Data Asset Recognition on the Balance Sheet: Theoretical Framework, Practical Challenges, and Implementation Pathways

Data elements have become crucial production factors driving corporate economic growth and value creation. This paper reviews the policy framework and evolutionary process of data asset recognition on the balance sheet. Through a systematic analysis of the current status and typical models of data asset recognition among listed companies, it delves into the challenges encountered in current practices from four dimensions: ownership confirmation dilemmas, valuation methods, corporate capabilities and willingness, and information disclosure versus commercial secret protection. Building on this foundation, it proposes implementation pathways for data asset recognition on the balance sheet and corresponding recommendations, aiming to provide operable guidance for enterprises’ data asset recognition and references for further standardization and refinement of accounting policies.