Research on the Impact of Data Asset Valuation on Corporate Financing Efficiency
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Abstract
As a new type of production factor, data assets increasingly affect corporate financing capacity and capital acquisition efficiency. Based on information asymmetry theory and the resource-based view, this paper constructs a theoretical model of the impact of data asset valuation on financing efficiency. A mixed research method combining questionnaire surveys and in-depth interviews is adopted to investigate credit-approval personnel of financial institutions and financial directors of digital economy enterprises. The results show that the quality of data asset valuation significantly improves financing efficiency by reducing information asymmetry. The standardization level of valuation plays a mediating role, while the recognition of valuation results by financial institutions exerts a moderating effect. Further analysis indicates that the cost approach is suitable for basic data assets, the income approach is suitable for operational data assets, and the market approach is applicable to transactional data assets under specific market conditions. The combined use of these methods can quantify data-asset value more comprehensively, providing theoretical guidance and practical reference for optimizing corporate financing decisions in the digital economy.
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