Annals of the University of Oradea: Economic Science (Jul 2020)
TO WHAT EXTENT DOES THE INFORMATION DISCLOSURE OF SPORTS AND ICT COMPANIES COMPLY WITH THE LEGAL REQUIREMENTS?
Abstract
Organizational decision-making, whether operational or strategic, involves risk because decisions are made in an environment characterised by uncertainty. Sufficient amount and high-quality data and information need to be provided for the preparation and decision-making in order to reduce risk. Accounting is a system for processing such economic and financial operations and value data that provides data and information to enterprises. This system is regulated in Hungary by Act C of 2000 on Accounting. Accounting information on the one hand serves the internal actors of the company as a basis for managerial decision-making, while on the other hand it also serves external actors, as it is important to present a reliable and realistic picture towards investors, credit institutions, partners and the state. Annual statements are required to be published and disclosed by every business entity, which means that they can be obtained quickly and free of charge by any external party, Therefore, the quantity and quality of the data included by the statement is important. The structure of the two parts of the statement, the balance sheet and the profit and loss account, is clearly stipulated by the Accounting Act. However, organizations are given slightly more space in terms of the structure of the third part, the notes to the annual statement. The notes to the annual statement is regulated by the Accounting Act in terms of its content, but the content of the published statements is not audited. For this reason, the present study examines the research question involving the extent to which the informative disclosures within the notes to the annual statement comply with the mandatory requirements of the Accounting Act. To answer this, the informative parts of the notes to the annual statements of companies from two different economic sectors are examined by means of text mining.
