上市公司数据资产入表分析——以A股上市公司年报为例
网络安全与数据治理
彭琳
上海国家会计学院
摘要: 以2024年A股上市公司年报为研究样本,首先从三个维度构建现状分析框架:一是入表规模分析,揭示入表公司的数量特征与金额总量;二是会计处理与表外披露分析,深入剖析数据资产从初始确认到后续计量再到披露的全流程;三是行业分布特征分析,识别哪些行业率先响应并已成为实践主力,哪些行业进度较慢。在此基础上,进一步深入探究企业入表行为差异背后的原因,为理解数据资产入表实践提供全面的分析框架,以辩证地看待数据资产入表这一新生事物在初级阶段的复杂性。
中图分类号:F275;F230文献标识码:ADOI:10.19358/j.issn.2097-1788.2025.10.002
引用格式:彭琳. 上市公司数据资产入表分析——以A股上市公司年报为例[J].网络安全与数据治理,2025,44(10):10-15,29.
引用格式:彭琳. 上市公司数据资产入表分析——以A股上市公司年报为例[J].网络安全与数据治理,2025,44(10):10-15,29.
Analysis of data asset recognition in financial statements of listed companies:evidence from annual reports of A-share companies
Peng Lin
Shanghai National Accounting Institute
Abstract: This study utilizes the 2024 annual reports of Ashare listed companies as its sample and constructs a threedimensional framework for analyzing the current situation. First, it examines the scale of recognition, revealing the quantitative characteristics and total monetary value of companies that have incorporated data assets into their financial statements. Second, it delves into accounting treatment and off-balance-sheet disclosure, providing an in-depth analysis of the entire process of data assets from initial recognition to subsequent measurement and disclosure. Third, it investigates the industry distribution characteristics, identifying which industries have taken the lead in adoption and become mainstream practitioners, and which ones have progressed more slowly. Based on this framework, the study further explores the reasons behind the differences in corporate behavior regarding data asset recognition, offering a comprehensive analytical perspective for understanding the practice. This approach allows for a dialectical view of the complexities inherent in this nascent phenomenon during its initial stages of development.
Key words : data assets; current status of recognition in financial statements; data resources
引言
随着数字经济成为核心经济形态,数据要素的资产化与资本化成为关键议题。2023年8月,财政部印发《企业数据资源相关会计处理暂行规定》(以下简称《暂行规定》),正式推动数据资源作为资产入表,标志着数据要素市场化迈入制度化阶段。2024年上市公司年报作为《暂行规定》实施后的首份披露文件,为观察数据资产入表的初始实践提供了重要窗口。
基于此,本文对A股上市公司数据资产入表的现状进行系统分析,现状分析表明:其一,在入表规模上,实践公司数量与入表总金额均处于初步探索阶段。其二,在会计处理与表外披露上,数据资产主要确认为“无形资产”与“开发支出”,摊销方法以直线法为主,年限集中在3~5年。仅有11家公司披露数据资源重要性标准,关键审计事项涉及数据资产的仅1家,披露具体成本构成有4家。其三,在行业分布上,数据资产入表企业密集分布于计算机、通信和生物医药等行业。在此基础上,本文将进一步探究企业入表行为差异背后的核心原因。
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作者信息:
彭琳
(上海国家会计学院,上海201702)

