Cycling in the aftermath of COVID-19: An empirical estimation of the social dynamics of bicycle adoption in Paris

Abstract

The adoption of cycling as an alternative mode of transport to the car offers a promising strategy for tackling several pressing societal challenges, reducing the ecological costs of transport, improving individual health, as well as the quality of life in cities that are often congested by road traffic. We propose an original approach to measure in the context of a natural experiment the influence of social influence on individual intentions within the theory of interpersonal behaviour, by modelling explicitly the diffusion of cycling within the population. We consider the time period following the end of the first COVID-19-lockdown in May 2020 in Paris, France, and estimate a simple model of social imitation based on data from the City of Paris’ Open Data initiative, integrating also in our estimation geographical and temporal fixed-effects, as well as controls for the level of precipitation. We find that the increasing adoption of cycling between May and July 2020 can indeed be explained as the result of a new social dynamic tending to increase the switching rate between transport modes.

Keywords

• Coronapistes
• Social imitation
• Urban design
• Cycling adoption
• COVID-19
• Theory of interpersonal behaviour