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浙江大学学报(人文社会科学版)  2023, Vol. 53 Issue (7): 5-19    DOI: 10.3785/j.issn.1008-942X.CN33-6000/C.2022.11.026
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基于技术接受模型(TAM)的智能投资顾问用户采纳意愿链式影响机制研究
吴晓波, 张伟齐, 李思涵, 邹腾剑
浙江大学 管理学院,浙江 杭州 310058
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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摘要 基于人工智能技术的智能投资顾问在为投资者提供理财服务的过程中扮演着愈发重要的角色,但目前仅有少数投资者愿意使用该项服务。基于技术接受模型(TAM)的研究发现,用户感知有用性、感知易用性和信任均能通过用户使用态度和用户行为意向两个中介渠道对智能投资顾问的采纳意愿产生显著正向影响。此发现在一定程度上拓展了TAM在金融服务领域的应用和研究,对金融服务领域的实践也具有重要意义。未来,智能投资顾问服务企业应加强数据分析能力,完善人工智能算法模型,注重提升用户体验,增强用户黏性;政府相关部门也应加强对智能投资顾问市场的监管力度。
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吴晓波
张伟齐
李思涵
邹腾剑
关键词 智能投资顾问人工智能技术接受模型用户采纳意愿多重中介    
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.
Key wordsRobo-advisor    artificial intelligence    TAM    users’ adoption willingness    multiple mediation   
收稿日期: 2022-11-02     
基金资助:国家自然科学基金青年项目(72202206);中央高校基本科研业务费专项资金项目;国家自然科学基金重点项目(71832013);教育部人文社会科学研究青年基金项目(22YJCZH257)
作者简介: 吴晓波(https://orcid.org/0000-0002-9663-0693),男,浙江大学管理学院教授,博士生导师,管理学博士,主要从事战略管理、创新管理、全球化制造与竞争战略等方面的研究;;张伟齐(https://orcid.org/0000-0002-3190-9984),男,浙江大学管理学院博士研究生,主要从事创新管理、战略管理、数字化转型等方面的研究;;李思涵(https://orcid.org/0000-0002-9113-528X)(通信作者),男,浙江大学管理学院博士研究生,主要从事创新管理、战略管理、数字化转型等方面的研究;;邹腾剑(https://orcid.org/0000-0003-0831-6643),男,浙江大学管理学院“百人计划”研究员,博士生导师,管理学博士,主要从事创新管理、战略管理等方面的研究;
引用本文:   
吴晓波, 张伟齐, 李思涵, 邹腾剑. 基于技术接受模型(TAM)的智能投资顾问用户采纳意愿链式影响机制研究[J]. 浙江大学学报(人文社会科学版), 2023, 53(7): 5-19. Wu Xiaobo, Zhang Weiqi, Li Sihan, Zou Tengjian. A Sequential Mediation Model of the Factors Influencing the User Adoption of Robo-advisor: A Technology Acceptance Model (TAM) Perspective. JOURNAL OF ZHEJIANG UNIVERSITY, 2023, 53(7): 5-19.
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https://www.zjujournals.com/soc/CN/10.3785/j.issn.1008-942X.CN33-6000/C.2022.11.026     或     https://www.zjujournals.com/soc/CN/Y2023/V53/I7/5
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