Gui Juhan
Enterprise credit construction is not only related to the long-term development and lasting vitality of enterprises, but also an important means to promote the entire industry to enhance credit awareness and improve comprehensive competitiveness, and is the basic guarantee for the healthy operation of the national economy. With the vigorous development of China's modern logistics industry, in the face of fierce market competition, it has become an urgent problem for logistics companies to improve their credit brand, expand their credit reputation, and enable them to obtain more business opportunities in the operation of the modern logistics market. Therefore, this paper will draw on the successful experience of credit evaluation in other industries, combine the current situation of the logistics enterprise credit evaluation index system, and establish a set of logistics enterprise credit evaluation index system according to the principles of credit evaluation system construction. In this paper, Logistic regression, decision tree and random forest method are used to establish a credit evaluation model of logistics enterprises. After research, it is found that the three models have better prediction effects on the credit evaluation of logistics enterprises, and the random forest model has the best applicability in the credit risk evaluation of listed companies.
Enterprise credit evaluation; Logistic regression; Decision tree; Random forest