Construction of Data Asset Value Assessment Model Based on Multi-Period Excess Return Method—Taking BYD as an Example

随着大数据时代的到来，数据资产作为一种新型资产形式，已成为企业核心竞争力的重要组成部分。数据资产与传统资产在性质上有显著不同，其价值难以用传统方法直接衡量。如何准确界定数据资产的范围和特性，以及如何让各方对数据资产的价值有共同的认识是一个巨大的挑战。本文以新能源汽车领军企业比亚迪为例，运用多期超额收益法构建数据资产价值模型。对比亚迪数据资产的分析，揭示其对企业价值的贡献。通过与同等资产规模的新能源汽车企业的数据资产价值进行对比，进一步表明了该模型的可靠性。With the arrival of the big data era, data assets, as a new form of assets, have become an important part of the core competitiveness of enterprises. Data assets are significantly different from traditional assets in nature, and their value is difficult to be directly measured by traditional methods. How to accurately define the scope and characteristics of data assets, as well as how to make all parties have a common understanding of the value of data assets is a great challenge. This paper takes BYD, a leading new energy automobile company, as an example, and uses the multi-period excess return method to construct a data asset value model. BYD’s data assets are analyzed to reveal their contribution to enterprise value. The reliability of the model is further demonstrated by comparing it with the data asset value of new energy automobile enterprises with the same asset size.