An Empirical Study of Factors Influencing the Intention to Use Robo-Advisors

Abstract

Artificial intelligence-based investment services (robo-advisors) are becoming increasingly commercialized. Robo-advisors are expected to expand further due to the enhancement of accessibility to investment for general investors through customized portfolio selection and automated transactions established upon the artificial intelligence-based algorithm. This study comprehensively investigates factors that influence acceptance intention of and resistance to robo-advisors using a combined model of technology acceptance model and innovation resistance model. The model was examined through conducting a choice-based conjoint analysis of 158 users with investment experience and age ranging from 20s to 60s. The independent variables of the research for robo-advisors are transparency, customization, social presence, and user control. The effects of the independent variables on acceptance intention and innovation resistance are analyzed, respectively, through mediator variables of perceived usefulness, perceived complexity, and perceived safety. This study indicates the fundamental factors for the promotion of the domestic robo-advisor market based on the analysis of further advanced overseas robo-advisor markets. The significance of this study derives from providing implications on the direction of development for companies or financial institutions in the sphere of robo-advisors.