Research On B2B E-commerce Network Modeling And Simulation Based On Local Core Preferred Connection Model

With the rapid development of e-commerce,more and more enterprises choose to join the B2 B e-commerce platform,and exchanges and cooperation between enterprises become more frequent.In view of the complexity of the cooperative network in the e-commerce platform,it is difficult for individual enterprises to deal with the risks of intricate relationship networks in the platform.Therefore,based on complex network theory and network simulation technology,this paper establishes a B2 B e-commerce network model,studies the cooperative network between enterprises in the platform from the perspective of complex network,and helps the platform control risks.Firstly,from the perspective of the formation of B2 B e-commerce network,the network characteristics of B2 B e-commerce network and the motivation of network evolution are analyzed.According to the relevant analysis,the dynamic rules of e-commerce network,local preferential connection rules and core evolution rules are proposed.Then a local core preferred connection model is proposed based on the analysis of the limitations of BA scale-free network and the characteristics of B2 B e-commerce transactions,and a small-world B2 B e-commerce network model is obtained through simulation experiments.After the construction of B2 B e-commerce network,the complexity and risk of B2 B e-commerce network are analyzed,and the risk of B2 B e-commerce network is transitive,dynamic and random.Then,a new measurement method for the complexity and robustness of the e-commerce network is given.Finally,through the complexity experiment,the B2 B e-commerce network model is verified to be complex and scale-free;the interference of nodes and random edges has strong robustness,and the interference of nodes has a greater impact on network efficiency than the interference of edges.When the relationship between the network enterprise node and the enterprise is suffered by different business risks,according to its impact on the network efficiency,some suggestions are given to the platform managers.