Analysis Of Structure Of Industrial Clusters And Application Of Cellular Automaton To Evolution Of Industrial Clusters

The Emergence of industrial clusters changes regional competition mode of many countries and demonstrate dominant competition capability. This leads to growing research efforts on studying it from the academia. However, current study of them still has the following shortcomings: 1. Study of the complexity of industrial cluster is very limited. Some publications have mentioned it but only conceptually discussed. They had not performed an in-depth research on generation and evolution of the complex phenomenon of industrial clusters. 2. Limitation of research idea and approach. Currently the approaches to studying industrial clusters are basically following the way of thinking from phenomenon to essence and analyzing the essence of a thing from up to down. In order to compensate these two shortcomings, after summarizing prior work on studying the theory of industrial clusters, this work first properly partitions groups of companies inside the industrial clusters, distinguishes between structural roles and assistant roles, and specifies that the major part of studying the development clusters system is the enterprises which have the structural function. Then, it partitions the types of structures of the industrial clusters from their industrial characteristics, and gives quantitative guidelines for partitioning structures of industrial clusters. Thirdly, this work still uses the up-to-down approach to summarize and analyze the cause of formation and the factors of evolution of different structures of the industrial clusters from the phenomenon. Especially, during the analysis of factors of evolution, this work attempts to use the theory of gamble and chess, numerical analysis and models of ecology to impersonally analyze the effect of competition and cooperation on the evolution of the industrial clusters from both positive and negative sides of views, establishes a basis for building a simple and representative fitness. Finally, according to the complex system theory from down to up, this work integrally proves the complexity of the industrial clusters system, successfully builds a cell automation (CA) model of the evolution of the industrial clusters, succeeds to realize simulation of evolution of industrial clusters using computer aid language, and also analyzes the simulation results then obtain seven new subjects about the study of industrial clusters. This thesis combines the up-to down and down-to-up ways of studying in order to promote in-depth study of the industrial clusters.