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

Hong, J., Mcarthur, D. P. and Livingston, M. (2019) The evaluation of large cycling infrastructure investments in Glasgow using crowdsourced cycle data. Transportation, (doi:10.1007/s11116-019-09988-4) (Early Online Publication)

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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.

Item Type:Articles
Additional Information:The authors would like to acknowledge support from the Economic and Social Research Council-funded Urban Big Data Centre at the University of Glasgow (Grant ES/L011921/1)
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Hong, Dr Jinhyun and Livingston, Dr Mark and Mcarthur, Dr David
Authors: Hong, J., Mcarthur, D. P., and Livingston, M.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Transportation
Publisher:Springer US
ISSN:0049-4488
ISSN (Online):1572-9435
Published Online:14 March 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Transportation 2019
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
651922Urban Big Data Research CentrePiyushimita ThakuriahEconomic and Social Research Council (ESRC)ES/L011921/1SPS - URBAN STUDIES