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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.
    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. 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).
    11. 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).
    12. 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.
    13. 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).
    14. 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.
    15. 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.
    16. 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.
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