The Empirical Research On The Structure Characteristics And Behavior Control Of Complex Technology Trading Network

The complex network theory is derived from graph theory."The network theory in21st century is regarded as the quantum mechanics in20th century" quoted by Li Guojie. It has been widely used in social relation, electric power transmission, disease spread, city traffic and other fields. This paper applies the complex network theory to the technology trading. And the whole content will analyze the structure characteristics and behavior of the complex technology trading network in the perspective of "network" by using the technology trading data of Beijing over the last20years. The main contents include the following parts:1. This paper uses the real data to build technology trading network model by mapping the vendors and vendees to vertices and mapping the trading relations to edges. The trading processes or relations can be easily shown by the network model.2. This paper identifies the difference between technology trading network and common complex network on structure characteristics. Technology trading network static structure empirical research mainly involves the degree distribution, clustering coefficient, betweenness centrality, closeness centrality and density. The technology trading network is a special complex network which has long tail degree distribution, low clustering coefficient, short average path length and high sparsity. With time passed by, the polarization of the network will become deeper. It is apparent different from the common complex network such as small-world network or scale-free network.3. This paper researches the evolution of this network and establishes time series model to fit and describe this evolution. The evolutions include the whole network, the vertices and edges, the structure characteristics and so on. Based on the real data between structures and functions, this paper establishes the time series model and predicts the trading volume.The technology trading network provides a new perspective for technology trading activities. Based on the empirical research, the conclusions and suggestions of this paper is aim to support the decisions of technology trading.