Performance evaluation of logistics enterprises based on non-radial and non-angle network SBM model

Abstract

For the logistics transshipment center, it can combine historical data to compare performance vertically to clarify its own performance level and development trend, and clarify its own development shortcomings, and finally improve its own shortcomings to improve its performance. In order to study the performance evaluation methods of logistics enterprises, this paper builds a logistics enterprise performance evaluation system based on the non-radial and non-angle network SBM model based on machine learning algorithms. Moreover, this paper combines the idea of balanced scorecard to comprehensively analyze the operating efficiency of my country’s listed logistics companies through data envelopment analysis model, Malmquist index model and Tobit regression model. In addition, this paper uses the network SBM model to conduct a static analysis of vertical comparison of listed logistics companies in different stages and different industries and combines the Malmquist index to dynamically analyze the operating efficiency of listed logistics companies in my country from a dynamic perspective. Finally, this paper analyzes the company’s operating efficiency with examples. The results show that the model constructed in this paper has a certain effect.