摘要
基于微观网络结构和宏观网络聚类的视角,借助联合申请发明专利数据作为支撑,选取东北三省装备制造业合作创新网络作为研究对象,分析了网络结构变量对网络成员创新产出影响效应及整体网络的聚类特征,讨论了网络特征对网络成员创新影响的作用效应及网络成员作用于网络的表现。结果表明:东北三省装备制造业合作创新网络中,中心性和结构洞对网络成员创新产出起到正向促进作用,而中间中心性并没有有效地促进创新产出;网络整体呈现"核心-边缘"的结构范式,几个创新能力较强的网络成员引领着联系紧密的子网络,处于整体网络的核心位置;由于网络连接的单一性,紧密连接的稳定网络并不一定会对其内部成员具有较大的作用力;网络密度对网络成员中介作用具有很大影响,并且创新能力较弱的成员倾向于与创新能力较强的成员组建网络密度较大技术创新联盟。
Based on the view of network structure and network cluster ,with the support of joint application inventive pa- tent data,we choosed the Cooperative Innovation Networks of Industry -University -Research Institution of equipment manufacturing industry in the northeast three province as our research object, and analysed the effect that how network structure Varibles affected innovation output of network members , found the clustering feature of whole network, dis- cussed the effect that how network feature affected innovation output of network members. Finally, We got the results as follows : In the cooperative Innovation Networks of Industry - University - Research Institution,centrality and structural hole promoted the innovation output of network members, but betweenness centrality played a negative role in promoting the innovation output ; the structure feature of central & peripheral was found in the cooperative innovative network, and some institutions with high innovation ability had taken central place in the network; For the oneness of network connection,stabilizing network did not always seriously promote its members' innovation ability; Network density had a great effect on the mediating effect of its network members, so the network members with low in- novation ability were apt to choose the network members with high innovation ability to build a technol- ogy innovation alliance.
出处
《中国软科学》
CSSCI
北大核心
2012年第2期96-107,共12页
China Soft Science
基金
国家软科学项目(2010GXS5B173)
高等学校博士点基金(20102304110008)
国防科技工业软科学项目(2008GFZC013)
国家自然科学基金项目(70873029)
黑龙江省教育厅人文社科项目(11554083)
关键词
合作创新网络
社会网络分析法
聚类分析
网络结构
cooperative innovative network
social network analytic method
Cluster analysis
network structure