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Knowledge base, innovation network, and innovation in different types of high-tech industries - a comparative study of STI (science-technology-innovation) and DUI (learning by doing, using and interacting)-type industry in China

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  • Zefeng Mi
  • Ying Sun
  • Zhixin Qiu
  • Jingxuan Fu

Abstract

As the core of national competitiveness and a key driver of innovation, China’s high-tech industry development has attracted much attention. This article divides knowledge base into scientific and technological knowledge and classifies high-tech industries into STI (Science-Technology-Innovation) and DUI (Learning by Doing, Using, and Interacting) industries. Using a negative binomial regression model, it examines the relationship between knowledge base, innovation network, and high-tech industries at the urban level and how knowledge base moderates the impact of innovation network on innovation performance. Results show that STI-type industry concentrate in a few developed regions with limited diffusion, driven by scientific knowledge, whereas DUI-type industry expand rapidly in central regions, relying more on technological knowledge. Both knowledge base and innovation network enhance innovation performance in different high-tech industries, and knowledge base positively moderates the impact of innovation network on industrial innovation performance.

Suggested Citation

  • Zefeng Mi & Ying Sun & Zhixin Qiu & Jingxuan Fu, 2025. "Knowledge base, innovation network, and innovation in different types of high-tech industries - a comparative study of STI (science-technology-innovation) and DUI (learning by doing, using and interac," Post-Communist Economies, Taylor & Francis Journals, vol. 37(6), pages 688-713, August.
    • Handle: RePEc:taf:pocoec:v:37:y:2025:i:6:p:688-713
    DOI: 10.1080/14631377.2025.2495372
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