Divergent pathways from autonomy to performance: talent strategies in top Chinese public research institutions

Dingyi You, Ke Wen (), Fei Qin (), Dacheng Song and Le Tang
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Dingyi You: Sichuan University
Ke Wen: University of Chinese Academy of Sciences
Fei Qin: University of Bath
Dacheng Song: University of Chinese Academy of Sciences
Le Tang: Suffolk University

Humanities and Social Sciences Communications, 2025, vol. 12, issue 1, 1-15

Abstract: Abstract Public research institutions are critical actors in driving innovation through publicly funded research. They need to build and deploy their core assets of human capital for knowledge production, yet they often operate with constrained autonomy. This study examines how financial management autonomy shapes talent strategies and, in turn, research productivity in China’s leading research institutions. Exploiting a quasi-natural experiment in which 30% of top institutions were granted autonomy over personnel budgets, we compare divergent pathways linking autonomy to performance. The analysis reveals that institutions with team-based knowledge production models performed better by incentivizing incumbent researchers, while those with individual-based models benefited more from hiring externally. These results highlight the overall value of autonomy in public research institutions, and the contingent nature of its translation into performance: the most effective talent strategy depends on its fit with the institution’s underlying knowledge-production model, rather than a one-size-fits-all approach.

Date: 2025
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DOI: 10.1057/s41599-025-06168-x

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