Ride‐pooling in the light of COVID‐19: Determining spatiotemporal demand characteristics on the example of MOIA

Abstract

Abstract The mobility provider MOIA operates Europe's largest contiguous electric ride‐pooling service in Hamburg, representing a testbed of how shared and digitized transport can help foster the transformation of urban mobility. The on‐demand service has been in operation since 2019 and was thus affected by the COVID‐19 pandemic in 2020. This study shows real‐world insights into travel behavior before and during the pandemic, contributing to the empirical evidence on recent mobility behavior. After the application of descriptive statistical analyses, several (spatial) regression models are estimated to understand the relationship between spatial variables and demand. MOIA trip data from three different time periods are used: (a) before the COVID‐19 pandemic in summer and autumn 2019, (b) during the time of the first lockdown in Germany in spring 2020, and (c) after the first lockdown in summer and autumn 2020. A significant positive effect on ride‐pooling demand is observed for number of inhabitants, workplaces, gastronomic facilities, and at the airport in all time periods. In the course of the pandemic, the main travel patterns remained stable. However, the positive influences of gastronomy and the airport on ride‐pooling demand diminished in 2020. In contrast, the impact of hospitals on ride‐pooling demand increased in the course of the pandemic. In areas with high car ownership, ride‐pooling demand declined compared to pre‐pandemic times.