IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i5p1526-d145767.html
   My bibliography  Save this article

Exploring Spatially Varying Influences on Metro-Bikeshare Transfer: A Geographically Weighted Poisson Regression Approach

Author

Listed:
  • Yanjie Ji

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Sipailou 2, Nanjing 210096, China)

  • Xinwei Ma

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Sipailou 2, Nanjing 210096, China)

  • Mingyuan Yang

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Sipailou 2, Nanjing 210096, China)

  • Yuchuan Jin

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Sipailou 2, Nanjing 210096, China)

  • Liangpeng Gao

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Sipailou 2, Nanjing 210096, China)

Abstract

The primary objective of this study was to explore the factors that influence metro-bikeshare ridership from a spatial perspective. First, a reproducible method of identifying metro-bikeshare transfer trips was derived using two types of smart-card data (metro and bikeshare). Next, a geographically weighted Poisson regression (GWPR) model was established to explore the relationships between metro-bikeshare transfer volume and several types of independent variables, including sociodemographic, travel-related, and built-environment variables. Moran’s I statistic was applied to examine the spatial autocorrelation of each explanatory variable. The modeling and spatial visualization results show that riding distance is negatively correlated with metro-bikeshare transfer demand, and the coefficient values are generally lower at the edge of the city, especially in underdeveloped areas. Moreover, the density of bus, bikeshare, and other metro stations within 2 km of a metro station has different impacts on metro-bikeshare transfer volume. Travelers whose origin or destination is entertainment related tend to choose bikeshare as a feeder mode to metro if this trip mode is available to them. These results improve our understanding of metro-bikeshare transfer spatial patterns, and several suggestions are provided for improving the integration between metro and bikeshare.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1526-:d:145767
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/5/1526/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/5/1526/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kerkman, Kasper & Martens, Karel & Meurs, Henk, 2017. "A multilevel spatial interaction model of transit flows incorporating spatial and network autocorrelation," Journal of Transport Geography, Elsevier, vol. 60(C), pages 155-166.
    2. Fan, Yingling & Guthrie, Andrew & Levinson, David, 2016. "Waiting time perceptions at transit stops and stations: Effects of basic amenities, gender, and security," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 251-264.
    3. Yang, Wenyue & Chen, Bi Yu & Cao, Xiaoshu & Li, Tao & Li, Peng, 2017. "The spatial characteristics and influencing factors of modal accessibility gaps: A case study for Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 21-32.
    4. Lu-Yi Qiu & Ling-Yun He, 2018. "Bike Sharing and the Economy, the Environment, and Health-Related Externalities," Sustainability, MDPI, vol. 10(4), pages 1-10, April.
    5. Vandenbulcke, Grégory & Dujardin, Claire & Thomas, Isabelle & Geus, Bas de & Degraeuwe, Bart & Meeusen, Romain & Panis, Luc Int, 2011. "Cycle commuting in Belgium: Spatial determinants and 're-cycling' strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(2), pages 118-137, February.
    6. Jing Lan & Yuge Ma & Dajian Zhu & Diana Mangalagiu & Thomas F. Thornton, 2017. "Enabling Value Co-Creation in the Sharing Economy: The Case of Mobike," Sustainability, MDPI, vol. 9(9), pages 1-20, August.
    7. Maizlish, N. & Woodcock, J. & Co, S. & Ostro, B. & Fanai, A. & Fairley, D., 2013. "Health cobenefits and transportation-related reductions in greenhouse gas emissions in the San Francisco Bay Area," American Journal of Public Health, American Public Health Association, vol. 103(4), pages 703-709.
    8. Bernardo Nugroho Yahya, 2017. "Overall Bike Effectiveness as a Sustainability Metric for Bike Sharing Systems," Sustainability, MDPI, vol. 9(11), pages 1-28, November.
    9. Iacono, Michael & Krizek, Kevin J. & El-Geneidy, Ahmed, 2010. "Measuring non-motorized accessibility: issues, alternatives, and execution," Journal of Transport Geography, Elsevier, vol. 18(1), pages 133-140.
    10. Chiou, Yu-Chiun & Jou, Rong-Chang & Yang, Cheng-Han, 2015. "Factors affecting public transportation usage rate: Geographically weighted regression," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 161-177.
    11. Wang, Yiming & Feng, Suwei & Deng, Zhongwei & Cheng, Shuangyu, 2016. "Transit premium and rent segmentation: A spatial quantile hedonic analysis of Shanghai Metro," Transport Policy, Elsevier, vol. 51(C), pages 61-69.
    12. Shaheen, Susan & Guzman, Stacey & Zhang, Hua, 2012. "Bikesharing across the Globe," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0qm296pf, Institute of Transportation Studies, UC Berkeley.
    13. Mohanty, Sudatta & Bansal, Sugam & Bairwa, Khushi, 2017. "Effect of integration of bicyclists and pedestrians with transit in New Delhi," Transport Policy, Elsevier, vol. 57(C), pages 31-40.
    14. Wafic El-Assi & Mohamed Salah Mahmoud & Khandker Nurul Habib, 2017. "Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto," Transportation, Springer, vol. 44(3), pages 589-613, May.
    15. Yeran Sun & Amin Mobasheri & Xuke Hu & Weikai Wang, 2017. "Investigating Impacts of Environmental Factors on the Cycling Behavior of Bicycle-Sharing Users," Sustainability, MDPI, vol. 9(6), pages 1-12, June.
    16. A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis," Environment and Planning A, , vol. 30(11), pages 1905-1927, November.
    17. Yang, Hongtai & Lu, Xiaozhao & Cherry, Christopher & Liu, Xiaohan & Li, Yanlai, 2017. "Spatial variations in active mode trip volume at intersections: a local analysis utilizing geographically weighted regression," Journal of Transport Geography, Elsevier, vol. 64(C), pages 184-194.
    18. Ranran Yang & Ruyin Long, 2016. "Analysis of the Influencing Factors of the Public Willingness to Participate in Public Bicycle Projects and Intervention Strategies—A Case Study of Jiangsu Province, China," Sustainability, MDPI, vol. 8(4), pages 1-16, April.
    19. 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.
    20. Neal Alexander, 2011. "Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 512-513, April.
    21. Brons, Martijn & Givoni, Moshe & Rietveld, Piet, 2009. "Access to railway stations and its potential in increasing rail use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 136-149, February.
    22. John Pucher & Ralph Buehler, 2017. "Cycling towards a more sustainable transport future," Transport Reviews, Taylor & Francis Journals, vol. 37(6), pages 689-694, November.
    23. Shaheen, Susan PhD & Martin, Elliot PhD & Cohen, Adam, 2013. "Public Bikesharing and Modal Shift Behavior: A Comparative Study of Early Bikesharing Systems in North America," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7010k9p3, Institute of Transportation Studies, UC Berkeley.
    24. 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.
    25. 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.
    26. 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.
    27. Martens, Karel, 2007. "Promoting bike-and-ride: The Dutch experience," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 326-338, May.
    28. Wang, Chih-Hao & Chen, Na, 2017. "A geographically weighted regression approach to investigating the spatially varied built-environment effects on community opportunity," Journal of Transport Geography, Elsevier, vol. 62(C), pages 136-147.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    3. Yuanyuan Zhang & Yuming Zhang, 2018. "Associations between Public Transit Usage and Bikesharing Behaviors in The United States," Sustainability, MDPI, vol. 10(6), pages 1-20, June.
    4. Ma, Xinwei & Ji, Yanjie & Yang, Mingyuan & Jin, Yuchuan & Tan, Xu, 2018. "Understanding bikeshare mode as a feeder to metro by isolating metro-bikeshare transfers from smart card data," Transport Policy, Elsevier, vol. 71(C), pages 57-69.
    5. 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.
    6. 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.
    7. 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).
    8. Cheng, Long & Wang, Kailai & De Vos, Jonas & Huang, Jie & Witlox, Frank, 2022. "Exploring non-linear built environment effects on the integration of free-floating bike-share and urban rail transport: A quantile regression approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 175-187.
    9. Qing Yu & Weifeng Li & Dongyuan Yang & Yingkun Xie, 2020. "Policy Zoning for Efficient Land Utilization Based on Spatio-Temporal Integration between the Bicycle-Sharing Service and the Metro Transit," Sustainability, MDPI, vol. 13(1), pages 1-14, December.
    10. Yeran Sun & Amin Mobasheri & Xuke Hu & Weikai Wang, 2017. "Investigating Impacts of Environmental Factors on the Cycling Behavior of Bicycle-Sharing Users," Sustainability, MDPI, vol. 9(6), pages 1-12, June.
    11. 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.
    12. Pucher, John & Buehler, Ralph & Seinen, Mark, 2011. "Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 451-475, July.
    13. 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.
    14. Weliwitiya, Hesara & Rose, Geoffrey & Johnson, Marilyn, 2019. "Bicycle train intermodality: Effects of demography, station characteristics and the built environment," Journal of Transport Geography, Elsevier, vol. 74(C), pages 395-404.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. Jian-gang Shi & Hongyun Si & Guangdong Wu & Yangyue Su & Jing Lan, 2018. "Critical Factors to Achieve Dockless Bike-Sharing Sustainability in China: A Stakeholder-Oriented Network Perspective," Sustainability, MDPI, vol. 10(6), pages 1-16, June.
    20. 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.

    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:10:y:2018:i:5:p:1526-:d:145767. 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.