Disclosure of the COVID-19 pandemic impact on companies' financial reporting as a condition of its transparency

IF 1.9 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Intelligenza Artificiale Pub Date : 2021-03-15 DOI:10.24891/IA.24.3.271
M. Vakhrushina, A. A. Vakhrushina
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Abstract

Subject. This article discusses the presentation of transparent IFRS reporting that details the COVID-19 pandemic impact on all areas of the company's activities. Objectives. The article aims to structure, systematize, and evaluate the quality of information on the COVID-19 pandemic impact on the performance of Russian companies presented their IFRS reporting in 2020. Methods. For the study, we used the methods of content analysis, quantitative and systematic analysis, and grouping. Results. The article consists of two parts: theoretical and empirical ones. The theoretical part substantiates the need to disclose the COVID-19 pandemic impact on companies, and it defines the areas of such disclosures. The empirical part assesses the quality of disclosure in the Interim IFRS reporting of fifty domestic public companies of twelve business types. Conclusions. All the companies studied have in one way or other disclosed data on the pandemic impact on their performance and/or financial situation in the Financial Reporting Notes, but overall the quality of such disclosures should be considered poor. However, not all of the companies sampled were affected by the pandemic. In their IFRS reporting, some of them reflected the positive impact of COVID?19 on the development of online commerce and as a result, on the increase in sales.
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披露COVID-19大流行对公司财务报告的影响,作为其透明度的条件
主题。本文讨论了透明的国际财务报告准则报告的呈现方式,该报告详细介绍了COVID-19大流行对公司活动所有领域的影响。本文旨在构建、系统化和评估有关2019冠状病毒病大流行对提交2020年国际财务报告准则报告的俄罗斯公司业绩影响的信息质量。在研究中,我们采用了内容分析、定量系统分析和分组分析的方法。本文由理论和实证两部分组成。理论部分阐述了披露新冠疫情对企业的影响的必要性,并界定了披露的领域。实证部分评估了12种业务类型的50家国内上市公司的中期国际财务报告准则报告的披露质量。所研究的所有公司都以这样或那样的方式在财务报告说明中披露了关于疫情对其业绩和/或财务状况影响的数据,但总体而言,这种披露的质量应被认为很差。然而,并非所有抽样公司都受到大流行的影响。在他们的国际财务报告准则报告中,其中一些反映了COVID - 19的积极影响。网上商务的发展以及由此带来的销售额的增长。
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来源期刊
Intelligenza Artificiale
Intelligenza Artificiale COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
3.50
自引率
6.70%
发文量
13
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