政府协助下产业集群演进的系统动力学分析

发布时间：2019-01-28 10:11

【摘要】：随着我国经济快速发展,产业集群已成为推动我国区域经济增长的"发动机",它具有其他产业组织形式无法比拟的集聚规模效益和集群竞争优势,是我国创新要素和生产要素最为集中的地方。从系统科学的角度来看,产业集群是一个动态的、开放的复杂巨系统。在众多影响产业集群发展、演进的因素中,政府在技术创新、资金以及政策扶持等方面对产业集群的发展起到了举足轻重的作用。因此,分析政府作用如何影响产业集群演进,并建立定性定量分析的模型具有重要意义。笔者通过阅读大量国内外文献,深入了解产业集群的形成动力和演进机制,详细分析了政府在产业集群各个演进阶段的不同作用,并从人力、资本和技术三个方面建立政府对产业集群的投入绩效评价体系;运用灰色关联度分析法,定量的分析政府的各种资本投入与集群规模的关联性。在研究产业集群演进的过程中,发现产业集群的演进与生物种群的演进具有一定的相似性;鉴于此,本文从生态学的视角出发,在种群增长Logistic模型的研究基础上,假设环境作用对产业集群的容量存在非线性影响,将与集群规模关联度最大的因子融入集群最大环境容量的分析,得到改进的Logistic模型。该模型与经典Logistic模型相比,加入了政府行为对集群容量的影响,扩大了集群容量,提高了模型的拟合优度,并在江苏省电子信息产业集群进行实证分析中,取得较好的效果。本文的创新性在于建立了基于生态学理论的协聚集Logistic模型,同时运用系统动力学理念来刻画产业集群的演进,将产业集群系统分为人才、资本和技术三个子系统,将各个变量间的关系抽象成数学公式,得到仿真模型,并对模型进行有效性分析和敏感性检验。其模拟结果与Logistic模型拟合到的曲线都是S型曲线,表明本文的系统动力学模型能够描述产业集群演进的各个阶段的集聚效应的变化,具有较强的模拟能力;同时,通过对模型结果的分析能够科学的为政府协助集群快速、健康的发展提供决策建议。
[Abstract]:With the rapid economic development of our country, industrial cluster has become the "engine" to promote the regional economic growth of our country. It has the agglomeration scale benefit and the cluster competitive advantage which other industrial organization forms cannot compare. Is our country innovation factor and production factor most concentrated place. From the point of view of system science, industrial cluster is a dynamic, open complex giant system. Among the factors that affect the development and evolution of industrial clusters, the government plays an important role in technological innovation, capital and policy support for the development of industrial clusters. Therefore, it is of great significance to analyze how the role of government affects the evolution of industrial clusters and to establish a qualitative and quantitative model. Through reading a large number of domestic and foreign literature, the author deeply understands the formation motive force and evolution mechanism of industrial cluster, and analyzes in detail the different roles of government in each stage of industrial cluster evolution, and analyzes the role of government in different stages of industrial cluster evolution. Establishing the performance evaluation system of government investment in industrial clusters from three aspects: capital and technology; Using grey correlation degree analysis, quantitative analysis of the government's various types of capital investment and cluster scale relevance. In the process of studying the evolution of industrial clusters, it is found that the evolution of industrial clusters is similar to the evolution of biological populations. In view of this, based on the study of Logistic model of population growth, this paper assumes that environmental action has nonlinear influence on the capacity of industrial clusters from the perspective of ecology. Based on the analysis of the maximum environmental capacity of the cluster, an improved Logistic model is proposed. Compared with the classical Logistic model, the model adds the influence of government behavior on the cluster capacity, expands the cluster capacity, and improves the goodness of fit of the model. The model achieves good results in the empirical analysis of the electronic information industry cluster in Jiangsu Province. The innovation of this paper lies in the establishment of the co-agglomeration Logistic model based on ecological theory, and the application of system dynamics to depict the evolution of industrial cluster. The industrial cluster system is divided into three subsystems: talent, capital and technology. The relationship between each variable is abstracted into mathematical formula, and the simulation model is obtained, and the validity analysis and sensitivity test of the model are carried out. The simulation results and the curves fitted by Logistic model are all S-shaped curves, which shows that the system dynamics model in this paper can describe the change of agglomeration effect in each stage of industrial cluster evolution, and has strong simulation ability. At the same time, the analysis of the results of the model can provide scientific advice for the government to assist the rapid and healthy development of the cluster.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F121.3;N941.3

【相似文献】