Evaluation Of B2C Enterprise Value Based Oneva Modified Model

In recent years,the trend of e-commerce in China is rapid,and the object of enterprise value evaluation is also inclined to the research of e-commerce industry.At present,the mainstream e-commerce mode is B2 C mode.Combined with the particularity of overseas listed enterprises in China,how to evaluate the value of B2 C e-commerce enterprises reasonably is the focus of current investors.This paper first introduces the traditional methods of value evaluation,including asset-based method,market method and income method.After analyzing the advantages,disadvantages and application scope of each evaluation method for B2 C e-commerce enterprises,this paper explains the evaluation method of EVA model.By selecting EVA method to evaluate the value of B2 C e-commerce enterprises,it truly reflects the ability of enterprises to create value under all capital.Industrial conditions,operating conditions and macroeconomic conditions are different for different enterprises.When evaluating enterprise value,we should consider the specific development stage of the enterprise and choose the appropriate enterprise value evaluation model.Without considering non-financial factors,but based on financial data,it is a disadvantage of EVA value model.Because the non-financial factors have an extremely important influence on the enterprise value itself,in order to make up for this shortcoming,the Non-financial Analysis of the enterprise's valuation idea is carried out,that is,the non-financial angle is modified on the basis of the traditional EVA model,the key lies in the selection of non-financial factors indicators,so as to determine the correction coefficient.In this paper,EVA modified model is used to analyze the value of vipshop,a NASDAQ listed B2 C e-commerce company.This paper uses the valuation results calculated by data and the comparison with the stock value on the benchmark date to verify the applicability and superiority of the new valuation method mentioned in this paper.