Creator | 姬文岳 |
Name | Ji Wenyue |
Student number | 2021000008005 |
Degree Grantor | 兰州财经大学 |
Phone | 15314231735 |
Electronicmail | wenyuewl@163.com |
Year of admission | 2021-9 |
Degree category | 专业硕士 |
Training level | 硕士研究生 |
Subject major name | 资产评估 |
subjectnumber | 0256 |
firstguildname | 南星恒 |
First Instructor | Nan Xingheng |
firstguildunit | 兰州财经大学 |
Title of First Tutor | 教授 |
Title | 网络文学企业数据资产估值研究——以掌阅科技为例 |
Englishname | Research on the Valuation of Data Assets of Online Literature Enterprises: A Case Study of IReader Technology Co., Ltd. |
Keyword | 网络文学企业 数据资产估值 实物期权法 掌阅科技 |
Englishhingeword | Network literature enterprise ; Data asset valuation ; Real option method ; IReader Technology Co., Ltd. |
Abstract | 21世纪以来,信息技术飞速发展,带来了数字经济的崛起,随之带来了数据 资产的爆炸式增长,在这一过程中,逐渐出现了数据资产的交易活动,进一步地, 逐渐形成了数据交易市场。而数据资产能够正常进行交易的前提是可以对数据资 产进行合理估值,由此市场上产生了数据资产价值评估的需求。但是就目前而言, 数据资产作为一种“新型”资产,针对数据资产的价值评估仍处于探索阶段,尚 未有成熟完整的估值体系对其进行合理有效的估值。此外,网络文学企业较之传 统企业具有一定的特殊性,此类企业的未来发展具有高度的不确定性,往往难以 确定其数据资产的成本及能够带来的价值,因此依赖于公司财务指标的传统估值 方法难以对其进行有效估值。 本文选取网络文学企业掌阅科技有限公司作为案例企业,以掌阅科技的数据 资产作为研究对象,综合考虑未来环境不确定性和案例企业“以用户价值创造” 为核心的特性,以不确定性理论、顾客价值理论、齐普夫定律及情景分析理论为 理论基础,构建了以实物期权B-S模型为基础的估值模型,并创造性地以情景分 析法结合DEVA模型对实物期权B-S模型进行改进。具体而言,本文首先对案 例企业的基本状况进行分析,并以此为基础对其数据资产构成展开分析。接着, 通过行业对比分析确定可能影响企业未来发展的驱动因素,搭建情景框架并确定 情景概率,基于此,计算出案例企业单位用户创造价值的预测值,以DEVA模型 计算出期权当前价值S0。最后将参数带入实物期权B-S模型中计算得出掌阅科 技数据资产估值结果,并对估值结果进行分析说明。 通过研究,本文得到以下结论:第一,通过网络文学行业商业模式分析及数 据资产构成分析,总结出网络文学企业的企业特征及其数据资产特性,其特性主 要包括非实体性、可加工性、价值不确定性、可复制性及高风险性、看涨期权性 和可选择性五大特性。第二,通过对网络文学行业的企业特征、商业模式及其数 据资产特性展开分析,基于实物期权法B-S模型构建了数据可得性强、计算流程 相对简化的网络文学企业数据资产估值模型。通过模型计算可知,案例企业数据 资产的估值结果在其整体市值中占较高比重,表明数据资产在网络文学企业中发 挥了较大的作用。进一步地,网络文学企业应当重视数据资产在企业资产中的底 层支撑作用,充分发挥数据资产的盈利能力。同时,本文所构建的估值模型对网络文学企业数据资产估值具有较强的适用性,亦可为后续网络文学企业数据资产 管理工作提供一定数据支撑和管理思路。 |
English abstract | Since the 21st century, the rapid development of information technology has brought about the rise of the digital economy and the explosive growth of data assets. In this process, the trading activities of data assets have gradually appeared, and further, the data trading market has gradually formed. The premise that data assets can be traded normally is that data assets can be reasonably valued, thus the demand for data asset value assessment is generated in the market. However, at present, as a "new" asset, the value evaluation of data assets is still in the exploratory stage, and there is no mature and complete valuation system for reasonable and effective valuation. In addition, compared with traditional enterprises, online literature enterprises have certain particularity. The future development of such enterprises is highly uncertain, and it is often difficult to determine the cost and value of their data assets. Therefore, traditional valuation methods that rely on corporate financial indicators are difficult to evaluate them effectively. This paper selects the online literature enterprise IReader Technology Co., Ltd. as the case enterprise, takes the data assets of IReader Technology as the research object, comprehensively considers the future environmental uncertainty and the characteristics of the case enterprise "user value creation" as the core, and takes uncertainty theory, customer value theory, Zipf's law and scenario analysis theory as the theoretical basis. This paper constructs a valuation model based on real option B-S model, and creatively uses scenario analysis and DEVA model to improve the real option B-S model. Specifically, this paper first analyzes the basic situation of the case enterprise, and then analyzes the composition of its data assets on this basis. Then, through industry comparative analysis, the driving factors that may affect the future development of the enterprise are determined, the scenario framework is built and the scenario probability is determined. Based on this, the predicted value of the value created by the unit user of the enterprise in the case is calculated, and the current value of the option S0 is calculated using the DEVA model. Finally, the parameters are put into the real option B-S model to calculate the asset valuation results of the technology data, and the valuation results are analyzed and explained. Through the research, this paper draws the following conclusions: First, through the analysis of business model and data asset composition of online literature industry, it summarizes the characteristics of online literature enterprises and their data assets, which mainly include non-entity, processability, value uncertainty, replicability and high risk, call option and selectivity. Secondly, by analyzing the enterprise characteristics, business model and data asset characteristics of online literature industry, based on the B-S model of real option method, a data asset valuation model of online literature enterprise with strong data availability and relatively simplified calculation process is constructed. Through the model calculation, it can be seen that the valuation results of data assets of the case enterprise account for a high proportion in its overall market value, indicating that data assets play a greater role in online literature enterprises. Further, network literature enterprises should attach importance to the underlying supporting role of data assets in enterprise assets and give full play to the profitability of data assets. At the same time, the valuation model constructed in this paper has strong applicability to the data asset valuation of network literature enterprises, and can also provide certain data support and management ideas for the subsequent data asset management of network literature enterprises. |
Subtype | 硕士 |
Date Issued | 2024-06 |
Place of Conferral | 甘肃省兰州市 |
Language | 中文 |
Totalpage | 60 |
References | 75 |
collectionNumber | 0005917 |
Security level | 公开 |
Classification number of the middle picture | F273.4/34 |
Document Type | 学位论文 |
Identifier | http://ir.lzufe.edu.cn/handle/39EH0E1M/36350 |
Collection | 会计学院 |
Recommended Citation GB/T 7714 | 姬文岳. 网络文学企业数据资产估值研究——以掌阅科技为例[D]. 甘肃省兰州市. 兰州财经大学,2024. |
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2021000008005.pdf(2297KB) | 学位论文 | 暂不开放 | CC BY-NC-SA | Application Full Text |
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