Exploring the impact of built environment factors on the use of public bikes at bike stations: case study in Zhongshan, China

Research output: Contribution to journalArticleAcademicpeer-review

29 Citations (Scopus)

Abstract

Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300 m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R2 for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future.
Original languageEnglish
Pages (from-to)59-70
JournalJournal of transport geography
Volume58
DOIs
Publication statusPublished - 2017

Fingerprint

China
demand
Land use
Linear regression
Catchments
public transport
built environment
public
station
land use
regression
urban planner
holidays
public transportation
weekend
population density
city center
turnover
travel demand
travel

Keywords

  • METIS-319894

Cite this

@article{c1d5c049aa954392b6522b8b98deb91f,
title = "Exploring the impact of built environment factors on the use of public bikes at bike stations: case study in Zhongshan, China",
abstract = "Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300 m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R2 for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future.",
keywords = "METIS-319894",
author = "Ying Zhang and Tom Thomas and M.J.G. Brussel and {van Maarseveen}, M.F.A.M.",
year = "2017",
doi = "10.1016/j.jtrangeo.2016.11.014",
language = "English",
volume = "58",
pages = "59--70",
journal = "Journal of transport geography",
issn = "0966-6923",
publisher = "Elsevier",

}

TY - JOUR

T1 - Exploring the impact of built environment factors on the use of public bikes at bike stations

T2 - case study in Zhongshan, China

AU - Zhang, Ying

AU - Thomas, Tom

AU - Brussel, M.J.G.

AU - van Maarseveen, M.F.A.M.

PY - 2017

Y1 - 2017

N2 - Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300 m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R2 for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future.

AB - Many countries have implemented public bike systems to promote sustainable public transportation. Despite the rapid development of such systems, few studies have investigated how built environment factors affect the use of public bikes at station level using trip data, taking account of the spatial correlation between nearby stations. Built environment factors are strongly associated with travel demand and play an important role in the success of public bike systems. Using trip data from Zhongshan's public bike system, this paper employed a multiple linear regression model to examine the influence of built environment variables on trip demand as well as on the ratio of demand to supply (D/S) at bike stations. It also considered the spatial correlations of PBS usage between nearby stations, using the spatial weighted matrix. These built environment variables mainly refer to station attributes and accessibility, cycling infrastructure, public transport facilities, and land use characteristics. Generally, we found that both trip demand and the ratio of demand to supply at bike stations were positively influenced by population density, length of bike lanes and branch roads, and diverse land-use types near the station, and were negatively influenced by the distance to city center and the number of other nearby stations. However, public transport facilities do not show a significant impact on both demand and D/S at stations, which might be attributed to local modal split. We also found that the PBS usage at stations is positively associated with usage at nearby stations. Model results also suggest that adding a new station (with empty capacity) within a 300 m catchment of a station to share the capacity of the bike station can improve the demand-supply ratio at the station. Referring to both trip demand models and D/S models, regression fits were quite strong with larger R2 for weekdays than for weekends and holidays, and for morning and evening peak hours than for off-peak hours. These quantitative analyses and findings can be beneficial to urban planners and operators to improve the demand and turnover of public bikes at bike stations, and to expand or build public bike systems in the future.

KW - METIS-319894

UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2017/isi/vanmaarseveen_exp.pdf

U2 - 10.1016/j.jtrangeo.2016.11.014

DO - 10.1016/j.jtrangeo.2016.11.014

M3 - Article

VL - 58

SP - 59

EP - 70

JO - Journal of transport geography

JF - Journal of transport geography

SN - 0966-6923

ER -