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Modeling the Factors Influencing the Activity Spaces of Bikeshare around Metro Stations: A Spatial Regression Model

Author

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  • Xinwei Ma

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

  • Yanjie Ji

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

  • Jianbiao Wang

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

  • Mingjia He

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

Abstract

Metro-bikeshare integration is considered a green and efficient travel model. To better understand bikeshare as a feeder mode to the metro, this study explored the factors that influence the activity spaces of bikeshare around metro stations. First, metro-bikeshare transfer trips were recognized by matching bikeshare smartcard data and metro smartcard data. Then, standard deviation ellipse (SDE) was used for the calculation of the metro-bikeshare activity spaces. Moreover, an ordinary least squares (OLS) regression and a spatial error model (SEM) were established to reveal the effects of social-demographic, travel-related, and built environment factors on the activity spaces of bikeshare around metro stations, and the SEM outperformed OLS significantly in terms of model fit. Results show that the average metro-bikeshare activity space on weekdays is larger than that on weekends. The proportion of local residents promotes the increase in activity space on weekends, while a high density of road and metro impedes the activity space on weekdays. Additionally, with increased job density, the activity space becomes smaller significantly throughout the week. Also, both on weekdays and weekends, the closer to the central business district (CBD), the smaller the activity space. This study can offer meaningful guidance to policymakers and city planners aiming to make the bikeshare distribution more reasonable.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:3949-:d:179238
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    as
    1. Bernardo Nugroho Yahya, 2017. "Overall Bike Effectiveness as a Sustainability Metric for Bike Sharing Systems," Sustainability, MDPI, vol. 9(11), pages 1-28, November.
    2. 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.
    3. 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.
    4. 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.
    5. Bin Wang & Wenzhong Shi & Zelang Miao, 2015. "Confidence Analysis of Standard Deviational Ellipse and Its Extension into Higher Dimensional Euclidean Space," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
    6. Molin, Eric & Maat, Kees, 2015. "Bicycle parking demand at railway stations: Capturing price-walking trade offs," Research in Transportation Economics, Elsevier, vol. 53(C), pages 3-12.
    7. 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.
    8. Manfred M. Fischer & Jinfeng Wang, 2011. "Spatial Data Analysis," SpringerBriefs in Regional Science, Springer, number 978-3-642-21720-3.
    9. Shaheen, Susan & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present, and Future," Institute of Transportation Studies, Working Paper Series qt79v822k5, Institute of Transportation Studies, UC Davis.
    10. Wong, Sandy, 2018. "The limitations of using activity space measurements for representing the mobilities of individuals with visual impairment: A mixed methods case study in the San Francisco Bay Area," Journal of Transport Geography, Elsevier, vol. 66(C), pages 300-308.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Shaheen, Susan A & Guzman, Stacey & Zhang, Hua, 2010. "Bikesharing in Europe, the Americas, and Asia: Past, Present and Future," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6qg8q6ft, Institute of Transportation Studies, UC Berkeley.
    16. 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.
    17. 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.
    18. Anable, Jillian, 2005. "'Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behaviour segments using attitude theory," Transport Policy, Elsevier, vol. 12(1), pages 65-78, January.
    19. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
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    2. Milad Malekzadeh & Jed A. Long, 2024. "Mobility deviation index: incorporating geographical context into analysis of human mobility," Journal of Geographical Systems, Springer, vol. 26(3), pages 427-448, July.
    3. Hu, Songhua & Chen, Mingyang & Jiang, Yuan & Sun, Wei & Xiong, Chenfeng, 2022. "Examining factors associated with bike-and-ride (BnR) activities around metro stations in large-scale dockless bikesharing systems," Journal of Transport Geography, Elsevier, vol. 98(C).
    4. 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).
    5. 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.
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    7. 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.
    8. Pfiester, Laura Mali & Thompson, Russell G. & Zhang, Lele, 2021. "Spatiotemporal exploration of Melbourne pedestrian demand," Journal of Transport Geography, Elsevier, vol. 95(C).
    9. 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.
    10. Zaouche, Mounia & Bode, Nikolai W.F., 2023. "Bayesian spatio-temporal models for mapping urban pedestrian traffic," Journal of Transport Geography, Elsevier, vol. 111(C).
    11. Chen, Qun & Pan, Xiaoyi & Liu, Fang & Xiong, Yong & Li, Zhitao & Tang, Jinjun, 2022. "Reposition optimization in free-floating bike-sharing system: A case study in Shenzhen City," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
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