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Industry Cluster Innovation Upgrading and Knowledge Evolution: A Simulation Analysis Based on Small-World Networks

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  • Di Ye
  • Linlin Zheng
  • Peixu He

Abstract

This article focuses on the innovation and knowledge evolution of industry clusters. We examine the effects of the hub firm and the interaction of network member firms on the upgrading of the cluster. Our study is based on two patterns of knowledge learning and innovation, namely, STI (science, technology, and innovation) and DUI (doing, using, and interacting). This article adopts a knowledge diffusion simulation model to study the exchange of knowledge between cluster network actors in the context of small-world networks. The results indicate that we must pay close attention to the influence of hub enterprises on cluster evolution. Although hub companies may have certain innovation capabilities, if knowledge absorption problems among members are not properly resolved in the cluster network, the innovation performance of the local clusters is likely to be weakened, despite the success of the hub firm.

Suggested Citation

  • Di Ye & Linlin Zheng & Peixu He, 2021. "Industry Cluster Innovation Upgrading and Knowledge Evolution: A Simulation Analysis Based on Small-World Networks," SAGE Open, , vol. 11(3), pages 21582440211, July.
    • Handle: RePEc:sae:sagope:v:11:y:2021:i:3:p:21582440211031604
    DOI: 10.1177/21582440211031604
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    3. Teng, Yuanyang & Zheng, Jianzhuang & Li, Yicun & Wu, Dong, 2024. "Optimizing digital transformation paths for industrial clusters: Insights from a simulation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

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