Research on the Impact Mechanism of Data Asset Management on Financial Performance under Digital Transformation
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Abstract
Under digital transformation, data has become a key production factor and strategic asset. Data asset management capability increasingly determines enterprise operational efficiency, cost control, revenue growth, risk governance, and value creation. Traditional financial management, which focuses mainly on tangible assets and ex-post accounting, cannot fully adapt to data-driven value creation models. Some enterprises still face problems of weak data governance, insufficient asset operation, and poor value conversion, causing a mismatch between digital investment and financial performance. This study examines the impact mechanism of data asset management on financial performance in the context of enterprise digital transformation. Based on resource-based theory, dynamic capability theory, value creation theory, and information asymmetry theory, the study defines data asset management through governance, quality, security and compliance, integration and sharing, and value operation. It further constructs a mechanism in which data asset management improves financial performance through operational efficiency, cost optimization, revenue expansion, risk control, and capital structure optimization, with digital maturity, industry attributes, and governance level as moderators. The framework is also applicable to enterprises that generate large-scale electromagnetic sensing, manufacturing, and communication data, where assetized data can support technical innovation and financial value creation. The study provides theoretical support and practical guidance for data-driven performance improvement.
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