Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area
Abstract
© 2019 Elsevier Ltd Emerging technologies and services stand poised to transform the transportation system, with large implications for energy use and mobility. The degree and speed of these impacts depend largely on who adopts these innovations and how quickly. Leveraging data from a novel survey of San Francisco Bay Area residents, we analyze adoption patterns for shared mobility, electrified vehicle technologies, and vehicle automation. We find that ride-hailing and adaptive cruise control have penetrated the market more extensively than have electrified vehicles or car-sharing services. Over half of respondents have adopted or expressed interest in adopting all levels of vehicle automation. Overall, there is substantial potential for market growth for the technologies and services we analyzed. Using county fixed effects regressions, we investigate which individual and location-level factors correlate to adoption and interest. We find that, although higher-income people are disproportionately represented among current adopters of most new technologies and services, low- to middle-income people are just as likely to have adopted pooled ride-hailing. Younger generations have high interest in automated and electrified vehicles relative to their current adoption of these technologies, suggesting that young people could contribute substantially to future market growth—as they are doing for ride-hailing. Wemore »
- Authors:
-
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Carnegie Mellon Univ., Pittsburgh, PA (United States)
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V); USDOE
- OSTI Identifier:
- 1496844
- Alternate Identifier(s):
- OSTI ID: 1547807; OSTI ID: 1605691
- Report Number(s):
- NREL/JA-5400-73340
Journal ID: ISSN 1361-9209
- Grant/Contract Number:
- AC36-08GO28308; AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Transportation Research. Part D, Transport and Environment
- Additional Journal Information:
- Journal Volume: 71; Journal ID: ISSN 1361-9209
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 29 ENERGY PLANNING, POLICY, AND ECONOMY; transportation decisions; technology adoption; ride-hailing; automated vehicles; car-sharing; electric vehicles
Citation Formats
Spurlock, C. Anna, Sears, James, Wong-Parodi, Gabrielle, Walker, Victor, Jin, Ling, Taylor, Margaret, Duvall, Andrew, Gopal, Anand, and Todd, Annika. Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area. United States: N. p., 2019.
Web. doi:10.1016/j.trd.2019.01.014.
Spurlock, C. Anna, Sears, James, Wong-Parodi, Gabrielle, Walker, Victor, Jin, Ling, Taylor, Margaret, Duvall, Andrew, Gopal, Anand, & Todd, Annika. Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area. United States. https://doi.org/10.1016/j.trd.2019.01.014
Spurlock, C. Anna, Sears, James, Wong-Parodi, Gabrielle, Walker, Victor, Jin, Ling, Taylor, Margaret, Duvall, Andrew, Gopal, Anand, and Todd, Annika. Thu .
"Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area". United States. https://doi.org/10.1016/j.trd.2019.01.014. https://www.osti.gov/servlets/purl/1496844.
@article{osti_1496844,
title = {Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area},
author = {Spurlock, C. Anna and Sears, James and Wong-Parodi, Gabrielle and Walker, Victor and Jin, Ling and Taylor, Margaret and Duvall, Andrew and Gopal, Anand and Todd, Annika},
abstractNote = {© 2019 Elsevier Ltd Emerging technologies and services stand poised to transform the transportation system, with large implications for energy use and mobility. The degree and speed of these impacts depend largely on who adopts these innovations and how quickly. Leveraging data from a novel survey of San Francisco Bay Area residents, we analyze adoption patterns for shared mobility, electrified vehicle technologies, and vehicle automation. We find that ride-hailing and adaptive cruise control have penetrated the market more extensively than have electrified vehicles or car-sharing services. Over half of respondents have adopted or expressed interest in adopting all levels of vehicle automation. Overall, there is substantial potential for market growth for the technologies and services we analyzed. Using county fixed effects regressions, we investigate which individual and location-level factors correlate to adoption and interest. We find that, although higher-income people are disproportionately represented among current adopters of most new technologies and services, low- to middle-income people are just as likely to have adopted pooled ride-hailing. Younger generations have high interest in automated and electrified vehicles relative to their current adoption of these technologies, suggesting that young people could contribute substantially to future market growth—as they are doing for ride-hailing. We find no evidence that longer commutes present a barrier to plug-in electric vehicle adoption. Finally, women are less likely than men to adopt and/or be interested in adopting most new transportation technologies, with the exception of ride-hailing; designing or marketing technologies with women's preferences in mind could contribute to future market expansion.},
doi = {10.1016/j.trd.2019.01.014},
journal = {Transportation Research. Part D, Transport and Environment},
number = ,
volume = 71,
place = {United States},
year = {Thu Jan 31 00:00:00 EST 2019},
month = {Thu Jan 31 00:00:00 EST 2019}
}
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