集群内知识溢出、知识势能与集群创新绩效

Knowledge Spillover,Knowledge Energy and Cluster Innovation Performance

集群内企业间的知识溢出是影响集群企业技术创新的重要因素,但知识溢出对集群创新是推动还是阻滞,学术界尚未定论。本文提出"知识势能"的概念,并将其分为两个维度:"共享性知识累积度"和"企业间知识差异度"。在此基础上首先建立了研究框架,然后采用数学模型和实证分析研究了集群内部知识溢出对集群技术创新绩效的影响。结果显示集群内企业间知识溢出对集群技术创新绩效具有双向影响,表现为随着知识溢出的增加,集群创新绩效呈倒U型变化。

Knowledge spillover of enterprises in the cluster is an important factor to affect technological innovation of enterprises in the cluster. There is no academic conclusion about the following questions： Whether knowledge spillover is to promote or hinder technological innovation in the cluster？ To what extent is it more conducive to technological innovation？ This paper considers ＂knowledge energy＂ as the intermediate variable, establishes an analysis framework for knowledge spillover in the cluster and the cluster innovation performance, and attempts to explain innovation advantages and innovation disadvantages in knowledge spillover. In this paper, knowledge energy is divided into two dimensions, one is sharing knowledge accumulation, and the other is knowledge difference between enterprises. The sharing knowledge accumulation is defined as the storage of sharing knowledge in the whole cluster that originates from the knowledge spillover and diffusion between enterprises. The knowledge difference between enterprises is defined as the degree of knowledge diversity between cluster enterprises because of different ways and methods of knowledge acquisition. This paper hypothesizes that knowledge spillover could increase the sharing knowledge accumulation and decrease the knowledge difference between enterprises. Moreover, sharing knowledge accumulation and knowledge difference between enterprises are two dimensions of＂knowledge energy＂. Both of these two dimensions have a positive influence on technology innovation. Under this hypothesis, the paper has done the following work： First, using the Griliches-Jaffe production function and the C-D production fimction for reference, we establish the cluster knowledge innovation function, and build the optimal control model of knowledge innovation. The Hamilton function is then used to solve this model. The results show that the cluster should keep a certain ratio for the sharing knowledge accumulation and the knowledge difference between enterprises, and also keep a certain ratio for the increased investment of sharing knowledge accumulation and the increased investment of the knowledge difference between enterprises at every stage. Second, we select a few clusters form Liaoning, Shandong and Zhejiang provinces as research objects, take technology innovation performance （IK） as the explained variable, take knowledge spillover （KS） as the explaining variable, take the sharing knowledge accumulation （KM） and the knowledge difference between enterprises （KH） as mediated variables, take the enterprises＇ age, scale, industrial property, location and the R＆D investment as control variables, and analyze 163 questionnaires. The results show that the knowledge spillover has an inverted U-shaped effect on cluster innovation performance. On the one hand, knowledge spillover increases the sharing knowledge accumulation and promotes the cluster technological innovation. On the other hand, knowledge spillover decreases the knowledge difference between enterprises and hinders the cluster technology innovation. Finally, we point out that a flexible attitude should be adopted to encourage or limit the knowledge spillover for different industry clusters and industrial clusters in different life cycles. At the beginning of indus^al cluster establishment, the lack of communication between enterprises lead to the lack of consensus, and the knowledge of each enterprise is different. If local government and agency establish corresponding infrastructure and management system to encourage knowledge spillover, it will increase the common knowledge of the cluster, and promote cooperation innovation between enterprises. At the same time, the cluster will release the redundant knowledge difference to solve the bottleneck of common knowledge. The cluster won＇t damage the interests of individual enterprises, and won＇t make the cluster enterprises homogeneous. But when the industry cluster develops into a certain extent, managers and employees from different enterprises have sufficient communication, and the situation of ＂knowledge is in the air＂ appears. At that time, it is no longer reasonable to encourage the knowledge spillover, bacause the factor that determines the cluster innovation performance is the diversity of knowledge. From a macro perspective, we should encourage cluster enterprises to access knowledge from various channels, and implement a certain degree of intellectual property rights protection in order to increase knowledge difference.