Research On The Value Evaluation Of Logistics Enterprise Data Assets Based On Excess Return Method

In recent years,with the rapid development of digital economy in the world,big data has become a strategic resource for the rapid and steady development of countries.Data,as a new factor of production,is fundamental to the development of digital economy,artificial intelligence and other technologies.The continuous development of big data technology also makes the digital transformation of the traditional logistics industry constantly upgraded and updated.In June 2020,the National Development and Reform Commission and the Ministry of Transport jointly issued the Notice on the Implementation of Further Reducing Logistics Costs,proposing to accelerate the digitalization and modernization of the management of freight,transport services and sorting facilities.At present,logistics enterprises use the Internet big data technology to generate a large number of data assets in logistics transportation,storage,packaging,loading and unloading,distribution and other links.Currently,there are no uniform scientific standards for pricing data goods in the logistics sector.In order to promote logistics companies to explore the potential value of data integration,to make a scientific and accurate evaluation of the value of big data assets,it is an urgent topic for the asset evaluation practice circle to solve.As an important part of modern logistics enterprises,big data assets are an important part of modern logistics businesses and have become the core competitivenessof businesses.The largest data transactions in China involve big data of logistics companies,indicating that big data assets of logistics companies are an important part of data transactions.In this context,this thesis chooses the data assets of SF Holding,which has a relatively complete intelligent logistics network construction,as the evaluation object.Firstly,the background and research status of data assets are analyzed,and on this basis,the relevant theories are summarized.Secondly,it compares and analyzes commonly used data asset value assessment methods,analyses the applicability of traditional evaluation methods,and advances evaluation ideas tailored to SF Express data resources.Third,because the value contribution of data assets is closely linked to the value contribution of other assets of the enterprise,which makes it difficult to divest,this thesis adopts analytic hierarchy process to optimize and adjust the multi-period excess return method,determines the objective layer,criterion layer and scheme layer,and makes a detailed discussion on them,so that users of the evaluation report can understand the influence degree of each factor more clearly and intuitively.The value of SF Holding data assets calculated based on the excess return model of analytic hierarchy process is 4.482 billion yuan,and the value obtained by market method is 4.399 billion yuan after verifying the evaluation results with market method,which explains the reason for the difference between the two.Finally,it discusses the deficiency and prospect in the process of data asset evaluation of logistics enterprises.In this thesis,the logistics enterprise data assets launched an in-depth study,and made a systematic conclusion and definition of its theory,in order to provide an effective reference for the theoretical definition and value evaluation of data assets.The thesis consists of 14 figures,39 tables and 79 references.