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Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach

Author

Listed:
  • Xusen Cheng

    (School of Information Technology & Management, University of International Business and Economics, Beijing 100029, China)

  • Fei Guo

    (School of Information Technology & Management, University of International Business and Economics, Beijing 100029, China)

  • Jin Chen

    (School of Information Technology & Management, University of International Business and Economics, Beijing 100029, China)

  • Kejiang Li

    (School of Information Technology & Management, University of International Business and Economics, Beijing 100029, China)

  • Yihui Zhang

    (School of Information Technology & Management, University of International Business and Economics, Beijing 100029, China)

  • Peng Gao

    (School of Information Technology & Management, University of International Business and Economics, Beijing 100029, China)

Abstract

As a typical application of fintech, the robo-advisor has increasingly gained attention over the last decade. However, most research regarding the robo-advisor has focused on its development issues such as performance improvement and regulation, while limited research has paid attention to trust. This research extends the literature by investigating the trust influencing mechanism of robo-advisors by a mixed method approach. Specifically, we identified six salient trust influencing factors by qualitative interviews and proposed the research model based on trust transfer theory. This model was tested via a survey of 230 investors. Our study finds the significant influencing role of supervisory control and validates the relationships among trust influencing factors, trust in technologies, trust in vendor and trust in robo-advisor. Moreover, several differences between junior investors and senior investors are also found in our research. This study examines trust transfer theory in the new context of the robo-advisor and contributes to further development of this increasingly utilized service.

Suggested Citation

  • Xusen Cheng & Fei Guo & Jin Chen & Kejiang Li & Yihui Zhang & Peng Gao, 2019. "Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach," Sustainability, MDPI, vol. 11(18), pages 1-20, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:4917-:d:265474
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    3. Claas Digmayer, 2024. "Automated Economic Welfare for Everyone? Examining Barriers to Adopting Robo-Advisors from the Perspective of Explainable Artificial Intelligence," Journal of Interdisciplinary Economics, , vol. 36(2), pages 224-245, July.
    4. Mike K. P. So, 2021. "Robo-Advising Risk Profiling through Content Analysis for Sustainable Development in the Hong Kong Financial Market," Sustainability, MDPI, vol. 13(3), pages 1-15, January.

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