Different mode, different travel? Insights into the travel behavior of e-scooter sharing using credit card big data and a mobile survey in Seoul

Abstract

Previous studies regarding e-scooter sharing mainly focused on analyzing the risk factors and the socioeconomic characteristics of users. Moreover, these studies had limitations, such as the small amount of data for policy implications and the restricted geographic scope centered on western countries with minimal attention on Asian urban areas. To overcome such limitations, this research has aimed to identify clearer features of behavioral aspects of e-scooter sharing by utilizing credit card big data and conducting a mobile survey amongst users in Seoul including various time slots during the COVID-19 outbreak. The findings revealed two peak times for e-scooter sharing during the week with heightened activity on weekends and holidays. It was noted that e-scooter sharing substituted other modes of transportation from midnight to 05:00. The majority of users were men and young people, driven primarily by the motivation for leisure and fun. High levels of patronage and customer satisfaction were identified, but there was a need for fundamental facilities to support sustained usage. Although the COVID-19 pandemic had an impact on e-scooter sharing usage, quantifying its extent has proven to be challenging. Weather conditions also influenced usage patterns, which varied across different regions. E-scooter sharing was used both as a complement and substitute for traditional transportation modes depending on specific situations. It was concluded that e-scooter sharing was not viewed as a replacement for cars, but often used to connect with mass transit. Consequently, the sustainability of its services remains a subject of debate.