Investor Decision-Making in Robo-Advisory Services: A Trust-Mediated Perspective

Abstract

Robo-advisory services offer automated, algorithm-based investment advice and portfolio management, enabling cost efficiency and wider access to financial services. Despite these advantages, adoption in emerging economies remains limited due to psychological, cognitive, and social barriers. Trust is particularly critical in financial decision-making, as it reduces perceived risk and uncertainty associated with algorithm-driven systems. Trust is an important component, since adoption depends on people's faith in technological advances and the safety of their investments. The study purposes to contribute to the larger in the field of financial technology analysing the factors which impact on the adoption of Robo-advisory services and provide new insights into the psychological and social dynamics. Using a quantitative research design, primary data were collected from 285 investors through a structured questionnaire. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was employed to test the proposed relationships among financial awareness, behavioral biases, innovativeness, subjective norms, trust, and intention to use robo-advisory services. The results indicate that trust is the strongest predictor of adoption intention and significantly mediates the effects of key antecedent variables. The findings could help policy-makers and financial institutions to enhance the features of robo-advisory services with targeted interventions and marketing strategies.