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

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  • 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
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    References listed on IDEAS

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    1. Karst T. Geurs & Roberto Patuelli & Tomaz Ponce Dentinho (ed.), 2016. "Accessibility, Equity and Efficiency," Books, Edward Elgar Publishing, number 16534, March.
    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 LLC, 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.
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    Cited by:

    1. 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.
    2. Angela Hsiang Ling Chen & Kuangnen Cheng & Wan-Ju Chang, 2023. "Unravelling commuters' modal splitting behaviour in mass transportation service operation," Public Transport, Springer, vol. 15(3), pages 813-838, October.
    3. 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.

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