Research On Financial Early Warning Of Yunnan Baiyao Based On Entropy Weight-Efficacy Coefficient Method

Listed companies are generally characterized by large scale of operation,many business segments,complex departmental structure and challenging management,so there may be a wide range of potential risk factors.The latest data released by the Ministry of Commerce Research Institute shows that as of May2022,there were a total of 4,447 non-financial listed companies in the A-share category.There were 2,295 companies with very low or low risk(AAA-BBB level),accounting for 51.61%;1,311 with controllable risks but financial deficiencies(BB-B level),accounting for 29.48%;and 841 with significant or high risk(CCC-D level),accounting for 18.91%.As can be seen,the number of enterprises with hidden dangers is quite large,and improving risk monitoring and early warning is essential for the development of the entire market.The author used the entropy weight-efficacy coefficient method to study the early warning of financial risks of Yunnan Baiyao Group.There are three reasons why Yunnan Baiyao Group was chosen as the study subject: first,the country has begun to implement the centralized procurement policy on a large scale,which is a significant test for pharmaceutical companies to reduce costs and improve profits under the premise of ensuring quality and quantity;Second,since the group completed the mixed ownership reform of state-owned enterprises at the end of2019,capital operation activities such as stock speculation and acquisition have continued,especially in 2021,the loss of stock speculation was as high as 2 billion yuan,and the financial risk was relatively large;Third,the financial early warning method currently used by the group is relatively old,which is not only influenced by human subjective judgment but also the early warning results are too lagging,so it is necessary to optimize its financial early warning model.The author firstly introduces the background,framework,and theory of the study;then analyzes the current financial status of Yunnan Baiyao Group and points out the necessity of optimizing its early warning method;then establishes the entropy weight-efficacy coefficient method early warning model,and analyzes the data of Yunnan Baiyao for the past five years and the latest 2022,and summarizes the financial problems of the group;finally proposes corresponding improvement suggestions based on enterprise diagnosis theory and stakeholder theory.The purpose of this thesis is to help managers of Yunnan Baiyao Group and other related parties,such as investors,creditors and suppliers,to identify the financial risks of the company in a timely manner,so that they can take more targeted measures and achieve win-win cooperation.It is also hoped that it can provide risk management ideas and experience for other companies in the same industry,in order to promote the healthy development of the company.There are two innovations in this thesis: first,the financial early warning index system is selected based on relevant literature and a sample of 69 non-ST companies in the Chinese medicine industry,and the SPSS software is used for screening index to ensure the scientific of the financial early warning model index system;second,the entropy power method and the improved efficacy coefficient method are combined to make the early warning results more accurate.In the existing literature,there are very few studies combining the two for enterprise financial risk early warning research.The entropy weight method overcomes the negative impact of artificial subjective assignment;the improved efficacy coefficient method adjusts the criteria of early warning results from two categories to five categories,and introduces the concept of dynamic integration ratio to make the early warning results more accurate.