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Understanding the Acceptance of Robo-Advisors: Towards a Hierarchical Model Integrated Product Features and User Perceptions

2021; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-030-78108-8_20

1611-3349

Man Wu, Qin Gao,

Consumer Retail Behavior Studies

Robo-advisors have recently become increasingly accessible and gaining interest among consumers. However, there still exist problems in acceptance of robo-advisors among consumers. In this study, we have identified influential factors of robo-advisor acceptance, conducting an online survey involving 207 participants to examine their relationship with use intention. A hierarchical model of robo-advisor acceptance was built that integrated product features, user perceptions, and use intention. The model showed that the competence and expected earnings of a robo-advisor contribute to users' perception of its usefulness. Furthermore, the customization and competence of a robo-advisor decreases users' perceived risk. Additionally, better designed account management and more authority for users increase perceived control over a robo-advisor. Moreover, although usefulness was regarded as the most important factor, only perceived risk (negatively) and perceived control (positively) were significantly associated with the intention to use robo-advisors. Based on the acceptance model, implications for the robo-advisor design were discussed.