Studies Of Industrial Clusters Based On Complexity Hypothesis

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.