复杂动态环境下产业集群知识协同能力评价研究

Research on the Index System Construction and Evaluation of Knowledge Collaboration Capability of Industrial Clusters in Complex Dynamic

摘要:

【目的/意义】在复杂动态环境下,对产业集群知识协同能力进行有效的评价是具有重要的理论意义和实践价值。【方法/过程】本文在给出产业集群知识协同能力概念的基础上,构建了“复杂动态环境下产业集群知识协同能力评价指标体系”,进而构建了“基于模糊神经网络(FUSSY-GRNN)的产业集群知识协同能力评价模型”,并进行了实例分析。【结果/结论】与已有研究相比,本文从“环境维度”、“网络维度”、“文化维度”和“规制维度”等维度构建了“四位一体”的复杂动态环境下产业集群知识协同能力评价指标体系,与已有的研究相比,该指标体系很好地反映了复杂动态环境下产业集群活动的“复杂性”、“动态性”、“多维性”、“网络化”等特点,可以客观地、有效地反映复杂动态环境下产业集群的知识协同能力水平；此外,本文还进一步构建了“基于Fussy-GRNN网络的产业集群知识协同能力评价模型”,与已有研究相比,该评价模型具有较高的训练效率、更好的稳定性、良好的小样本适应性等优点。

Abstract:

[Objective/Significance] In complex dynamic environment, it is of great theoretical and practical significance to evaluate the Knowledge Collaboration Capability of Industrial Clusters effectively(KCC-IC). [Method/Process] On the basis of giving the concept of Knowledge Collaboration of Industrial Clusters, this paper constructs the evaluation index system of Knowledge Collaboration capability of industrial clusters in complex dynamic environment, and then constructs the evaluation model of KCC-IC based on fuzzy neural network (FUSSY-GRNN), and an example is analyzed with this method. [Results/Conclusion] Compared with the existing research, the four-in-one evaluation index system of KCC-IC in complex dynamic environment constructed from the dimensions of "environment dimension", "network dimension", "culture dimension" and "regulation dimension" well reflects the characteristics of "complexity", "dynamics", "multidimensional" and "networking" of industrial cluster activities in complex dynamic environment, and can objectively and effectively reflect the level of Knowledge Collaboration capability of industrial clusters in complex dynamic environment. In addition, compared with the traditional evaluation methods, the "Knowledge Collaboration Capability Evaluation Model of Industrial Cluster Based on Fussy-GRNN Network" has the advantages of high training efficiency, better stability and good adaptability to small samples.