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The data-driven decision-making, sustainable value creation, and international firm performance: Micro-level evidence based on AI language models

Author

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  • Miao Xu
  • Bing Lu

Abstract

Data-driven decision-making (DDDM) has become integral to managerial and organizational processes in the era of digitalization and internationalization. This study explores the impact of DDDM on international firm performance. Leveraging AI language models, specifically BERT and ChatGLM2-6B, to quantify DDDM, we find that DDDM positively impacts international firm performance. To uncover the mechanisms underlying this correlation, we develop a framework explaining how DDDM creates sustainable value for firms, thereby enhancing international firm performance across four dimensions: pollution prevention (current internal), green innovation (future internal), sustainability information disclosure (current external), and sustainability vision co-creation (future external). Additionally, this study reveals that the positive impact of DDDM on international firm performance is amplified by higher market competition, greater foreign shareholding, and state ownership.

Suggested Citation

  • Miao Xu & Bing Lu, 2026. "The data-driven decision-making, sustainable value creation, and international firm performance: Micro-level evidence based on AI language models," PLOS ONE, Public Library of Science, vol. 21(2), pages 1-22, February.
    • Handle: RePEc:plo:pone00:0340731
    DOI: 10.1371/journal.pone.0340731
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