This study investigates the socio-behavioral and psychological determinants influencing the adoption of Shared Automated Electric Vehicles (SAEVs) in urban environments, using London as a case study. The research addresses a critical gap in the literature by exploring how a sense of belonging (SoB) impacts transportation mode choices, alongside traditional sociodemographic factors. Employing an Integrated Choice Latent Variable Model (ICLVM), the study merges Structural Equation Modeling (SEM) and Multinomial Logit (MNL) approaches to analyze data from a Stated Preference Discrete Choice Experiment involving 557 London residents. Results indicate that SoB significantly influences SAEV adoption, suggesting that fostering community engagement could promote sustainable mobility. Furthermore, Ridesharing experience emerges as a key predictor, facilitating openness to SAEVs and bridging the gap between private vehicle reliance and shared mobility acceptance. However, the analysis also highlights challenges, including a persistent preference for private vehicles among licensed drivers, and the model’s mixed predictive performance for SAEVs. Policy implications underscore the need for community-based strategies and ridesharing integration to enhance SAEV uptake. The study concludes that a holistic approach, incorporating both technological advancements and psychological factors, is vital for developing socially inclusive and environmentally sustainable urban transport systems.