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When do intrafirm networks accelerate follow-on invention? Evidence from biotechnology firms

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  • Nan, Ding
  • Markus, Arjan
  • Wang, Liukai
  • Xiong, Yu
  • Zhang, Yali

Abstract

This study examines how the structure of intrafirm inventor networks influences the speed at which biotechnology firms generate follow-on inventions. We conceptualize follow-on invention speed as how quickly a firm recombines and builds on its own prior knowledge. Drawing on social network theory, we focus on two structural dimensions: network clustering and average path length. We theorize that their effects depend on the firm's knowledge environment and tie characteristics—specifically, team knowledge diversity, tie strength, and invention radicalness. Using longitudinal data from 223 U.S. public biotechnology firms (2004–2013), we find that clustering slows invention speed, while longer average path length accelerates it—but only under specific conditions. Team knowledge diversity and radicalness mitigate the downsides of clustering but dampen the benefits of longer path lengths. Tie strength intensifies the negative effects of clustering while enhancing the value of path length. These findings underscore the need to align intrafirm network structure with the firm's internal knowledge context, offering new insights into the microfoundations underlying the speed of internal knowledge reuse and demonstrating that the value of intrafirm networks is contingent rather than universal. For managers, the results highlight that there is no one-size-fits-all optimal network structure: firms can accelerate follow-on invention only by aligning network features with the diversity, strength, and radicalness of their internal knowledge base and relational context.

Suggested Citation

  • Nan, Ding & Markus, Arjan & Wang, Liukai & Xiong, Yu & Zhang, Yali, 2026. "When do intrafirm networks accelerate follow-on invention? Evidence from biotechnology firms," Technovation, Elsevier, vol. 151(C).
  • Handle: RePEc:eee:techno:v:151:y:2026:i:c:s0166497225002354
    DOI: 10.1016/j.technovation.2025.103403
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