The ridership performance of the built environment for BRT systems: Evidence from Latin America
Despite the increasing popularity of BRT worldwide, there is a lack of empirical evidence regarding the built environment characteristics that determine BRT ridership. We examine associations between BRT station level demand and built environment attributes for 120 stations in seven Latin American c...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2018
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/22484
- Acceso en línea:
- https://doi.org/10.1016/j.jtrangeo.2018.06.018
https://repository.urosario.edu.co/handle/10336/22484
- Palabra clave:
- Bus transport
Cluster analysis
Factor analysis
Land use
Public transport
Residential development
Sustainability
Travel demand
Latin america
Built environment
Bus rapid transit (brt)
Demand
Latin america
Transit-oriented development
- Rights
- License
- Abierto (Texto Completo)
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cc471959-8066-4071-987d-20d1070fae0d-1f36ea845-caea-4eed-b5d6-89f0f7f2e458-12020-05-25T23:56:41Z2020-05-25T23:56:41Z2018Despite the increasing popularity of BRT worldwide, there is a lack of empirical evidence regarding the built environment characteristics that determine BRT ridership. We examine associations between BRT station level demand and built environment attributes for 120 stations in seven Latin American cities. Using direct ridership models, we study whether underlying built environment factors identified using factor analysis and the package of these factors embodied in station “types” identified using cluster analysis were associated with higher ridership. Of the nine factors identified, those describing compactness with dominant multifamily residential uses and stations with public and institutional land uses along the corridor were positively associated with ridership, while factors describing single-family residential development away from the CBD were negatively associated with ridership. Thirteen station types were identified, of which six were associated with BRT ridership. Relevant station types for ridership included those with a high mixture of land uses, the presence of institutional uses and public facilities, major transfer nodes in peripheral areas, and stations with a strong pedestrian environment. Taken together, our findings suggest that the mix and dominance of various land uses around the stop, the location of BRT stations relative to the CBD, the developable land around the station, and the integration of the station to the urban fabric are important characteristics that determine BRT ridership. These insights will help substantiate the case for prioritizing-built environment changes as a means to build more prosperous and sustainable mass transit systems. © 2018 Elsevier Ltdapplication/pdfhttps://doi.org/10.1016/j.jtrangeo.2018.06.0189666923https://repository.urosario.edu.co/handle/10336/22484engElsevier Ltd184172Journal of Transport GeographyVol. 73Journal of Transport Geography, ISSN:9666923, Vol.73,(2018); pp. 172-184https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049065944&doi=10.1016%2fj.jtrangeo.2018.06.018&partnerID=40&md5=29454fa28612122f0d2549cfe0bcd751Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURBus transportCluster analysisFactor analysisLand usePublic transportResidential developmentSustainabilityTravel demandLatin americaBuilt environmentBus rapid transit (brt)DemandLatin americaTransit-oriented developmentThe ridership performance of the built environment for BRT systems: Evidence from Latin AmericaarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Vergel-Tovar C.E.Rodriguez D.A.10336/22484oai:repository.urosario.edu.co:10336/224842022-05-02 07:37:14.194004https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
title |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
spellingShingle |
The ridership performance of the built environment for BRT systems: Evidence from Latin America Bus transport Cluster analysis Factor analysis Land use Public transport Residential development Sustainability Travel demand Latin america Built environment Bus rapid transit (brt) Demand Latin america Transit-oriented development |
title_short |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
title_full |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
title_fullStr |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
title_full_unstemmed |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
title_sort |
The ridership performance of the built environment for BRT systems: Evidence from Latin America |
dc.subject.keyword.spa.fl_str_mv |
Bus transport Cluster analysis Factor analysis Land use Public transport Residential development Sustainability Travel demand Latin america Built environment Bus rapid transit (brt) Demand Latin america Transit-oriented development |
topic |
Bus transport Cluster analysis Factor analysis Land use Public transport Residential development Sustainability Travel demand Latin america Built environment Bus rapid transit (brt) Demand Latin america Transit-oriented development |
description |
Despite the increasing popularity of BRT worldwide, there is a lack of empirical evidence regarding the built environment characteristics that determine BRT ridership. We examine associations between BRT station level demand and built environment attributes for 120 stations in seven Latin American cities. Using direct ridership models, we study whether underlying built environment factors identified using factor analysis and the package of these factors embodied in station “types” identified using cluster analysis were associated with higher ridership. Of the nine factors identified, those describing compactness with dominant multifamily residential uses and stations with public and institutional land uses along the corridor were positively associated with ridership, while factors describing single-family residential development away from the CBD were negatively associated with ridership. Thirteen station types were identified, of which six were associated with BRT ridership. Relevant station types for ridership included those with a high mixture of land uses, the presence of institutional uses and public facilities, major transfer nodes in peripheral areas, and stations with a strong pedestrian environment. Taken together, our findings suggest that the mix and dominance of various land uses around the stop, the location of BRT stations relative to the CBD, the developable land around the station, and the integration of the station to the urban fabric are important characteristics that determine BRT ridership. These insights will help substantiate the case for prioritizing-built environment changes as a means to build more prosperous and sustainable mass transit systems. © 2018 Elsevier Ltd |
publishDate |
2018 |
dc.date.created.spa.fl_str_mv |
2018 |
dc.date.accessioned.none.fl_str_mv |
2020-05-25T23:56:41Z |
dc.date.available.none.fl_str_mv |
2020-05-25T23:56:41Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1016/j.jtrangeo.2018.06.018 |
dc.identifier.issn.none.fl_str_mv |
9666923 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/22484 |
url |
https://doi.org/10.1016/j.jtrangeo.2018.06.018 https://repository.urosario.edu.co/handle/10336/22484 |
identifier_str_mv |
9666923 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
184 |
dc.relation.citationStartPage.none.fl_str_mv |
172 |
dc.relation.citationTitle.none.fl_str_mv |
Journal of Transport Geography |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 73 |
dc.relation.ispartof.spa.fl_str_mv |
Journal of Transport Geography, ISSN:9666923, Vol.73,(2018); pp. 172-184 |
dc.relation.uri.spa.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049065944&doi=10.1016%2fj.jtrangeo.2018.06.018&partnerID=40&md5=29454fa28612122f0d2549cfe0bcd751 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.acceso.spa.fl_str_mv |
Abierto (Texto Completo) |
rights_invalid_str_mv |
Abierto (Texto Completo) http://purl.org/coar/access_right/c_abf2 |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Elsevier Ltd |
institution |
Universidad del Rosario |
dc.source.instname.spa.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167537634508800 |