Analysing ride behaviours of shared e-scooter users – a case study of Liverpool

Abstract

[EN] The shared e-scooter is a relatively new form of Micromobility service in urban transit. A better understanding of the use of the scheme will help operators and stakeholders promote this travel mode, contributing to a more sustainable, resilient, environmentally friendly and inclusive transportation system. The availability of high resolution sensor-based location data, when co-analysed with socio-demographic survey data allows insights on where, how, and by whom the service is used. This study focuses on analysing the usage pattern of a recently introduced shared e-scooter scheme in Liverpool, UK, combining survey data of users’ sociodemographic attributes and their full trip records at a fine spatiotemporal granularity. Recency-Frequency (RF) segmentation is used to categorise user behaviour based on their frequency and recency of usage, and a Functional Signatures (FS) dataset is used to enrich contextual information on the origin and destination of e-scooter trips. Overall, this study provides insights into the behaviour of users of shared e-scooters and how the behaviours might vary in different user groups regarding sociodemographic characteristics. The developed analysis framework is also readily transferable to other cities.