会计学院知识库

近年来，随着物流网络化、智能化、信息化工程稳步开展，数据资产已成为数字经济时代物流企业的基础性资源和关键生产要素，是企业的核心竞争力。因此，衡量物流企业数据资产的价值，对企业而言可以有效提升企业执行效率和管理能力，为投资者了解企业数据资源价值、提升决策效率提供有用信息。对市场而言建立起公允合理的数据资产价值评估体系可以鼓励拥有数据资产的企业及时充分的进行信息披露，进而使资本市场更加公开透明。然而，我国对于数据资产的研究还处于初期阶段，也没有建立起全面系统的价值评估体系。因此，对物流企业数据资产进行价值评估，不仅可以促进企业对数据资产的管理，提升企业的价值，而且对于促进市场有序发展和经济高质量提升有重要意义。

本文通过对数据资产和物流行业的发展现状进行分析，提出本文的研究意义。之后通过对评估方法相关的基础理论和数据资产的国内外文献综述进行梳理，为后文的研究提供理论基础。接着，通过介绍物流行业数据资产的特点及价值维度，指出数据资产的特殊性，说明传统评估方法的不适用。同时，由于数据资产具备期权的特征且这些特征与实物期权法的使用条件相匹配，因此本文在对物流行业数据资产进行评估时引入实物期权中的B-S模型，以期挖掘数据资产的潜在价值。本文在评估模型的构建过程中首先运用模糊数学法对B-S模型的参数进行修正，运用修正后的B-S模型对企业的整体价值进行评估，之后再运用收益分成法从企业整体价值中分离出数据资产的价值。最后，本文以顺丰控股为案例研究对象，将所构建的评估模型应用其中来验证模型的可行性。

本文的研究结果表明，运用实物期权法对数据资产的价值进行评估，充分考虑了数据资产的收益不确定性和可选择性；并且运用模糊数学的方法对B-S模型的参数进行修正，充分考虑了市场的不确定性因素；运用层析分析法和集值统计法计算数据资产的收益分成率，消除了主观因素对数据资产权重确定的影响，可以使评估结果更接近实际价值。这一价值评估体系可以为物流企业数据资产评估提供一种借鉴思路，加速物流企业进行数字化转型升级。

In recent years, with the steady development of logistics networking, intelligence, and informatization projects, data assets have become the fundamental resources and key production factors of logistics enterprises in the digital economy era, and are the core competitiveness of enterprises. Therefore, measuring the value of data assets in logistics enterprises can effectively improve their execution efficiency and management capabilities, providing useful information for investors to understand the value of enterprise data resources and improve decision-making efficiency. Establishing a fair and reasonable data asset valuation system for the market can encourage enterprises with data assets to timely and fully disclose information, thereby making the capital market more open and transparent. However, research on data assets in China is still in its early stages and a comprehensive and systematic value evaluation system has not been established. Therefore, evaluating the value of data assets in logistics enterprises can not only promote the management of data assets and enhance their value, but also have important significance for promoting orderly market development and high-quality economic growth.

This article shares the current development status of data assets and logistics industry, and proposes the research significance of this article. Afterwards, a review of the basic theories related to evaluation methods and domestic and foreign literature on data assets will be conducted to provide a theoretical basis for subsequent research. Next, by introducing the characteristics and value dimensions of data assets in the logistics industry, the particularity of data assets is pointed out, and the inapplicability of traditional evaluation methods is explained. Meanwhile, due to the fact that data assets have the characteristics of options and these characteristics match the conditions for using the real options method, this article introduces the B-S model in real options when evaluating data assets in the logistics industry, in order to explore the potential value of data assets. In the process of constructing the evaluation model, this article first uses fuzzy mathematics to modify the parameters of the B-S model, evaluates the overall value of the enterprise using the modified B-S model, and then uses the profit sharing method to separate the value of data assets from the overall value of the enterprise. Finally, this article takes SF Holdings as the case study object and applies the constructed evaluation model to verify the feasibility of the model.

The research results of this article indicate that using the real options method to evaluate the value of data assets fully considers the option attributes of data assets, and using fuzzy mathematics methods to modify the parameters of the B-S model, fully considering market uncertainty factors, can make the evaluation results closer to actual value. This value evaluation system can provide a reference for the evaluation of data assets in logistics enterprises, accelerating their transformation and upgrading.