IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i11p8710-d1157903.html
   My bibliography  Save this article

Exploring Influential Factors of Free-Floating Bike-Sharing Usage Frequency before and after COVID-19

Author

Listed:
  • Xinyi Xie

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Mingyang Du

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Xuefeng Li

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
    School of Transportation, Southeast University, Nanjing 211189, China)

  • Yunjian Jiang

    (Zhejiang Scientific Research Institute of Transport, Hangzhou 310023, China)

Abstract

In order to better understand the impact of COVID-19 on the free-floating bike-sharing (FFBS) system and the potential role of FFBS played in the pandemic period, this study explores the impact mechanism of travel frequency of FFBS users before and after the pandemic. Using the online questionnaire collected in Nanjing, China, we first analyze the changes of travel frequency, travel distance, and travel duration in these two periods. Then, two ordered logit models are applied to explore the contributing factors of the weekly trip frequency of FFBS users before and after COVID-19. The results show that: (1) While the overall travel duration and travel distance of FFBS users decreased after the pandemic, the trip frequency of FFBS users increased as the travel duration increased. (2) Since COVID-19, attitude perception variables of the comfort level and the low travel price have had significantly positive impacts on the weekly trip frequency of FFBS users. (3) Respondents who use FFBS as a substitution for public transport are more likely to travel frequently in a week after the outbreak of COVID-19. (4) The travel time in off-peak hours of working days, weekends, and holidays has a significantly positive correlation with the trip frequency of FFBS users. Finally, several relevant policy recommendations and management strategies are proposed for the operation and development of FFBS during the similar disruptive public health crisis.

Suggested Citation

  • Xinyi Xie & Mingyang Du & Xuefeng Li & Yunjian Jiang, 2023. "Exploring Influential Factors of Free-Floating Bike-Sharing Usage Frequency before and after COVID-19," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8710-:d:1157903
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/11/8710/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/11/8710/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Teixeira, João Filipe & Silva, Cecília & Moura e Sá, Frederico, 2022. "The strengths and weaknesses of bike sharing as an alternative mode during disruptive public health crisis: A qualitative analysis on the users’ motivations during COVID-19," Transport Policy, Elsevier, vol. 129(C), pages 24-37.
    2. Du, Mingyang & Cheng, Lin & Li, Xuefeng & Tang, Fang, 2020. "Static rebalancing optimization with considering the collection of malfunctioning bikes in free-floating bike sharing system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    3. Xiaohong Jiang & Ting Tang & Luhui Sun & Tengfei Lin & Xuan Duan & Xiucheng Guo, 2020. "Research on Consumers’ Preferences for the Self-Service Mode of Express Cabinets in Stations Based on the Subway Distribution to Promote Sustainability," Sustainability, MDPI, vol. 12(17), pages 1-20, September.
    4. Büchel, Beda & Marra, Alessio Daniele & Corman, Francesco, 2022. "COVID-19 as a window of opportunity for cycling: Evidence from the first wave," Transport Policy, Elsevier, vol. 116(C), pages 144-156.
    5. Wang, Haoyun & Noland, Robert B., 2021. "Bikeshare and subway ridership changes during the COVID-19 pandemic in New York City," Transport Policy, Elsevier, vol. 106(C), pages 262-270.
    6. Mingyang Du & Lin Cheng & Xuefeng Li & Jingzong Yang, 2019. "Investigating the Influential Factors of Shared Travel Behavior: Comparison between App-Based Third Taxi Service and Free-Floating Bike Sharing in Nanjing, China," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    7. Filipe Teixeira, João & Silva, Cecília & Moura e Sá, Frederico, 2022. "The role of bike sharing during the coronavirus pandemic: An analysis of the mobility patterns and perceptions of Lisbon’s GIRA users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 17-34.
    8. Bergantino, Angela Stefania & Intini, Mario & Tangari, Luca, 2021. "Influencing factors for potential bike-sharing users: an empirical analysis during the COVID-19 pandemic," Research in Transportation Economics, Elsevier, vol. 86(C).
    9. Zhang, Bin & Chen, Shuyan & Ma, Yongfeng & Li, Tiezhu & Tang, Kun, 2020. "Analysis on spatiotemporal urban mobility based on online car-hailing data," Journal of Transport Geography, Elsevier, vol. 82(C).
    10. Mingyang Du & Lin Cheng, 2018. "Better Understanding the Characteristics and Influential Factors of Different Travel Patterns in Free-Floating Bike Sharing: Evidence from Nanjing, China," Sustainability, MDPI, vol. 10(4), pages 1-14, April.
    11. Shang, Wen-Long & Chen, Jinyu & Bi, Huibo & Sui, Yi & Chen, Yanyan & Yu, Haitao, 2021. "Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis," Applied Energy, Elsevier, vol. 285(C).
    12. Carroll, James & Brazil, William & Morando, Bruno & Denny, Eleanor, 2020. "What drives the gender-cycling-gap? Census analysis from Ireland," Transport Policy, Elsevier, vol. 97(C), pages 95-102.
    13. Wei Yu & Hua Bai & Jun Chen & Xingchen Yan, 2019. "Analysis of Space-Time Variation of Passenger Flow and Commuting Characteristics of Residents Using Smart Card Data of Nanjing Metro," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    14. Li, Haojie & Zhang, Yingheng & Zhu, Manman & Ren, Gang, 2021. "Impacts of COVID-19 on the usage of public bicycle share in London," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 140-155.
    15. Lan Wu & Qi Shen & Gen Li, 2022. "Identifying Risk Factors for Autos and Trucks on Highway-Railroad Grade Crossings Based on Mixed Logit Model," IJERPH, MDPI, vol. 19(22), pages 1-13, November.
    16. Hu, Songhua & Xiong, Chenfeng & Liu, Zhanqin & Zhang, Lei, 2021. "Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic," Journal of Transport Geography, Elsevier, vol. 91(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Xinwei & Zhang, Shuai & Wu, Tao & Yang, Yizhe & Yu, Jiajie, 2023. "Can dockless and docked bike-sharing substitute each other? Evidence from Nanjing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lucia Rotaris & Mario Intini & Alessandro Gardelli, 2022. "Impacts of the COVID-19 Pandemic on Bike-Sharing: A Literature Review," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    2. Song, Jie & Zhang, Liye & Qin, Zheng & Ramli, Muhamad Azfar, 2022. "Spatiotemporal evolving patterns of bike-share mobility networks and their associations with land-use conditions before and after the COVID-19 outbreak," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    3. Zhang, Xiang & Li, Wence, 2023. "Effects of a bike sharing system and COVID-19 on low-carbon traffic modal shift and emission reduction," Transport Policy, Elsevier, vol. 132(C), pages 42-64.
    4. Ma, Xinwei & Zhang, Shuai & Wu, Tao & Yang, Yizhe & Yu, Jiajie, 2023. "Can dockless and docked bike-sharing substitute each other? Evidence from Nanjing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    5. Teixeira, João Filipe & Silva, Cecília & Moura e Sá, Frederico, 2023. "Factors influencing modal shift to bike sharing: Evidence from a travel survey conducted during COVID-19," Journal of Transport Geography, Elsevier, vol. 111(C).
    6. Jiang, Shixiong & Cai, Canhuang, 2022. "Unraveling the dynamic impacts of COVID-19 on metro ridership: An empirical analysis of Beijing and Shanghai, China," Transport Policy, Elsevier, vol. 127(C), pages 158-170.
    7. Dongdong Feng & Lin Cheng & Mingyang Du, 2020. "Exploring the Impact of Dockless Bikeshare on Docked Bikeshare—A Case Study in London," Sustainability, MDPI, vol. 12(15), pages 1-18, July.
    8. Teixeira, João Filipe & Silva, Cecília & Moura e Sá, Frederico, 2022. "The strengths and weaknesses of bike sharing as an alternative mode during disruptive public health crisis: A qualitative analysis on the users’ motivations during COVID-19," Transport Policy, Elsevier, vol. 129(C), pages 24-37.
    9. Filipe Teixeira, João & Silva, Cecília & Moura e Sá, Frederico, 2022. "The role of bike sharing during the coronavirus pandemic: An analysis of the mobility patterns and perceptions of Lisbon’s GIRA users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 17-34.
    10. Meng, Xin & Guo, Mingxue & Gao, Ziyou & Kang, Liujiang, 2023. "Interaction between travel restriction policies and the spread of COVID-19," Transport Policy, Elsevier, vol. 136(C), pages 209-227.
    11. Xiaoyu Zhang & Chunfu Shao & Bobin Wang & Shichen Huang, 2022. "The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China," IJERPH, MDPI, vol. 19(12), pages 1-19, June.
    12. Shahram Heydari & Garyfallos Konstantinoudis & Abdul Wahid Behsoodi, 2021. "Effect of the COVID-19 pandemic on bike-sharing demand and hire time: Evidence from Santander Cycles in London," Papers 2107.11589, arXiv.org.
    13. Goh, Hyewon & Choi, Gahyun & Song, Yena, 2023. "How the COVID-19 pandemic changed travel behaviour? A case study on public bikes in Seoul," Research in Transportation Economics, Elsevier, vol. 101(C).
    14. Shirgaokar, Manish & Reynard, Darcy & Collins, Damian, 2021. "Using twitter to investigate responses to street reallocation during COVID-19: Findings from the U.S. and Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 300-312.
    15. Elif Bozkaya & Levent Eriskin & Mumtaz Karatas, 2023. "Data analytics during pandemics: a transportation and location planning perspective," Annals of Operations Research, Springer, vol. 328(1), pages 193-244, September.
    16. Choi, Seung Jun & Jiao, Junfeng & Lee, Hye Kyung & Farahi, Arya, 2023. "Combatting the mismatch: Modeling bike-sharing rental and return machine learning classification forecast in Seoul, South Korea," Journal of Transport Geography, Elsevier, vol. 109(C).
    17. Zhao, Zhiyuan & Yao, Wei & Wu, Sheng & Yang, Xiping & Wu, Qunyong & Fang, Zhixiang, 2023. "Identifying the collaborative scheduling areas between ride-hailing and traditional taxi services based on vehicle trajectory data," Journal of Transport Geography, Elsevier, vol. 107(C).
    18. 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).
    19. Shuanfeng Zhao & Chao Wang & Pei Wei & Qingqing Zhao, 2020. "Research on the Deep Recognition of Urban Road Vehicle Flow Based on Deep Learning," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
    20. Gu, Tianqi & Kim, Inhi & Currie, Graham, 2019. "To be or not to be dockless: Empirical analysis of dockless bikeshare development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 122-147.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8710-:d:1157903. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.