Development Strategies Of High-Tech Industrial Parks On The Perspective Of Evolution

High-tech industrial parks have become the main platform for cultivating high-tech industries in China and an important carrier for implementing the national innovation strategy.After more than 30 years of development,the evolutionary course of high-tech industrial parks in China has shown stages.Along with the evolution of high-tech industrial parks,problems in the development of the parks have been gradually exposed,such as the fragility of enterprise agglomeration,the unclarity of leading industries,and the lack of cooperative innovation drive.Therefore,based on the perspective of the evolution of high-tech industrial parks,this thesis takes the evolution stage of high-tech industrial parks as the logical main line.Based on complex network theory,life cycle theory and game theory,the thesis aims at the existing problems in the development of high-tech industrial parks,and explores the development strategies under different evolution stages of high-tech industrial parks according to the actual needs of the development planning of high-tech industrial parks.It is hoped that this thesis will provide a scientific basis for the formulation of the development plan for the park,and provide the reference for the strategy selection of the park management bodies and high-tech enterprises.This thesis has the following main research contents and conclusions.(1)Classification and identification of the evolutionary stages of high-tech industrial parks.Firstly,based on the complex network theory,a complex network model of the hightech industrial park is established,and the influencing factors of the evolution of the park network are analyzed by means of numerical simulation,and then the evolution mechanism of the high-tech industrial park is explained,namely,the growth mechanism,the selforganization mechanism and the merit-based connection mechanism.Secondly,a three-stage hypothesis on the evolution of high-tech industrial parks is proposed,namely,the stage of enterprise agglomeration,the stage of leading industry selection,and the stage of cooperative innovation incentive,which is verified with case studies.Then,the link prediction algorithm based on node similarity is improved,and a link prediction algorithm based on the combined influence of predicting nodes and neighbor nodes is proposed to predict the park network structure.The experimental results show that the link prediction algorithm proposed in this thesis can achieve good prediction accuracy with a small number of experiments.Finally,based on the analysis of the characteristics and rules of the evolution of the park network structure,the basis for identifying the evolutionary stages of high-tech industrial parks is provided.(2)Development strategies for the enterprise agglomeration stage of high-tech industrial parks.Firstly,based on the life cycle theory,the life cycle attributes of the enterprise agglomeration stage are analyzed.Secondly,based on the dynamic game of incomplete information,the game model of the enterprise agglomeration formation period is constructed.The game results show that the preferential policies of the local government in the region where the park is located are the main competitiveness of the park in this period,and suggestions are made for the strategy of the formation period.Finally,based on evolutionary game theory,evolutionary game models are built for the growth and maturity periods of enterprise agglomeration.The results show that the government chooses to introduce strong preferential policies and high-tech enterprises enter the park as the evolutionarily stable strategy of the game,and the development strategies for the growth period and maturity period are proposed according to the game results.(3)Development strategies for the leading industry selection stage of high-tech industrial parks.Relying on the energy value theory in ecology,an algorithm for predicting industrial network links based on energy flow is proposed in an attempt to make up for the shortcomings of previous studies that used classical link prediction algorithms and ignored the influence of energy flow relationships between industrial sectors on the evolution of industrial network structure.The experimental results of link prediction show that high-end equipment manufacturing,information chemical manufacturing,computer,electronic and communication equipment industries are both in line with the trend of industrial structure evolution and have the characteristics of high-tech industries,which are the key directions for the selection of leading industries in high-tech industrial parks.Accordingly,the direction and countermeasure suggestions for the selection of leading industries in high-tech industrial parks are proposed.(4)Development strategies for the cooperative innovation incentive stage of high-tech industrial parks.Based on game theory on complex networks,a network deer hunting game model is constructed to explore the cooperative innovation behavior among high-tech enterprises in the park and its influencing factors,and also to make up for the shortcomings of the traditional evolutionary game model,which cannot portray the influence of the interaction mode among high-tech enterprises in the park on the game outcome.The results of the simulation experiments show that: the evolutionary stabilization strategy of the network deer hunting game for high-tech enterprises to choose cooperative innovation;the evolutionary results of the game are insensitive to changes in the size of the network;the accumulation of more cooperative innovation relationships at the early stage of the game plays a role in promoting cooperative innovation among high-tech enterprises in the park.Based on the influencing factors of cooperative innovation behavior,development strategies for the cooperative innovation incentive stage are proposed at three levels: management bodies,resident enterprises and service institutions,with a view to enhancing the innovation-driven capability of high-tech industrial parks.