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Unveiling the dynamics of team age structure and its impact on scientific innovation

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Abstract

In the dynamic landscape of contemporary scientific research characterized by increasing collaboration, this study, leveraging a comprehensive dataset spanning six decades and encompassing 16 diverse fields with 30 million journal papers, conducts the first large-scale analysis of age structure within scientific teams. Our findings illuminate a consistent upward trajectory in the average team age over time, coupled with a concurrent decline in team age diversity. Examining their intricate relationships with scientific impact, we unveil intriguing inverted-U associations between team age, team age diversity, and scientific impact. This underscores the optimal performance of moderately aged and diverse teams in terms of team impact. Additionally, our research uncovers a U-shaped relationship between team age, team age diversity, and scientific disruption, emphasizing the disruptive potential of extreme team age patterns. Importantly, these discerned patterns hold robustly across various fields and team sizes, offering valuable insights for strategically composing scientific teams and enhancing their productivity in the collaborative landscape of scientific research.

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Code availability

We have made all the codes used to redraw the figures and reconduct the analysis in our paper publicly available at https://github.com/AlexJieYang/team-age-structure.

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Acknowledgements

The paper is a substantially extended version of the ISSI2023 conference paper. This paper is supported by the Youth Program of National Natural Science Foundation in China (No: 72104007), Shanghai Pujiang Program (No: 21PJC026) and Key Project of the National Natural Science Foundation of China (No: 72234001). The authors deeply appreciate the constructive comments from the reviewers.

Funding

This paper is supported by the Youth Program of National Natural Science Foundation in China (No: 72104007), Shanghai Pujiang Program (No: 21PJC026) and Key Project of the National Natural Science Foundation of China (No: 72234001).

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Authors and Affiliations

  1. School of Information Management, Nanjing University, Nanjing, China

    Alex J. Yang

  2. School of Information, University of Texas at Austin, Austin, TX, USA

    Huimin Xu & Ying Ding

  3. Department of Population Health, Dell Medical School, University of Texas at Austin, Austin, TX, USA

    Ying Ding

  4. Institute for Global Public Policy, Fudan University, Shanghai, China

    Meijun Liu

  5. LSE-Fudan Research Centre for Global Public Policy, London, UK

    Meijun Liu

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Correspondence to Meijun Liu.

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Yang, A.J., Xu, H., Ding, Y. et al. Unveiling the dynamics of team age structure and its impact on scientific innovation. Scientometrics (2024). https://doi.org/10.1007/s11192-024-04987-4

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