Tinkamiausio bankroto prognozavimo modelio parinkimas statybų sektoriaus įmonėms /

Summary The aim of the work is to select the most suitable bankruptcy forecasting model for companies belonging to the construction sector, based on the example of UAB ,,Gilesta“ and UAB ,,Statybos ir restauravimo darbai“. The work consists of three parts: analysis of scientific literature, research methodology, summarization of research results. The first part begins with an introduction to the development and concept of bankruptcy. After analyzing the ideas of the authors presented in the scientific literature, the conclusion is finished that bankruptcy is the state of an insolvent company that has been filed for bankruptcy. During the analysis of scientific literature, an analysis of the causes and process of bankruptcy is also caried out, in which the most frequent and relevant external and internal causes are revealed and purified. The first part concludes with the presentation of bankruptcy prediction models. Taking this into account, the most popular models are selected, their grouping (classical statistical, artificial intelligence) is indicated, and each of them is presented in detail. The second part dedicated to the presentation of the research methodology. In this part, the problem of the research, the goal and the tasks to achieve it are presented. Since a successful research largely depends on careful preparation for it, a research methodology plan has been drawn up, on the basis of which the work research is carried out. The third part is dedicated to conducting the research and presenting the results. During the research, the probability of bankruptcy was estimated for UAB ,,Gilesta“ and UAB ,,Statybos ir restauravimo darbai“ companies, based on 8 bankruptcy forecasting models. After a thorough examination of the received answers and applying the Chi square criterion, the conclusion is reached that the Altman and Springate models are the most suitable for predicting bankruptcy for the companies belonging to the construction sector. The conclusions summarize the analysis of the scientific literature, the results ofthe research, and provide recommendations.

Grantor dc:publisher

Institutional Repository of Vilnius University

Year dc:date

2024

Author dc:creator

• Kutko, Violeta,

Statement dc:rights

• info:eu-repo/semantics/openAccess

Language dc:language

lit

Repository record dc:identifier

https://repository.vu.lt/VU:ELABAETD210581264&prefLang=en_US

OAI identifier oai:identifier

oai:vu.lt:elaba:210581264