关键词: 创新网络, 战略性新兴产业, 知识流动, Agent仿真, 刺激-反应

Abstract:    Based on the realistic background that strategic emerging industries (SEIs) are in the early stage of development, the resource advantages of various subjects, which is conducive to conquering key technologies can be integrated and concentrated by building a high-level innovation network. Thus, it is necessary to explore the formation mechanism of innovation network and fully grasp the rules of interaction of all elements.Previous studies have concluded that the process of innovation network formation is accompanied by knowledge flow and that the government macro-regulation has an important impact on the quality of innovation network formation. However, it still has the following shortcomings. First of all, previous studies have not examined the influence of knowledge innovation subject attribute on the formation of innovation network in terms of knowledge complementarity and symbiosis of SEIs. Secondly, previous studies lack the research on the influence of interaction rules among knowledge innovation subjects, environment and the government on the formation of innovation network. Finally, the research on analyzing the dynamic interaction process of the SEIs innovation network based on its static formation mechanism needs to be enriched.According to the above analysis, the formation mechanism of the innovation network of SEIs was studied by static regression based on the stimulus-response model in this paper. On this basis, the agent simulation model was used to analyze the dynamic interaction process among the innovation subject, the government and the environment under the market mechanism and government regulation, which is to explore the dynamic evolution mechanism. The contribution of this paper is to enrich the theoretical framework of research related to innovation networks in SEIs, and provides a theoretical basis for enterprise decision making and government policy formulation. On the one hand, the attributes of knowledge sender and receiver are considered comprehensively. On the other hand, the interaction rules and dynamic interaction process among innovation subjects, environment and the government are fully explored. The mechanism of SEIs innovation network formation is deeply revealed. The results shown that in the process of interaction between knowledge innovation subject, the knowledge innovation behavior of the knowledge receiver is positively affected by its own knowledge absorption capacity, knowledge sharing willingness, information stimulus intensity and knowledge power of the knowledge sender. In the process of interaction between the government and knowledge innovation subject, the knowledge innovation behavior of knowledge receiver positively affected by the government support intensity. At the same time, the perceived information stimulus intensity of knowledge receiver has a mediating effect on the relationship between the government support and knowledge innovation behavior. After the formation and stabilization of the innovation network, the number of knowledge-interactive innovation subjects is more than that of knowledge-integrated innovation. Compared with the market mechanism, the number of knowledge-integrated innovation subjects in the government-driven innovation network has always maintained a stable growth trend and the proportion of quitters is small.Based on the conclusions, this paper draws the following enlightenment. First of all, the subject of knowledge innovation should strengthen the accuracy of the prediction about opportunity, timeliness and ambiguity of opportunity information. As the sender of knowledge, it is necessary to enhance the expertise, irreplaceability and inimitability of its knowledge resources to increase its knowledge power. As the receiver of knowledge, it is necessary to continuously strengthen its own knowledge absorption ability and willingness to share knowledge. The knowledge resources of the innovation network can be used more effectively and maintain the stable operation of the innovation network. Secondly, the government should be able to quickly formulate more guiding policies and improve the policy implementation. Through the joint efforts of enterprises and the government, a high-level innovation network of SEIs will eventually be formed. Thus, a solid foundation will be laid for driving the innovation of traditional industries.

Key words:  innovative network, strategic emerging industry, knowledge flow, Agent simulation, stimulus-response