Data-driven insights into private EV-charger sharing: A multi-group analysis across London’s ultra-low emission zones

Abstract

The rapid growth of electric vehicles (EVs) has heightened the need for innovative charging solutions. Charger sharing services (CSS), an emerging sharing model, leverage privately-owned chargers to supplement public infrastructure, and contribute to sustainable urban mobility. Drawing on survey data collected from 604 charger-owning households living in the ULEZ zones, we estimate a variance-based structural equation model and conduct a multi-group comparison between the Inner ULEZ and the surrounding Expanded ULEZ. Across both zones, economic, moral and social motives strongly and positively shape attitudes, and attitude in turn dominates intention to share. Secondary drivers vary spatially: knowledge about sharing services raises attitudes only inside the IULEZ, whereas perceived scarcity of public chargers suppresses sharing willingness only there. No structural paths differ significantly in magnitude between zones, indicating a robust core decision calculus with context-specific modifiers. As one of the first study to focus on this innovative sharing mobility model, this study provides nuanced data-driven insights into regional variations in private charger owners’ sharing decision and offering evidence-based recommendations for policymakers and practitioners to optimize resource utilization.