This research explores the opportunities and challenges of implementing the Balanced Scorecard (BSC) model in public enterprises in the Federation of Bosnia and Herzegovina (FBiH), with particular attention to adapting the model to public sector characteristics. The study examines the impact of organisational, human, and economic factors on BSC implementation. Based on a quantitative analysis of 138 responses from employees in finance, accounting, and strategic management, seven hypotheses were tested regarding the determinants of BSC implementation. The findings reveal that the size of the enterprise, capabilities of accountants, costs of using the BSC, and its linkage to operational performance significantly and positively influence adoption. Larger enterprises with stronger capacities and qualified personnel are more likely to implement advanced performance management models. Conversely, organisational culture, management awareness, and perceived benefits showed no significant effect, partly due to the homogeneity of responses. These findings enhance the understanding of the prerequisites for BSC adoption in the public sector, highlighting the importance of structural capacities, human resources, and financial justification.

Abstract This paper examines the factors influencing the ethical conduct of accountants and auditors in Bosnia and Herzegovina (BiH), focusing on four key dimensions: personal interests and motives, work experience and professional competence, legal protection and market factors, and moral attitudes and the cultural environment, including religion and social norms. The research was conducted on a sample of 89 accountants and auditors using a structured questionnaire based on a five-point Likert scale. Respondents expressed their views on various aspects of ethical behaviour within the profession. Parametric statistical methods, the Z-test and Repeated Measures ANOVA, were employed to test the hypotheses. The results suggest that the cultural environment, including national customs and social norms, exerts a stronger influence on the ethical behaviour of accountants and auditors than religious beliefs. The study provides empirical evidence on the relative importance of different factors shaping ethical behaviour in the accounting and auditing profession, with particular emphasis on the role of culture as opposed to religion.

The paper examines the impact of budgetary accounting organization on the perception of corruption in the public sector, focusing on three key independent variables: the financial reporting framework, the accounting basis, and the level of independence of state auditing. The Corruption Perceptions Index (CPI), which measures the perceived level of corruption in the public sector, is used as an indicator of the dependent variable. The study includes data from 89 countries. For statistical analysis, categorical independent variables were encoded using the one-hot encoding method. Statistical tests were applied to assess the correlation between the independent variables and the CPI. The results show variations in correlation depending on the combination of financial reporting factors, the regulatory framework, and the quality of state auditing. The obtained results of multiple linear regression indicate that the model has a statistically significant impact on the CPI (p = 0.0217) and explains 21% of its variability. Keywords: public sector accounting, budgetary accounting organization, perception of corruption, public financial management reform.

This paper presents a data mining approach for Audit opinion pre¬diction in Government-owned enterprises within the Federation of Bosnia and Herzegovina using the Decision tree algorithm. A database was constructed from financial statements covering 2004-2019, incorporating indicators from balance sheets, income statements, and cash flow statements, alongside cor¬responding Audit opinions from the state audit body. The study evaluates three Decision tree algorithms (J48, RandomTree, REPTree) on data from 2020-2023, with REPTree achieving 73% classification accuracy through seven predictive rules. The findings demonstrate the potential of data mining techniques for pattern recognition in audit reports, contributing to transparency in financial reporting and supporting regulatory authorities in detecting irregularities within Government-owned enterprises.

This paper investigates the impact of different accounting bases and financial reporting frameworks on the Corruption Perceptions Index (CPI) in the public sector. Specifically, it examines how various accounting approaches (cash, modified cash, accrual, and modified accrual) and reporting frameworks (national accounting standards, International Public Sector Accounting Standards-IPSAS with or without modifications, and other frameworks) influence the perception of corruption in public institutions. The study uses a sample of 147 countries, with the CPI as the dependent variable and accounting basis and financial reporting framework as independent variables. The results of the ANOVA analysis reveal a statistically significant difference in corruption perception indices among countries employing different accounting bases. The results of this study indicate that countries applying simpler accounting frameworks, such as national standards and IPSAS modified for the local context, show a lower perception of corruption, as evidenced by a higher CPI value. In contrast, more complex frameworks, including IPSAS or national standards referencing IPSAS, combined with cash and partial accrual bases, do not significantly reduce corruption perception. Additionally, countries using national standards based on IFRS exhibit the lowest levels of perceived corruption in the public sector.

The paper aims to explore the impact of state audits of grants in the public sector on reducing non-compliance with legal regulations. The research was conducted over a ten-year period among federal and cantonal ministries in the Federation of Bosnia and Herzegovina (FBiH) responsible for planning and distributing grant funds as part of their regular duties. The research results show that the total number of recommendations given during the observed 10-year period was 1,666, including: 245 recommendations related to grant planning, 684 recommendations related to the distribution of grant funds, 554 recommendations concerning the oversight of the designated expenditure of allocated funds, 74 recommendations concerning grant implementation reporting, and 109 recommendations regarding the accuracy of accounting records. During the observed ten-year period, the number of recommendations decreased by 75%. The research results also indicate that the adoption of stricter guidelines for grant management has a strong impact on reducing the number of identified irregularities. The paper also presents an analysis of the most common causes of irregularities. The results of the conducted research will contribute to filling the literature gap on the importance of grant audits, the most common causes of identified irregularities, and the significance of stricter legal regulations and clearer rules related to grant management.

This paper aims to generalize linear models for the multiproduct break-even point. Taking into consideration identified research gaps, the paper focuses on deriving formulas for determining the multiproduct break-even point through determination models. Different assumptions regarding the constancy of individual product contribution structures to total physical production volume, total revenue, total variable costs, and total contribution margin are taken into account. Additionally, connections between the obtained solutions from different models and different assumptions regarding the constancy of individual product contributions are established. The verification of the optimality of solutions obtained through different determination models is conducted by comparing them with solutions derived from linear programming as a benchmark. The developed models are tested using a case study of a multiproduct company in the metal processing industry. Through comparative analysis, the hypotheses concerning obtaining an optimal solution and the identical nature of solutions derived from the determination model and linear programming are examined. This paper contributes to the understanding of the multiproduct break-even point, providing a theoretical and practical framework for evaluation and enabling the application of various determination models in the context of a multiproduct situation.

he study aims to assess the capability of various data mining techniques in detecting inaccurate financial statements of government-owned enterprises operating in the Federation of Bosnia and Herzegovina (FBiH). Inaccurate financial statements indicate potential financial fraud. Prediction models of four classification algorithms (J48, KNN, MLP, and BayesNet) were examined using a dataset comprising 200 audited financial statements from government-owned enterprises under the supervision of the Audit Office of the Institutions in the Federation of Bosnia and Herzegovina. The results obtained through data mining analysis reveal that a dataset encompassing seven balance sheet items provides the most comprehensive depiction of financial statement quality. These seven attributes are: opening entry of accounts receivable, profit (loss) at the end of the period, operating assets at the end of the period, accounts receivable at the end of the period, opening entry of operating assets, short term financial investments at the end of the period, and opening entry of short-term financial investments. By employing these seven attributes, the MLP algorithm was implemented to construct the most precise predictive model, achieving a 76% accurate classification rate for financial statements. Leveraging the identified attributes, a mathematical model could potentially be formulated to effectively predict financial statements of government-owned enterprises in FBiH. This, in turn, could considerably facilitate the process of selecting GOEs for inclusion in the annual work plan of state auditors. Presently, due to resource constraints, government-owned enterprises in FBiH do not undergo regular annual scrutiny by state auditors, with only 10 to 15 such enterprises being subject to audits each year. The results of this research can also be beneficial to both the public and the Financial Intelligence Agency in the FBiH. The paper contributes to filling the gap in the literature regarding the applied methodology, particularly in the part concerning the attributes used in the research.

This paper aims to investigate the status of alignment and harmonization of corporate reporting in Western Balkans (WB) countries with the European Sustainability Reporting Standards (ESRS). Specifically, the research will focus on understanding the extent to which WB countries have initiated the adoption of ESRS, particularly in the context of the Corporate Sustainability Reporting Directive (CSRD) that mandates its use for companies within the European Union (EU) and its branches. The paper will compare the achieved level of sustainability reporting in Western Balkan countries with other countries located in Europe that are not members of the European Union. Despite the mandatory nature of ESRS for companies within the EU, our preliminary analysis indicates a lack of progress in the alignment and harmonization process among the WB countries. Western Balkan countries are also lagging behind, compared to other non-EU member countries, such as Switzerland and Norway, which have been selected for comparative analysis. The research seeks to uncover the reasons behind this lag and to explore the potential challenges faced by companies in the WB region in implementing these standards. It is crucial to understand the current state of sustainability reporting practices in WB countries and the challenges faced in aligning with ESRS. It will provide valuable insights for policymakers, businesses, and stakeholders on the necessary steps to enhance sustainability reporting practices in the region and foster alignment with international standards.

Abstract The paper focuses on analyzing key factors influencing the effectiveness of internal audit in the public sector of Bosnia and Herzegovina (BiH). Through multiple regression analysis (Ordinary Least Squares-OLS), the impact of five independent variables (competence of internal auditors, size of internal audit department, relationship between internal and external auditors, management support for internal audit, and independence of internal auditors), two control variables (organization’s sector and total number of employees in the organization), on the dependent variable (effectiveness of internal audit) was measured. Research results indicate that a significant portion (.2 = 45.00%, Adj .2 = 40.90%) of the variability in the effectiveness of internal audit can be explained by the variability of the five independent variables in the model. The largest positive impact on the effectiveness of internal audit is attributed to the size of the internal audit department and the independence of internal auditors. Conversely, management support for internal audit had the least impact, which contradicts our predictions and the results of previous research. The limited impact of management support on the effectiveness of internal audit in the public sector of BiH may stem from a lack of understanding regarding the role and importance of internal audit, as well as from perceiving it as merely a formal legal requirement without substantial value.

Abstract Considering the burning problem of corruption and non-transparency of public enterprises in the Federation of Bosnia and Herzegovina (FBiH), the paper aims to investigate whether the Beneish M-score model can be used to predict inaccurate financial statements. Where, the cause of inaccurate financial statements are intentional or unintentional errors. On a sample of 200 financial statements of public enterprises and related audit reports issued by the Audit Office of the Institutions in FBiH, we made a link between the Beneish M score model with its partial indicators (DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, TATA) and four types of opinions: positive, opinion with distraction, negative and refraining from giving opinions. The research was conducted using descriptive statistics and an artificial neural network with the “scaled conjugate gradient backpropagation (trainscg)” algorithm for pattern recognition and classification. The research results show that it is possible on the basis of 8 partial indicators (DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, TATA) i.e. 24 balance sheet position for their calculation, predict the auditor’s opinion on the quality of financial statements of public companies with an accuracy ranging between 98 and 100% in repeated procedures. The results of the research have their practical usefulness and can serve to researchers, creditors, customers, suppliers and state auditors in planning resources and priorities for performing financial audits at public companies in the FBiH.