Citation

Radzimski A, Dzięcielski M. Transp. Res. A Policy Pract. 2021; 145: 189-202.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.tra.2021.01.003

PMID

unavailable

Abstract

It is widely believed that bike-sharing has the potential to encourage sustainable travel by combining the flexibility of cycling with the reliability of public transport. However, there is actually little empirical evidence concerning the scale of that effect. While many models of bike-sharing travel patterns include station locations, only a few have accounted for heterogeneity in service levels. This paper aims to fill this gap by examining the case of the bike-sharing system in the city of Poznań (536,000 inhabitants). We hypothesise that a higher number of bike-sharing trips could be found in places with a higher frequency of public transport. A model based on trips data mined through a web application programming interface (over 19,240,000 GPS recorded bicycle positions), and open public transport frequency data from the general transit feed specification is used. Regression results show that while including control variables and spatial effects, the frequency of public transport was significantly associated with the number of bike-sharing trips. A positive effect existed for short and medium trips, whereas no relationship was found for long trips.

FINDINGS support the view that public transport frequency is a relevant factor for bike-sharing which should be taken into account in planning.

Language: en

Keywords

Big data; Bike-sharing; Data mining; Multimodal travel; Public transport; Spatial regression