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The impact of artificial intelligence technology on cross-border trade in Southeast Asia: A meta-analytic approach

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  • Jun Cui

Abstract

This study investigates the impact of artificial intelligence (AI) technology on cross-border trade using a qualitative content analysis approach. By synthesizing existing empirical studies, we aim to quantify the overall effect of AI on trade flows and identify the key moderating and mediating variables. Besides, our results show that AI adoption significantly increases trade volumes in Southeast Asia. Likewise, these effects are stronger in regions with advanced technological infrastructure and favorable regulatory frameworks. In addition, Trade firm size partially mediates the relationship between AI technology and trade performance. Furthermore, this study draws on several key theoretical frameworks that provide a comprehensive understanding of the mechanisms through which AI technology is affecting cross-border trade in Southeast Asia. The primary theories used in this research include the technology, organization, and environment (TOE) framework, the diffuse innovation (DOI) theory, Dynamic Capabilities Theory, Comparative Advantage Theory, Network theory, Transaction Cost Economics (TCE), the resource-based view, and the institution theory. Consequently, this study contributes to the existing literature by providing a comprehensive analysis of the role of AI in international trade and highlighting the importance of contextual factors in maximizing the benefits of AI. Thus, our findings underscore the need for favorable policies and robust infrastructure to facilitate AI-driven trade growth. A discussion of limitations and future research directions will also be part of the report in Southeast Asia Trade.

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  • Jun Cui, 2025. "The impact of artificial intelligence technology on cross-border trade in Southeast Asia: A meta-analytic approach," Papers 2503.13529, arXiv.org.
    • Handle: RePEc:arx:papers:2503.13529
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