Research On The Evaluation Of Big Data Assets Of Logistics Enterprises In Digital Economy

At present,the world is in a phase of digital industrialization,where the internet industry or traditional manufacturing industries are accelerating the integration of big data to drive improvements in business models,build digital economy platforms and create new economic growth poles.As early as 2016,the national government has elevated the development of big data technology to the level of national development strategy and announced in the 14th Five-Year Plan that it will increase research and investment in related core technologies(such as big data analysis and cloud computing)to promote the construction of our digital power.To promote and facilitate the trading of data,big data trading centers are currently being set up all over the country,and China is already occupying the high ground of the global big data industry.The development of big data and information technology has also contributed to the upgrading of traditional logistics industry,and entities in the logistics industry are scrambling to actively promote the construction and implementation of intelligent logistics networks,with a view to achieving precise control of all aspects of logistics and transportation,thereby enhancing both logistics and distribution efficiency and corporate profitability.As an essential part of modern logistics enterprises,big data assets have become the core of the enterprise and the source of core competitiveness.However,there are still some difficulties in the valuation and pricing of big data assets of logistics enterprises,and the question of what method of valuation can improve the scientific and accurate nature of this process is a pressing issue in current asset valuation practice.This paper firstly compares the relevant literature around the topic of big data assets,elaborates on the relevant basic theories of big data assets,the current status of domestic and international research,further explores in depth the factors influencing its value,and introduces the relevant connotations of big data assets in the logistics industry.Then,through a comparative analysis of several asset valuation methods previously adopted,the applicability of each method is elucidated;a suitable big data asset value assessment model is established,taking into account the characteristics of this asset.At the same time,Yuan Tong Express Company Limited,which is located in the forefront of domestic logistics enterprises,was selected as the sample,and the big data assets owned by it were taken as the research object,and the traditional income approach was used as the basis for the modified and improved model in view of the characteristics of big data assets in the logistics industry.The modified model was also applied to evaluate the big data assets of Yuan Tong Express to measure the value of its big data assets at the valuation base date.In the measurement,the hierarchical analysis method was combined with the fuzzy integrated analysis model to make up for the shortcomings of the multi-period excess earnings method,which ignores the asset’s own development status and focuses only on the impact of financial indicators,and the correction coefficients were calculated and adjusted,thus making the performance of the impact of the asset’s value elements clearer and more intuitive,and the valuation results more accurate,reducing the bias generated at the subjective level and more in line with the enterprise’s internal The study helps logistics companies to gain a comprehensive understanding of their assets.This study helps logistics enterprises to understand their big data assets comprehensively,and at the same time,it enriches the basic theory and value assessment model of data asset valuation,providing a reference for future research in this field and putting forward corresponding policy recommendations to promote the development of big data asset valuation.