Study On Network Complexity Of Industrial Symbiosis System

Some industrial symbiosis systems belong to complex system, just like ecological system and social system, their counterparts in the Nature and the Society. By applying network analysis to some well-known industrial symbiosis systems including the Kalundborg system, however, we cannot find the complexity characteristics for them. This preliminary observation results to this study, aiming to find whether and how the network complexity of industrial symbiosis system is affected by choosing different system boundaries, factors and mechanisms. Four parts are included in this paper. First, the progress of industrial symbiosis system is reviewed, including definitions, spatial scales, comparisons between industrial systems and ecosystems, couplings between actual systems and analytical methods, and the preliminary applications for network analysis methods.Next, some basic concepts, indicators and models for network complexity are introduced. The particularities for complexity of industrial symbiosis system are discussed. The relevant analytical method is constructed and used to analyze the network complexity of Kalundborg case.Third, a network database for industrial symbiosis system analysis is established. Along with the approach of scaling identification, data collection and network construction, the database establishment method for the networks based on'real materials','ideal materials'and enterprises is presented.Finally, the characteristics for complexity of the industrial system of Gongyi, a county in China, are analyzed. The analyzable networks are selected. The relevant basic parameters, determinant parameters, size of components and betweenness of nodes are measured. The characteristics for node influence and for size, collectivity, connectivity, complexity, small-world and scale-free of industrial symbiosis networks are analyzed and summarized.Based on the work above, we find that the Kalundborg industrial symbiosis network do NOT have network complexity, whereas with some initialization of system element and scaling, Gongyi DO have. This result implies that the network complexity depends on the system itself, its element and scaling. For ideal materials network, we find that the depending is notable. Moreover, system partition in more detail and breaking system boundary will induce increasing complexity. For symbiosis network based on enterprises, we find that the connectivity and complexity will increase if the competitiveness and cooperation is added to the material relationship.