Investigating the factors affecting the distance travel and health conditions of e-bike users in Toronto

This paper investigates the factors influencing the physical health condition and the trip distance of e-bike users’ in Toronto, Canada. The research is based on a survey of e-bike and bicycle users' health condition and travel behaviour in Toronto. A Bivariate Ordered Probit model is used to draw links between different factors that affect the health conditions and trip distance of the users. It is important to note that modelling results at best indicate an association (not causation) between the dependent and independent variables. The health condition model reveals that e-bikers from low-income households have higher health risk than the e-bikers from the high-income household. In terms of the trip distance, the model results indicate that the individuals who typically make longer distance trips using e-bikes are more likely to be in an excellent health condition than the individuals who make shorter distance trips using e-bikes. In terms of policy recommendations, a Monte Carlo analysis based on the estimated model reveals that strategies targeted at different demographics (e.g., income, age) are more likely to be effective. The implications of these empirical findings provide essential elements of guidance to the policymakers, and these findings are transferable to the other North American cities.


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  • Accession Number: 01764565
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Dec 12 2020 3:07PM