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<p>Understanding the dynamic characteristics of Heterogeneous Knowledge Transfer Networks (HKTNs) and their evolutionary impact is crucial for enhancing firms’ knowledge transfer and innovation capabilities. Using 2011–2020 complex relational data from prior work, we constructed HKTNs and employed social network analysis and negative binomial regression to explore the dynamic characteristics of network positions and their evolutionary effects. Key findings include: (1) Entities with stronger information control and influence shift dynamically as HKTNs evolve. (2) The evolutionary positions of centrality and structural holes significantly enhance firm innovation capability. (3) Digitalization does not significantly moderate the centrality–firm innovation relationship, but negatively moderates the structural hole–firm innovation relationship.</p>

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Heterogeneous network location, digitalization, and patent applications in China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月18日

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  • Baoxiang Li

摘要

Understanding the dynamic characteristics of Heterogeneous Knowledge Transfer Networks (HKTNs) and their evolutionary impact is crucial for enhancing firms’ knowledge transfer and innovation capabilities. Using 2011–2020 complex relational data from prior work, we constructed HKTNs and employed social network analysis and negative binomial regression to explore the dynamic characteristics of network positions and their evolutionary effects. Key findings include: (1) Entities with stronger information control and influence shift dynamically as HKTNs evolve. (2) The evolutionary positions of centrality and structural holes significantly enhance firm innovation capability. (3) Digitalization does not significantly moderate the centrality–firm innovation relationship, but negatively moderates the structural hole–firm innovation relationship.