaced Trips in a Car, and Many Replaced Walk Trips. While in most regions, a larger portion of scooter trips replaced car trips as compared to walking, biking, or transit trips (Figure 25), an analysis across different types of U.S. metros suggests that urban context—population density, the built environment, and existing transit services—influences shared scooters’ potential to provide substantial positive impacts as opposed to simply replacing existing sustainable transportation options. In high-density, transit-oriented regions, 55% of scooter trips replaced trips that would have otherwise been made by a car—either alone, with another passenger, or via a ride-hail service like Uber or Lyft. This number increased to 78% of trips in medium-density, low-transit areas, suggesting that there is potentially an even greater opportunity for shared electric scooters to Source: Populus Groundtruth survey 2019. Figure 23. Trip purpose for last scooter trip, weighted by trip frequency.

56 Transit and Micromobility influence mode shift to more sustainable modes in these auto-dependent regions. However, in the lowest-density regions, scooter trips were likely to have replaced a car trip less than half the time (46%). Across all regions, walking was the second most common mode replaced, with results ranging from 15% of replaced trips in medium-density, low-transit metros, to as high as 37% of replaced trips in low-density, low-transit metros (the group that also had the lowest level of car trip replace- ment). Trips on public transit represented 0.5% to 10% of those replaced, and private bikes and bikeshare were an even smaller proportion, ranging from 0.5% to 6%. Scooters appear to create some trips that would not have taken place otherwise, between 6% to 13% of the time (likely representing many of the “joyride” trips just for fun noted in the previous section). Scooting to and from Transit Populus Groundtruth survey data were also used to better understand whether and to what degree scooter adopters used scooters for first-/last-mile connections to/from public transit. Scooter users were asked how often they used a shared scooter to get to or from public transit (Figure 26). Similar to the analysis of scooter trip purposes, reasons for mode choice, and mode substitution analysis, these results are weighted by frequency of scooter use. Source: Populus Groundtruth survey 2019. Figure 24. Reason for using a scooter on last scooter trip, weighted by trip frequency.

Micromobility Users and Utilization 57   Source: Populus Groundtruth survey 2019. Figure 25. Modes replaced by scooters, weighted by trip frequency. Source: Populus Groundtruth survey 2019. Figure 26. How often scooters were used to get to/from public transit, weighted by trip frequency.

58 Transit and Micromobility Where Transit Is More Available, More Scooter Trips Are to or from Transit In the high-density, high-transit-use metro areas, slightly more trips were “sometimes” or “always” made to or from transit (36%) as opposed to “never” or “rarely” (33%). In lower-density, low-transit metros, the majority of trips “never” or “rarely” (nearly 60%) were made to or from transit, which largely reflects the lack of transit availability in these metropolitan areas. However, even in areas with low transit and low density, scooters were used to connect to transit more than a quarter of the time, and the most frequent occurrence of this purpose was in the medium- density metros, suggesting a connection with the longer distances and diminished walkability of these areas.

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Micromobility refers to small, low-speed vehicles intended for personal use and includes station-based bikeshare systems, dockless bikeshare systems, electric-assist bikeshare, and electric scooters. Micromobility has the potential to increase the number of transit trips by expanding the reach of multimodal transportation, but it also could replace transit trips.

The TRB Transit Cooperative Research Program's TCRP Research Report 230: Transit and Micromobility provides an analysis of the full benefits and impacts of micromobility on public transportation systems in transit-rich markets as well as in medium-sized and smaller urban areas.

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