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

2020 ◽  
pp. 1-12
Author(s):  
Huang Man ◽  
Lian Jie

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.

2003 ◽  
Vol 14 (2) ◽  
pp. 22-34 ◽  
Author(s):  
Hokey Min ◽  
Seong Jong Joo

In an era of downsizing and financial cutbacks, the operational efficiency of trucking firms dictates their competitiveness and survival. In an effort to help trucking firms develop a winning formula in the fiercely competitive logistics industry, this research aims to develop a meaningful set of benchmarks that will set the tone for best practices. In particular, a data envelopment analysis (DEA) is described. DEA has proven to be useful for measuring the operational efficiency of various profit or non-profit organizations. Using the examples of major trucking businesses in the United States, the usefulness of data envelopment analysis for the continuous improvement of trucking services is illustrated.


2020 ◽  
Vol 15 (2) ◽  
pp. 165
Author(s):  
Asmina Akter

In this study an Output-oriented DEA (Data Envelopment Analysis) model is used to measure operational efficiency of foreign branches of Bangladeshi banks as financial intermediary organization for borrowing funds from savers and lending those funds to others for making profit. Among 58 Bangladeshi banks there are only three Bangladeshi banks which have in total seven foreign branches in different foreign locations. A branch of bank can’t be separated legally from its parent company and supervised by its home authorities as part of supervision of the banking group as a whole. By employing DEA model and using “Financial Intermediary Approach” this study found that as a financial intermediary organization between savers and borrowers these foreign branches of Bangladeshi banks are performing efficiently over the years. Among three banks Janata Bank Limited and AB Bank limited are performing most efficiently and Sonali Bank Limited is performing less efficiently relative to two other banks in operating their foreign branches as a financial intermediary organization for borrowing funds from savers and lending those funds to others for making profit.


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