An analytical support methodology for transformational processes
| dc.contributor.author | Havrylenko, Nataliia | |
| dc.date.accessioned | 2023-03-03T08:31:22Z | |
| dc.date.available | 2023-03-03T08:31:22Z | |
| dc.description | Havrylenko, N. An analytical support methodology for transformational processes // Digital technologies in the contemporary economy : collective monograph / N. Havrylenko. – Kaunas : Public Security Academy of Mykolas Romeris University, 2023. – P. 187–197. | uk_UA |
| dc.description.abstract1 | This article is devoted to the problems of the analytical support for digitalization of the modern economy and their impact on economic growth and social welfare. It is shown that businesses in the field of computer and information technologies, as well as the sharing businesses, are developing rapidly based on the widespread use of Internet services and cloud technologies. It is noted that for businesses that rely on Internet services, the analytical support system is simplified, which is reduced to managing the creation, processing and redistribution of information, rather than creating new products and industries, which also inhibits economic growth. The results of the study of the compliance of the methodology of analytical support of digital transformation processes with the modern conditions of the digital economy allow the author to state that the development of the methodology of the accounting and analytical process involves: first, the study of cause-and-effect relationships in the economy and the management and institutional sphere of regulation of this process; second, the establishment of an organic link between the state of the economic and institutional environment with the content of the accounting and analytical process; and third, the formation and establishment of such a link allows economic entities to develop in accordance with corporate interests, which are defined in the economic strategy. However, it has been proven that the practice of accounting and financial reporting has accumulated negative properties that make it difficult to update the concept of information support for setting and implementing management goals, the need for which is long overdue. We believe that in order to improve the effectiveness of control measures, the accounting and analytical array should be supplemented with information from big data databases, which are formed from management, tax, and statistical reports, information summary reports of financial regulators, and sources of non-financial information. Suggestions for improving the methodology of analytical support for digital transformation processes and specific practical recommendations will contribute to the acceleration of digital transformation accounting and analytical processes, and this will allow timely identification of risks of loss of stability and efficiency of economic entities, helping them to take into account measures to eliminate or mitigate negative consequences in formulating development strategies. Proper methodological support for any transformation processes of an economic entity reflects the level of its economic development, priorities, strategic guidelines, and opportunities to achieve them. In addition, it must be adequate to the industry specifics of those regulatory objects under the management of which the necessary regulations are created, otherwise these regulations will be useless. | uk_UA |
| dc.identifier.isbn | 978-609-488-049-0 (Elektroninis - PDF) | |
| dc.identifier.issn | 978-609-488-050-6 (Spausdintinis) | |
| dc.identifier.uri | https://eir.nuos.edu.ua/handle/123456789/6570 | |
| dc.language.iso | en | uk_UA |
| dc.publisher | Mykolas Romeris University.Public Security Academy | uk_UA |
| dc.subject | digitalization of the modern economy | uk_UA |
| dc.subject | transformational processes | uk_UA |
| dc.subject | analytical support | uk_UA |
| dc.subject | IT platform | uk_UA |
| dc.subject | information technologies | uk_UA |
| dc.title | An analytical support methodology for transformational processes | uk_UA |
| dc.title2 | 2023 | |
| dc.type | Book chapter | uk_UA |
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