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The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data

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  • Jinhyun Hong

    (The University of Glasgow)

  • David Philip McArthur

    (The University of Glasgow)

  • Mark Livingston

    (The University of Glasgow)

Abstract

The benefits of cycling have been well established for several decades. It can improve public health and make cities more active and environmentally friendly. Due to the significant net benefits, many local governments in Scotland have promoted cycling. Glasgow City Council constructed four significant pieces of cycling infrastructure between 2013 and 2015, partly in preparation for the 2014 Commonwealth Games and partly to encourage cycling more generally. This required substantial capital investment. However, the effectiveness of these big new infrastructure investments has not been well examined, mostly due to data limitations. In this study, we utilised data from the activity tracking app Strava for the years 2013–2016 and fixed effects panel data regression models to examine whether the new cycling infrastructure has increased cycling volumes on these routes. Our results show that three of the infrastructure projects have a positive effect on the monthly total volume of cycling trips made by users of the app, with flows up by around 12% to 18%. Although this result is promising, it needs to be interpreted with care due to the characteristics of the data.

Suggested Citation

  • Jinhyun Hong & David Philip McArthur & Mark Livingston, 2020. "The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data," Transportation, Springer, vol. 47(6), pages 2859-2872, December.
    • Handle: RePEc:kap:transp:v:47:y:2020:i:6:d:10.1007_s11116-019-09988-4
    DOI: 10.1007/s11116-019-09988-4
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    Cited by:

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    4. Verduzco Torres, Jose Rafael & Raturi, Varun, 2024. "A methodological evaluation of app location data extraction and processing for traffic flow applications," OSF Preprints vut58, Center for Open Science.
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    6. Francesca Pontin & Nik Lomax & Graham Clarke & Michelle A. Morris, 2021. "Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach," IJERPH, MDPI, vol. 18(21), pages 1-27, October.
    7. Mogens Fosgerau & Miroslawa Lukawska & Mads Paulsen & Thomas Kj{ae}r Rasmussen, 2022. "Bikeability and the induced demand for cycling," Papers 2210.02504, arXiv.org, revised Dec 2022.
    8. Van Veghel, Daniel & Scott, Darren M., 2024. "Investigating the impacts of bike lanes on bike share ridership: A holistic approach and demonstration," Journal of Transport Geography, Elsevier, vol. 115(C).
    9. Credit, Kevin & O'Driscoll, Conor, 2024. "Assessing modal tradeoffs and associated built environment characteristics using a cost-distance framework," Journal of Transport Geography, Elsevier, vol. 117(C).
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    13. Desmond Lartey & Meredith A. Glaser, 2024. "Towards a Sustainable Transport System: Exploring Capacity Building for Active Travel in Africa," Sustainability, MDPI, vol. 16(3), pages 1-20, February.

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