Research On Goodwill Value Evaluation Of Internet Companies Based On GRNN Neural Network

In recent years,the frequent occurrence of "goodwill thunderstorms" of Internet companies has attracted widespread attention from government departments and all sectors of society.Goodwill is an important part of Internet companies,and the value of Internet companies’ goodwill reflects the company’s market position in the market.The traditional goodwill value evaluation method is too subjective,and the measured goodwill value of the enterprise does not match the market positioning of the enterprise,which leads to problems in the operation of the enterprise.If this phenomenon is widespread,it will make the capital market healthy.development is affected.Based on the current problems in the evaluation of goodwill value,combined with the trend that the theoretical research of goodwill value evaluation mainly focuses on factor analysis,this thesis introduces a new evaluation method of goodwill value—GRNN neural network model evaluation method,which further enriches the An evaluation system for the goodwill value of Internet companies.First,this thesis systematically sorts out the literature related to the definition of goodwill and the evaluation method of goodwill value,and selects the influencing factors of goodwill.Combined with the development status of the Internet industry and the characteristics of Internet companies,the influencing factors of the goodwill value of Internet companies are determined.Use the existing literature to analyze the quantification of the influencing factor indicators;secondly,based on the principal component analysis method,the rough selection indicators are screened,and the non-linear related independent variables are retained as the evaluation indicators of the goodwill value of Internet companies;The GRNN neural network model is established and tested with the sample data;finally,the traditional goodwill value evaluation method and the model established in this thesis are used to evaluate the goodwill value of the target Internet company Shanghai Tian Xi Hu Yu,and the evaluation results of the two are compared and analyzed..To sum up,the research conclusions of this thesis are as follows:(1)Based on the GRNN neural network theory,a preliminary exploration and establishment of the goodwill value evaluation index system of Internet online game enterprises is established.Using the GRNN neural network model with the characteristics of nonlinear mapping,based on the analysis of the sources and characteristics of the goodwill value of Internet companies in the existing literature research results,according to the source of the goodwill value of Internet companies Externally analyze the factors affecting the goodwill of enterprises,and determine the goodwill value of Internet enterprises from the aspects of reflecting the historical importance of Internet enterprises,enterprise scale,operation ability,growth ability,macroeconomic market conditions reflecting the M&A transaction environment,and the scale of M&A transactions.Evaluation index system.(2)Introduce and establish the GRNN neural network model to evaluate the goodwill value of Internet companies,and demonstrate the feasibility of using the GRNN neural network model to evaluate the goodwill value of Internet companies.For the acquired Internet companies,due to the characteristics of light assets,difficult to determine the development direction and less relevant public data in the M&A market,the neural network model based on GRNN has good nonlinear mapping ability and strong data learning ability,etc.It is specially introduced into the evaluation system of goodwill value to further enrich the evaluation content of goodwill value.The conclusion drawn from the empirical analysis results shows that it is reasonable to use the GRNN neural network model to evaluate the goodwill value of Internet companies.