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Suggested Citation:"Appendix D Shared Mobility Survey Methodology." National Academies of Sciences, Engineering, and Medicine. 2018. Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles. Washington, DC: The National Academies Press. doi: 10.17226/24996.
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Page 65
Page 66
Suggested Citation:"Appendix D Shared Mobility Survey Methodology." National Academies of Sciences, Engineering, and Medicine. 2018. Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles. Washington, DC: The National Academies Press. doi: 10.17226/24996.
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Page 66

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65 This section covers the shared mobility survey developed and administered by the authors of this study, and which also informed TCRP Research Report 188. The survey developed and administered by the four public transit agencies (in which the authors had no role) is described in Appendix F. For the survey, the survey sample frame included adult residents of the study regions who have used one or more shared-use modes, including transit. The researchers requested dis- tribution by transit agencies and shared mobility operators in all the study markets, as well as in New York City. The recruitment method was through invitations to a web-based survey instrument emailed directly to known users by cooperating agencies and operators. Provider- specific links, called collectors, allowed the researchers to track where the responses were coming from and to shut off responses at the end of their open period. Distribution partners in each market are listed in Table D-1. The survey contained an initial screening question about overall experience with new shared-use modes, asked whether respondents had “ever used a shared form of transportation like bike-sharing, car-sharing, or ride-sharing like Uber or Lyft.” Respondents who answered “No” went immediately to a portion of the survey that only asked about transit technology, followed by collection of demographic information, including home zip code. The geographic distribution of home zips generally matches the distribution locations. Sampling Considerations Because the researchers were limited to working with convenience samples in each market— those individuals we were able to reach via the partners who agreed to distribute our survey, all of whom had previously supplied their email addresses to the agencies or operators—we must be cautious about inferring to the wider population of shared-use mobility and transit users and certainly to the general population. First, the survey was administered via an online form, and links to this form were distributed by email. This implies a basic level of technological facility and a willingness to participate in research about transportation. Second, the survey took place in several of the largest, most dense, and most expensive cities in the country; thus, the sample is likely over-representative of higher-income, more highly educated individuals compared to the general public. We should also make note of the small sample sizes in some markets relative to others: we received only 69 responses via the Boston collectors, and fewer than 200 in San Francisco. In addition, we might expect some bias related to the mode of the distribution channels for the various surveys. In Los Angeles, Nashville, and San Francisco the survey was distributed almost exclusively via the transit agencies; in Boston and New York, the survey was distributed solely via A P P E N D I X D Shared Mobility Survey Methodology

66 Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles bikeshare operators; and in Austin and Seattle the primary channel was a carsharing operator. One subpopulation this distribution might miss would be people who use ridesourcing exclusively among shared-use modes, and have zero history with transit. Unfortunately, we don’t have a way of estimating the size of this population until more is known about levels of ridesourcing usage in urban areas and the traveling population overall. This is an area for further research. Overall, the familiarity with and level of information about shared-use modes in the general population is likely to differ somewhat from what we found from our respondents. The survey was distributed in several phases through both private shared-use operators and transit agencies starting in mid-September 2015. The survey link was directly emailed to more than 75,000 email recipients plus many newsletter and social media followers, and received 10,348 at least partial responses, of which 7,961 reached the end of the survey. The number of responses to individual questions varied, with some respondents skipping individual questions while answering others later in the survey. The circulated version of the survey instrument is attached in Appendix E. Additional Data In addition to asking for home zip code, the survey asked respondents in which metro area they generally used their top shared-use mode—this distinction was intended to elicit infor- mation about where the shared-mode use actually took place, even if these services were not available near respondents’ homes (e.g., people who use the public train and bikesharing when they’re in Washington, D.C., even though their hometown only has bus service). As would be expected, all but a few respondents told us that they most commonly use shared- use modes in one of the eight metro areas where the survey was fielded (the seven study cities plus New York City). We received fewer than 100 responses to this question for either Boston or San Francisco, reinforcing the caution we must take with what we infer from our results about those areas due to their small sample size. Market Agency or operator Field dates Total responses Austin Car2go 9/17/15-10/1/15 539 Boston Motivate/Hubway 10/8/15-10/22/15 69 Chicago Motivate/Divvy 9/24/15-10/8/15 424 CTA 1/29/16-2/18/16 4861 Los Angeles LA Metro 10/6/15-10/20/15 653 Nashville MTA, RTA 2/27/17-3/13/17 936 New York City Motivate/CitiBike 9/23/15-10/7/15 508 San Francisco Bay Area BART 9/18/15-10/8/15 (staggered samples) 179 Motivate/Bay Area Bikeshare 9/16/15-9/30/15 5 Seattle Car2go 9/17/15-10/1/15 992 Motivate/Pronto Cycle Share 9/15/15-9/29/15 30 Washington, D.C. WMATA 9/16/15-9/30/15 830 Motivate/Capital Bikeshare 9/17/15-10/1/15 74 Car2Go 9/17/15-10/1/15 248 Total 10,348 Table D-1. Survey distribution partners, dates, and response counts.

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TRB's Transit Cooperative Research Program (TCRP) Research Report 195: Broadening Understanding of the Interplay Among Public Transit, Shared Mobility, and Personal Automobiles explores the effects of app-based transportation network companies on the cities in which they operate, including on public transit ridership, single-occupancy vehicle trips, and traffic congestion. Built upon the findings of TCRP Research Report 188, this report explores how shared modes—and ridesourcing companies in particular—interact with the use of public transit and personal automobiles.

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