Understanding knowledge growth in scientific collaboration process: Evidence from NSFC projects
Zhizhen Yao,
Xiaoming Huang,
Haochen Song,
Guoyang Rong and
Feicheng Ma
Journal of Informetrics, 2025, vol. 19, issue 2
Abstract:
Scientific collaboration has become increasingly popular due to the growing complexity of scientific tasks, especially for scientific projects supported by large funding agencies such as The National Natural Science Foundation of China (NSFC). This study focuses on modeling the network incremental elements within the scientific collaboration process of NSFC project teams to understand the intricate knowledge growth mechanisms. Four elements representing incremental knowledge were defined: Isolation, Mixed Addition, Inclusion, and Internal Correlation. Additionally, four knowledge incremental patterns and different collaboration processes were identified. The study discovered the following key findings: (1) NSFC project teams prioritize knowledge absorption and integration during collaboration, predominantly advancing knowledge through Mixed Addition approaches. (2) Teams in Management Science and Engineering (MSE) discipline tend to expand through Mixed Addition approaches, while Economic Science (ES) teams prefer Inclusion and Internal Correlation approaches for team development compared to MSE teams. (3) The knowledge pioneering pattern negatively impacts productivity, while the emergence of knowledge expansion and enhancement patterns can lead to significant improvements. Overall, this study explores the team collaboration process from the knowledge growth perspective, which provides valuable insights for optimizing team management and improving collaboration efficiency.
Keywords: Network incremental elements; Knowledge incremental pattern; Scientific collaboration process; NSFC projects; Team productivity (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:19:y:2025:i:2:s1751157725000288
DOI: 10.1016/j.joi.2025.101664
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