Micromobility services before and after a global pandemic: impact on spatio-temporal travel patterns

Abstract

Sudden changes in urban mobility were caused due to the COVID-19 pandemic. The impacts are yet to be furtherly measured and analyzed. Our article uses GPS records provided by three different micromobility operators in Madrid to study how the pandemic affected their service usage and its relationships with land use. Thus, spatio-temporal travel patterns are compared between pre-COVID 19 (from January 2019 to February 2020) and COVID times (from March to December 2020). Additionally, multiple regression analyses are conducted to assess how the two scenarios differentiate in relation to micromobility trips, generated or attracted, to or from different land uses, and during morning or afternoon peak hours. Results show that the most pandemic-resilient shared mode is bike-sharing, and that COVID-19 has caused a downfall in micromobility trips of approximately 10%, which is relatively lower compared to the 80% ridership drop reported by the public transport system. Our models reveal that residential and commercial areas gained importance after the pandemic, while workplace locations (office and industrial), educational and transport facilities lost relevance with teleworking and online studying. These findings could help authorities to plan future policies and improve the infrastructure needed to promote micromobility services.

Keywords:

• Micromobility
• shared mobility
• spatial analysis
• COVID-19 pandemic

Declaration of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

The authors gratefully acknowledge funding from the MCIN-AEI/10.13039/501100011033/(Projects NEWGEOMOB - PID2020-116656RB-I00 and DARUMA - PCI2020-120706-2). Additionally, the study falls within the framework of the “Cátedra Extraordinaria de Movilidad Ciclista UCM-EMT” and INNJOBMAD-CM (H2019/HUM-5761, co-financed by Comunidad de Madrid and European Social Fund). We are also grateful to Movo and Muving for sharing their data for research purposes.