IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i16p9265-d616801.html
   My bibliography  Save this article

Public’s Intention and Influencing Factors of Dockless Bike-Sharing in Central Urban Areas: A Case Study of Lanzhou City, China

Author

Listed:
  • Wei Ji

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Chengpeng Lu

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Jinhuang Mao

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Yiping Liu

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China)

  • Muchen Hou

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

  • Xiaoli Pan

    (Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
    School of Economics, Lanzhou University, Lanzhou 730000, China)

Abstract

Taking the main district in Lanzhou city of China as an example, the questionnaires were designed and distributed, and then the effects of five factors, i.e., behavioral attitude, subjective norm, perceived behavioral control, perceived ease of use and perceived usefulness, on the behavioral intention of dockless bike-sharing (DBS) use were empirically analyzed based on the integrated model of technology acceptance model (TAM) and the theory of planned behavior (TPB) as well as the structural equation model. Results show that the five factors all impose significantly positive effects on the public’s behavioral intention of DBS use but differ in influencing degrees. Behavioral attitude, subjective norm and perceived behavioral control can all directly affect the public’s behavioral intention of DBS use, with direct influence coefficients of 0.691, 0.257 and 0.198, while perceived ease of use and perceived usefulness impose indirectly effects on behavioral intention, with indirect influence coefficients of 0.372 and 0.396. Overall, behavioral attitude imposes the most significant effect, followed by perceived ease of use, perceived usefulness and subjective norm, and finally perceived behavioral control. This indicates that the public’s behavioral intention of DBS use depends heavily on their behavioral attitude towards the shared bikes. In view of the limited open space of the main district in Lanzhou, the explosive growth of shared bikes, oversaturated arrangements, disordered competition, unclear and unscientific divisions of parking regions, and hindrance of traffic, this study proposes a lot of policy suggestions from the research results. A series of supporting service systems related to DBS should be formulated. The shared bikes with different characteristics should be launched for different age groups, gender groups and work groups. The corresponding feedback platform for realtime acquisition, organization, analysis and solution of data information, as well as the adequate platform feedback mechanism, should be established.

Suggested Citation

  • Wei Ji & Chengpeng Lu & Jinhuang Mao & Yiping Liu & Muchen Hou & Xiaoli Pan, 2021. "Public’s Intention and Influencing Factors of Dockless Bike-Sharing in Central Urban Areas: A Case Study of Lanzhou City, China," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9265-:d:616801
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/16/9265/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/16/9265/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Böcker, Lars & Anderson, Ellinor & Uteng, Tanu Priya & Throndsen, Torstein, 2020. "Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 389-401.
    2. Peter Newton & Denny Meyer, 2013. "Exploring the Attitudes-Action Gap in Household Resource Consumption: Does “Environmental Lifestyle” Segmentation Align with Consumer Behaviour?," Sustainability, MDPI, vol. 5(3), pages 1-23, March.
    3. Lin, Jenn-Rong & Yang, Ta-Hui, 2011. "Strategic design of public bicycle sharing systems with service level constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(2), pages 284-294, March.
    4. Han, Sun Sheng, 2020. "The spatial spread of dockless bike-sharing programs among Chinese cities," Journal of Transport Geography, Elsevier, vol. 86(C).
    5. 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.
    6. Médard de Chardon, Cyrille & Caruso, Geoffrey, 2015. "Estimating bike-share trips using station level data," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 260-279.
    7. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    8. Xiaojia Guo & Chengpeng Lu & Dongqi Sun & Yexin Gao & Bing Xue, 2021. "Comparison of Usage and Influencing Factors between Governmental Public Bicycles and Dockless Bicycles in Linfen City, China," Sustainability, MDPI, vol. 13(12), pages 1-14, June.
    9. Kyung Hwan Lee & Eun Jeong Ko, 2014. "Relationships between neighbourhood environments and residents' bicycle mode choice: a case study of Seoul," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 18(3), pages 383-395, November.
    10. 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.
    11. Faghih-Imani, Ahmadreza & Eluru, Naveen & El-Geneidy, Ahmed M. & Rabbat, Michael & Haq, Usama, 2014. "How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal," Journal of Transport Geography, Elsevier, vol. 41(C), pages 306-314.
    12. Xing, Yingying & Wang, Ke & Lu, Jian John, 2020. "Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 87(C).
    13. Vogel, Marie & Hamon, Ronan & Lozenguez, Guillaume & Merchez, Luc & Abry, Patrice & Barnier, Julien & Borgnat, Pierre & Flandrin, Patrick & Mallon, Isabelle & Robardet, Céline, 2014. "From bicycle sharing system movements to users: a typology of Vélo’v cyclists in Lyon based on large-scale behavioural dataset," Journal of Transport Geography, Elsevier, vol. 41(C), pages 280-291.
    14. Kaplan, Sigal & Manca, Francesco & Nielsen, Thomas Alexander Sick & Prato, Carlo Giacomo, 2015. "Intentions to use bike-sharing for holiday cycling: An application of the Theory of Planned Behavior," Tourism Management, Elsevier, vol. 47(C), pages 34-46.
    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. Ruiwei Li & Gobi Krishna Sinniah & Xiangyu Li, 2022. "The Factors Influencing Resident’s Intentions on E-Bike Sharing Usage in China," Sustainability, MDPI, vol. 14(9), pages 1-15, April.

    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. Mix, Richard & Hurtubia, Ricardo & Raveau, Sebastián, 2022. "Optimal location of bike-sharing stations: A built environment and accessibility approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 126-142.
    2. Caulfield, Brian & O'Mahony, Margaret & Brazil, William & Weldon, Peter, 2017. "Examining usage patterns of a bike-sharing scheme in a medium sized city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 152-161.
    3. Faghih-Imani, Ahmadreza & Hampshire, Robert & Marla, Lavanya & Eluru, Naveen, 2017. "An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 177-191.
    4. Zhang, Ying & Thomas, Tom & Brussel, Mark & van Maarseveen, Martin, 2017. "Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China," Journal of Transport Geography, Elsevier, vol. 58(C), pages 59-70.
    5. Médard de Chardon, Cyrille & Caruso, Geoffrey & Thomas, Isabelle, 2017. "Bicycle sharing system ‘success’ determinants," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 202-214.
    6. Kyoungok Kim, 2024. "Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul," Transportation, Springer, vol. 51(4), pages 1373-1407, August.
    7. Elżbieta Macioszek & Paulina Świerk & Agata Kurek, 2020. "The Bike-Sharing System as an Element of Enhancing Sustainable Mobility—A Case Study based on a City in Poland," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
    8. 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).
    9. Médard de Chardon, Cyrille & Caruso, Geoffrey, 2015. "Estimating bike-share trips using station level data," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 260-279.
    10. De Zhao & Ghim Ping Ong & Wei Wang & Wei Zhou, 2021. "Estimating Public Bicycle Trip Characteristics with Consideration of Built Environment Data," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    11. Wang, Ruoxuan & Wu, Jianping & Qi, Geqi, 2022. "Exploring regional sustainable commuting patterns based on dockless bike-sharing data and POI data," Journal of Transport Geography, Elsevier, vol. 102(C).
    12. Alimo, Philip Kofi & Agyeman, Stephen & Danesh, Ali & Yu, Chunhui & Ma, Wanjing, 2023. "Is public bike-sharing feasible in Ghana? Road users' perceptions and policy interventions," Journal of Transport Geography, Elsevier, vol. 106(C).
    13. 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.
    14. Wang, Jueyu & Lindsey, Greg, 2019. "Neighborhood socio-demographic characteristics and bike share member patterns of use," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    15. 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).
    16. Chen, Shang-Yu, 2016. "Using the sustainable modified TAM and TPB to analyze the effects of perceived green value on loyalty to a public bike system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 58-72.
    17. Zhao, De & Ong, Ghim Ping & Wang, Wei & Hu, Xiao Jian, 2019. "Effect of built environment on shared bicycle reallocation: A case study on Nanjing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 73-88.
    18. 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.
    19. Pengfei Lin & Jiancheng Weng & Quan Liang & Dimitrios Alivanistos & Siyong Ma, 2020. "Impact of Weather Conditions and Built Environment on Public Bikesharing Trips in Beijing," Networks and Spatial Economics, Springer, vol. 20(1), pages 1-17, March.
    20. Zhou, Xiaolu & Wang, Mingshu & Li, Dongying, 2019. "Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.

    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:13:y:2021:i:16:p:9265-:d:616801. 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.