基于指数随机图模型的协同创新网络形成机理研究  

The Formation Mechanism of Collaborative Innovation Networks Based on Exponential Random Graph Model

作　　者：罗泰晔[1] 马翠嫦[2] 

机构地区：[1]中山大学新华学院,广东广州510520 [2]中山大学图书馆,广东广州510275

出　　处：《情报理论与实践》2018年第10期143-146,72,共5页Information Studies:Theory & Application

基　　金：广州市哲学社会科学发展"十三五"规划项目"基于多层次网络分析的广州科技协同创新网络形成及演化机制研究"的成果;项目编号:2018GZGJ150

摘　　要：[目的/意义]厘清协同创新网络的形成机理是对协同创新进行有效管理的前提。[方法/过程]文章以101家生物科技研发机构的共有专利数据为例构建协同创新网络,并使用指数随机图模型对这个网络的形成机理进行了分析检验。[结果/结论]分析结果显示:构建的协同创新网络是一个小世界网络。网络中的边、交互三角形等结构对整个网络的形成有显著影响。网络节点的研发能力和同质性也能显著影响网络的形成。[Purpose/significance] Clarifying the formation mechanism of collaborative innovation network is the premise to manage collaborative innovation efficiently. [Method/process] Taking the patent data of 101 bio-tech research and development（ RD） institutions as an example,this paper constructs the collaborative innovation network,and tests the formation mechanism of the network by using Exponential Random Graph Model（ ERGM）. [Result/conclusion]It is found that the network constructed in this paper is a small-world network. Network structures such as edges,alt-triangles have significant impacts on the formation of the whole network. The RD capability and homogeneity of network nodes can also significantly affect the formation of the network.

关 键 词：指数随机图模型 协同创新 小世界网络 形成机理 

分 类 号：G202[文化科学—传播学]