Shared e-scooter Usage Trends in a Swedish City: A Spatial Analysis

Paper in proceeding, 2024

Amidst rapid urbanization and evolving transport needs, electric scooters (e-scooters) have been reshaping short-distance urban trips. This study offers a systematic framework for spatial analysis of shared micro-mobility in Gothenburg, Sweden—using Geographically Weighted Regression (GWR) and Multiscale-GWR (MGWR) models. The research aims to decipher the city’s shared e-scooter demand for various factors such as transit proximity, land use patterns, road infrastructure, demographics, and weather conditions. Investigation comparatively deciphers GWR and MGWR models, which outperform global regression models in terms of fitness, and interpretability for the spatial heterogeneity in shared e-scooter demand. However, MGWR’s complexity sometimes leads to overfitting, with its results lacking clear interpretation. The study identifies significant spatial variations in shared e-scooter demand, linked with specific urban characteristics, providing a deeper understanding of how different factors contribute to shared e-scooter usage across various city zones. These findings are crucial for shared e-scooter ventures, urban planners and policymakers, offering a nuanced framework for integrating e-scooters into urban transport systems. The research underscores the effectiveness of spatial econometric approaches in urban mobility management, highlighting the importance of efficient spatial models for shared e-scooter demand analysis in urban contexts.