Abstract
Nowadays the explosive growth of digital assets has become a new economic growth point. The entry of data assets into the balance sheet and embracing the capital market to exert its multiplier effect have become trending topics. However, the quantification of data asset valuation, as data asset utilizations cornerstone, still faces many obstacles, such as discriminatory analysis, lack of scenario generalization valuation systems and multi objective quantitative dimension,etc.Starting from both subjective and objective dimensions and coordinating multiple market entities, this article constructs a multi factor valuation screening and scoring model to quantify the value of data assets and addresses these practical challenges. Quantify factors through methods such as the Short Ratio Method and Delphi Expert Method. Due to the heterogeneous preferences and requirements of different industries for different factors, this article uses the Compound Analytic Hierarchy Process and effect functions to rank and combine factors for weighting, meeting the specific application effects in various scenarios while also achieving a scenario generalization approach to meet the needs of cross industry trading of data assets. Finally, apply the model to the water resources data assets of the Yangtze River comprehensive management province. This case study promotes the valuation of water resources data assets and the multi-party trading and circulation between governments and market entities.This article aims to provide new models and academic recommendations for data asset valuation and value quantification, to assist in the utilization and circulation of data assets, as well as the construction of data asset trading markets.
Published Version
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