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Intelligent finance and change management implications

Author

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  • Haochen Guo

    (Southeast University)

  • Petr Polak

    (Mendel University in Brno)

Abstract

Change management is the embodiment of an enterprise’s core competence. It provides competitive differentiation and effectively adapts to the ever-changing world. This paper explores the implications of intelligent finance on change management and provides insights into how organizations can effectively manage change to achieve the desired outcomes. The study examines the case of Ping An (Ping An Insurance (Group) Company of China, Ltd.), a leading insurance company in China that has successfully implemented intelligent finance and change management strategies. The paper begins with a literature review that provides an overview of the concept of intelligent finance, the relevance of change management in the context of intelligent finance, models, and frameworks for intelligent finance, and approaches to change management. The study then presents a case analysis of Ping An, including descriptive statistics, inferential statistics, regression analysis, and qualitative findings. The paper concludes with implications for practice and theory, contributions of the study, and recommendations for future research. Overall, this paper contributes to the growing literature on intelligent finance and change management and provides practical insights for organizations seeking to adopt intelligent finance.

Suggested Citation

  • Haochen Guo & Petr Polak, 2023. "Intelligent finance and change management implications," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-8, December.
    • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01923-4
    DOI: 10.1057/s41599-023-01923-4
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    References listed on IDEAS

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    1. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    2. Emmanouil Papagiannidis & Ida Merete Enholm & Chirstian Dremel & Patrick Mikalef & John Krogstie, 2023. "Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes," Information Systems Frontiers, Springer, vol. 25(1), pages 123-141, February.
    3. Gratiela Dana Boca, 2013. "Adkar Model Vs. Quality Management Change," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 246-253.
    4. Jon Truby, 2020. "Governing Artificial Intelligence to benefit the UN Sustainable Development Goals," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 946-959, July.
    5. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
    6. Heping Pan & Didier Sornette & Kenneth Kortanek, 2006. "Intelligent finance—an emerging direction," Quantitative Finance, Taylor & Francis Journals, vol. 6(4), pages 273-277.
    7. Huang, Feiqi & Vasarhelyi, Miklos A., 2019. "Applying robotic process automation (RPA) in auditing: A framework," International Journal of Accounting Information Systems, Elsevier, vol. 35(C).
    8. Verhoef, Peter C. & Broekhuizen, Thijs & Bart, Yakov & Bhattacharya, Abhi & Qi Dong, John & Fabian, Nicolai & Haenlein, Michael, 2021. "Digital transformation: A multidisciplinary reflection and research agenda," Journal of Business Research, Elsevier, vol. 122(C), pages 889-901.
    9. repec:eme:mfppss:mf-04-2020-0169 is not listed on IDEAS
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    2. Claudiu George Bocean & Anca Antoaneta Vărzaru, 2023. "EU countries’ digital transformation, economic performance, and sustainability analysis," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.

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