The effect of COVID restriction levels on shared micromobility travel patterns: A comparison between dockless bike sharing and e-scooter services

TL;DR

This study analyzes how COVID-19 restrictions impacted shared micromobility usage in Turin, revealing differences between bike sharing and e-scooter services in demand variability, spatial patterns, and their relationship with public transport.

Contribution

It provides a comparative analysis of dockless bike and e-scooter usage patterns under varying COVID-19 restrictions, highlighting their distinct responses and spatial behaviors.

Findings

E-scooters showed larger demand variability and quicker recovery.

Shared bikes were less affected by restrictions, indicating different usage purposes.

E-scooters both substitute and complement public transport depending on restrictions.

Abstract

The spread of the coronavirus pandemic had negative repercussions on the majority of transport systems in virtually all countries. After the lockdown period, travel restriction policies are now frequently adapted almost real-time according to observed trends in the spread of the disease, resulting in a rapidly changing transport market situation. Shared micromobility operators, whose revenues entirely come from their customers, need to understand how the demand is affected to adapt their operations. Within this framework, the present paper investigates how different COVID-19 restriction levels have affected the usage patterns of shared micromobility. Usage data of two dockless micromobility services (bike and e-scooters) operating in Turin (Italy) are analyzed between October 2020 and March 2021, a period characterized by different travel restriction levels. The average number of daily trips, trip distances and trip duration are retrieved for both services, and then compared to identify significant differences in trends as restriction levels change. Additionally, related impacts on the spatial dimension of the services are studied through hotspot maps. Results show that both services decreased during restrictions, however e-scooters experienced a larger variability in their demand and they had a quicker recovery when travel restrictions were loosened. Shared bikes, in general, suffered less from travel restriction levels, suggesting their larger usage for work and study-related trip purposes, which is confirmed also by the analysis of hotspots. E-scooters are both substituting and complementing public transport according to restriction levels, while usage patterns of shared bikes are more independent.