Impact of Weather Conditions and Built Environment on Public Bikesharing Trips in Beijing

Pengfei Lin (), Jiancheng Weng (), Quan Liang (), Dimitrios Alivanistos () and Siyong Ma ()
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Pengfei Lin: Beijing University of Technology
Jiancheng Weng: Beijing University of Technology
Quan Liang: Beijing University of Technology
Dimitrios Alivanistos: Vrije Universiteit Amsterdam
Siyong Ma: Beijing University of Technology

Networks and Spatial Economics, 2020, vol. 20, issue 1, No 1, 17 pages

Abstract: Abstract As bicycling regains popularity around the world, the Beijing Public Bikesharing System, launched in 2012, enables users to access shared bicycles for short trips. After five years of operation, while the system is widely used, it faces the problems of bike unavailability and dock shortage at various stations due to the tidal characteristics of bicycle travel. It is necessary to investigate the influence of different weather conditions and nearby built station environments on bikesharing trips. Using historical trip data from 2016 concerning 543 stations in Beijing, log-linear regression models are developed to estimate the impact of daily weather and time events on bikesharing trips. Moreover, the effects of built environment variables, such as land use and transport infrastructure, are investigated both on workday and non-workday usage at the station level. The results indicate that temperature is not linearly associated with daily usage. Daily usage decreases according to rainfall, snowfall, wind speed and weekends/holidays. Light and heavy pollution have no significant influence on bikesharing demand; however, severe pollution has a negative influence on usage. The effect of transport infrastructure (subway stations, bus stops and bikeway length) is crucial in increasing bikesharing demand. The number of residential and shopping locations is generally associated with usage. Proximity to colleges does not show an obvious usage increase, which is different from the results obtained in other cities. Parks encourage more bikesharing usage on weekends/holidays than on workdays. The findings may help planners or managers to design and modify public bikesharing stations effectively, increasing usage while reducing rebalance costs.

Keywords: Public bikesharing; Daily weather; Temporal factors; Land use; Transport infrastructure; Log-linear regression (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11067-019-09465-6

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