Research On The Data Asset Valuation Driven By The Digital Economy

With the development and innovation of digital technologies such as Artificial Intelligence,Blockchain,Cloud Computing,and 5G,data has become a key production factor in the digital economy era.In the process of data assetization,data asset valuation plays an indispensable role in the in-depth utilization,efficient circulation,fair transaction and high-quality management of data.At the same time,it faces bottlenecks such as unclear definition of concepts,unclear division of ownership,vague formation mechanism of value,and limited applicability of valuation models.Therefore,how to clearly define data asset and its ownership,clarify the value formation mechanism of data asset,how to optimize the data asset valuation model and improve the data asset valuation system,have become important issues in the field of data asset theoretical research.This paper,with the title of "Research on the Data Asset Valuation Driven by the Digital Economy",conducts a systematic study on the theoretical,empirical and case studies on the data asset valuation,aiming at activating the potential of data value,promoting the effective circulation of data,ensuring the fair transaction of data,and improving the level of data management.The main research contents of this paper:(1)Clarifies the basic premise of valuation such as the concept of data asset and right system,combines with accounting standards and asset valuation standards,summarize the definition and judgment process of data asset;and combines with the legal dilemma of data transfer and the rights system in Chinese and overseas,to explore ways of balancing the interests of multiple subjects.(2)Carries out data asset value analysis,based on the perspective of value manifestation,the formation stage of data asset value,the manifestation and realization methods of value,and the influencing factors of value are sorted out in detail,and uses the system dynamics causal flow diagram to analyze the formation mechanism of data asset value.(3)Optimizes the classic method model of data asset value valuation,in view of the weak correspondence between cost and value,a cost approach valuation optimization model of "Cost+Premium-Depreciation" is constructed,and the SD model is constructed using the system dynamics principle to measure the expected use premium;and in view of the dependency of data asset,the excess income approach valuation optimization model is constructed,and the adjustment coefficient k of the whole set of contribution asset excluding data asset is empirically calculated by using Nonlinear OLS and Gauss-Newton iterative method,and in view of the low activity of data market in the early stage of data market construction,the application of market approach is difficult,and the model of "Benchmark+Correction" is constructed.(4)Bases on the characteristics of the digital economy era,discuss the practical application system of data asset value valuation and the supporting measures to ensure its realization.The main research conclusions of this paper:(1)The transformation of data into data asset needs to pass the ECPQN-M judgment process;the rights and interests boundary among multiple subjects of data assets is that after the data producers “trade” the data,the data asset rights system grants them data personality rights,but does not enjoy data.Property rights and data government rights.(2)Data asset value formation has three stages of TIA,and data asset value can be formed at any stage;the influencing factors of data asset value includes attributes class,cost class,economics class,risks class,and the above factors work together to form ACER;The formation mechanism of data asset value includes CA type,AE type,CE type,RA type,RC type.(3)The cost approach valuation optimization model of "Cost+Premium-Depreciation" is universal,and the SD simulation model can be extended to the valuation of other data asset;the excess income approach valuation optimization model is operable,and the calculation method of the adjustment coefficient k of the whole set of contribution asset excluding data asset is also applicable to the calculation of adjustment coefficients of various industries;the Benchmark Correction model can be used as an effective path support when the basic application conditions of the market method cannot be met.(4)Data asset value valuation practice activities should be guided by the overall valuation thinking,abide by the evaluation industry standards,determine the valuation purpose and evaluation method according to the entrusted business in the main part of the evaluation,and be supported by a sound evaluation system as a guarantee.The possible innovations of this paper:(1)In terms of research ideas,the characteristics of data assets are quantified and incorporated into the valuation model,and the optimization models of three classical valuation methods are constructed respectively;(2)From the research point of view,it proposes the judgment process of data asset,the multi-dimensional subject rights system,the ACER system and the five formation mechanisms of value;(3)In terms of research methods,various quantitative and qualitative methods such as Nonlinear OLS,Gauss-Newton iterative method,AHP,and system dynamics analysis method are it introduced into the classical valuation optimization model to enrich the calculation methods of model parameters.This paper aims to improve the scientificity and rationality of data asset valuation driven by digital economy,in order to deepen the existing theory,empirical and case studies of data asset valuation.At the same time,it not only strengthens the weak link of data asset valuation theory,but also further expands the research on data asset valuation.At the same time,it provides technical support and practical reference for promoting market-oriented allocation of data elements,engaging in data asset trading and value management for data asset holders,and formulating data asset valuation and management policies for relevant government departments and industry associations.