Exploring the spatiotemporal patterns of shared bicycle usage: a case study of MetroBike in Austin, Texas

Abstract Shared bike services are rapidly expanding across the globe due to their potential to alleviate urban transportation congestion, offer environmental benefits, and address first- and last-mile connectivity. The city of Austin, Texas, is actively working to scale up its MetroBike system by increasing the number of available bicycles and expanding bike lanes. While previous studies have primarily focused on the accessibility or community detection separately, relatively little attention has been given to comprehensive usage patterns, spatial accessibility, and the factors that influence them. Understanding these components is crucial for the efficient and sustainable expansion of shared micromobility services. This study investigates the MetroBike system in Austin through a multi-method approach. First, a community detection analysis is used to identify spatial clusters of bike-sharing activity, revealing variations in urban structure and usage across space and time. Second, we employ a two-step floating catchment area (2SFCA) method to evaluate accessibility to bike kiosks at both the census block group and community levels. Finally, we examine the socio-demographic factors that influence accessibility based on a geographically weighted regression (GWR). The findings provide critical insights into spatial disparities and usage trends in Austin's bike-share system, offering data-driven guidance for the equitable and strategic expansion of MetroBike. This research contributes to the broader understanding of micromobility accessibility and supports urban policy aimed at sustainable transportation planning.