Valuation Of Data Assets Of E-commerce Enterprises Based On Multi-period Excess Return Method

In recent years,with the continuous emergence and application of new technologies,the accelerated growth of massive data and the rapid development of digital economy,data has become the basic strategic resources and revolutionary key elements in the era of digital economy.The Fourth Plenary Session of the 19 th CPC Central Committee in 2019 clearly defined data as a factor of production for the first time and participated in the distribution according to contribution,which means that data assets will be paid more and more attention.In this context,more and more enterprises dig deeply into the value of data,especially in the field of e-commerce,and data assets increasingly become the main component of enterprise core value.In this context,this thesis takes the data assets of the e-commerce industry as the research object and adopts the multi-period excess return method to evaluate the data assets of e-commerce enterprises.In this thesis,the multi-period excess return method is used to study the value of data assets.It is mainly divided into the following three parts: The first part firstly summarizes the research background and significance of data assets,and summarizes the literature of domestic and foreign scholars in the field of data assets.On this basis,the research ideas of this thesis are put forward.Secondly,the definition and characteristics of e-commerce enterprises and data assets are given,and the theoretical basis of the value evaluation of e-commerce enterprises’ data assets is introduced.Finally,the thesis reviews the traditional data asset evaluation methods,discusses the applicability and limitations of the methods,and puts forward the evaluation methods in this thesis.In the second part,firstly,an evaluation model of e-commerce enterprise data assets based on multi-period excess return method is constructed.The specific evaluation idea is as follows: deducting the income brought by other tangible assets from the overall income of the enterprise,obtaining the income of intangible assets,and then calculating the proportion of data assets in intangible assets with the sharing rate,obtaining the income brought by data assets.Finally,the value of data assets on the base date of evaluation is obtained by discounting it with the discount rate.The time series ARIMA model is used to forecast the business revenue in the next five years.In the calculation of data asset sharing rate,in order to reduce the differences between individual experts,group decision making AHP is selected for calculation.In the third part,we test the applicability of the data asset value evaluation process based on the focus technology data.Based on the above discussion,this thesis summarizes the full text,and puts forward suggestions and research prospects.There are three main conclusions of this thesis: First,compared with traditional evaluation methods,multi-period excess return method has stronger applicability and can provide reference methods for the value evaluation of e-commerce enterprises.However,this method still has some shortcomings and needs to be adjusted and improved continuously in the future.Secondly,the accuracy of each parameter should be improved to make the evaluation result more accurate when the multi-period excess return method is used to evaluate the value of data assets.In the use of analytic hierarchy process,the sample size of experts should be expanded,and the expert rating should be given a reasonable weight to reduce the subjectivity of calculation.Third,data assets contain huge business value and can bring huge incremental benefits to enterprises.In the future production practice,enterprises should strengthen the application and mining of data assets,so as to promote the development of enterprises.