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<p>The diffusion of digital technologies has driven the transformation and upgrading of manufacturing industries. However, the main pathways and formation mechanisms of digital technology diffusion remain unclear. Using patent data of China’s manufacturing digital technologies from 2000–2024, this study constructs a multilayer network comprising patent citation networks, inter-organizational technology diffusion networks, and geographical technology diffusion networks. Through main path analysis and exponential random graph models (ERGM), we analyze the formation mechanisms of China’s digital technology diffusion pathways. The findings identify 14 main paths in patent citation networks, spanning from core technologies like image recognition to enabling applications. Inter-organizational paths center on key universities, while geographical networks exhibit a “core-periphery” structure. ERGM results reveal that technological collaboration value and combination opportunities consistently promote main path formation. However, technological diversity and proximity exhibit differentiated effects across network layers. In patent networks, neither diversity nor proximity shows significant impact, suggesting that patent citation-based diffusion prioritizes technological value and recombination potential over field diversity or similarity. In inter-organizational networks, only diversity promotes path formation, highlighting how knowledge recombination drives micro-level trajectories. Conversely, in geographical networks, both diversity and proximity inhibit path formation, indicating that macro-regional evolution requires specialized focus and complementary knowledge. Heterogeneity analysis further reveals distinct evolutionary logics: universities bridge distant domains through knowledge diversity, whereas market-driven enterprises heavily rely on high-value core technologies. Spatially, Western regions rely heavily on core technological hubs, Eastern regions are driven by knowledge recombination opportunities, and Central regions have not yet formed a dominant diffusion mechanism. This study uncovers digital diffusion dynamics and provides theoretical foundations for policymaking.</p>

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Mapping China’s digital transformation: a multilayer network analysis of technology diffusion in manufacturing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月17日

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  • Jialu Ren,
  • Yong Zhou,
  • Yangyang Yang,
  • Shengkai Wang

摘要

The diffusion of digital technologies has driven the transformation and upgrading of manufacturing industries. However, the main pathways and formation mechanisms of digital technology diffusion remain unclear. Using patent data of China’s manufacturing digital technologies from 2000–2024, this study constructs a multilayer network comprising patent citation networks, inter-organizational technology diffusion networks, and geographical technology diffusion networks. Through main path analysis and exponential random graph models (ERGM), we analyze the formation mechanisms of China’s digital technology diffusion pathways. The findings identify 14 main paths in patent citation networks, spanning from core technologies like image recognition to enabling applications. Inter-organizational paths center on key universities, while geographical networks exhibit a “core-periphery” structure. ERGM results reveal that technological collaboration value and combination opportunities consistently promote main path formation. However, technological diversity and proximity exhibit differentiated effects across network layers. In patent networks, neither diversity nor proximity shows significant impact, suggesting that patent citation-based diffusion prioritizes technological value and recombination potential over field diversity or similarity. In inter-organizational networks, only diversity promotes path formation, highlighting how knowledge recombination drives micro-level trajectories. Conversely, in geographical networks, both diversity and proximity inhibit path formation, indicating that macro-regional evolution requires specialized focus and complementary knowledge. Heterogeneity analysis further reveals distinct evolutionary logics: universities bridge distant domains through knowledge diversity, whereas market-driven enterprises heavily rely on high-value core technologies. Spatially, Western regions rely heavily on core technological hubs, Eastern regions are driven by knowledge recombination opportunities, and Central regions have not yet formed a dominant diffusion mechanism. This study uncovers digital diffusion dynamics and provides theoretical foundations for policymaking.