Abstract
Artificial intelligence (AI) is profoundly reshaping the global supply chain landscape. However, the mechanism through which Chinese small and medium-sized enterprises (SMEs), under resource constraints, acquire AI capabilities through digital platforms and transform them into supply chain resilience has not been adequately theorized. This paper develops an integrated theoretical framework that combines the Technology–Organization–Environment (TOE) framework with dynamic capability theory. It proposes the analytical concept of “platform-enabled AI adoption" to characterize the distinctive technology adoption pattern through which Chinese SMEs acquire, integrate, and utilize AI capabilities via external digital platforms. Using a literature review and case analysis approach, and drawing on the 2025 survey report of the China Academy of Information and Communications Technology, publicly available operating data from the 1688 platform and Haizhi Online, and relevant academic literature from the past decade, this paper systematically analyzes three mediating pathways through which platform-enabled AI adoption affects supply chain resilience: supply chain visibility, supply chain agility, and supply chain collaboration. It further discusses the moderating roles of technological readiness and organizational readiness in this relationship and offers methodological suggestions for future empirical research. This paper provides a theoretical foundation for understanding the relationship between AI adoption and supply chain resilience among Chinese SMEs in the digital platform context and offers testable research propositions for subsequent empirical examination.
Keywords
Platform-enabled AI AdoptionSupply Chain ResilienceChinese SMEsTOE FrameworkDynamic CapabilitiesDigital Platforms
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Cite This Article
Pan, D. (2026). Platform-enabled ai adoption and supply chain resilience in chinese smes: an integrated theoretical framework. Academic Journal of Sociology and Management, 4(5), 6-12. https://doi.org/10.70393/616a736d.343430
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