Comprehensive efficiency analysis of logistics industry based on machine learning and self-service data envelopment analysis model

• Published in: Journal of intelligent & fuzzy systems Vol. 40; no. 4; pp. 6913 - 6924
• Main Authors: Man, Huang, Jie, Lian
• Format: Journal Article
• Language: English
• Published: Amsterdam IOS Press BV 01.01.2021
• Subjects: Data analysis; Data envelopment analysis; Efficiency; Empirical analysis; Logistics; Machine learning; Profitability; Qualitative analysis
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-189522

The research on operational efficiency focuses on the macro-level research. However, there are relatively few studies on the industry level. In particular, there are fewer studies on the logistics industry, which has a leading and fundamental significance in the national economic system and is regarded as the third important source of profit. Moreover, scholars are more focused on the research on the operational performance and profitability of logistics enterprises. In order to study the efficiency of the logistics industry, this paper uses machine learning technology as the foundation and self-service data envelopment analysis to construct a comprehensive efficiency analysis model for the logistics industry. Moreover, this paper adopts a combination of qualitative and quantitative analysis to conduct empirical research on the operational efficiency and influencing factors of the logistics industry to explore the factors that affect the operational efficiency of logistics enterprises. In addition, this article optimizes the model data through statistics, and compares the model analysis data with the actual situation. It can be seen from the research results that the model constructed in this paper has a certain effect.