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Digital disruption, knowledge and collaborative networks and green innovation in China manufacturing transformation

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  • Xiao, Yao
  • Xiang, Rong
  • Sun, Yong-lei
  • Chen, Jin
  • Hao, Yun-hong

Abstract

Green innovation is essential for sustainable development but often incurs high costs, reducing economic returns. Grounded in disruptive innovation and social network theory, this study examines whether disruptive events experienced by Chinese manufacturing firms during their digital transformation can reduce green R&D and manufacturing costs, thereby promoting green innovation. Using patent data from China's high-tech manufacturing sector (2014–2023), the study finds an inverted U-shaped relationship between Digital Disruptive Events (DDE) and Green Innovation (GI). The network structure of knowledge and collaboration plays varying moderating roles in this relationship. Structural holes in a firm's knowledge network negatively moderate the effect of DDE on GI, while degree centrality shows no significant moderation. Conversely, more structural holes and lower degree centrality in collaboration networks positively influence GI. The findings highlight the importance of leveraging multilayered network structures to drive green innovation during digital transformation.

Suggested Citation

  • Xiao, Yao & Xiang, Rong & Sun, Yong-lei & Chen, Jin & Hao, Yun-hong, 2025. "Digital disruption, knowledge and collaborative networks and green innovation in China manufacturing transformation," Technological Forecasting and Social Change, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:tefoso:v:216:y:2025:i:c:s0040162525001519
    DOI: 10.1016/j.techfore.2025.124120
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