Decoding Investors’ Behaviour in Adoption of Robo-advisors: A PLS-SEM and FsQCA Approach

Abstract

Despite advancements in robotic finance, individuals seem stuck and struggling to embrace these novel technologies, highlighting the need to uncover the behavioural reasons behind adoption. Following the literature review, the study drafts a conceptual model integrating insights using ‘diffusion of innovation theory’ and ‘unified theory of acceptance and use of technology’ with behavioural economics. Using mixed ‘partial least squares structural equation modelling (PLS-SEM) and fuzzy-set qualitative comparative analysis (FsQCA)’, 513 valid responses from investors were analyzed to examine the relationships. The results revealed that relative advantage and internal locus of control emerged as the most prominent antecedents for investment intention using robo-advisors. Notably, an integrated framework increased the model’s applicability, predictability and robustness by recognizing behavioural antecedents that affect technology perception and finally behavioural intention. This research offers the significance of behavioural economics in research pertaining to information systems because they had never been explored with respect to fintech adoption in the available literature. Moreover, these biases have not been included in the theoretical models that still assume rational behaviour in the fintech domain and hence present a strong case for novelty.