Collaborative Innovation Network, Knowledge Base, and Technological Innovation Performance-Thinking in Response to COVID-19.

Su Jialu, Ma Zhiqiang, Zhu Binxin, Xie Haoyang, Agyeman Fredrick Oteng, Weijun Hu
Author Information
  1. Su Jialu: School of Management, Jiangsu University, Zhenjiang, China.
  2. Ma Zhiqiang: School of Management, Jiangsu University, Zhenjiang, China.
  3. Zhu Binxin: School of Management, Jiangsu University, Zhenjiang, China.
  4. Xie Haoyang: School of Mathematical Science, Zhejiang University, Zhejiang, China.
  5. Agyeman Fredrick Oteng: School of Management, Jiangsu University, Zhenjiang, China.
  6. Weijun Hu: School of Archaeology, Jilin University, Changchun, China.

Abstract

Amid the pandemic of COVID-19, the collaborative innovation network of enterprises is conducive to the sharing of innovation resources, knowledge transfer, and technology diffusion, which is closely related to the improvement of corporate technological innovation performance. Based on the patent application data of listed enterprises in Jiangsu, Zhejiang, and Shanghai in China, this study constructs a cooperation matrix, describes the characteristics of collaborative innovation network from two dimensions of network structure and network relationship, introduces the breadth of the knowledge base as a moderating variable, and analyzes the nexus between characteristics of a collaborative innovation network and technological innovation performance. Based on the panel data of 193 listed companies in Jiangsu, Zhejiang, and Shanghai, this study uses a multiple linear regression model for empirical analysis. The results show a U-shaped relationship between clustering coefficient and technological innovation performance. The breadth of knowledge base strengthens the positive relationship between the structural hole and technological innovation performance. In contrast, the breadth of knowledge base weakens the positive relationship between network relationships strength and technological innovation performance. The study findings will enhance enterprises' participation in a suitable collaborative innovation according to their knowledge-based characteristics and improve the technological innovation performance.

Keywords

References

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