Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos / Science and Studies of Accounting and Finance: Problems and Perspectives 2021, vol. 15, no. 1

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  • Publication
    Biologinio turto ir žemės ūkio produktų savikainos kalkuliavimo sisteminis tyrimas
    [A systematic study of biological assets and agricultural products costing]
    research article; ;
    Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos / Science and Studies of Accounting and Finance: Problems and Perspectives, 2021, vol. 15, no. 1, p. 1-14
    In the context of modern agribusiness, it is important to form suitable management accounting policy for agricultural business entities and properly collect information on costs in order to use it for cost calculation of biological assets and agricultural products, prepare financial and tax reports, and analyse and make innovative management decisions. Therefore, the aim of this study is to propose a model for the formation of costing methodology for biological assets and agricultural products and determine the impact of formed cost calculation scenarios to the financial performance of the entity. Based on the results of the scientific literature analysis and the questionnaire survey of the persons managing the accounting of agricultural business entities, a matrix of scenarios for calculating the cost of agricultural production was created. After applying it to the case study and combining different indirect cost allocation alternatives with different methods of costs allocating to costing objects, the influence of the formed alternatives on the indicators of the main agricultural production cost and financial result of the agricultural entities was determined. A comparison of the alternatives for calculating the cost of agricultural production revealed significant fluctuations in indirect manufacturing costs and manufacturing production cost, which had a significant impact to changes in financial results. It was found, that the choice of the allocation base for indirect manufacturing costs has a more significant effect. Therefore, in order to prepare financial statements that give a true and fair view of the company’s operations, it is important to select differentiated bases for allocating indirect manufacturing costs as accurately as possible that would reflect the fairest possible relationship between accounting objects of manufacturing costs and certain indirect manufacturing cost items, as well as to[...]
      189  174
  • journal article
    Šiaulytė, Rosita
    ;
    Lakštutienė, Aušrinė
    Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos / Science and Studies of Accounting and Finance: Problems and Perspectives, 2021, vol. 15, no. 1, p. 15-22
    Rapidly evolving financial technologies (FinTech) are changing established, time-tested financial services delivery and competition strategies. The growing diversity of financial services is evolving entrepreneurial ecosystems, making it a challenge for all financial market participants. One of the largest Fintech markets in Lithuania is the lending market. This market acts as an alternative to traditional financial institutions’ credit and distinguish by its relatively new and developing. Therefore, the research aims to evaluate the activities and peculiarities of operating lending platforms in Lithuania. The analysis uses P2P lending market development indicators, return and risk identified and analyzed in the research. The study revealed that the portfolio of consumer loans provided through operators of P2P lending platforms is growing steadily every year. AB NEO Finance maintains the same tendencies and secures a leading position in the Lithuanian P2P lending market. AB NEO Finance stands out as the only one of all P2P lending platforms, because it is listed on Lithuania’s stock exchange. It covers more than half of the P2P lending market regarding the amount and number of disbursed consumer loans. Were found that the remaining loan repayment is proliferating in the P2P lending market. However, AB NEO Finance is experiencing a lower number of overdue payment days than the P2P lending market, which indicates a lower risk.
      107  114
  • Publication
    Nuosavybės struktūros poveikis Lietuvos listinguojamų įmonių kapitalo struktūrai
    [Effect of ownership structure on capital structure of Lithuanian listed companies]
    journal article
    Vaičekauskaitė, Rimantė
    ;
    Norvaišienė, Rasa
    Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos / Science and Studies of Accounting and Finance: Problems and Perspectives, 2021, vol. 15, no. 1, p. 23-33
    Verslo įmonėse priimamus finansavimo sprendimus nemaža dalimi lemia tai, kokio požiūrio laikosi jos savininkai, kokią įmonės ateities viziją jie mato, o tai, savo ruožtu, priklauso nuo to, kokie savininkai valdo įmonę. Šio tyrimo tikslas –palyginti kapitalo struktūrą ir jos kitimo tendencijas skirtingos nuosavybės struktūros įmonių grupėse, ištirti nuosavybės struktūros poveikį Lietuvos listinguojamų įmonių kapitalo struktūrai.Šiam tyrimui atlikti yra pasirinktas dešimties metų laikotarpis nuo 2009 iki 2018 metų. Į tyrimą įtrauktos nefinansinės įmonės, listinguojamos Nasdaq Vilnius vertybinių popierių biržoje. Nuosavybės struktūra vertinta pagal nuosavybės koncentraciją ir pagalsavininko identitetą. Pirmoje tyrimo dalyje atlikta skirtingos nuosavybės struktūros įmonių kapitalo struktūros palyginamoji analizė. Antrame tyrimo etape, siekiant nustatyti listinguojamų įmonių nuosavybės struktūros poveikį kapitalo struktūrai, atlikta regresinė analizė. Atliktas tyrimas parodė nemenkus kapitalo struktūros skirtumus Lietuvos listinguojamų įmonių skirtingos nuosavybės koncentracijos įmonių grupėse ir skirtingas kapitalo struktūros kitimo tendencijas atskirose įmonių grupėse: vidutinės nuosavybės koncentracijos įmonės stengiasi naudoti vis mažiau finansinių skolų, o taip pat mažinti skolinto kapitalo dalį kapitalo struktūroje, o mažos ir didelėsnuosavybės koncentracijos įmonės linkusios vis daugiau skolintis. Apibendrinus palyginamosios analizės rezultatus padaryta prielaida, kad Lietuvos listinguojamų įmonių įsiskolinimo lygio priklausomybė nuo nuosavybės koncentracijos yra U (parabolės) formos, t. y.,kai įmonių nuosavybės koncentracija yra maža (mažesnė nei 25%) arba didelė (didesnė nei50%), įmonės linkusios naudoti daugiau skolintų lėšų, o esant vidutinei nuosavybės koncentracijai (kai pirmas didžiausias akcininkas valdo nuo 25% iki 50% akcijų), stengiamasi mažinti įsiskolinimo lygį, o taip pat finansinių skolų lygį. Atliktos regresinės analizės rezultatai šią prielaidą paneigė ir leido padaryti išvadą, kad tarp nuosavybės koncentracijos ir įmonių įsiskolinimo yra statistiškai reikšmingas neigiamas tiesinis ryšys, t.y. didėjanti Lietuvos listinguojamų įmonių nuosavybės koncentracija turi statistiškai reikšmingą neigiamą poveikį tiek bendrai skolinto kapitalo daliai kapitalo struktūroje, tiek finansinių skolų daliai kapitalo struktūroje. Nepaisant to,statistiškai reikšmingos savininko identiteto įtakosLietuvos listinguojamų įmonių įsiskolinimo lygiui, o taip pat finansinio įsiskolinimo lygiui regresinės analizės rezultatai neparodė.
      133  132
  • Publication
    Pelno valdymas nasdaq Vilnius vertybinių popierių biržoje kotiruojamose įmonėse
    [Earnings management in nasdaq Vilnius stock exchange companies]
    research article
    Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos / Science and Studies of Accounting and Finance: Problems and Perspectives, 2021, vol. 15, no. 1, p. 34-43
    Financial information is one of the most important sources of information used for decision making of internal and external interested parties. Therefore, the quality of financial information determines the quality of decisions based on this information. Managers experience the pressure of various interested parties. On one hand, interested parties expect receiving qualitatively prepared financial reports disclosing precise and true information. On the other hand, managers feel pressure to reach the set targets. Striving to combine expectations of all interested parties may encourage managers using various earning management patterns. The aim of this research is to detect whether Nasdaq Vilnius stock exchange companies are using earnings management and which pattern of earnings management – accrual based or real earnings management – they use. Discretionary accruals estimation model is used for detecting usage of accrual based earnings management. The abnormal cash flow, abnormal production costs and abnormal discretionary expenses valuation model is used for detecting real earnings management. The research in this paper is implemented by using comparative analysis, generalization, content analysis, monography and statistical methods. Prior implemented empirical researches’ analysis shows that managers apply earnings management in order to show better results. Accrual based earnings management is implemented through accounting policy. Real earnings management is implemented through operations that differ from typical structure and timing of the company. The results of this research show that Nasdaq Vilnius stock exchange companies use earnings management by applying both patterns of earnings management - accrual based or real earnings management. The companies did not give priority to any of the pattern of earnings management. The results of this research imply the expediency of evaluation of both pattern[...]
      133  152
  • journal article
    Stankevičienė, Jurgita
    ;
    Prazdeckaitė, Gabija
    Apskaitos ir finansų mokslas ir studijos: problemos ir perspektyvos / Science and Studies of Accounting and Finance: Problems and Perspectives, 2021, vol. 15, no. 1, p. 44-53
    The aim of this research is to analyze the accuracy of selected bankruptcy prediction models on the example of Lithuanian companies. The research involves financial statements of 23 companies that have gone bankrupt over the period of 2013-2019. We used three different groups of models. The first two are considered as classic models which were developed using discriminant analysis (Altman, modified Altman, Springate, Taffler and Tishaw, and Grover models) and logistic regression (Ohlson, Zmijewski, and Grigaravičius models). The third group is based on artificial intelligence (we used a decision tree model, which is the most innovative and the least explored model of all used).The analysis evidenced that the logistic regression models, such as Zmijewski and Ohlson, demonstrated the best results in the group of classic prediction models, i.e., high probability of bankruptcy even earlier than one year prior to actual bankruptcy in the case of most companies. However, the decision tree must be considered as the most accurate model as it predicted bankruptcy of all analyzed companies one year before actual bankruptcy; this could be interpreted as 100% accuracy. Too late bankruptcy process causes many negative consequences for company’s employees, partners, and the state. Though problems with financial resources such as growing accounts payable and the shortfall of working capital which contribute to insolvency can be seen in the financial statements, in addition to the analysis of financial indicators, it is particularly important to use the above-mentioned bankruptcy prediction models, which help to detect financial problems in time and make the right decisions concerning future activities.
      97  141