【摘要】 在数字经济时代，数据资产已成为企业核心竞争力的关键要素，但其价值评估仍面临理论标准缺失与实务操作复杂的双重挑战。尤其信息技术行业，因数据动态性、权属复杂性等问题，传统评估方法存在显著局限。本文以卓创资讯为例，提出改进的超额收益法，融合灰色预测模型、马尔可夫链及组合赋权法，构建动态估值框架。通过灰色预测捕捉数据资产收益趋势，马尔可夫链修正非线性波动，组合赋权法综合主客观因素确定数据资产贡献率。研究表明，该方法可突破传统收益法的静态假设，为信息技术行业数据资产价值量化提供新的视角，助力企业释放数据要素价值。更多还原

【Abstract】 In the era of digital economy, data assets have become a key element of enterprise core competitiveness, but their value evaluation still faces the dual challenges of theoretical standard deficiency and complex practical operation. Especially in the information technology industry, traditional evaluation methods have significant limitations due to issues such as data dynamics and ownership complexity. This article takes Zhuochuang Information as an example to propose an improved excess return method, which integrates grey prediction model, Markov chain, and combination weighting method to construct a dynamic valuation framework. Capturing the trend of data asset returns through grey prediction, correcting nonlinear fluctuations with Markov chain, and determining the contribution rate of data assets through a combination weighting method that integrates subjective and objective factors. Research has shown that this method can break through the static assumptions of traditional income methods, provide a new perspective for quantifying the value of data assets in the information technology industry, and help enterprises unleash the value of data elements.更多还原