The DOI matches its Crossref record.
Exploring the influence of built environment on Uber demand
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 28
- Alemi, 2018, What influences travelers to use Uber? Exploring the factors affecting the adoption of on-demand ride services in California, Travel Behav. Soc., 13, 88, 10.1016/j.tbs.2018.06.002 · DOI
- Aziz, 2018, Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data, Transportation, 45, 1207, 10.1007/s11116-017-9760-8 · DOI
- Cervero, 2010, Effects of built environments on vehicle miles traveled: Evidence from 370 US urbanized areas, Environ. Plan. A, 42, 400, 10.1068/a4236 · DOI
- Cervero, 1997, Travel demand and the 3Ds: density, diversity, and design, Transp. Res. Part D: Transp. Environ., 2, 199, 10.1016/S1361-9209(97)00009-6 · DOI
- Dias, 2017, A behavioral choice model of the use of car-sharing and ride-sourcing services, Transportation, 44, 1307, 10.1007/s11116-017-9797-8 · DOI · Paper page
- Ewing, 2001, Travel and the built environment: a synthesis, Transp. Res. Rec.: J. Transp. Res. Board, 1780, 87, 10.3141/1780-10 · DOI
- Ewing, 2010, Travel and the built environment: a meta-analysis, J. Am. Plan. Assoc., 76, 265, 10.1080/01944361003766766 · DOI
- Ewing, 2014, Structural equation models of VMT growth in US urbanized areas, Urban Stud., 51, 3079, 10.1177/0042098013516521 · DOI
- Ewing, 2005, Turning highways into main streets: Two innovations in planning methodology, J. Am. Plan. Assoc., 71, 269, 10.1080/01944360508976698 · DOI
- Ewing, 2004, School Location and Student Travel Analysis of Factors Affecting Mode Choice, Transportation Research Record, 1895, 55, 10.3141/1895-08 · DOI
- Ewing, 2015, Varying influences of the built environment on household travel in 15 diverse regions of the United States, Urban Stud., 52, 2330, 10.1177/0042098014560991 · DOI
- Frank, 2008, Urban form, travel time, and cost relationships with tour complexity and mode choice, Transportation, 35, 37, 10.1007/s11116-007-9136-6 · DOI
- Gerte, 2018, Is there a limit to adoption of dynamic ridesharing systems? Evidence from analysis of Uber demand data from New York City, Transp. Res. Rec., 2672, 127, 10.1177/0361198118788462 · DOI
- Hamre, 2014, Commuter mode choice and free car parking, public transportation benefits, showers/lockers, and bike parking at work: evidence from the Washington, DC Region, J. Public Transp., 17, 10.5038/2375-0901.17.2.4 · DOI
- Hill, 1998, Multilevel modeling of educational data with cross-classification and missing identification for units, J. Educ. Behav. Stat., 23, 117, 10.3102/10769986023002117 · DOI
- Kitamura, 2001, Accessibility in a metropolis: toward a better understanding of land use and travel, Transp. Res. Rec.: J. Transp. Res. Board, 1780, 64, 10.3141/1780-08 · DOI
- Lavieri, 2018, A model of ridesourcing demand generation and distribution, Transp. Res. Rec., 2672, 31, 10.1177/0361198118756628 · DOI
- Li, 2019, Revealing the varying impact of urban built environment on online car-hailing travel in spatio-temporal dimension: an exploratory analysis in Chengdu, China, Sustainability, 11, 1336, 10.3390/su11051336 · DOI
- Limtanakool, 2006, The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium-and longer-distance trips, J. Transp. Geogr., 14, 327, 10.1016/j.jtrangeo.2005.06.004 · DOI
- Ozbil, 2011, Understanding the link between street connectivity, landuse and pedestrian flows, Urban Design Int., 16, 125, 10.1057/udi.2011.2 · DOI
- Pinjari, 2011, Modeling the choice continuum: an integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions, Transportation, 38, 933, 10.1007/s11116-011-9360-y · DOI
- Rayle, 2016, Just a better taxi? A survey- based comparison of taxis, transit, and ridesourcing services in San Francisco, Transp. Policy, 45, 168, 10.1016/j.tranpol.2015.10.004 · DOI
- Sabouri, 2020, Exploring the relationship between ride-sourcing services and vehicle ownership, using both inferential and machine learning approaches, J. Landscape Urban Plann., 10.1016/j.landurbplan.2020.103797 · DOI
- Salon, 2015, Heterogeneity in the relationship between the built environment and driving: Focus on neighborhood type and travel purpose, Res. Transp. Econ., 52, 34, 10.1016/j.retrec.2015.10.008 · DOI
- Wang, 2013, Built environments, social environments, and activity-travel behavior: a case study of Hong Kong, J. Transp. Geogr., 31, 286, 10.1016/j.jtrangeo.2013.04.012 · DOI
- Yu, 2019, Exploring the spatial variation of ridesourcing demand and its relationship to build environment and socioeconomic factors with the geographically weighted Poisson regression, J. Transp. Geogr., 75
- Yu, 2019, The impacts of built environment on ridesourcing demand: A neighbourhood level analysis in Austin, Texas, Urban Stud.
- Zailani, 2016, Is the intention to use public transport for different travel purposes determined by different factors?, Transp. Res. D, 49, 18, 10.1016/j.trd.2016.08.038 · DOI
Cited by
Sorted by citations
Ready to ride: security and transit-related determinants of ride-hailing adoption in Latin America
Oviedo, D., Sabogal-Cardona, O., & Scholl, L. (2022) · Inter-American Development Bank · doi:10.18235/0004656 · Cited by 6
“(Sabouri et al., 2020 page 9).”
Metadata
- Authors
- Sabouri, S., Park, K., Smith, A., Tian, G., & Ewing, R.
- Affiliations
- University of Utah (US)
- Utah State University (US)
- LSU New Orleans (US)
- Corresponding author
- Sabouri, Sadegh
- Venue
- Transportation Research Part D: Transport and Environment
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 81
- Pages
- 102296
- ISSN
- 1361-9209 (ISSN-L)
- OpenAlex
- W3011967978
- Cited by
- 104
- References
- 0
- Citations by year
- 2026: 13 · 2025: 18 · 2024: 17 · 2023: 13 · 2022: 28 · 2021: 13 · 2020: 2
- FWCI
- 5.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Transportation Research Part D Transport and Environment (publishedVersion)
- Topics
- Social Sciences › Transportation › Transportation and Mobility Innovations
- Social Sciences › Transportation › Urban Transport and Accessibility
- Social Sciences › Transportation › Transportation Planning and Optimization
- Keywords
- Uber, built environment, travel demand, population density, mixed land use, intersection density, destination accessibility, activity density, employment, car dependence, mode choice, trip data
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review