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

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  • Ying Zhang
  • Tom Thomas
  • M J G Brussel
  • M F A M van Maarseveen

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.

Suggested Citation

  • Ying Zhang & Tom Thomas & M J G Brussel & M F A M van Maarseveen, 2016. "Expanding Bicycle-Sharing Systems: Lessons Learnt from an Analysis of Usage," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-25, December.
  • Handle: RePEc:plo:pone00:0168604
    DOI: 10.1371/journal.pone.0168604
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    References listed on IDEAS

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    1. O’Brien, Oliver & Cheshire, James & Batty, Michael, 2014. "Mining bicycle sharing data for generating insights into sustainable transport systems," Journal of Transport Geography, Elsevier, vol. 34(C), pages 262-273.
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    2. Liu, Junrong & Duan, Qihong & Ma, Wen-Xiu, 2020. "The evolution of a clogging sidewalk caused by a dockless bicycle-sharing system: A stochastic particles model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 516-526.
    3. Suzanne Maas & Paraskevas Nikolaou & Maria Attard & Loukas Dimitriou, 2021. "Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands," Sustainability, MDPI, vol. 13(6), pages 1-21, March.
    4. Zhan Gao & Sheng Wei & Lei Wang & Sijia Fan, 2020. "Exploring the Spatial-Temporal Characteristics of Traditional Public Bicycle Use in Yancheng, China: A Perspective of Time Series Cluster of Stations," Sustainability, MDPI, vol. 12(16), pages 1-17, August.
    5. Yuyan Gao & David C. Schwebel & Lingling Zhang & Wangxin Xiao & Guoqing Hu, 2020. "Unsafe Bicycling Behavior in Changsha, China: A Video-Based Observational Study," IJERPH, MDPI, vol. 17(9), pages 1-10, May.
    6. Jain, Taru & Wang, Xinyi & Rose, Geoffrey & Johnson, Marilyn, 2018. "Does the role of a bicycle share system in a city change over time? A longitudinal analysis of casual users and long-term subscribers," Journal of Transport Geography, Elsevier, vol. 71(C), pages 45-57.
    7. Schimohr, Katja & Scheiner, Joachim, 2021. "Spatial and temporal analysis of bike-sharing use in Cologne taking into account a public transit disruption," Journal of Transport Geography, Elsevier, vol. 92(C).
    8. Tae San Kim & Won Kyung Lee & So Young Sohn, 2019. "Graph convolutional network approach applied to predict hourly bike-sharing demands considering spatial, temporal, and global effects," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-16, September.
    9. Lovelace, Robin & Beecham, Roger & Heinen, Eva & Vidal Tortosa, Eugeni & Yang, Yuanxuan & Slade, Chris & Roberts, Antonia, 2020. "Is the London Cycle Hire Scheme becoming more inclusive? An evaluation of the shifting spatial distribution of uptake based on 70 million trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 1-15.

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