IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i4p1426-d320852.html
   My bibliography  Save this article

Use Frequency of Metro–Bikeshare Integration: Evidence from Nanjing, China

Author

Listed:
  • Yang Liu

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Southeast University Road 2, Nanjing 211189, China)

  • Yanjie Ji

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Southeast University Road 2, Nanjing 211189, China)

  • Tao Feng

    (Department of Urban Science and Systems, Eindhoven University of Technology, P.O.Box 513, 5600MB Eindhoven, The Netherlands)

  • Zhuangbin Shi

    (Intelligent Transportation System Research Center, Southeast University, Southeast University Road 2, Nanjing 211189, China)

Abstract

Promoting a transition in individuals’ travel mode from car to an integrated metro and bikeshare systems is expected to effectively reduce the traffic congestion that results mainly from commute trips performed by individual automobiles. This paper focuses on the use frequency of an integrated metro–bikeshare by individuals, and presents empirical evidence from Nanjing, China. Using one-week GPS data collected from the Mobike company, the spatiotemporal characteristics of origin/destination for cyclists who would likely to use shared bike as a feeder mode to metro are examined. Three areas of travel-related spatiotemporal information were extracted including (1) the distribution of walking distances between metro stations and shared bike parking lots; (2) the distribution of cycling times between origins/destinations and metro stations; and (3) the times when metro–bikeshare users pick up/drop off shared bikes to transfer to/from a metro. Incorporating these three features into a questionnaire design, an intercept survey of possible factors on the use of the combined mode was conducted at seven functional metro stations. An ordered logistic regression model was used to examine the significant factors that influence groupings of metro passengers. Results showed that the high-, medium- and low-frequency groups of metro–bikeshare users accounted for 9.92%, 21.98% and 68.1%, respectively. Education, individual income, travel purpose, travel time on the metro, workplace location and bike lane infrastructure were found to have significant impacts on metro passengers’ use frequency of integrated metro–bikeshares. Relevant policies and interventions for metro passengers of Nanjing are proposed to encourage the integration of metro and bikeshare systems.

Suggested Citation

  • Yang Liu & Yanjie Ji & Tao Feng & Zhuangbin Shi, 2020. "Use Frequency of Metro–Bikeshare Integration: Evidence from Nanjing, China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1426-:d:320852
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/4/1426/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/4/1426/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karst T. Geurs & Roberto Patuelli & Tomaz Ponce Dentinho (ed.), 2016. "Accessibility, Equity and Efficiency," Books, Edward Elgar Publishing, number 16534.
    2. Krygsman, Stephan & Dijst, Martin & Arentze, Theo, 2004. "Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio," Transport Policy, Elsevier, vol. 11(3), pages 265-275, July.
    3. Richard Williams, 2006. "Generalized ordered logit/partial proportional odds models for ordinal dependent variables," Stata Journal, StataCorp LP, vol. 6(1), pages 58-82, March.
    4. Lara Engelfriet & Eric Koomen, 2018. "The impact of urban form on commuting in large Chinese cities," Transportation, Springer, vol. 45(5), pages 1269-1295, September.
    5. Zuo, Ting & Wei, Heng & Rohne, Andrew, 2018. "Determining transit service coverage by non-motorized accessibility to transit: Case study of applying GPS data in Cincinnati metropolitan area," Journal of Transport Geography, Elsevier, vol. 67(C), pages 1-11.
    6. Karst T. Geurs & Tomaz Ponce Dentinho & Roberto Patuelli, 2016. "Accessibility, equity and efficiency," Chapters, in: Karst T. Geurs & Roberto Patuelli & Tomaz Ponce Dentinho (ed.), Accessibility, Equity and Efficiency, chapter 1, pages 3-8, Edward Elgar Publishing.
    7. 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.
    8. Zhao, Jinbao & Deng, Wei & Song, Yan, 2014. "Ridership and effectiveness of bikesharing: The effects of urban features and system characteristics on daily use and turnover rate of public bikes in China," Transport Policy, Elsevier, vol. 35(C), pages 253-264.
    9. Yanjie Ji & Xinwei Ma & Mingyuan Yang & Yuchuan Jin & Liangpeng Gao, 2018. "Exploring Spatially Varying Influences on Metro-Bikeshare Transfer: A Geographically Weighted Poisson Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
    10. Shelat, Sanmay & Huisman, Raymond & van Oort, Niels, 2018. "Analysing the trip and user characteristics of the combined bicycle and transit mode," Research in Transportation Economics, Elsevier, vol. 69(C), pages 68-76.
    11. 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.
    12. Cheng, Yung-Hsiang & Liu, Kuo-Chu, 2012. "Evaluating bicycle-transit users’ perceptions of intermodal inconvenience," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1690-1706.
    13. Zhao, Pengjun & Li, Shengxiao, 2017. "Bicycle-metro integration in a growing city: The determinants of cycling as a transfer mode in metro station areas in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 46-60.
    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. Dehdari Ebrahimi, Zhila & Momenitabar, Mohsen & Nasri, Arefeh A. & Mattson, Jeremy, 2022. "Using a GIS-based spatial approach to determine the optimal locations of bikeshare stations: The case of Washington D.C," Transport Policy, Elsevier, vol. 127(C), pages 48-60.
    2. Radzimski, Adam & Dzięcielski, Michał, 2021. "Exploring the relationship between bike-sharing and public transport in Poznań, Poland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 189-202.

    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. Ying Ni & Jiaqi Chen, 2020. "Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    2. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    3. Xinwei Ma & Yanjie Ji & Yuchuan Jin & Jianbiao Wang & Mingjia He, 2018. "Modeling the Factors Influencing the Activity Spaces of Bikeshare around Metro Stations: A Spatial Regression Model," Sustainability, MDPI, vol. 10(11), pages 1-12, October.
    4. Li, Wenxiang & Chen, Shawen & Dong, Jieshuang & Wu, Jingxian, 2021. "Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros," Journal of Transport Geography, Elsevier, vol. 92(C).
    5. 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.
    6. Zijia Wang & Lei Cheng & Yongxing Li & Zhiqiang Li, 2020. "Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    7. Lidong Zhu & Mujahid Ali & Elżbieta Macioszek & Mahdi Aghaabbasi & Amin Jan, 2022. "Approaching Sustainable Bike-Sharing Development: A Systematic Review of the Influence of Built Environment Features on Bike-Sharing Ridership," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    8. Samuel Nello-Deakin & Marco te Brömmelstroet, 2021. "Scaling up cycling or replacing driving? Triggers and trajectories of bike–train uptake in the Randstad area," Transportation, Springer, vol. 48(6), pages 3239-3267, December.
    9. Xueying Wu & Yi Lu & Yaoyu Lin & Yiyang Yang, 2019. "Measuring the Destination Accessibility of Cycling Transfer Trips in Metro Station Areas: A Big Data Approach," IJERPH, MDPI, vol. 16(15), pages 1-16, July.
    10. Zhan, Zilin & Guo, Yuanyuan & Noland, Robert B. & He, Sylvia Y. & Wang, Yacan, 2023. "Analysis of links between dockless bikeshare and metro trips in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    11. Liu, Yang & Feng, Tao & Shi, Zhuangbin & He, Mingwei, 2022. "Understanding the route choice behaviour of metro-bikeshare users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 460-475.
    12. Wu, Xueying & Lu, Yi & Gong, Yongxi & Kang, Yuhao & Yang, Linchuan & Gou, Zhonghua, 2021. "The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space," Journal of Transport Geography, Elsevier, vol. 97(C).
    13. Yanjie Ji & Xinwei Ma & Mingyuan Yang & Yuchuan Jin & Liangpeng Gao, 2018. "Exploring Spatially Varying Influences on Metro-Bikeshare Transfer: A Geographically Weighted Poisson Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
    14. Zhao, Pengjun & Li, Shengxiao, 2017. "Bicycle-metro integration in a growing city: The determinants of cycling as a transfer mode in metro station areas in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 46-60.
    15. Yongjun Shen & Qiong Bao & Elke Hermans, 2020. "Applying an Alternative Approach for Assessing Sustainable Road Transport: A Benchmarking Analysis on EU Countries," Sustainability, MDPI, vol. 12(24), pages 1-16, December.
    16. Daniela- Luminița CONSTANTIN & Corina- Cristiana NASTACĂ & Emilia GEAMBASU, 2021. "Population Accessibility To Rail Services. Insights Through The Lens Of Territorial Cohesion," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 81-98, June.
    17. Gan, Zuoxian & Yang, Min & Zeng, Qingcheng & Timmermans, Harry J.P., 2021. "Associations between built environment, perceived walkability/bikeability and metro transfer patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 171-187.
    18. Cheng, Long & Huang, Jie & Jin, Tanhua & Chen, Wendong & Li, Aoyong & Witlox, Frank, 2023. "Comparison of station-based and free-floating bikeshare systems as feeder modes to the metro," Journal of Transport Geography, Elsevier, vol. 107(C).
    19. Kumar Dey, Bibhas & Anowar, Sabreena & Eluru, Naveen, 2021. "A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 119-133.
    20. Anders Larsson & Jerry Olsson, 2017. "Potentials and limitations for the use of accessibility measures for national transport policy goals in freight transport and logistics: evidence from Västra Götaland County, Sweden," REGION, European Regional Science Association, vol. 4, pages 71-92.

    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:12:y:2020:i:4:p:1426-:d:320852. 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.