Affiliations: [a] School of Accounting, Zhongnan University of Economics and Law, Wuhan, Hubei, China
| [b] School of Accounting, Capital University of Economics and Business, Beijing, China
Correspondence:
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Corresponding author. Caiyun Chen, School of Accounting, Zhongnan University of Economics and Law, Wuhan, Hubei, 430073, China. E-mail: [email protected].
Abstract: There are many problems in the supply chain management of Chinese enterprises, which restricts the development of enterprises and the improvement of benefits. In order to improve the decision-making ability of Internet of Things (IoT) applications in enterprise supply chain management, the collaborative filtering algorithm is optimized. The algorithm determines the collaboration type according to the nature of the optimization target, and calculates the user similarity based on the user browsing behavior, so as to seek the recommendation function of the user to best evaluate the individual. According to the two objectives of the shortest time and the highest overall satisfaction in emergency dispatching in enterprise supply chain management, a two-level planning model of commodity scheduling is constructed, the time function of the supply chain delivery process calculated. The simulation results of the model show that the demand forecasting algorithm based on neighborhood rough set and GA-SVM is used to predict the demand of chain retail supply chain, which achieves high prediction accuracy. The maximum error is 5.71%, the minimum error is 0.60. The average error is %, which is 2.84%. The research in this paper has implications for enterprise application of IoT in supply chain management. The use of decision-making model can greatly improve the operational efficiency of the supply chain.
