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Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (9): 10-20    DOI: 10.11925/infotech.2096-3467.2021.0275
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Diffusion Model for Tacit Knowledge of Scientific Cooperation Network Based on Relevance: Case Study of Major Sci-Tech Projects
Lu Yunmeng,Liu Tiezhong()
School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China
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Abstract  

[Objective] Tacit knowledge is an important resource for R&D and innovation of major science and technology projects. It is of practical significance to study the simultaneous diffusion of multiple types of interrelated tacit knowledge. [Objective] We proposed a method for evaluating the knowledge distance between scientific teams with the help of knowledge relevance, and constructed a tacit knowledge diffusion model based on the scientific cooperation network. We also investigated the influencing mechanism of knowledge relevance and interaction strategies on the diffusion of tacit knowledge through multi-agent simulation. [Results] In the early stage of dissemination, the speed of knowledge diffusion with strong knowledge relevance was faster than those of weak knowledge relevance. As the difference of knowledge among scientific teams became smaller, and the similarity of knowledge structure between scientific teams increased, and the influence of knowledge relevance on knowledge diffusion gradually weakened. The interaction strategy between subjects had greater impacts on knowledge diffusion. [Limitations] The carrier network of tacit knowledge is a real scientific cooperation network, but its dissemination process was simulated in the lab. [Conclusions] This paper analyzes the dynamic process and effects of tacit knowledge diffusion, and provides suggestions to promote the using of tacit knowledge.

Key wordsScientific Collaboration Network      Knowledge Diffusion      Major Sci-Tech Projects      Knowledge Relevance     
Received: 18 March 2021      Published: 15 October 2021
ZTFLH:  F204  
Fund:*National Science and Technology Major Project(GFZX01020205)
Corresponding Authors: Liu Tiezhong     E-mail: liutiezhong@bit.edu.cn

Cite this article:

Lu Yunmeng,Liu Tiezhong. Diffusion Model for Tacit Knowledge of Scientific Cooperation Network Based on Relevance: Case Study of Major Sci-Tech Projects. Data Analysis and Knowledge Discovery, 2021, 5(9): 10-20.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2021.0275     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2021/V5/I9/10

名称 符号 赋值
科研团队数量 N 623
科研团队知识量 K i p ( t ) random(0,50)
专家组知识量 K sc p ( t ) 60
环境依赖性 α (0,1)
扩散双方主观意愿 S I ij ( t ) random-normal(0.75,0.10)
关系强度 R D ij ( t ) random-normal(0.50,0.19)
Simulation Initial Parameter Setting
Average Tacit Knowledge Level Under Different Knowledge Relevance
Knowledge Diffusion Rate Under Different Knowledge Relevance
Knowledge Distribution Balance Under Different Knowledge Relevance
Average Tacit Knowledge Level Under Different Interaction Strategies
The Diffusion Speed of Tacit Knowledge Under Different Interaction Strategies
Distribution Balance of Tacit Knowledge Under Different Interaction Strategies
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