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ORIGINAL RESEARCH article

Front. Public Health

Sec. Health Economics

Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1437212

Research on the Evolution of Biotechnology Cooperation Networks -A Study Based on Patent Data in China from 2004 to 2023

Provisionally accepted
  • 1 Qingdao University, Qingdao, China
  • 2 Ocean University of China, Qingdao, Shandong Province, China

The final, formatted version of the article will be published soon.

    Biotechnology has significant potential in public health, offering critical support for communicable disease control, chronic illness management, and drug development. To foster biotechnology innovation, governments increasingly incentivize cooperations among organizations, resulting in more interconnected biotechnology cooperation networks. However, research on the evolution of these networks rely primarily on static network analysis and neglect the micromechanisms under the evolution, which lead to deviations in policymaking. Using temporal exponential random graph model (TERGM), which accounts for dynamic network correlations, and based on micromechanisms framework consisting of agency, opportunity and inertia, this study analyzes the impacts of both endogenous and exogenous factors on the evolution of biotechnology cooperation networks. The empirical analysis based on China’s biotechnology patent data from 2004 to 2023 reveals the following findings and policy recommendations. First, the evolution of the biotechnology cooperation networks is temporally dependent, highlighting the need for awareness of policy lags. Second, two endogenous factors – transitivity and convergence – emerge in the evolution, implying the need for government to create information platforms, establish targeted project subsidies, and enforce technical confidentiality policies. Finally, with regard to exogenous factors, the networks exhibit geographical homogeneity, implying the needs for government to promote cross-regional cooperation by establishing innovation centers and unified standards to mitigate lock-in effects and barriers.

    Keywords: TERGM, biotechnology cooperation networks, Networks evolution, Time dependence, endogenous factors, exogenous factors, Micromechanisms

    Received: 23 May 2024; Accepted: 26 Feb 2025.

    Copyright: © 2025 Wang, Wang, Zhong and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jie Xu, Ocean University of China, Qingdao, 266003, Shandong Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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