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From Intuition To Algorithms: The Transformation Of Decision- Making Through Intelligent Data Technologies – A Bibliometric Study (2019-2024)

Author

Listed:
  • Doroteea Andreea SURLEA

    (University of Oradea, Doctoral School in Economic Sciences, Oradea, Romania)

Abstract

This paper examines the relationship between decision-making in the financial sector and the role of intelligent data analysis technologies. The present study uses bibliometric methods on articles published between 2019 and 2024, sourced from Web of Science and Scopus, and processed with Bibliometrix (RStudio) and VOSviewer. After filtering and unifying the datasets, a final sample of 2,522 articles was analysed. The results identify clusters, highlighting the growing emphasis on artificial intelligence, big data, and machine learning as tools to support decision-making. In addition to the existing mapping trends, this study highlights the structural organization of the field by identifying motor themes, emerging themes, and conceptual clusters that shape the current scientific dialogue. The combination of the two bibliometric analysis tools, R Bibliometrix and VOSviewer, improves the robustness of the results by ensuring cross-validation between the analytical tools. The findings confirm a paradigm shift: traditional reliance on intuition is increasingly being replaced by evidence-based approaches driven by smart technologies. The article provides a strategic perspective on how intelligent data analysis technologies are reshaping the decision-making process in the financial field, going beyond a descriptive overview of the literature. This study contributes to the literature by providing an updated mapping of research trends and outlining the evolution and multidisciplinary nature of this emerging research area, offering valuable insights for scholars and practitioners in finance and management. The results of the study indicate that current research integrates several fields, making it multidisciplinary. In this case, the study encompasses technological, economic- financial, and managerial fields.

Suggested Citation

  • Doroteea Andreea SURLEA, 2025. "From Intuition To Algorithms: The Transformation Of Decision- Making Through Intelligent Data Technologies – A Bibliometric Study (2019-2024)," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 34(2), pages 292-300, December.
    • Handle: RePEc:ora:journl:v:34:y:2025:i:2:p:292-300
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    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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