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<p>Artificial intelligence (AI) is increasingly integrated into business operations, including production, innovation, and marketing. However, there is limited understanding of how industry-level and firm-level AI development jointly affect firms’ domestic and overseas performance. Drawing on the perspective of transaction cost, our research investigates how industry AI exposure differentially affects firms’ domestic and overseas performance by reducing the costs associated with information search, communication, decision-making, and supervision and how firm-level AI deployment moderates these relationships. To test our theoretical model, we employ fixed-effect models using a sample of 21,314 observations from 2,847 firms. The results reveal the direct positive influence of industry AI exposure on firm performance, with notably stronger effects observed for overseas operations compared to domestic performance. Furthermore, we identify firm-level AI deployment as a crucial moderating factor, particularly in overseas business contexts where the moderating effect proves more pronounced than in domestic markets. This study enriches the existing literature on AI and transaction costs, providing a more comprehensive understanding of AI’s role in domestic and international business transactions.</p>

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Navigating domestic and overseas performance with artificial intelligence: opportunity or threat?

  • 期刊论文

  • 发表日期：

    2025年11月12日

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  • Qingwen Bo,
  • Peng Ding,
  • Wen Helena Li,
  • Wei Liu

摘要

Artificial intelligence (AI) is increasingly integrated into business operations, including production, innovation, and marketing. However, there is limited understanding of how industry-level and firm-level AI development jointly affect firms’ domestic and overseas performance. Drawing on the perspective of transaction cost, our research investigates how industry AI exposure differentially affects firms’ domestic and overseas performance by reducing the costs associated with information search, communication, decision-making, and supervision and how firm-level AI deployment moderates these relationships. To test our theoretical model, we employ fixed-effect models using a sample of 21,314 observations from 2,847 firms. The results reveal the direct positive influence of industry AI exposure on firm performance, with notably stronger effects observed for overseas operations compared to domestic performance. Furthermore, we identify firm-level AI deployment as a crucial moderating factor, particularly in overseas business contexts where the moderating effect proves more pronounced than in domestic markets. This study enriches the existing literature on AI and transaction costs, providing a more comprehensive understanding of AI’s role in domestic and international business transactions.