Expanding Bicycle-Sharing Systems: Lessons Learnt from an Analysis of Usage

Abstract

Bike-sharing programs, with initiatives to increase bike use and improve accessibility of urban transit, have received increasing attention in growing number of cities across the world. The latest generation of bike-sharing systems has employed smart card technology that produces station-based data or trip-level data. This facilitates the studies of the practical use of these systems. However, few studies have paid attention to the changes in users and system usage over the years, as well as the impact of system expansion on its usage. Monitoring the changes of system usage over years enables the identification of system performance and can serve as an input for improving the location-allocation of stations. The objective of this study is to explore the impact of the expansion of a bicycle-sharing system on the usage of the system. This was conducted for a bicycle-sharing system in Zhongshan (China), using operational usage data of different years following system expansion. To this end, we performed statistical and spatial analyses to examine the changes in both users and system usage between before and after the system expansion. The findings show that there is a big variation in users and aggregate usage following the system expansion. However, the trend in spatial distribution of demand shows no substantial difference over the years, i.e. the same high-demand and low-demand areas appear. There are decreases in demand for some old stations over the years, which can be attributed to either the negative performance of the system or the competition of nearby new stations. Expanding the system not only extends the original users’ ability to reach new areas but also attracts new users to use bike-sharing systems. In the conclusions, we present and discuss the findings, and offer recommendations for the further expansion of system.

Exploring the Spatial-Temporal Characteristics of Traditional Public Bicycle Use in Yancheng, China: A Perspective of Time Series Cluster of Stations

“…There were strong similarities between the three clusters ( Figure 11). Generally, most public bicycle use is short-distance activities according to previous studies [6,33]. In our study, all the clusters generated in most rentals were happened within a one to two km radius of the stations, after which the rental volume was gradually declined.…”

Effects of new dock-less bicycle-sharing programs on cycling: a retrospective study in Shanghai

“…As a strategy for promoting cycling and sustainable transportation overall, public bicycle-sharing programmes (PBSPs) have been introduced in many cities around the world to provide bicycles as a mode of transportation for relatively short trips and to bridge ‘the last mile’ of public transport services 15 16. These PBSPs usually have docking stations where users obtain and return the rental bicycles 17.…”

The public bicycle-sharing scheme in Brisbane, Australia: Evaluating the influence of its introduction on changes in time spent cycling amongst a middle- and older-age population

“…Fishman et al, 2015;2014a;Bachand-Marleau et al, 2012;Buck andBuehler, 2012, Daddio, 2012;Wang et al, 2016;Rixey, 2013;Nair et al, 2013;Hampshire and Marla, 2012;Fuller et al, 2011). BSS stations located in the city centre and on the university campus generally have high ridership (Mattson and Godavarthy, 2017;Zhang et al, 2016). Docking station density and population size are positively associated with the use of BSS (Médard de Chardon et al, 2017).…”