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Artificial Intelligence and Firm Value: A Bibliometric and Systematic Literature Review

Author

Listed:
  • Alexandros Koulis

    (School of Social Sciences, Hellenic Open University, 26331 Patras, Greece)

  • Constantinos Kyriakopoulos

    (Department of Mathematics, National and Kapodistrian University of Athens, 15772 Athens, Greece)

  • Ioannis Lakkas

    (School of Social Sciences, Hellenic Open University, 26331 Patras, Greece)

Abstract

Objective: This study investigates how artificial intelligence (AI) research relates to firm value, focusing on dominant thematic trends, theoretical foundations, and global collaboration patterns. Methods: A PRISMA-guided systematic review was conducted on 219 peer-reviewed articles published between 2013 and May 2025 in the Web of Science Social Sciences Citation Index. Bibliometric techniques, including co-word, co-citation, and collaboration network analyses, were performed using the bibliometrix (version 4.2.3) in R (version 4.4.2) package to map key concepts, intellectual structures, and international research partnerships. Results: The literature is primarily grounded in strategic management theories such as the resource-based view (RBV) and dynamic capabilities. Emerging research streams emphasize digital transformation, big data analytics, and decision support systems. Frequently co-occurring terms include “firm performance,” “artificial intelligence,” “dynamic capabilities,” “information technology,” and “decision-making.” Collaboration mapping highlights the United States, United Kingdom, and China as leading hubs, with increasing contributions from emerging economies such as India, Malaysia, and Saudi Arabia. The alignment between co-word and co-citation structures reflects a shift from foundational theory to applied AI capabilities in firm-value creation. Implications: By integrating a systematic review with advanced bibliometric and science-mapping methods, this work establishes a structured foundation for theory development, empirical testing, and policy formulation in AI-driven business landscapes.

Suggested Citation

  • Alexandros Koulis & Constantinos Kyriakopoulos & Ioannis Lakkas, 2025. "Artificial Intelligence and Firm Value: A Bibliometric and Systematic Literature Review," FinTech, MDPI, vol. 4(4), pages 1-20, October.
    • Handle: RePEc:gam:jfinte:v:4:y:2025:i:4:p:54-:d:1765389
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    References listed on IDEAS

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    Cited by:

    1. Catherine Georgiou, 2025. "Puzzling behavioral mechanisms under extreme market conditions: A bibliometric and systematic literature review," Bulletin of Applied Economics, Risk Market Journals, vol. 12(2), pages 209-229.

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