Management Efficiency Evaluation And Application Based On Factor Analysis, Cluster Analysis And Two Stages Network DEA

Evaluation of the efficiency of the industry or company’s management has been a lot of scholars, and the data envelopment analysis method is very popular. From 1978 to now, a lot of theories and applications have produced a rapid development in science and technology innovation trend. Especially for the so-called "open the black box" network DEA theories and methods be put forward which make data envelopment analysis more popular. For the evaluation of the operational efficiency of multiple input multiple output multiple decision making units, this paper establishes a new operating efficiency evaluation method which based on the two stage of network DEA and combined with the factor analysis and cluster analysis of two multivariate statistical analysis method, and make a empirical analysis on the operating efficiency of 47 listed companies in the production of iron and steel.This paper studies the operating efficiency of the listed steel enterprises in 2014. Firstly, in accordance with the requirements of the DEA model, the collected alternative data indexs are divided into the input variables, the intermediate variables and the output variables; Secondly, many enterprises are divided into 8 types by the method of clustering analysis, which are the decision-making units of KH model; Then, the final input variables and output variables are extracted from the many alternative input variables and output variables by the method of factor analysis; Finally, taking the datas into the KH model to calculate, the datas is also brought into the traditional DEA model(CCR model and BCC model) to calculate, and comparing these results. In the whole process of calculation, SPSS is used for clustering analysis and factor analysis, and DEAP2.1 and MATLAB software are used to calculate DEA models. The analysis results show that the smaller the business efficiency is higher in many listed iron and steel enterprises, and the number of inventory is positively related to the operating efficiency.