Big data analytical capabilities (BDAC) have emerged as a significant strategic tool for enhancing environmental performance in today's ever‐growing green and digital economy. However, the serial process through which BDAC influences environmental performance remains understudied, particularly in multinational corporations (MNCs). Drawing on the dynamic capability view (DCV) and the natural resource‐based view (NRBV), this study constructs a serial mediation model to explore the connection between BDAC, ambidextrous green innovation, green competitive advantage, and corporate environmental performance. A cross‐sectional survey involving 244 MNCs in Germany was used for the analysis. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM). Our findings reveal that the impact of BDAC on environmental performance is sequential, occurring through ambidextrous green innovation and the development of green competitive advantage. Specifically, BDAC leads to ambidextrous green innovation, which in turn drives green competitive advantage and ultimately enhances the environmental performance of MNCs. The theoretical and managerial implications are drawn.

中文翻译：

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对大数据分析功能在影响企业环境绩效中的作用进行建模：序列中介分析

在当今不断增长的绿色和数字经济中，大数据分析能力 （BDAC） 已成为提高环境绩效的重要战略工具。然而，BDAC 影响环境绩效的一系列过程仍然没有得到充分研究，尤其是在跨国公司 （MNC） 中。借鉴动态能力视图 （DCV） 和基于自然资源的视图 （NRBV），本研究构建了一个系列中介模型，以探索 BDAC、灵巧绿色创新、绿色竞争优势和企业环境绩效之间的联系。分析采用了一项涉及德国 244 家跨国公司的横断面调查。使用偏最小二乘结构方程模型 （PLS-SEM） 对数据进行分析。我们的研究结果表明，BDAC 对环境绩效的影响是连续的，通过灵巧的绿色创新和绿色竞争优势的发展发生。具体来说，BDAC 导致了灵巧的绿色创新，这反过来又推动了绿色竞争优势，并最终提高了跨国公司的环境绩效。得出了理论和管理意义。