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Under the pressure of dynamic business environments, firms in the banking and finance industry are gradually embracing Fintech, such as robo-advisors, as part of their digital transformation process. While robo-advisory services are expected to witness lucrative growth, challenges persist in the current landscape where most consumers are unready to adopt and even resist the new service. The study aims to investigate resistance to robo-advisors through the privacy and justice perspective. The human-like attributes are modeled as the antecedents to perceived justice, followed by the subsequent outcomes of privacy concerns, perceived intrusiveness and resistance.

An online survey was conducted to gather consumer responses about their perceptions of robo-advisors. Two hundred valid questionnaires were collected and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results revealed that (1) perceived anthropomorphism and perceived autonomy are the positive determinants of perceived justice, (2) perceived justice negatively impacts privacy concerns and perceived intrusiveness and (3) privacy concerns and perceived intrusiveness positively influence resistance to robo-advisors.

The present study contributes to robo-advisory service research by applying a privacy and justice perspective to explain consumer resistance to robo-advisors, thereby complementing past studies that focused on the technology acceptance paradigm. The study also offers practical implications for mitigating resistance to robo-advisors.