Research On Asset Value Assessment Of Platform Data Based On AHP Method

In the report of the 19 th National Congress,Xi Jinping emphasized that in the future development,it is necessary to strengthen the deep integration of big data and the real economy.In the 21 st century,when data assets explode sharply,data resources are gradually evolving into an important driving force for the transformation and development of enterprises.Despite the increasing frequency of data assets transactions on the Internet,little research has been done on their value.Because of the narrow scope of intangible assets recognition in the field of asset evaluation,there is still no clear definition of platform data assets,and the theory and research of relevant evaluation methods are few.At the same time,due to the particularity of platform data assets,there are too many uncertainties and non-quantitative indicators in their value,which makes it more difficult to evaluate their value.Based on the current situation and problems of the platform data asset valuation,this paper takes the platform data asset valuation as the research object,clarifies the definition of the platform data asset for the purpose of analyzing and quantifying the platform data asset value,and uses AHP method to construct the evaluation platform data asset value model framework,and uses MySQL database to accurately evaluate the results of the research object.First,through the reading of relevant literature at home and abroad,the definition of platform data assets is clarified,and the characteristics,classification,value sources of the platform data assets and the current trading status in the market are understood.At the same time,this paper compared the existing methods of evaluating the assets,clarified the difficulties of the evaluation,and found that the evaluation method using the analytic hierarchy is feasible,so improved based on this method.Then comprehensively analyze the value influencing factors of the platform data assets,and summarize them into five indicators(granularity,diversity,scale,relevance and activity)and corresponding subdivision factors.The platform data asset value analysis model framework(input layer,hidden layer,output layer)is constructed,and the evaluation formula is established by using the analytic hierarchy process.The input layer indicators are specifically quantified by referring to the computer field related calculation and comprehensive scoring method.Thus a systematic approach to evaluating platform data assets is proposed.Finally,this paper uses the platform data asset value assessment model to conduct a case evaluation of the specific Zhilian recruitment platform data assets,and conducts an in-depth analysis of the specific input layer index standard definitions.The MySQL database and the Navicat database visualization tool are used to process the evaluation objects.The comparison of the actual transaction value confirms the feasibility of the model and then this paper proposes corresponding improvement suggestions.There are still some shortcomings in the research.The using of expert scoring method to determine the scores of individual difficult indicators lacks of relative objectivity.The model also needs to be investigated and improved for different platform data asset cases.In the era of big data,the increasingly frequent data purchase and demand for the asset evaluation will become more and more strict.How to analyze and measure the platform data assets more rationally is the main research direction of the asset evaluation industry in the future.