Value-centric analysis of user adoption for sustainable urban micro-mobility transportation through shared e-scooter services

Abstract

Micro-mobility services, which are considered a sustainable alternative to traditional transportation modes, have gained substantial popularity due to advancements in mobile technology. As one of those modes of transportation, shared e-scooter services have encouraged several startups in urban areas, allowing them to reach massive numbers of consumers in a highly competitive environment. This study aims to explore gains and barriers that affect the intention of consumers to use shared e-scooter services, all within the framework of sustainability-driven considerations. The Latent Dirichlet Allocation (LDA) Algorithm was used to analyse 24.798 reviews from the Google Play Store, uncovering eight topics. Those topics were used to discover customer value perceptions in the shared e-scooter context and compare them with the related literature on perceived value. Besides, their impact on user ratings on the mobile application platform was measured using machine learning algorithms. The study's findings are expected to contribute to developing regulations for shared e-scooter services, which have gained popularity as an eco-friendly mode of transportation sustainability in urban areas by introducing a novel perspective.