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Artificial intelligence technology, competitive aggressiveness and foreign diversification
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DOI：10.1007/s10490-026-10160-7.png)
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Abstract
En 中文
Foreign diversification has become increasingly important for EMNEs seeking to enhance resilience amid rising de-globalization pressures. Yet broad geographic expansion remains particularly challenging for EMNEs because they often lack transferable firm-specific advantages and accumulated international experience. Although recent research has begun to examine the role of AI in internationalization, limited attention has been paid to whether and how AI shapes the geographic breadth of firms’ international expansion. Drawing on an human–AI hybrid search perspective, this study examines how the adoption of AI technology influences EMNEs’ foreign diversification and through what mechanisms this effect unfolds. Using a longitudinal panel of Chinese A-share listed firms with overseas subsidiaries from 2011 to 2022, we find that the adoption of AI technology is positively associated with broader foreign diversification. This relationship is partially mediated by competitive aggressiveness, suggesting that AI facilitates geographic expansion by strengthening firms’ proactive and opportunity-seeking strategic posture. We further identify two boundary conditions: regional digital development strengthens the relationship between the adoption of AI technology and competitive aggressiveness, while internationalization experience strengthens the relationship between competitive aggressiveness and foreign diversification. By shifting attention from the pace, mode, and performance of internationalization to the geographic breadth of expansion, this study advances research on AI-driven internationalization and EMNE strategy. It also highlights the strategic importance of integrating AI-enabled analytics with managerial judgment in pursuing foreign diversification under global uncertainty.
Keywords:
Foreign diversification
Artificial intelligence technology
Competitive aggressiveness
Human–AI hybrid search perspective
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