The mechanism of pollution prevention.

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.

在数字化与国际化时代，数据驱动决策（Data-driven decision-making，DDDM）已成为管理与组织运营流程中不可或缺的核心组成部分。本研究聚焦数据驱动决策对跨国企业经营绩效的影响。本研究采用人工智能语言模型（具体为BERT与ChatGLM2-6B）对数据驱动决策水平进行量化，研究结果表明，数据驱动决策对跨国企业经营绩效具有显著正向影响。为揭示该关联背后的作用机理，本研究构建了一套分析框架，阐释数据驱动决策如何为企业创造可持续价值，进而从四大维度提升跨国企业经营绩效：污染防治（当前内部维度）、绿色创新（未来内部维度）、可持续发展信息披露（当前外部维度）以及可持续发展愿景共创（未来外部维度）。此外，本研究还发现，市场竞争程度越高、外资持股比例越大以及国有产权属性，均会强化数据驱动决策对跨国企业经营绩效的正向影响。