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Cross-National Findings of Factors Affecting the Acceptance of AI-Based Sustainable Fintech

Author

Listed:
  • Sujin Park

    (Department of Global Business, Kyonggi University, Suwon 16227, Republic of Korea)

  • Sungjoon Yoon

    (Department of Global Business, Kyonggi University, Suwon 16227, Republic of Korea)

Abstract

This study utilized mixed (qualitative and quantitative) methods to discover the current research trends for AI in sustainable Fintech and to validate a research model through empirical analysis. The primary purpose of this research is to explore the factors influencing the acceptance of AI tools within the sustainable Fintech industry through a cross-national perspective, identifying key benefit and sacrifice dimensions, along with sustainability considerations, that affect users’ intentions to adopt AI tools. Drawing on a bibliometric keywords approach, we first conducted an overall review of academic literature using Web of Science and VOSviewer (version 1.6.17), covering areas related to AI applications in Fintech and sustainable Fintech practices. Additionally, for a cross-national study, this study built and validated a conceptual framework on the intention to use AI tools by selecting subjects from Republic of Korea and China. As core theoretical premises of the conceptual framework, the study drew on the Value-Based Adoption Model (VAM) and the Technology Acceptance Model (TAM). Furthermore, we extended the TAM to embrace sustainable dimensions (perceived responsibility and perceived transparency). Overall, the study concludes that AI not only improves Fintech efficiency but also significantly contributes to sustainable development, suggesting collaboration between experts in AI, finance, sustainability, and other relevant fields for more research on AI integration with sustainable Fintech management. This research contributes to existing literature by highlighting the synergistic benefits of combining AI and sustainable Fintech and offers practical insights for industry practitioners and policymakers.

Suggested Citation

  • Sujin Park & Sungjoon Yoon, 2024. "Cross-National Findings of Factors Affecting the Acceptance of AI-Based Sustainable Fintech," Sustainability, MDPI, vol. 17(1), pages 1-32, December.
    • Handle: RePEc:gam:jsusta:v:17:y:2024:i:1:p:49-:d:1553122
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    References listed on IDEAS

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    1. Manuela Veloso & Tucker Balch & Daniel Borrajo & Prashant Reddy & Sameena Shah, 2021. "Artificial intelligence research in finance: discussion and examples," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 564-584.
    2. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    3. Asrar Ahmed Sabir & Iftikhar Ahmad & Hassan Ahmad & Muhammad Rafiq & Muhammad Asghar Khan & Neelum Noreen, 2023. "Consumer Acceptance and Adoption of AI Robo-Advisors in Fintech Industry," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
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