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| A Sequential Mediation Model of the Factors Influencing the User Adoption of Robo-advisor: A Technology Acceptance Model (TAM) Perspective |
| Wu Xiaobo, Zhang Weiqi, Li Sihan, Zou Tengjian |
| School of Management, Zhejiang University, Hangzhou 310058, China |
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Abstract In the era of digital economy, a new generation of digital technologies represented by artificial intelligence, cloud computing, big data, and blockchain has flourished and gradually developed into an important pillar of the global technology and economy. The effective integration of digital technology and traditional industry is not only a trendy topic in China’s current socio-economic development stage, but also an important issue in academic research. This study mainly focuses on the application of artificial intelligence technology in the financial services sector. The adoption and application of artificial intelligence technology have become the key factors in improving efficiency, convenience, and security. They continuously drive the transformation of economic models, thus becoming a new growth pole in the digital economy. The intelligent investment advisor based on artificial intelligence technology is a typical manifestation of intelligent finance. In the extant research that regards investment tools with artificial intelligence algorithms as the research object, more attention is paid to two aspects: algorithm model and data analysis, as well as investment risk analysis. While continuously promoting technology optimization, the scope of audience is also expanding. Few studies have explored the subjective mechanism and internal driving factors of adoption intention from the perspective of users. This study takes Technology Acceptance Model (TAM) as the main theoretical basis and research foundation. According to the three-tier structure of “attitude-intention-behavior” in the TAM framework, we explore in depth the impact of perceived usefulness, perceived ease of use, and trust on user’s attitude, behavior intention, and willingness to adopt Robo-advisor, which has both theoretical contributions and practical implications. We use the method of questionnaire survey in the empirical analysis, with a total of 335 questionnaires distributed and 325 valid samples obtained. Perceived usefulness, perceived ease of use, and trust are taken as our independent variables. The bootstrap method and the hierarchical regression analysis are used to verify the dual mechanism (i.e., attitude, behavior intention) through which the three independent variables ultimately affect users’ adoption willingness. The research conclusions and findings are mainly reflected in the following three aspects. First, the empirical results show that individual investor users’ perceived usefulness, perceived ease of use and trust in intelligent investment advisors can significantly improve the user’s attitude for use. In addition, according to the characteristics of Robo-advisors as well as the psychological traits of individual investment users, this study includes trust into exogenous factors, which extend the applicability of TAM models in fields like intelligent financial services. Second, the study finds that individual investor users’ perceived usefulness, perceived ease of use, and trust in intelligent investment advisors promote user behavior intention by enhancing their attitude for use, which provides an empirical basis for the important mechanism of “exogenous variable-attitude-intention” in the TAM model. Third, this study takes perceived usefulness, perceived ease of use, and trust as exogenous variables. The empirical results show that individual investor users’ perceived usefulness, perceived ease of use, and trust in intelligent investment advisors can enhance their attitude for use, thereby enhancing users’ behavior intention, and ultimately increasing users’ willingness to adopt Robo-advisors. These findings provide an important empirical basis for the “attitude-intention-behavior” structure influenced by exogenous variables. They also fill in the research gap that the current micro-research on artificial intelligence technology in the field of financial services is less and incomplete. Overall, from the three perspectives of the service objects of intelligent investment advisors, individual investors participating in the capital market, and policy-making departments, this study puts forward a number of helpful suggestions for the development of the industry. These suggestions can on the one hand foster the beneficial change of the sector by adopting new digital technologies, and on the other hand prevent “pseudo-intelligence” from disrupting the order of the financial service market and better protect the rights and interests of users.
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Received: 02 November 2022
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2023, Vol. 53 
