A Study On Risk Diffusion Of The Supply Chain Network Based On Computational Experiment

Supply chain network is a self-organizing network of complex structure which is a Commonwealth composed of node enterprises with contracts or business relations. Within the network, all companies are interdepended, when some risk factors appear in any company, they will continue to accumulate and transfer to other network nodes enterprise through chain reaction, and thereby affecting the normal operation of these enterprises and the safety of the entire supply chain network. Risk diffusion progress in supply chain network is a complex process and the traditionally way to study risk conduction is qualitatively analysis which ignored the dynamic nature of the risk of conduction. This paper study the risk diffusion progress with computational experimental which does not only to overcome the above defects, we can also study the laws of the risk conduction.Firstly, the paper analyzes the mixed community characteristics of the new supply chain network and models the supply chain network. Then, the Cowan knowledge dissemination model is improved and the paper refine the risk knowledge of innovative concepts and build a knowledge of risk of diffusion networks in order to achieve the purpose of prevention and control risks in the supply chain network. After that, the paper sum up the three basic concepts of risk diffusion process:risk inputs, risk tolerance limits and the risk output, study the necessity of researching risk diffusion with risk knowledge. By drawing on artificial neural network model and defining the relationship of risk knowledge and risk tolerance, a quantifiable supply chain network risk conduction model is proposed.On the experimental platform of Repast Simphony, the above experimental models are built step by step to verify the validity of this supply chain network model. Subsequently, five groups computational experiments are designed, in which two groups study the characteristics and effects of the dissemination of knowledge within the supply chain network, and the other three groups discussed the conduction circumstances of the risk within the supply chain network.With analysis of the results, we get the conclusion that internal innovation can get higher utility than knowledge exchange, but due to enterprises innovation capacity differences, innovation will to some extent increase heterogeneity of knowledge within the supply chain network. To the aspect of risk control, the daily operations of risk monitoring and risk prevention measures should be established in the enterprises and through the soft-power, the position in the supply chain and core competitiveness can be enhanced. Among all factors, knowledge innovation can create the most direct and effective anti-risk ability.