摘要
【目的】隐性知识是重大科技工程研发创新的重要资源,针对工程中隐性知识的关联性特征,研究多类相互关联的隐性知识同时扩散具有实践意义。【方法】考虑知识关联性,提出科研团队间的知识距离评估方法,并构建了基于科研合作网络的隐性知识扩散模型,通过多主体仿真分析知识关联性和交互策略对隐性知识扩散的影响机理。【结果】扩散初期,知识强关联下的知识扩散速度高于知识弱关联的情况,但随着时间增长,科研团队间知识量差距变小,知识结构相似性增加,知识关联性对知识扩散的影响逐渐弱化。科研团队间的知识交互策略对知识扩散影响较大。【局限】隐性知识的载体网络是真实的科研合作网络,但其传播过程来源于模拟仿真。【结论】分析了工程中相互关联的多类隐性知识扩散的动态过程与效果,并提出了促进隐性知识扩散与学习的建议。
[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.[Methods]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.
作者
鲁云蒙
刘铁忠
Lu Yunmeng;Liu Tiezhong(School of Management and Economics,Beijing Institute of Technology,Beijing 100081,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2021年第9期10-20,共11页
Data Analysis and Knowledge Discovery
基金
国家科技重大专项(项目编号:GFZX01020205)的研究成果之一。
关键词
科研合作网络
知识扩散
重大科技工程
知识关联性
Scientific Collaboration Network
Knowledge Diffusion
Major Sci-Tech Projects
Knowledge Relevance