Early Warning Model Of Agriculture-Supermarket Docking Supply Chain Risk Based On Bayesian Network

The issue of "agriculture,rural areas and farmers" has always been the focus of attention in China.As agricultural products are important economic sources in rural areas,improving the production and circulation efficiency of agricultural products is an effective means to promote the development of rural economy.As a special supply chain of agricultural products,"Agriculture-Supermarket Docking" is conducive to the establishment of a direct relationship between farmers and supermarkets,which can effectively to solve the problems of disconnection between production and sales of agricultural products,quality and safety,and is one of the important ways to improve the circulation efficiency and effect of agricultural products.Theoretically,the mode of "Agriculture-Supermarket Docking" is conducive to the modern development of agricultural products circulation,but in fact,the implementation effect of "AgricultureSupermarket Docking" in China is not ideal.Problems such as unstable docking and small implementation scope lead to the slow development of "rural and super docking" in China."Agriculture-Supermarket Docking" supply chain is facing many risks.Effective risk warning and management can help to enhance the stability of the "Agriculture-Supermarket Docking" supply chain and promote the participation of each subject.Therefore,it is of great significance to research the risks of "AgricultureSupermarket Docking" supply chain.This paper builds a risk early-warning model for the "Agriculture-Supermarket Docking" supply chain based on the Bayesian network.Firstly,this paper analyzes the current situation of "Agriculture-Supermarket Docking" in China from the docking mode and main elements based on the case study and related literature.Secondly,based on summarizing and combing the previous researches on the risk of supply chain of agricultural products,combining with the characteristics of the mode of "AgricultureSupermarket Docking" in China,this paper analyzes the risk of "AgricultureSupermarket Docking" supply chain from seven aspects: production management,enterprise management,connection cooperation,technology,natural environment,market environment and political economy.Then obtains the main risk factors of "agriculture-super connection" supply chain through empirical research.Thirdly,With the empirical research for reference to construct the risk factors of farmers and the supply chain risk early warning index system,with the empirical research of the questionnaire survey data as the training data set for training Bayesian network structure and parameters.Then set up the risk early warning lights range,build the "Agriculture-Supermarket Docking" supply chain risk early warning model.Finally,to verify the applicability of the model through model simulation analysis.Carry out the forward reasoning experiment and reverse reasoning simulation experiment of the model to predict and diagnose the supply chain risk of "Agriculture-Supermarket Docking" based on the actual case.According to the simulation results of the early warning model,this paper gives the risk management countermeasures and suggestions of enterprise management,production management and docking cooperation in the supply chain of "Agriculture-Supermarket Docking".The purpose of this paper is to research the risk early warning model of "Agriculture-Supermarket Docking" supply chain.It is a new attempt to apply the Bayesian network,which belongs to the field of machine learning to the risk research of "agriculture-super connection" supply chain.The risk early warning model is helpful for managers to effectively guard against risks and optimize the allocation of resources,to provide a good reference for the management of "Agriculture-Supermarket Docking" supply chain risk in China.Improving the risk management level of China's "Agriculture-Supermarket Docking" supply chain is conducive to the development of the mode of "Agriculture-Supermarket Docking" and has a positive effect on improving the circulation level of agricultural products in China.