| Enterprise disease is seriously hindering the healthy development of Chinese enterprises.By helping enterprises improve their competitiveness,enterprise diagnosis is very good for China's enterprises to achieve sustained and healthy development and the healthy operation of market economy.Due to the influence of personal knowledge,experience and subjective color,the traditional enterprise diagnosis often suffers from serious personal preferences and lacks scientific nature.Based on this beam Liang Gefu and Pang Dalian(2004),the enterprise diagnosis is divided into four main modules and the computer aided calculation is introduced.A new semi structured diagnosis model,enterprise management diagnosis system(MCS)model,is proposed.The proposed model is of great significance to improve the scientific and efficient diagnosis of the diagnosis.The arrival of the large data age provides a new opportunity for the optimization and development of the MCS model as well as the higher requirements and challenges for the data processing and analysis of the MCS model.Through reading and summarizing a large number of literature,it is found that rough set theory has the advantages of no prior knowledge,strong attribute reduction and attribute importance principle.These advantages make the rough set superior to the decision analysis of data driven decision making.The decision making is usually based on a few key success factors.Based on this paper,the rough set theory is introduced to identify the key success factors in the data driven MCS model.The main part of this article is third and 42 chapters.First,in the third chapter,the application of the MCS model and its 4 main modules,especially the key success factors,is briefly outlined in the third chapter,to deepen the understanding of the system model and to clarify the logical relationships within the model.In this paper,the key success factor identification method(PCA),which is most commonly used in the MCS model selection and formation module,is used as an example to illustrate the limitations and shortcomings of the key success factor identification method in the application process of the current MCS model.The core content of the research.Secondly,in the fourth chapter,the fourth chapter is based on the limitations and shortcomings of the key success factor identification method in the current MCS model,the advantages of the rough set theory and its suitability for the identification of key success factors which should be used in the MCS model,and constructs a framework for the identification of key success factors in the rough set in the MCS model.The rough set theory is introduced into the model,so as to discuss the specific process of the rough set theory in the selection of the model project theme and the key success factor identification in the formation stage,and then to realize the transformation and optimization of the MCS model from the method level,and construct a more scientific,rational and operational MCS model,which makes the current enterprise diagnosis.The method,mode,efficiency and effect have been improved.Finally,taking the X express company's enterprise competitiveness diagnosis project as an example,this paper introduces the practical process of the MCS model of the rough set method as the key success factor identification method in the diagnosis of the competitiveness of the X express company.Through the empirical study,it is further demonstrated that the rough set theory method is more superior to the current use method(principal component analysis,factor analysis,etc.)when the MCS model is used for enterprise diagnosis.It effectively improves the efficiency of the diagnosis expert decision making scheme and the scientificity and maneuverability of the scheme,and also verifies the effectiveness of using rough set theory to deal with the uncertainty decision problem. |
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