基于复杂性的产业集群研究
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摘要
产业集群对于一个区域、一个国家乃至世界都是非常重要的。产业集群是推动地区经济发展的一种有效形式,在全球化的时代里依然普遍存在而又具有代表性。许多国家,包括中国,都得益于众多的产业集群。提高区域或国家的竞争优势,有必要对产业集群开展深入的研究。
尽管对产业集群的研究已经持续了百多年,但绝大多数研究拘泥于传统福特主义的观点和方法论,未能透彻掌握产业集群这一复杂系统的精要。直到20世纪90年代,复杂性和复杂系统的研究成果促使学者们重新审视产业集群和其它地理积聚的现象。复杂性研究的复兴带来了产业集群研究的再次兴盛。相关文献表明:在产业集群复杂性的研究方面,到目前为止的研究依然处于初步阶段,或局限于框架式的研究,或局限于某个侧重面或个别案例的研究。本文创新地引入了产业集群复杂自适应系统的分形数学模型,辅以仿真模拟和博弈分析的方法研究了产业集群内部各层次的主体间的互动和联系——企业集群间、企业间以及个体间的竞争合作;阐述了产业集群复杂自适应系统和其它主要系统,如社会系统及其它产业集群间的相互关系和作用。
本文研究工作主要从以下几个方面展开:
1,)以复杂自适应系统为出发点,对产业集群进行详细、合理的划分,建立了一个具有多个层次和主体的CAS模型。以分形粒子的数学模型为基础,描述、解释产业集群内部各企业、各创新个体相互作用,如何开始形成集聚。利用这一模型推导出形成产业集聚的重要条件之一是:各企业、创新个体所生存的经济、地理环境差异越小越好。在后续的章节中证实了产业集群的社会网络能够减少这种差异。
2,)剖析产业集群的内部市场是一个分形市场。产业集群内部市场的本质是投资市场、分形市场;产业集群的企业家或创新个体的本质是不同阶层的投资者。多样性是产业集群存在的现实基础。
3,)在肯定集群内企业充分竞争的基础上,揭示了这些企业间存在合作和联盟。应用分形粒子模型模拟了集群内企业横向合作、联盟的形态。解释了这种合作、联盟的可能性基础是共同利益,实现保证是以亲情为主的社会约束。
4,)案例数据说明,产业集群不仅仅是企业的地理集聚、资源的地理集聚,更是创新个体(人才)的集聚。分形粒子模型模拟了知识如何通过人才流动在集群内传播。解释了集群社会网络如何为集群内集聚的创新个体提供创新便利和激励,如何在保证多样性的前提下减少企业和个体生存的环境差异。
5,)从系统的角度分析、阐述产业集群这一自适应复杂系统是如何与其它相关系统进行互动的。从所在社会系统角度分析产业集群潜在的体系缺陷和系统冲突;阐述中国产业集群健康发展的主要障碍——政府作为的不当与不足。还探讨了同产业、不同产业集群间合作联盟的可能性。
本文主要的创新性点主要有:
(1)建立了一个多层次的产业集群分形结构模型,其中的创新个体是最基本的分形体。引入一个描述对称性产业集群的分形数学模型。从理论上证明了完全竞争条件下仍有可能形成产业和企业的集聚;解释了主体环境的差异是如何影响企业的积聚行为的。(2)将产业集群内的企业家、创新个体的经营、创造行为视为投资行为,揭示产业集群内
部市场是一个以多样性为基础的分形市场。这有助于解释集群内充分竞争基础上存在的合作和联盟。
(3)以系统的方法来研究产业集群与其所依存的社会系统间的关系,阐述潜在的系统缺陷和冲突。为集群政策的研究和制定提供了新的视角。
Industrial clusters are very important for an area, a country and even for the world. Industrial clustering is an efficient way to develop area economy. It is still popular and typical in current globalization stage. Many countries, including China, get more benefits from industrial clusters. To improve countries’competitive advantage, study industrial clusters more is still necessary and useful.
Even industrial clusters have been studied more than 100 years, most of them are based on conventional Fordism methods, and miss to get all the key points of this complex system. Till to 1990’s, the progress on the studies of complexity and complex system supplied researchers very useful hypothesis and method to re-study the industrial clusters and other geographic gathering phenomena. The renaissance of study on complexity booms the re-study on industrial clusters. The literature review shows: the studies on industrial cluster complexity is still at the beginning stage. Some of them focused on the outline; others just focused on special topics or case studies. This paper firstly introduced the mathematic fractal model to simulate the symmetric industrial cluster as a complex adaptive system (CAS). With computer simulation and game analysis, the relationships and the cooperation-competition modes of the agents, which are enterprise clusters, enterprise and innovation agent at different levels, were studied. The relationship and reaction between industrial cluster CAS and other key systems, such as its community system and other industrial clusters, also was discussed.
This paper covers following studies:
1,) With CAS hypothesis, industrial cluster was dissect to a structure with different levels and agents. A mathematic fractal model was introduced to simulate and explain how the agents act and react; and how the gathering starts. With this model, the necessary condition for clustering was predicted as less environment difference among the enterprises. It was confirmed that industrial clusters could reduce the difference with its community network in the followed chapters.
2,) Analysis on the cluster internal markets showed they were fractal markets. These fractal markets are indeed investment markets. The enterprisers and innovation agents are investors in different levels. Diversity is the fatal foundation for clusters and their internal markets.
3,) Confirmed the completive competition among the enterprises, paper discussed the cooperation and alliance. Fractal grains model was introduced to simulate the cooperation and alliance. The possibility of cooperation and alliance is from agents common interests. The realization is ensured by the community restriction which is based on consanguinity and friendship.
4,) Case study data showed that industrial clusters are not only the enterprises gathering and resource gathering, but also innovation agents gathering at the same area. Another fractal model was introduced to simulate how knowledge diffuses in enterprises arrays by agents moving. The paper explained how the cluster community networks benefit innovation, remove the difference barriers for agents as well as keeps the diversity.
5,) From system views, this paper discussed how this CAS, industrial cluster, reacts to other relevant systems. The risks of cluster defects and conflicts to community system were analysed. It explained the main issues for clusters improvement in China– too much control or un-suitable controlee from local governments. The possibility of cooperation and alliance between different clusters which belong to same industry was also discussed.
The main innovations in this paper are as following:
1,) Industrial clusters were modeled as different levels and agents. The capitalized innovation agents in a cluster are regarded as basic fractals. A mathematic fractal model was introduced to simulate and explain symmetric clusters. The model shows the possibility that a cluster may form even under the full-competitive conditions. It explained how cluster environment affects the enterprises behavior contribution on clustering.
2,) Regarded the enterprisers and innovators as investors, the cluster internal markets perform as a fractal investment market. It helps to explain the cooperation and alliance based on completive competition.
3,) Analysed the structures and relationships of clusters and their community systems; explained the potential cluster system defects and conflicts between two systems. It provides new points for studying and making cluster policies.
尽管对产业集群的研究已经持续了百多年,但绝大多数研究拘泥于传统福特主义的观点和方法论,未能透彻掌握产业集群这一复杂系统的精要。直到20世纪90年代,复杂性和复杂系统的研究成果促使学者们重新审视产业集群和其它地理积聚的现象。复杂性研究的复兴带来了产业集群研究的再次兴盛。相关文献表明:在产业集群复杂性的研究方面,到目前为止的研究依然处于初步阶段,或局限于框架式的研究,或局限于某个侧重面或个别案例的研究。本文创新地引入了产业集群复杂自适应系统的分形数学模型,辅以仿真模拟和博弈分析的方法研究了产业集群内部各层次的主体间的互动和联系——企业集群间、企业间以及个体间的竞争合作;阐述了产业集群复杂自适应系统和其它主要系统,如社会系统及其它产业集群间的相互关系和作用。
本文研究工作主要从以下几个方面展开:
1,)以复杂自适应系统为出发点,对产业集群进行详细、合理的划分,建立了一个具有多个层次和主体的CAS模型。以分形粒子的数学模型为基础,描述、解释产业集群内部各企业、各创新个体相互作用,如何开始形成集聚。利用这一模型推导出形成产业集聚的重要条件之一是:各企业、创新个体所生存的经济、地理环境差异越小越好。在后续的章节中证实了产业集群的社会网络能够减少这种差异。
2,)剖析产业集群的内部市场是一个分形市场。产业集群内部市场的本质是投资市场、分形市场;产业集群的企业家或创新个体的本质是不同阶层的投资者。多样性是产业集群存在的现实基础。
3,)在肯定集群内企业充分竞争的基础上,揭示了这些企业间存在合作和联盟。应用分形粒子模型模拟了集群内企业横向合作、联盟的形态。解释了这种合作、联盟的可能性基础是共同利益,实现保证是以亲情为主的社会约束。
4,)案例数据说明,产业集群不仅仅是企业的地理集聚、资源的地理集聚,更是创新个体(人才)的集聚。分形粒子模型模拟了知识如何通过人才流动在集群内传播。解释了集群社会网络如何为集群内集聚的创新个体提供创新便利和激励,如何在保证多样性的前提下减少企业和个体生存的环境差异。
5,)从系统的角度分析、阐述产业集群这一自适应复杂系统是如何与其它相关系统进行互动的。从所在社会系统角度分析产业集群潜在的体系缺陷和系统冲突;阐述中国产业集群健康发展的主要障碍——政府作为的不当与不足。还探讨了同产业、不同产业集群间合作联盟的可能性。
本文主要的创新性点主要有:
(1)建立了一个多层次的产业集群分形结构模型,其中的创新个体是最基本的分形体。引入一个描述对称性产业集群的分形数学模型。从理论上证明了完全竞争条件下仍有可能形成产业和企业的集聚;解释了主体环境的差异是如何影响企业的积聚行为的。(2)将产业集群内的企业家、创新个体的经营、创造行为视为投资行为,揭示产业集群内
部市场是一个以多样性为基础的分形市场。这有助于解释集群内充分竞争基础上存在的合作和联盟。
(3)以系统的方法来研究产业集群与其所依存的社会系统间的关系,阐述潜在的系统缺陷和冲突。为集群政策的研究和制定提供了新的视角。
Industrial clusters are very important for an area, a country and even for the world. Industrial clustering is an efficient way to develop area economy. It is still popular and typical in current globalization stage. Many countries, including China, get more benefits from industrial clusters. To improve countries’competitive advantage, study industrial clusters more is still necessary and useful.
Even industrial clusters have been studied more than 100 years, most of them are based on conventional Fordism methods, and miss to get all the key points of this complex system. Till to 1990’s, the progress on the studies of complexity and complex system supplied researchers very useful hypothesis and method to re-study the industrial clusters and other geographic gathering phenomena. The renaissance of study on complexity booms the re-study on industrial clusters. The literature review shows: the studies on industrial cluster complexity is still at the beginning stage. Some of them focused on the outline; others just focused on special topics or case studies. This paper firstly introduced the mathematic fractal model to simulate the symmetric industrial cluster as a complex adaptive system (CAS). With computer simulation and game analysis, the relationships and the cooperation-competition modes of the agents, which are enterprise clusters, enterprise and innovation agent at different levels, were studied. The relationship and reaction between industrial cluster CAS and other key systems, such as its community system and other industrial clusters, also was discussed.
This paper covers following studies:
1,) With CAS hypothesis, industrial cluster was dissect to a structure with different levels and agents. A mathematic fractal model was introduced to simulate and explain how the agents act and react; and how the gathering starts. With this model, the necessary condition for clustering was predicted as less environment difference among the enterprises. It was confirmed that industrial clusters could reduce the difference with its community network in the followed chapters.
2,) Analysis on the cluster internal markets showed they were fractal markets. These fractal markets are indeed investment markets. The enterprisers and innovation agents are investors in different levels. Diversity is the fatal foundation for clusters and their internal markets.
3,) Confirmed the completive competition among the enterprises, paper discussed the cooperation and alliance. Fractal grains model was introduced to simulate the cooperation and alliance. The possibility of cooperation and alliance is from agents common interests. The realization is ensured by the community restriction which is based on consanguinity and friendship.
4,) Case study data showed that industrial clusters are not only the enterprises gathering and resource gathering, but also innovation agents gathering at the same area. Another fractal model was introduced to simulate how knowledge diffuses in enterprises arrays by agents moving. The paper explained how the cluster community networks benefit innovation, remove the difference barriers for agents as well as keeps the diversity.
5,) From system views, this paper discussed how this CAS, industrial cluster, reacts to other relevant systems. The risks of cluster defects and conflicts to community system were analysed. It explained the main issues for clusters improvement in China– too much control or un-suitable controlee from local governments. The possibility of cooperation and alliance between different clusters which belong to same industry was also discussed.
The main innovations in this paper are as following:
1,) Industrial clusters were modeled as different levels and agents. The capitalized innovation agents in a cluster are regarded as basic fractals. A mathematic fractal model was introduced to simulate and explain symmetric clusters. The model shows the possibility that a cluster may form even under the full-competitive conditions. It explained how cluster environment affects the enterprises behavior contribution on clustering.
2,) Regarded the enterprisers and innovators as investors, the cluster internal markets perform as a fractal investment market. It helps to explain the cooperation and alliance based on completive competition.
3,) Analysed the structures and relationships of clusters and their community systems; explained the potential cluster system defects and conflicts between two systems. It provides new points for studying and making cluster policies.
引文
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