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- 01GJE45DYP9514J9BHPEG0WK1G classification A1.
- 01GJE45DYP9514J9BHPEG0WK1G date "2022".
- 01GJE45DYP9514J9BHPEG0WK1G language "eng".
- 01GJE45DYP9514J9BHPEG0WK1G type journalArticle.
- 01GJE45DYP9514J9BHPEG0WK1G subject "Earth and Environmental Sciences".
- 01GJE45DYP9514J9BHPEG0WK1G doi "10.1016/j.trd.2021.103167".
- 01GJE45DYP9514J9BHPEG0WK1G issn "1361-9209".
- 01GJE45DYP9514J9BHPEG0WK1G issn "1879-2340".
- 01GJE45DYP9514J9BHPEG0WK1G volume "104".
- 01GJE45DYP9514J9BHPEG0WK1G abstract "In this study, we explore the heterogeneous impacts of ridehailing on the use of other travel modes using survey data (N = 1,438) collected from June to October 2019 (i.e., before the COVID-19 pandemic) across three regions in southern U.S. states: Phoenix, Arizona; Atlanta, Georgia; and Austin, Texas. We apply a latent-class cluster analysis to indicators of changes in the use of various travel modes as a result of ridehailing adoption, with covariates of socioeconomics, demographics, a land-use attribute, and individual attitudes. We identify four distinctive latent classes of behavioral changes in response to the use of ridehailing. About half of ridehailing users in the sample (49.7%) are found to behave as Mobility augmenters, who use ridehailing rarely, in addition to other travel modes, and do not change their travel routines much as a result of the adoption of this mobility service. The second largest class includes Exogenous changers (24.5%), whose members report many changes in their use of various travel modes, but which can be largely explained by other reasons. Private car/taxi substituters (15%) frequently hail a ride, and as a result, reduce their use of private vehicles while making more trips by public transit and active modes, as the result of using ridehailing. Interestingly, Transit/active mode substituters (10.8%) often use ridehailing, likely for trips that they previously made by public transit or active modes, and consequently reduce their use of these less-polluting modes while enjoying enhanced mobility. This study reveals substantial heterogeneity in ridehailing impacts, which were masked in previous studies that focused on average impacts, and it suggests that policy responses should be customized by users' socioeconomics and residential neighborhoods.".
- 01GJE45DYP9514J9BHPEG0WK1G author 22d7f9ed-7b0e-11ec-944b-f0b1754d10e9.
- 01GJE45DYP9514J9BHPEG0WK1G author urn:uuid:3cd3b04f-4602-43ca-8b29-bc816971d6eb.
- 01GJE45DYP9514J9BHPEG0WK1G author urn:uuid:a17d606f-5ec8-45e0-a04e-5c49fe5e6eb6.
- 01GJE45DYP9514J9BHPEG0WK1G author urn:uuid:e627ddbd-a975-4f9f-92db-2b564678b15f.
- 01GJE45DYP9514J9BHPEG0WK1G dateCreated "2022-11-21T22:15:28Z".
- 01GJE45DYP9514J9BHPEG0WK1G dateModified "2024-07-09T07:41:14Z".
- 01GJE45DYP9514J9BHPEG0WK1G name "Substitution or complementarity? A latent-class cluster analysis of ridehailing impacts on the use of other travel modes in three southern U.S. cities".
- 01GJE45DYP9514J9BHPEG0WK1G pagination urn:uuid:939e870c-c327-446a-8071-ca3eb2a10e7a.
- 01GJE45DYP9514J9BHPEG0WK1G sameAs LU-01GJE45DYP9514J9BHPEG0WK1G.
- 01GJE45DYP9514J9BHPEG0WK1G sourceOrganization urn:uuid:3a4506ab-e9cd-4ffb-aaeb-241d1d77b67e.
- 01GJE45DYP9514J9BHPEG0WK1G type A1.