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What’s your type: a multidimensional cyclist typology

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  • Gabriel Damant-Sirois
  • Michael Grimsrud
  • Ahmed El-Geneidy

Abstract

Increasing bicycle use for utilitarian trips is a common city objective for health and environmental improvement and congestion reduction, but cyclists react heterogeneously to interventions and infrastructure. Understanding cyclist types helps in comprehending and planning for this diverse population. This study uses data from 2004 surveyed Montreal cyclists to generate a multidimensional cyclist typology based on seven factors derived from 35 variables, mostly proven determinants of the intensity of bicycle usage. The analysis revealed four distinct cyclist types: dedicated cyclists, path-using cyclists, fairweather utilitarians, and leisure cyclists. The cycling frequencies of each group respond differently to potential interventions and vary within commuting rate ranges with apparent minima and maxima. Building a network adapted to different cyclist types and emphasizing its convenience, flexibility and speed, could be an effective strategy to increase cycling mode share and frequency among the various groups. Findings from this study can be of benefit to transportation engineers, planners and policy makers as they help in better understanding the impacts of various interventions on the different groups of cyclists. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Gabriel Damant-Sirois & Michael Grimsrud & Ahmed El-Geneidy, 2014. "What’s your type: a multidimensional cyclist typology," Transportation, Springer, vol. 41(6), pages 1153-1169, November.
    • Handle: RePEc:kap:transp:v:41:y:2014:i:6:p:1153-1169
    DOI: 10.1007/s11116-014-9523-8
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    Cited by:

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    5. Bhat, Chandra R. & Astroza, Sebastian & Hamdi, Amin S., 2017. "A spatial generalized ordered-response model with skew normal kernel error terms with an application to bicycling frequency," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 126-148.
    6. Deboosere, Robbin & El-Geneidy, Ahmed, 2018. "Evaluating equity and accessibility to jobs by public transport across Canada," Journal of Transport Geography, Elsevier, vol. 73(C), pages 54-63.
    7. Faghih Imani, Ahmadreza & Miller, Eric J. & Saxe, Shoshanna, 2019. "Cycle accessibility and level of traffic stress: A case study of Toronto," Journal of Transport Geography, Elsevier, vol. 80(C).
    8. Lowry, Michael B. & Furth, Peter & Hadden-Loh, Tracy, 2016. "Prioritizing new bicycle facilities to improve low-stress network connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 124-140.
    9. Damant-Sirois, Gabriel & El-Geneidy, Ahmed M., 2015. "Who cycles more? Determining cycling frequency through a segmentation approach in Montreal, Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 113-125.
    10. Wang, Haizhong & Palm, Matthew & Chen, Chen & Vogt, Rachel & Wang, Yiyi, 2016. "Does bicycle network level of traffic stress (LTS) explain bicycle travel behavior? Mixed results from an Oregon case study," Journal of Transport Geography, Elsevier, vol. 57(C), pages 8-18.
    11. José I. Castillo-Manzano & Mercedes Castro-Nuño & Lourdes Lopez-Valpuesta, 2015. "The relationship between public and private bicycle use: the case of Seville," ERSA conference papers ersa15p206, European Regional Science Association.
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    13. Iwińska, Katarzyna & Blicharska, Malgorzata & Pierotti, Livia & Tainio, Marko & de Nazelle, Audrey, 2018. "Cycling in Warsaw, Poland – Perceived enablers and barriers according to cyclists and non-cyclists," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 291-301.
    14. Thigpen, Calvin, 2017. "The Reciprocal Relationship between Children and Young Adults' Travel Behavior and Their Travel Attitudes, Skills, and Norms," Institute of Transportation Studies, Working Paper Series qt383679dd, Institute of Transportation Studies, UC Davis.
    15. Fu, Liwei & Farber, Steven, 2017. "Bicycling frequency: A study of preferences and travel behavior in Salt Lake City, Utah," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 30-50.

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