知识管理
知识库
背景(考古学)
中间性中心性
计算机科学
结构孔
匹配(统计)
比例(比率)
独创性
业务
中心性
社会资本
人工智能
社会学
定性研究
物理
古生物学
社会科学
组合数学
统计
生物
量子力学
数学
出处
期刊:Journal of Knowledge Management
[Emerald (MCB UP)]
日期:2023-02-28
卷期号:27 (9): 2526-2547
被引量:1
标识
DOI:10.1108/jkm-12-2021-0959
摘要
Purpose This paper aims to focus on the characteristics of a two-tier network featuring internal subject cooperation and external embedded cooperation in the context of regional innovation systems (RISs) and explore the influence of network characteristics on knowledge emergence. Design/methodology/approach Using social network analysis, a two-tier internal and external cooperation network of a RIS is constructed. A negative binomial regression method is used to explore the effects of the characteristics of these two-tier internal and external networks on knowledge emergence, the moderating effect of the cooperation knowledge base in this context is investigated and grouping and quantile regressions are used to conduct heterogeneity analysis. Findings The scale of the internal cooperation network has a positive effect on knowledge emergence, and the betweenness centralization of the internal cooperation network has an inverted U-shaped effect on knowledge emergence. The scale and structural holes of the external embedded network have an inverted U-shaped effect on knowledge emergence. Furthermore, the internal cooperation knowledge base weakens the influence of the external embedded network on knowledge emergence. Practical implications This research may enlighten policymakers with respect to improving the scale and structure of the RIS cooperation network and matching the embedded network based on the internal cooperation knowledge base to promote knowledge emergence. Originality/value This research contributes to the study of knowledge emergence by exploring the influence of a two-tier network structure and scale characteristics on knowledge emergence in RISs. This paper also extends the framework of relevant research by integrating the internal cooperation knowledge base into the analysis of externally embedded cooperation and knowledge emergence.
科研通智能强力驱动
Strongly Powered by AbleSci AI