Cracking the Code of Initial Trust: Pathways to Adoption of Financial Robo-Advisors via Cognitive Absorption

With growing dependence on financial robo-advisors, comprehending how users develop initial-trust becomes critical, particularly given the high uncertainty and perceived risk in automation-backed financial services. The study relies on human-computer interaction framework to categorize antecedents of initial-trust into technological features, task-specific factors, and investor-specific characteristics. It further examines how cognitive absorption mediates the connection between initial-trust and intention to adopt robo-advisors. Data collected from 491 young investors were analyzed using structural equation modeling. Findings reveal Robo anthropomorphism as the most influential antecedent of initial-trust followed by Robo Service-Fit, service quality and system quality, while 'perceived service risk' impacts initial-trust negatively. Initial-trust has a direct and positive effect on adoption intention, with cognitive absorption partially mediating the relationship. Grounded in human-computer interaction, the study provides theoretical and practical insights into how initial-trust drives adoption intention through cognitive absorption, offering an integrated framework to augment both academic discourse and Fintech design strategies.