Buhalterinės apskaitos teorija ir praktika
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The Implementation of Accrual Accounting in Lithuania’s Public Sector: Retrospective Assessment of the Challenges
Get PDFThe article analyses the reform of the Lithuanian public sector accounting system, with an emphasis on the transition from cash-based to accrual-based accounting based on International Public Sector Accounting Standards (IPSAS). The study examines the stages of the reform and the challenges encountered, including the lack of qualified personnel, complex legal systems and insufficient technological infrastructure. Based on a literature review and qualitative expert interviews, the study finds that external pressures - EU policy, IPSAS recommendations, and internal motivation - led to the initiation of the reform. Although the long-term benefits of the reform are evident, the study highlights persistent systemic challenges, including gaps in legal alignment with the accrual basis, uneven technological readiness, and varying levels of accounting professionals’ competence. Therefore, to ensure the sustainability and effectiveness of accrual-based public sector accounting in Lithuania, it is essential to further develop the legal and institutional framework, continuously enhance professional development, and strengthen inter-institutional cooperation. The article contributes to the international discourse on public sector accounting harmonisation by providing a detailed, context-specific case study of the Lithuanian experience
Tvarumo subalansuotų rodiklių sistemos kūrimas: atvejo analizė
Get PDFThis article explores the issue of sustainability management, focusing on the application of the Balanced Scorecard (BSC) for evaluating company sustainability. The aim of the study is to reveal the development process of such a system in an agricultural production company by analyzing the key aspects of creating a Sustainability Balanced Scorecard (SBSC). The relevance of the research stems from the growing need for companies in the agricultural sector to integrate sustainability principles into their performance assessment and to develop management systems that reflect not only economic but also social and environmental performance. The study is based on a descriptive case study strategy, drawing on the practical example of a single company and aiming to describe how the SBSC is implemented in practice. The findings indicate that the introduction of the SBSC enables better alignment of strategic goals with sustainability principles and fosters more socially responsible behavior. The results of the article may be useful for other companies in the agricultural production sector seeking to implement sustainability strategies and assess their effectiveness through an integrated and well-structured indicator system.Straipsnyje nagrinėjama tvarumo valdymo problematika, orientuojantis į subalansuotų rodiklių sistemos (BSC) pritaikymą įmonių tvarumui vertinti. Tyrimo tikslas – išanalizavus pagrindinius tvarumo subalansuotų rodiklių sistemos kūrimo aspektus, atskleisti tokios sistemos kūrimo eigą agrikultūrinių produktų gamybos įmonėje. Tyrimo aktualumą lemia augantis poreikis žemės ūkio sektoriaus įmonėms integruoti tvarumo principus į savo veiklos vertinimą bei kurti valdymo sistemas, kurios atspindėtų tiek ekonominius, tiek socialinius ir aplinkosauginius veiklos rezultatus. Tyrimas grindžiamas aprašomosios atvejo analizės strategija: buvo remiamasi vienos įmonės praktiniu pavyzdžiu ir siekiama aprašyti, kaip joje diegiama tvarumo subalansuota rodiklių sistema. Tyrimo išvados atskleidžia, kad įdiegus tvarumo subalansuotų rodiklių sistemą, strateginiai tikslai geriau suderinami su tvarumo principais, labiau skatinama socialiai atsakinga veikla. Straipsnio rezultatai gali būti naudingi kitoms agrikultūrinius produktus gaminančioms įmonėms, siekiančioms įgyvendinti tvarumo strategijas ir vertinti jų efektyvumą integruotai, pasitelkiant aiškią rodiklių sistemą
The Hidden Link between Motivations Driving Earnings Management and Capital Structure Decisions: A Bibliometric Perspective
Get PDFIn this paper, earnings management and capital structure decisions are analysed from a new perspective. Bibliometric analysis of the link between capital structure and earnings management is performed, providing new insights on historical evolution of research in the field. The links between keywords in the research area are analysed and grouped in clusters. Valuable insights on the level of research carried out in the field are presented. Current studies are expanded by adding theoretical background analysis: capital structure decisions and the motives of earnings management are compared in the context of various theories. In this paper, common incentives behind capital structure decisions and earnings management are revealed. Systematic comparison between capital structure decisions and motives of earnings management together with results of bibliometric analysis provide new insights on the topic and can assist in future research
Investigating the Impact of Leadership Styles on Finance and Accounting Specialists’ Performance
Get PDFThis study examined the impact of leadership styles (transformational, transactional, and democratic) on finance and accounting specialists’ productivity and commitment in selected deposit money banks in Akure, Ondo State, Nigeria. The study employed a cross-sectional survey approach. Data was collected from 179 employees through structured questionnaires. The findings revealed that transactional and transformational leadership styles significantly enhance employee productivity; democratic leadership did not show a significant impact on productivity. In terms of employee commitment, transactional and transformational leadership were again found to be significant predictors, while democratic leadership showed no significant effect. The study concludes that transactional and transformational leadership styles are essential for enhancing employee productivity and commitment in the banking sector. It recommends that deposit money banks focus on developing these leadership capabilities through targeted training programs. This study contributes to the existing literature by providing empirical evidence on the effectiveness of different leadership styles on finance and accounting specialists’ performance. This offers insights for both scholars and practitioners in the field of organizational leadership
Comparative Analysis of Deep Learning Models for Cryptocurrency Price Predictions: Evidence Based on Bitcoin (BTC), Ethereum (ETH), Ripple (XRP) and Solana (SOL)
Get PDFThis research examines deep-learning and machine-learning models for cryptocurrency price prediction, with a keen focus on Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Solana (SOL). Cryptocurrencies exhibit high volatility, non-linear behavior and are able to react strongly to exogenous events, making their prediction and forecasting challenging. The primary aim of this research is to determine which predictive models yield optimal performance in characterizing these complexities and to provide empirical guidance on real-life investment and risk-management applications. Four approaches were used for this forecasting: Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), a combination of LSTM-GRU models, and Stochastic Gradient Descent (SGD) regression. The daily historical data were used to train and test each model on different forecast horizons, and performance was measured accordingly by Mean Squared Error (MSE) and Mean Absolute Error (MAE) values. As shown in the results, it can be observed that GRU exhibited the lowest error rates in the majority of the assets, particularly in short-term predictions. LSTM demonstrated a promising ability to capture long dependencies, whereas the hybrid LSTM-GRU system showed a similar performance proficiency by combining the relative superiorities of the two respective models. On the other hand, the conventional SGD regression was the worst among all the deep-learning algorithms, thereby demonstrating the extreme capability of these algorithms in modelling non-linear time sequences. The results confirm GRU as the most viable model for AI-powered crypto prediction and demonstrate the potential of hybrid architecture, at least in certain situations. This study will contribute to the existing debates about the role of deep learning in predicting financial outcomes and provide valuable insights to traders, analysts, and researchers navigating the uncertainties of the digital asset world
Darbo užmokesčio ir jam įtaką darančių išorinių veiksnių vertinimas Baltijos šalyse
Get PDFWages remain one of the most relevant factors from both microeconomic and macroeconomic perspectives. The aim of this study is to assess the impact of external factors on the average wage in the Baltic countries, as well as across different sectors of economic activity. The study covers the period from 2011 to 2023, incorporating significant macroeconomic shifts such as the COVID-19 pandemic and the war in Ukraine. The novelty of the research lies in its cross-country (Lithuania, Latvia, Estonia) and sectoral analysis. The research includes an expert survey, dynamic analysis of selected indicators, and applies correlation and regression analysis methods. These methods enable the evaluation of how external factors—such as GDP, minimum monthly wage (MMW), unemployment, foreign direct investment (FDI), inflation, the number of employed individuals with higher education, and tax policy—affect average wages in individual Baltic countries, the Baltic region as a whole, and various sectors of economic activity (classified according to NACE). The results indicate that average wages in Lithuania are influenced by inflation, MMW, and employment; in Latvia—by FDI and employment; and in Estonia—by GDP and inflation. For the Baltic region as a group, the average wage is primarily affected by MMW and GDP. Sectoral analysis reveals that these factors have varying impacts across countries and sectors.Darbo užmokestis išlieka vienas aktualiausių veiksnių tiek mikroekonominiu, tiek makroekonominiu aspektu. Tyrimo tikslas – įvertinti išorinių veiksnių įtaką vidutiniam darbo užmokesčiui Baltijos šalyse bei atskiruose ekonominės veiklos sektoriuose. Tyrime analizuojamas 2011–2023 m. laikotarpis, įtraukiant reikšmingus makroekonominius pokyčius, tokius kaip COVID-19 pandemija ir karas Ukrainoje. Tyrimo naujumas grindžiamas tarpvalstybine (Lietuva, Latvija, Estija) ir sektorine analize. Tyrime atliekama ekspertų apklausa, dinaminė atrinktų rodiklių analizė, skaičiavimams atlikti naudojami koreliacinės bei regresinės analizės metodai, kurie leidžia atskleisti tokių išorinių veiksnių kaip antai BVP, MMA, nedarbo, TUI, infliacijos, užimtų darbuotojų su aukštuoju išsilavinimu skaičiaus bei mokesčių politikos įtaką vidutiniam darbo užmokesčiui atskirose Baltijos šalyse, Baltijos šalių grupei bei skirtinguose ekonominės veiklos rūšies sektoriuose (pagal EVRK). Tyrimo rezultatai rodo, kad Lietuvos vidutinis darbo užmokestis veikiamas infliacijos, MMA, užimtumo, Latvijos – TUI, užimtumo, o Estijos – BVP ir infliacijos veiksnių. Tuo tarpu Baltijos šalių grupės vidutinis darbo užmokestis yra veikiamas tokių veiksnių, kaip antai MMA ir BVP. Sektorinės analizės rezultatai atkleidė, jog minėti veiksniai skirtingai veikia darbo užmokestį skirtingose šalyse
Bankroto prognozavimas Lietuvos maitinimo paslaugų sektoriuje: tradicinių, mašininio mokymosi ir hibridinių modelių taikymas bei makroekonominių veiksnių įtaka
Get PDFThis study examines bankruptcy prediction models specifically for Lithuania\u27s food service sector, which is known for its high economic sensitivity and significant bankruptcy risk. The primary issue addressed is the limited accuracy of traditional bankruptcy prediction models when applied to this industry—an important concern for business management and investors. The aim of the study is to evaluate the effectiveness of different types of bankruptcy prediction models for companies in Lithuania’s food service sector and to develop a hybrid model based on advanced technologies, tailored to the specific characteristics of the sector. The models investigated include the Altman Z-score, Ohlson O-score, Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), with macroeconomic indicators incorporated into the advanced models. The empirical analysis was conducted using a dataset comprising 96 Lithuanian food service companies. Model performance was assessed through metrics such as AUC (ROC), F1 score, Brier score, and other key indicators. The findings reveal that the developed hybrid model with integrated macroeconomic factors achieved the highest prediction accuracy at 93.06%, along with the best overall balance of sensitivity, precision, and calibration, highlighting its potential as an effective tool for practical bankruptcy risk assessment in this sector.Straipsnyje analizuojamas bankroto prognozavimo modelių taikymas Lietuvos maitinimo paslaugų sektoriui, kuriam būdingas didelis ekonominis jautrumas ir aukšta bankroto rizika. Sprendžiama problema – tradicinių bankroto prognozavimo modelių nepakankamas tikslumas šio sektoriaus įmonių bankroto prognozavimui riboja jų efektyvų taikymą priimant verslo valdymo ir investicinius sprendimus. Tyrimo tikslas – įvertinti skirtingų bankroto prognozavimo modelių tipų tinkamumą Lietuvos maitinimo paslaugų sektoriaus įmonėms ir sukurti pažangiomis technologijomis pagrįstą hibridinį bankroto prognozavimo modelį, pritaikytą sektoriaus specifikai. Tyrimui taikyti Altman Z, Ohlson O, atraminių vektorių klasifikatoriaus (SVM) ir gradiento didinimo mašinų (GBM) modeliai, į pažangiuosius modelius integruojant ir makroekonominius rodiklius. Duomenų analizė atlikta su 96 Lietuvos maitinimo paslaugų įmonėmis, modelių veikimas vertintas naudojant AUC (ROC), F1, Brier ir kitus rodiklius. Tyrimo rezultatai parodė, kad sukurtas hibridinis modelis su makroekonominių veiksnių integracija pasiekė aukščiausią tikslumą (93,06 %) ir geriausią pusiausvyrą tarp jautrumo, preciziškumo bei kalibracijos, todėl gali būti laikomas efektyviu įrankiu praktiniam bankroto rizikos vertinimui maitinimo paslaugų sektoriuje
Evaluation of Corporate Sustainability Disclosure Practices in Listed Companies of the Baltic States
Get PDFThe relevance and novelty of this study lie in the growing importance of corporate sustainability disclosure as a mechanism for enhancing transparency, accountability, and stakeholder trust. Despite the increasing regulatory emphasis across the European Union, a critical research gap remains: the sustainability reporting practices of listed companies in smaller-market economies, such as the Baltic States, have been underexplored. This study addresses the scientific question of how well listed companies in the Baltic region are adapting to the evolving EU sustainability regulatory environment, particularly in terms of the scope of sustainability disclosures. The methodology includes a systematic literature review and a document analysis of disclosures for the period 2021–2024. Using sustainability disclosure and assessment models based on GRI topic standards and ESRS standards, the study examines the sustainability level disclosure through the ESG approach and by sectors. The study reveals that publicly listed companies in the Baltic States show limited and uneven sustainability disclosure, with economic and social indicators particularly underreported, and environmental data often strategically selected rather than substantively addressed. Sectoral analysis highlights broader engagement in construction, food, and manufacturing sectors, while financial, retail, and real estate sectors lag behind in transparency, especially on social and environmental issues. ESRS-based disclosures show a focus on climate change and business conduct, but significant gaps persist in areas such as pollution, biodiversity, and value chain impacts, indicating selective implementation and limited regulatory readiness
Unifying CSR and Responsibility Accounting: Towards an Integrated Accountability Framework
Get PDFTraditional responsibility accounting and accountability frameworks often lack integration of corporate social responsibility, despite corporate social responsibility being considered a paramount of modern business practice. Business managers increasingly face challenges when balancing various often competing stakeholder interests in complex and dynamic environments, which complicates high-quality decision-making. This study reviews and synthesizes academic literature on responsibility accounting and CSR to identify the strengths and limitations of conventional accountability systems and to explore the underlying motivations behind socially responsible management. The aim of this study is to propose an integrated accountability framework which includes not only financial goal setting and tracking, but also socially responsible management evaluation and decisions. Societal expectations from businesses have significantly increased, but corporate social responsibility is often perceived as a company’s promotional asset or image-enhancement strategy aimed at boosting profitability, which fundamentally contradicts the principles of socially responsible business. Corporate social responsibility should not be evaluated in isolation from overall business performance. To ensure that CSR serves as a genuine driver of sustainable economic development rather than a symbolic gesture, it must be embedded within the broader performance management system. The proposed framework emphasizes the need to integrate CSR throughout all key management processes, including organizational structure analysis, responsibility center goal-setting, performance evaluation, and accountability control
The Relationship of Audit Quality and Leverage on Tax Avoidance
Get PDFThis study explores the relationship between audit quality, financial leverage, and tax avoidance strategies in publicly traded non-financial firms in Indonesia from 2018 to 2022. Given that taxation is a key source of state revenue, variations in tax regulations and corporate incentives contribute to diverse tax avoidance practices. The research examines three dimensions of audit quality—audit tenure, audit specialization, and audit firm type—and their respective impacts on tax avoidance. Employing a quantitative approach with secondary financial data from 843 IDX-listed firms, the study applies the Feasible Generalized Least Squares (FGLS) method to mitigate heteroscedasticity and autocorrelation in panel data, enhancing the robustness of findings. Results reveal that audit specialization significantly reduces tax avoidance, suggesting that industry expertise among auditors strengthens compliance. However, audit tenure, audit firm type, and leverage exhibit no significant influence. These insights emphasize the need for greater awareness among auditors and policymakers regarding tax avoidance determinants within Indonesia\u27s regulatory landscape. Future research should further explore external factors, such as the COVID-19 pandemic, and additional variables to provide a more comprehensive understanding of corporate tax behavior