Intention to use Robo-Advisors, considering the Behavioral Reasoning Theory, and moderating effect of prior knowledge and experience.

Abstract

Robo-advisors, AI-powered financial services, offer personalized investing solutions but have not achieved the expected adoption rates. This study addresses a critical gap in the literature by examining how the value of openness to change influences the intention to use robo-advisors, through the mediating roles of Reasons for and Reasons Against adoption, within the framework of Behavioral Reasoning Theory (BRT). Additionally, the study explores how financial knowledge and investing experience moderate these mediated relationships in a nonlinear fashion. Data collected from 400 participants through a structured survey was analyzed using Structural Equation Modeling (SEM). The results indicate that while personal values indirectly influence adoption intentions, Reasons For significantly enhance, and Reasons Against impede, the intention to use robo-advisors. The nonlinear moderating effects of financial knowledge and investing experience reveal that the influence of these reasons on intention is most pronounced at moderate levels of these moderators but diminishes at low and high levels. Specifically, financial knowledge strengthens the positive impact of Reasons For and mitigates the negative impact of Reasons Against at moderate levels, while investing experience shows a more complex pattern, amplifying and then weakening these effects. These findings underscore the need for targeted strategies that address both the benefits and perceived barriers to robo-advisor adoption, emphasizing the nuanced role of user knowledge and experience in shaping engagement with AI-driven financial technologies.