dc.rights.license | Kūrybinių bendrijų licencija / Creative Commons licence | en_US |
dc.contributor.author | Liodorova, Julija | |
dc.contributor.author | Voronova, Irina | |
dc.date.accessioned | 2024-11-19T10:11:17Z | |
dc.date.available | 2024-11-19T10:11:17Z | |
dc.date.issued | 2019 | |
dc.identifier.isbn | 9786094761614 | en_US |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/155739 | |
dc.description.abstract | To protect investment and ensure repayment of payables, recent studies have focused on identifying the relationships between company bankruptcy and internal fraud. The P-score model that is based on the most popular Altman Z-score model has been developed to indicate the manipulation of financial statements. Purpose of the study is to determinate the accuracy and the feasibility of P-score and Z-score models to detect fraudulent bankruptcy in regional conditions, based on reports of the Latvian construction companies that failed due to fraud, and during the verification of other known data. Research methodology is based on the background studies of P-score testifying, applying this approach to the Latvian condition. The present study analyzes the behaviour of the two models in identifying distress and fraud. To testify the results of the study, the authors use the financial analysis methods, comparison, statistical and quantitative research methods. Findings have shown the possibility of using the P-score and Z-score technique for bankruptcy fraud detection at the Latvian companies, based on the construction sector samples. The accuracy of the method is above 80%. Research limitations – acquisition a large amount of data on companies that are in the process of analytical studies on the recognition of their insolvency and having signs of fraud is not possible due to the confidentiality of information. Practical implications – the results of the study may be applicable to the audit of the company, investment reliability assessment, partnership evaluation and economic examination to detect fraud. Originality/Value of the study is the first test of practical implication of P-score model in Latvia and the Baltic countries on the samples of small and medium-sized construction companies. The authors propose improving the coefficients of the P-score model taking into account the requirements for financial statements in Latvia. | en_US |
dc.format.extent | 12 p. | en_US |
dc.format.medium | Tekstas / Text | en_US |
dc.language.iso | en | en_US |
dc.relation.uri | https://etalpykla.vilniustech.lt/handle/123456789/155623 | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source.uri | http://cibmee.vgtu.lt/index.php/verslas/2019/paper/view/445 | en_US |
dc.subject | bankruptcy fraud | en_US |
dc.subject | P-score | en_US |
dc.subject | Z-score | en_US |
dc.subject | Latvia | en_US |
dc.subject | construction | en_US |
dc.title | Z-score and P-score for bankruptcy fraud detection: a case of the construction sector in Latvia | en_US |
dc.type | Konferencijos publikacija / Conference paper | en_US |
dcterms.accessRights | Laisvai prieinamas / Openly available | en_US |
dcterms.accrualMethod | Rankinis pateikimas / Manual submission | en_US |
dcterms.alternative | Contemporary financial management | en_US |
dcterms.issued | 2019-05-10 | |
dcterms.license | CC BY | en_US |
dcterms.references | 28 | en_US |
dc.description.version | Taip / Yes | en_US |
dc.contributor.institution | University of Latvia | en_US |
dc.contributor.institution | Riga Technical University | en_US |
dcterms.sourcetitle | International Scientific Conference „Contemporary Issues in Business, Management and Economics Engineering ‘2019“ | en_US |
dc.identifier.eisbn | 9786094761621 | en_US |
dc.identifier.eissn | 2538-8711 | en_US |
dc.publisher.name | Vilnius Gediminas Technical University | en_US |
dc.publisher.name | Vilniaus Gedimino technikos universitetas | en_US |
dc.publisher.country | Lithuania | en_US |
dc.publisher.country | Lietuva | en_US |
dc.publisher.city | Vilnius | en_US |
dc.identifier.doi | https://doi.org/10.3846/cibmee.2019.029 | en_US |