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| Knowledge Network Construction and Knowledge Measurement of the S&T Innovation Team |
| Shi Jing1, Sun Jianjun1,2 |
1.School of Information Management, Nanjing University, Nanjing 210023
2.Laboratory for Data Intelligence and Cross-Innovation of Nanjing University, Nanjing 210023 |
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Abstract As integrated innovation is increasing in the Science and Technology (S&T) field, teamwork has been identified as an important way to recreate knowledge. Measuring and portraying the knowledge base of S&T innovation teams with precision is of essential significance for interpreting team behaviors and innovation mechanisms, and for managing and developing these teams. This study creatively combines network analysis and knowledge embeddedness to improve traditional knowledge measures and enhance their suitability for S&T innovation teams. Firstly, we applied Maximal Connected Subgraph to identify S&T teams. Thereafter, we expanded the individual member knowledge network base on direct connection and indirect citation, and then collectively calculated a fine-grained team knowledge network. Further, from the positional and relational approaches, two analysis perspectives in network study, we constructed Knowledge Overlap, Knowledge Diversity, and Knowledge Cohesion to measure team knowledge. When calculating, we improved the previous measurements by embedding team knowledge into the whole field-wide knowledge network. Finally, we chose biomedicine as an empirical case where we further discussed and analyzed the team knowledge measurement indicators and their connotations. Positional indicators, Knowledge Overlap and Knowledge Diversity, measure shared knowledge and heterogeneous knowledge respectively, which reflects the composition of team knowledge; the relational indicator, Knowledge Cohesion, reflects the structural consistency and content coherence of knowledge from different teams. In most teams, knowledge nodes are evenly distributed, but the structure of knowledge differs considerably. An inverted “U” relationship can be observed between Knowledge Diversity, which is an important source of team breakthrough creativity, and team performance. Surprisingly, Knowledge Cohesion proved to have a weak effect on performance, despite exhibiting a positive relation with team size.
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Received: 08 October 2021
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