集群知识网络结构特征对集群弹性的影响研究——基于双元性创新的视角

Research on Effect of Structural Properties of Knowledge Networks on Cluster Resilience--A Perspective from Ambidextrous Innovation

本文从双元性创新的视角研究了集群知识网络的结构特征对集群弹性的影响。在网络视角下,集群是由本地化知识网络构成的关系结构。这一关系结构的结构特征可以通过度分布和度相关性统计指标来衡量。根据集群知识网络的层级与匹配性,集群知识网络呈现出三种典型的结构,它们分别是随机网络、同配性核心/外围网络、异配性核心/外围网络。研究表明,集群中知识网络的同配性特征会弱化集群对新观念吸收与应用的整合能力,这可能是区域负向锁定的根源。而具备异配性特征的网络能够对挖掘性创新的知识和探索性创新的知识进行整合,有利于双元性创新,因而能够加强集群的弹性能力。

This paper develops a framework of cluster resilience with a primary focus on the structural properties of local knowledge networks based on ambidextrous innovation.From the perspective of networks,a cluster can be defined as a local relational structure that results from localized knowledge networks,and its structural properties can be measured through two simple statistical signatures including degree distribution and degree correlation.With the change of hierarchy and assortativity in clusters,structure in clusters knowledge networks displays three kinds of states,namely the random network,the core/periphery and assortative network,and the core/periphery and resilient network.The results show that the property of assortativity of local knowledge networks can be a source of negative regional lock-in,while the disassortative patterns of relations combining explorative and exploitive knowledge can increase cluster resilience capabilities.