Experimental Study On The Impact Of Information Sharing On Supply Chain Risk

As a risk carrier conduction factor, information involving two or more members of the supply chain, it is seen as the biggest risk faced by the members of the supply chain, further more it is the essence of supply chain risk. Supply chain risk comes from the asymmetry between supply chain nodes, so information sharing is considered to be an important way to relieve asymmetric information and reduce supply chain risk.In the case of imperfect information, combined Stackelberg model, introducing information sharing coefficient k, the establishment of information sharing with secondary supply chain between manufacturers and retailers, analyze its mathematical relationships, use the elastic coefficient reflect the level of information sharing between supply chain nodes to illustrate the effect of risk transfer in the secondary supply chain, and ultimately reveals the phenomenon of the information sharing level has led to changes in sales prices and profit risk transfer in the supply chain nodes. Through analysis shows that not all risks are passed along with the strength of association between enterprises in supply chain information sharing increases weakened, it may be a range.Next, in order to reflect relationship of the supply chain members and select the key factors- information sharing, as a inducible factor of supply chain default risk. O n the basis of bounded rationality setting bid rules, using Swarm simulation for computer experiment, in bid process, utility deviation as a measure of effectiveness indicators of default risk, and use the "combination bias" to measure the default risk intensity of economic agents in different information sharing.Finally, from the information flowing of supply chain members, use system dynamics theory to build inventory state transition model, the fluctuations in the level of inventory in the supply chain for each members is intermediate variables, and by averaging stocks volatility and standard deviation to quantify risk. Formulate assumptions and introduce the case studies in Computer Science JAVA programming language simulation, analyze the relationship between different information sharing and risk delivery in the supply chain.