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Understanding the influencing factors of bicycle-sharing demand based on residents’ trips

Author

Listed:
  • Hu, Beibei
  • Zhong, Zhenfang
  • Zhang, Yanli
  • Sun, Yue
  • Jiang, Li
  • Dong, Xianlei
  • Sun, Huijun

Abstract

Bicycle-sharing is an eco-friendly transportation operating model in the context of “Internet Plus” and the sharing economy. It not only meets the short-distance travel needs of residents but has great significance for promoting the sustainable development of urban public transportation. However, a series of problems have appeared in the bicycle-sharing market, such as unreasonable resource allocation, low operating efficiency and management difficulties. Based on booking data and GPS trajectory data in Beijing of Mobike, this paper statistically analyzes the spatial and temporal distribution characteristics of residents’ bicycle-sharing trips. Then, we construct a multi-factor influence model of bicycle-sharing demand based on a negative binomial regression and variable selection model, which quantifies a series of factors that influence bicycle-sharing trips, such as population and the regional economy, building land attributes, transportation accessibility, weather, and climatic conditions, etc. The results show that, firstly, there is a spatial imbalance in the distribution of bicycle-sharing demand among different districts in Beijing. Bicycle-sharing demand is mainly concentrated in the six core districts of the city, with more than 80% of all demand. We also find that the bicycle-sharing demand has different distribution characteristics on working days and nonworking days. Compared with nonworking days, residents’ demand for bicycle-sharing on weekdays shows obvious peak periods in the morning, noon, and evening. Secondly, factors that have a major impact on the demand for bicycle-sharing include: per capita disposable income, pass facilities, parking lots etc. Among them, factors such as per capita disposable income, pass facilities, parking lots and bus/subway stations have a significant positive influence on bicycle-sharing demand. However, the number of functional zones such as airports, ports and marinas, tourist attraction and automobile sales has a significant negative influence. In addition, a comfortable temperature and good air quality encourage residents to use bicycle-sharing more for travel, while high humidity is not conducive to bicycle-sharing. We suggest that companies and related departments should jointly participate in the regulation and management of the bicycle-sharing industry, in various aspects such as bicycle scheduling, bicycle management and industry systems. In this way, cities can allocate bicycle-sharing resources reasonably and improve overall operating efficiency. The advantages of bicycle-sharing can be better used to promote the sustainable development of urban public transportation in the future.

Suggested Citation

  • Hu, Beibei & Zhong, Zhenfang & Zhang, Yanli & Sun, Yue & Jiang, Li & Dong, Xianlei & Sun, Huijun, 2022. "Understanding the influencing factors of bicycle-sharing demand based on residents’ trips," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
  • Handle: RePEc:eee:phsmap:v:586:y:2022:i:c:s0378437121007457
    DOI: 10.1016/j.physa.2021.126472
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    References listed on IDEAS

    as
    1. Szeto, W.Y. & Shui, C.S., 2018. "Exact loading and unloading strategies for the static multi-vehicle bike repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 176-211.
    2. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    3. Lu-Yi Qiu & Ling-Yun He, 2018. "Bike Sharing and the Economy, the Environment, and Health-Related Externalities," Sustainability, MDPI, vol. 10(4), pages 1-10, April.
    4. Shaheen, Susan & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present, and Future," Institute of Transportation Studies, Working Paper Series qt79v822k5, Institute of Transportation Studies, UC Davis.
    5. Xiaolu Zhou, 2015. "Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
    6. Felipe González & Carlos Melo-Riquelme & Louis Grange, 2016. "A combined destination and route choice model for a bicycle sharing system," Transportation, Springer, vol. 43(3), pages 407-423, May.
    7. Martin, Elliot W. & Shaheen, Susan A., 2014. "Evaluating public transit modal shift dynamics in response to bikesharing: a tale of two U.S. cities," Journal of Transport Geography, Elsevier, vol. 41(C), pages 315-324.
    8. Martin, Elliot PhD & Shaheen, Susan PhD, 2014. "Evaluating Public Transit Modal Shift Dynamics In Response to Bikesharing: A Tale of Two U.S. Cities," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6x29n876, Institute of Transportation Studies, UC Berkeley.
    9. Jia Shu & Mabel C. Chou & Qizhang Liu & Chung-Piaw Teo & I-Lin Wang, 2013. "Models for Effective Deployment and Redistribution of Bicycles Within Public Bicycle-Sharing Systems," Operations Research, INFORMS, vol. 61(6), pages 1346-1359, December.
    10. Ho, Sin C. & Szeto, W.Y., 2014. "Solving a static repositioning problem in bike-sharing systems using iterated tabu search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 180-198.
    11. Li, Weibo & Kamargianni, Maria, 2018. "Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 277-291.
    12. Sun, Lishan & Wang, Shunchao & Liu, Shuli & Yao, Liya & Luo, Wei & Shukla, Ashish, 2018. "A completive research on the feasibility and adaptation of shared transportation in mega-cities – A case study in Beijing," Applied Energy, Elsevier, vol. 230(C), pages 1014-1033.
    13. Mateo-Babiano, Iderlina & Bean, Richard & Corcoran, Jonathan & Pojani, Dorina, 2016. "How does our natural and built environment affect the use of bicycle sharing?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 295-307.
    14. Wafic El-Assi & Mohamed Salah Mahmoud & Khandker Nurul Habib, 2017. "Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto," Transportation, Springer, vol. 44(3), pages 589-613, May.
    15. Kyle Gebhart & Robert Noland, 2014. "The impact of weather conditions on bikeshare trips in Washington, DC," Transportation, Springer, vol. 41(6), pages 1205-1225, November.
    16. Roma, Paolo & Perrone, Giovanni, 2016. "Cooperation among competitors: A comparison of cost-sharing mechanisms," International Journal of Production Economics, Elsevier, vol. 180(C), pages 172-182.
    17. Osama, Ahmed & Sayed, Tarek & Bigazzi, Alexander Y., 2017. "Models for estimating zone-level bike kilometers traveled using bike network, land use, and road facility variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 14-28.
    18. Bergström, A. & Magnusson, R., 2003. "Potential of transferring car trips to bicycle during winter," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(8), pages 649-666, October.
    19. Shaheen, Susan A & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present and Future," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6qg8q6ft, Institute of Transportation Studies, UC Berkeley.
    20. Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
    21. Noland, Robert B. & Smart, Michael J. & Guo, Ziye, 2016. "Bikeshare trip generation in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 164-181.
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    2. Li, Lili & Li, Xiaohan & Yu, Senbin & Li, Xiaojia & Dai, Jiaqi, 2022. "Unbalanced usage of free-floating bike sharing connecting with metro stations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

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