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The impact of team compositions on disruptive and novel research in large-scale research infrastructures

Author

Listed:
  • Mingze Zhang

    (National Science Library, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Lili Wang

    (UNU-MERIT, Maastricht University)

  • Zexia Li

    (National Science Library, Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

Modern science has evolved into big science, where collaboration has become a common choice for global scientists. Lots of expensive Large-scale Research Infrastructures (LSRIs) have been constructed and have become essential for advancing scientific knowledge and technological innovation. By fostering international collaboration and enabling scientific discoveries that drive innovation, LSRIs have attracted significant attention from academia, industry, governments, and the public. However, despite the importance of LSRIs, the collaborative effects—especially those related to advancing academic knowledge and achieving scientific breakthroughs—are not yet well known. This study quantifies the potential impact of inter-community and intra-community collaboration on LSRIs’ scientific performance, measured by the disruption index and novelty metrics, which represent the output types and novelty degrees, respectively. Based on the scientific publications from five world-leading LSRIs, the result shows that staff participation in LSRIs associated with more disruptive and novel knowledge. Additionally, diversity in team composition and leadership is also positively associated with better scientific performance. The findings suggest that inter-community collaborations in LSRIs should be encouraged, long-term collaborative relationships should be established, and organizational policies may need to be revised to encourage and protect the staff’s contributions to users’ research.

Suggested Citation

  • Mingze Zhang & Lili Wang & Zexia Li, 2025. "The impact of team compositions on disruptive and novel research in large-scale research infrastructures," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(5), pages 2987-3011, May.
  • Handle: RePEc:spr:scient:v:130:y:2025:i:5:d:10.1007_s11192-025-05319-w
    DOI: 10.1007/s11192-025-05319-w
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