Please wait a minute...
Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (9): 10-20    DOI: 10.11925/infotech.2096-3467.2021.0275
Current Issue | Archive | Adv Search |
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
Download: PDF (989 KB)   HTML ( 14
Export: BibTeX | EndNote (RIS)      

[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:

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:     OR

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
[1] 杨阳, 侯光明. 国防科技重大工程协同创新联盟组织模式研究[J]. 科技进步与对策, 2014, 31(5):12-15.
[1] ( Yang Yang, Hou Guangming. Research on Collaborative Innovation Alliance Mode of National Defense Science and Technology Major Project[J]. Science & Technology Progress and Policy, 2014, 31(5):12-15.)
[2] 孔德成, 侯光明. 国防科技重大工程多层次隐性知识传递模型——基于技术总成视角[J]. 科学学研究, 2012, 30(8):1246-1252.
[2] ( Kong Decheng, Hou Guangming. Model Research on Multi-level Tacit Knowledge Inheritance of National Defense Science and Technology Major Project: Based on Technology Assembly[J]. Studies in Science of Science, 2012, 30(8):1246-1252.)
[3] 杨湘浩, 段哲哲, 王筱莉. 考虑遗忘机制的企业隐性知识传播SIR模型研究[J]. 中国管理科学, 2019, 27(7):195-202.
[3] ( Yang Xianghao, Duan Zhezhe, Wang Xiaoli. Enterprise Tacit Knowledge Propagation SIR Model with Consideration of Forgetting Mechanisms[J]. Chinese Journal of Management Science, 2019, 27(7):195-202.)
[4] 曾德明, 禹献云, 陈艳丽. 基于多Agent的创新网络隐性知识转移过程建模与仿真[J]. 管理学报, 2012, 9(12):1832-1837.
[4] ( Zeng Deming, Yu Xianyun, Chen Yanli. Modeling and Simulation of Knowledge Transferring Process in Innovation Network Based on Multi-agent[J]. Chinese Journal of Management, 2012, 9(12):1832-1837.)
[5] 王龙伟, 宋美鸽, 李晓冬. 契约完备程度对隐性知识获取影响的实证研究[J]. 科研管理, 2018, 39(12):53-60.
[5] ( Wang Longwei, Song Meige, Li Xiaodong. An Empirical Study of the Effect of Contract Completeness on Tacit Knowledge Acquisition[J]. Science Research Management, 2018, 39(12):53-60.)
[6] 李纲. 基于核心员工流失的隐性知识传播模型研究[J]. 科技进步与对策, 2011, 28(20):130-133.
[6] ( Li Gang. Research on the Tacit Knowledge Transmission Model Based on Core Employee Turnover[J]. Science & Technology Progress and Policy, 2011, 28(20):130-133.)
[7] 朱宏淼, 张生太, 闫辛. 微信群中隐性知识传播模型研究[J]. 科研管理, 2019, 40(2):106-115.
[7] ( Zhu Hongmiao, Zhang Shengtai, Yan Xin. A Study of the Tacit Knowledge Transmission Model in a WeChat Group[J]. Science Research Management, 2019, 40(2):106-115.)
[8] 张素琪, 高星, 郭京津, 等. 科研项目合作网络的分析与研究[J]. 科研管理, 2018, 39(5):86-93.
[8] ( Zhang Suqi, Gao Xing, Guo Jingjin, et al. A Research on the Collaboration Network of Scientific Project[J]. Science Research Management, 2018, 39(5):86-93.)
[9] Kermack W O, McKendrick A G. Contributions to the Mathematical Theory of Epidemics: IV. Analysis of Experimental Epidemics of the Virus Disease Mouse Ectromelia[J]. Journal of Hygiene, 1937, 37(2):172-187.
pmid: 20475371
[10] 岳增慧, 许海云, 方曙. 基于个体行为的科研合作网络知识扩散建模研究[J]. 情报学报, 2015, 34(8):819-832.
[10] ( Yue Zenghui, Xu Haiyun, Fang Shu. Modeling of Knowledge Diffusion in Scientific Collaboration Network Based on Individual Behavior[J]. Journal of the China Society for Scientific and Technical Information, 2015, 34(8):819-832.)
[11] 朱宏淼, 靳祯, 齐佳音, 等. 线上线下双层耦合网络上的知识传播动力学研究[J]. 系统工程理论与实践, 2020, 40(2):403-414.
[11] ( Zhu Hongmiao, Jin Zhen, Qi Jiayin, et al. Research on Knowledge Spreading Dynamics on Online and Offline Double-layer Coupled Network[J]. Systems Engineering - Theory & Practice, 2020, 40(2):403-414.)
[12] Cowan R, Jonard N. Network Structure and the Diffusion of Knowledge[J]. Journal of Economic Dynamics and Control, 2004, 28(8):1557-1575.
doi: 10.1016/j.jedc.2003.04.002
[13] Cowan R, Jonard N, Özman M. Knowledge Dynamics in a Network Industry[J]. Technological Forecasting and Social Change, 2004, 71(5):469-484.
doi: 10.1016/S0040-1625(03)00045-3
[14] Lin M, Li N. Scale-free Network Provides an Optimal Pattern for Knowledge Transfer[J]. Physica A: Statistical Mechanics and Its Applications, 2010, 389(3):473-480.
doi: 10.1016/j.physa.2009.10.004
[15] 王文平, 张兵. 动态关系强度下知识网络知识流动的涌现特性[J]. 管理科学学报, 2013, 16(2):1-11.
[15] ( Wang Wenping, Zhang Bing. Emergence Characteristics of Knowledge Flow in Knowledge Networks Under Dynamic Relationship Strengths[J]. Journal of Management Sciences in China, 2013, 16(2):1-11.)
[16] 朱宏淼, 张生太, 靳祯, 等. 微信群与线下交流耦合网络知识传播模型研究[J]. 系统工程理论与实践, 2019, 39(7):1796-1806.
[16] ( Zhu Hongmiao, Zhang Shengtai, Jin Zhen, et al. Knowledge Transmission Model on the Coupled Network Formed by WeChat Group and Offline Communication[J]. Systems Engineering-Theory & Practice, 2019, 39(7):1796-1806.)
[17] Morone P, Taylor R. Knowledge Diffusion Dynamics and Network Properties of Face-to-Face Interactions[J]. Journal of Evolutionary Economics, 2004, 14(3):327-351.
doi: 10.1007/s00191-004-0211-2
[18] 苏加福, 杨育, 张娜. 基于异质元胞自动机的知识协同团队隐性知识扩散研究[J]. 管理学报, 2017, 14(2):245-253.
[18] ( Su Jiafu, Yang Yu, Zhang Na. Study on the Tacit Knowledge Diffusion in Knowledge Collaboration Team Based on Heterogeneous Cellular Automata[J]. Chinese Journal of Management, 2017, 14(2):245-253.)
[19] 单汨源, 冯彦, 张人龙. 基于Multi-Agent的创新型组织隐性知识传播模型研究[J]. 科技管理研究, 2014, 34(17):92-95.
[19] ( Shan Miyuan, Feng Yan, Zhang Renlong. Modeling and Simulation of Knowledge Transfer in Innovative Organization Based on Multi-agent[J]. Science and Technology Management Research, 2014, 34(17):92-95.)
[20] Kim H, Park Y. Structural Effects of R&D Collaboration Network on Knowledge Diffusion Performance[J]. Expert Systems with Applications, 2009, 36(5):8986-8992.
doi: 10.1016/j.eswa.2008.11.039
[21] 武开, 张慧颖, 张亮. 产业集群内隐性知识传播的仿真研究[J]. 情报学报, 2015, 34(4):371-379.
[21] ( Wu Kai, Zhang Huiying, Zhang Liang. Simulation Analysis of Tacit Knowledge Dissemination in Industrial Cluster[J]. Journal of the China Society for Scientific and Technical Information, 2015, 34(4):371-379.)
[22] 张海红, 吴文清. 孵化器内创业者知识超网络涌现研究[J]. 管理学报, 2017, 14(5):695-703.
[22] ( Zhang Haihong, Wu Wenqing. Study on the Emergence of Entrepreneurs' Knowledge Supernetwork in Business Incubator[J]. Chinese Journal of Management, 2017, 14(5):695-703.)
[23] 席运江, 党延忠, 廖开际. 组织知识系统的知识超网络模型及应用[J]. 管理科学学报, 2009, 12(3):12-21.
[23] ( Xi Yunjiang, Dang Yanzhong, Liao Kaiji. Knowledge Supernetwork Model and Its Application in Organizational Knowledge Systems[J]. Journal of Management Sciences in China, 2009, 12(3):12-21.)
[24] 张子柯. 在线社交网络信息传播机制与动力学研究综述[J]. 情报学报, 2017, 36(4):422-431.
[24] ( Zhang Zike. Mechanisms and Dynamics of Information Spreading on Online Social Networks: A State-of-the-Art Survey[J]. Journal of the China Society for Scientific and Technical Information, 2017, 36(4):422-431.)
[25] 徐芳, 瞿静. 基于社交网络的隐性知识共享模式构建[J]. 情报理论与实践, 2018, 41(3):68-72.
[25] ( Xu Fang, Qu Jing. Construction of Tacit Knowledge Sharing Mode Based on Social Network[J]. Information Studies: Theory & Application, 2018, 41(3):68-72.)
[26] Zhao L J, Wang J J, Chen Y C, et al. SIHR Rumor Spreading Model in Social Networks[J]. Physica A: Statistical Mechanics and Its Applications, 2012, 391(7):2444-2453.
doi: 10.1016/j.physa.2011.12.008
[27] 文林, 冯婵璟. 浙江省设立重大科技专项和成果转化工程专家组[J]. 今日科技, 2011(11):21.
[27] ( Wen Lin, Feng Chanjing. Zhejiang Province Sets Up Expert Groups for Major Science and Technology Projects and Achievement Transformation Engineering[J]. Today Science & Technology, 2011(11):21.)
[1] Yu Chuanming,Gong Yutian,Zhao Xiaoli,An Lu. Collaboration Recommendation of Finance Research Based on Multi-feature Fusion[J]. 数据分析与知识发现, 2017, 1(8): 39-47.
[2] Li Shengqing, Cai Guoyong. Study on Network Evolution and Knowledge Dissemination of Scientific Collaboration Network in the Field of Complex Networks[J]. 现代图书情报技术, 2013, (5): 64-72.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938