摘要
基于集群创新合作网络,建立集群主体的理性创新合作决策模型及合作网络的自组织演化机制,运用数值仿真方法研究网络的动态演化规律及最终形成的稳定状态网络,根据遗传算法原理优化计算得到最优效率网络。在不同的知识溢出效率水平下,比较分析稳定状态网络和最优效率网络的效率和公平性、基本拓扑结构特征以及集群主体创新合作的知识互补性。研究结果表明,合作网络会自组织演化至稳定状态;当知识溢出效率处于中等水平时,网络的自组织演化效率提升空间更大;稳定状态网络是小世界网络,最优效率网络更接近于随机网络;合作网络自组织演化的低效率源于合作不充分、缺乏高成本的远程合作关系、合作过于局部化、偏好连接下的合作规模非均衡性以及过分依赖知识互补性等因素。最后从网络效率优化的角度提出相应的提升集群创新合作绩效的政策建议。
Based on innovation collaboration network of cluster, we build a rational decision model of innovation collaboration and self-organized evolution mechanism of collaboration network. We use numerical simulations to explore dynamic evolution and final stable network, and perform genetic algorithms to optimize and compute efficient innovation networks. We then compare the effi- ciency, fairness, topology structural properties of stable and efficient networks, and knowledge complementation of innovation collaboration network of cluster under different knowledge spillover efficiency. We find that collaboration can reach stable state through self-organizing. The efficiency of self-organized network remains a greater range when the knowledge spillover efficiency is middle. Stable network is a small world network that leads the optimal efficiency to close random network. Low efficiency of self-organized collaboration network is from insufficient connections, lack of costly distant connections, too localized connections, asymmetries connections between organizations under ＂preference connection＂, and too much dependence on knowledge comple- mentation. At last, we put forward implications for the innovation collaboration performances in the industrial cluster from net- work efficiency optimization.
出处
《管理科学》
CSSCI
北大核心
2013年第6期83-93,共11页
Journal of Management Science
基金
国家自然科学基金(71001022
71201108
71371044)
中国博士后科学基金(20100471460
2013T60295)~~
关键词
产业集群
创新合作网络
合作和创新
效率
遗传算法
数值仿真
industrial cluster
innovation collaboration network
collaboration and innovation
efficiency
genetic algorithms
numer- ical simulations
作者简介
黄玮强（1982-），男，福建长汀人，毕业于东北大学，获博士学位，现为东北大学工商管理学院副教授，研究方向：复杂社会网络和产业集群等。E—mail：wqhuang@mail．neu．edu．cn
