IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i15p2641-d251190.html
   My bibliography  Save this article

Measuring the Destination Accessibility of Cycling Transfer Trips in Metro Station Areas: A Big Data Approach

Author

Listed:
  • Xueying Wu

    (School of Architecture, Harbin Institute of Technology, Shenzhen 518000, China)

  • Yi Lu

    (Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China
    City University of Hong Kong Shenzhen Research Institute, Shenzhen 518057, China)

  • Yaoyu Lin

    (School of Architecture, Harbin Institute of Technology, Shenzhen 518000, China)

  • Yiyang Yang

    (Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong, China)

Abstract

Cycling is a green, sustainable, and healthy choice for transportation that has been widely advocated worldwide in recent years. It can also encourage the use of public transit by solving the “last-mile” issue, because transit passengers can cycle to and from transit stations to achieve a combination of speed and flexibility. Cycling as a transfer mode has been shown to be affected by various built environment characteristics, such as the urban density, land-use mix, and destination accessibility, that is, the ease with which cyclists can reach their destinations. However, cycling destination accessibility is loosely defined in the literature and the methods of assessing cycling accessibility is often assumed to be equivalent to walking accessibility using the same decay curves, such as the negative exponential function, which ignores the competitive relationship between cycling and walking within a short distance range around transit stations. In this study, we aim to fill the above gap by measuring the cycling destination accessibility of metro station areas using data from more than three million bicycle-metro transfer trips from a dockless bicycle-sharing program in Shenzhen, China. We found that the frequency of bicycle-metro trips has a positive association with a trip distance of 500 m or less and a negative association with a trip distance beyond 500 m. A new cycling accessibility metric with a lognormal distribution decay curve was developed by considering the distance decay characteristics and cycling’s competition with walking. The new accessibility model outperformed the traditional model with an exponential decay function, or that without a distance decay function, in predicting the frequency of bicycle-metro trips. Hence, to promote bicycle-metro integration, urban planners and government agencies should carefully consider the destination accessibility of metro station areas.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:15:p:2641-:d:251190
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/15/2641/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/15/2641/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Jingxu Chen & Xuewu Chen & Hang Jiang & Senlai Zhu & Xiaowei Li & Zhibin Li, 2015. "Determining the Optimal Layout Design for Public Bicycle System within the Attractive Scope of a Metro Station," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-8, March.
    3. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    4. Cervero, R. & Duncan, M., 2003. "Walking, Bicycling, and Urban Landscapes: Evidence from the San Francisco Bay Area," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1478-1483.
    5. Sun, Daniel (Jian) & Guan, Shituo, 2016. "Measuring vulnerability of urban metro network from line operation perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 348-359.
    6. 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.
    7. Zheng Tan & Charlie Q.L. Xue, 2014. "Walking as a Planned Activity: Elevated Pedestrian Network and Urban Design Regulation in Hong Kong," Journal of Urban Design, Taylor & Francis Journals, vol. 19(5), pages 722-744, December.
    8. 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.
    9. Susan Handy & Bert van Wee & Maarten Kroesen, 2014. "Promoting Cycling for Transport: Research Needs and Challenges," Transport Reviews, Taylor & Francis Journals, vol. 34(1), pages 4-24, January.
    10. Cervero, Robert & Duncan, Michael, 2003. "Walking, Bicycling, and Urban Landscapes: Evidence from the San Francisco Bay Area," University of California Transportation Center, Working Papers qt6zr1x95m, University of California Transportation Center.
    11. Nielsen, Thomas Alexander Sick & Skov-Petersen, Hans, 2018. "Bikeability – Urban structures supporting cycling. Effects of local, urban and regional scale urban form factors on cycling from home and workplace locations in Denmark," Journal of Transport Geography, Elsevier, vol. 69(C), pages 36-44.
    12. Saberi, Meead & Ghamami, Mehrnaz & Gu, Yi & Shojaei, Mohammad Hossein (Sam) & Fishman, Elliot, 2018. "Understanding the impacts of a public transit disruption on bicycle sharing mobility patterns: A case of Tube strike in London," Journal of Transport Geography, Elsevier, vol. 66(C), pages 154-166.
    13. John Parkin & Mark Wardman & Matthew Page, 2008. "Estimation of the determinants of bicycle mode share for the journey to work using census data," Transportation, Springer, vol. 35(1), pages 93-109, January.
    14. Tilahun, Nebiyou Y. & Levinson, David M. & Krizek, Kevin J., 2007. "Trails, lanes, or traffic: Valuing bicycle facilities with an adaptive stated preference survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 287-301, May.
    15. Ralph Buehler & John Pucher, 2012. "Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes," Transportation, Springer, vol. 39(2), pages 409-432, March.
    16. Liu, Hung-Chi & Lin, Jen-Jia, 2019. "Associations of built environments with spatiotemporal patterns of public bicycle use," Journal of Transport Geography, Elsevier, vol. 74(C), pages 299-312.
    17. 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.
    18. 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. Dorsa Alipour & Hussein Dia, 2023. "A Systematic Review of the Role of Land Use, Transport, and Energy-Environment Integration in Shaping Sustainable Cities," Sustainability, MDPI, vol. 15(8), pages 1-29, 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. 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.
    2. Braun, Lindsay M. & Rodriguez, Daniel A. & Cole-Hunter, Tom & Ambros, Albert & Donaire-Gonzalez, David & Jerrett, Michael & Mendez, Michelle A. & Nieuwenhuijsen, Mark J. & de Nazelle, Audrey, 2016. "Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona, Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 164-183.
    3. Spencer, Phoebe & Watts, Richard & Vivanco, Luis & Flynn, Brian, 2013. "The effect of environmental factors on bicycle commuters in Vermont: influences of a northern climate," Journal of Transport Geography, Elsevier, vol. 31(C), pages 11-17.
    4. Wadud, Zia, 2014. "Cycling in a changed climate," Journal of Transport Geography, Elsevier, vol. 35(C), pages 12-20.
    5. Umer Mansoor & Mohammad Tamim Kashifi & Fazal Rehman Safi & Syed Masiur Rahman, 2022. "A review of factors and benefits of non-motorized transport: a way forward for developing countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 1560-1582, February.
    6. Hochmair, Hartwig H. & Bardin, Eric & Ahmouda, Ahmed, 2019. "Estimating bicycle trip volume for Miami-Dade county from Strava tracking data," Journal of Transport Geography, Elsevier, vol. 75(C), pages 58-69.
    7. Ledsham, Trudy & Farber, Steven & Wessel, Nate, 2017. "Dwelling Type Matters: Untangling the Paradox of Intensification and Bicycle Mode Choice," SocArXiv nvg64, Center for Open Science.
    8. Zhitao Li & Yuzhen Shang & Guanwei Zhao & Muzhuang Yang, 2022. "Exploring the Multiscale Relationship between the Built Environment and the Metro-Oriented Dockless Bike-Sharing Usage," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    9. Greg Rybarczyk & Changshan Wu, 2014. "Examining the Impact of Urban Morphology on Bicycle Mode Choice," Environment and Planning B, , vol. 41(2), pages 272-288, April.
    10. Hyochul Park & Yong Lee & Hee Shin & Keemin Sohn, 2011. "Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist," Transportation, Springer, vol. 38(2), pages 305-319, March.
    11. Downward, Paul & Rasciute, Simona, 2015. "Assessing the impact of the National Cycle Network and physical activity lifestyle on cycling behaviour in England," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 425-437.
    12. Rybarczyk, Greg & Gallagher, Laura, 2014. "Measuring the potential for bicycling and walking at a metropolitan commuter university," Journal of Transport Geography, Elsevier, vol. 39(C), pages 1-10.
    13. Yi Yao & Yifang Zhang & Lixin Tian & Nianxing Zhou & Zhilin Li & Minggang Wang, 2019. "Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    14. Elise Desjardins & Christopher D. Higgins & Darren M. Scott & Emma Apatu & Antonio Páez, 2022. "Correlates of bicycling trip flows in Hamilton, Ontario: fastest, quietest, or balanced routes?," Transportation, Springer, vol. 49(3), pages 867-895, June.
    15. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    16. Acheampong, Ransford A. & Siiba, Alhassan, 2018. "Examining the determinants of utility bicycling using a socio-ecological framework: An exploratory study of the Tamale Metropolis in Northern Ghana," Journal of Transport Geography, Elsevier, vol. 69(C), pages 1-10.
    17. Dandan Xu & Yang Bian & Shinan Shu, 2020. "Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing," Sustainability, MDPI, vol. 12(7), pages 1-18, April.
    18. Lei Kang & Jon Fricker, 2013. "Bicyclist commuters’ choice of on-street versus off-street route segments," Transportation, Springer, vol. 40(5), pages 887-902, September.
    19. 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.
    20. Osama, Ahmed & Sayed, Tarek & Bigazzi, Alexander Y., 2017. "Models for estimating zone-level bike kilometers traveled using bike network, land use, and road facility variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 14-28.

    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:jijerp:v:16:y:2019:i:15:p:2641-:d:251190. 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.