Purpose: This study aims to investigate what are the capabilities and limits of external audit in detecting frauds in companies operating in the territory of the Republics: Serbia, Croatia, Macedonia and Bosnia and Herzegovina. Design/methodology/approach: In total, 51 certified auditors from Serbia, Croatia, Macedonia and Bosnia and Herzegovina were surveyed to analyze what are the most frequent warning signals of the existence of the frauds auditors encounter during the verification of company’s financial statements. Findings: The study indicated that the auditors of the Republic of Serbia more often encountered groundless overstatement of revenues compared with other countries, while regarding manipulative representation of inventories, the largest mean value and median are still among the auditors of the Republic of Serbia. Practical implications: Based on the research results, it can be concluded that it is necessary to expand the legal obligation and power of external auditors when, in financial statement auditing, they come to clear findings that indicate fraud. Expansion of external auditors’ powers would reduce their current limitations and expand the domain of action. Originality/value: Limitations in external auditors’ work prevent the processing of frauds. However, auditors’ analysis of financial statements and pointing to potential irregularities can be a good manner for the early detection and prevention of frauds in company’s operations.

The primary aim of this paper is to determine the indicators that have an influence on the company growth in the field of agriculture, forestry, and fisheries during the six-year period (2014–2019). This sector is very important for sustainable development, bearing in mind the need to preserve natural resources, i.e., land, water, plant, and animal resources. Sustainable development of this sector is of satisfactory technical-technological development, economically sustainable, and socially acceptable. The sample consists of 1333 observations of active companies on the European market. Multiple regression analysis was used in order to thoroughly analyze the variables of growth. The obtained results showed that company size has a negative impact on growth, while return on assets and leverage have a positive impact on growth. The impact of these variables was statistically significant. Along with the influence of observed determinants based on data from financial statements, the future growth and development of companies in this sector will certainly depend on the volume of investments, pricing policy, credit and natural conditions, agricultural policy measures, and adequate institutional support through the provision of financial support and encouragement of exports of products. Institutional incentives for more intensive integration of the agriculture, forestry, and fisheries sector are aimed at achieving the concept of integrated sustainable development.

The main purpose of this paper is to research the factors that have an impact on the company profitability in the logistics industry during a five-year period (2013-2017). The sample includes 748 active companies operating in the logistics industry in the Balkan countries. Bearing in mind that logistics is an essential instrument of competitiveness and profitability of the company operations and that logistics is one of the most profitable industries, this paper used the panel data model with fixed effect in order to analyse profitability. The obtained results showed that four out of the six studied variables (company size, tangibility of assets, liquidity, and asset turnover ratio) have a statistically significant impact on profitability. The results provide guidelines for increasing profitability and improving the performance of logistics companies, given that an efficient planning system, managing and controlling the logistics system are key determinants of profitable business operations.

This paper aims to investigate the main drivers of sustainable profitability trends in the Serbian insurance industry over the years 2008–2019 (inclusive). Our study is motivated by the fact that insurance companies contribute to economic growth, and thus it is essential to understand the factors that contribute to their financial strength and stability. We use a set of standard panel regression models, including the mixed-effects model, followed by a more robust GMM estimation to uncover the linkage between selected micro-specific, macroeconomic, and institutional factors, and return of assets (ROA) and return on total premiums (ROTP). The present paper constitutes a significant contribution to the existing literature on the account of its comprehensiveness both in terms of the institutional datasets that we use, and in terms of the methodologies we apply (in particular, mixed effects and the generalized method of moments (GMM)). The estimated parameters are model-specific, and we find that firm size, GDP, the population growth rates, political stability, and the degree of specialization (in some empirical models) all lead to higher profitability. On the other hand, we observe that excessive risk-taking and inflation (in some specifications) are inversely related to profitability. Finally, we note that regulatory quality, average wage, and life expectancies are found to be not statistically significant. Accordingly, we argue that a profitability-centric managerial strategy should be based on expanded market share and stringent risk management protocols. At the macro level, we conclude that pro-growth and pro-population policies, combined with a well-oiled institutional setting that ensures political stability, constitute the best possible prescription for strong operational performance and profit sustainability in the Serbian insurance industry.

Most entrepreneurs have adequate knowledge and skills, however, they lack internal resources for commercialization of products on foreign markets. This group of entrepreneurs recognizes the chance through collaboration with other organizations, ensuring the engagement of new technologies that contribute to fast and early commercialization on the global market. The focus of this research is related to the analysis of the influence of entrepreneurs’ competences on cooperation with the other organization as well as on the internationalization of a new business venture. In order to provide deeper insight, the subject of research is also expanded with the field of new technology usage, as a moderator variable, to consider its role of strengthening the relationship between cooperation with other organizations and internationalization of a new venture. This paper aims to analyse the impact of entrepreneurial competences based on knowledge, skills and abilities (KSA’s) on cooperation with the other organization as well as mediating influence of cooperation with other organizations on internationalization of a new venture, in the South East Europe region. The main source of data in this study is the GEM research database for 2013. For this research, the authors included six countries in the research sample of the South East Europe region: Slovenia, Croatia, Hungary, Romania, Bosnia and Herzegovina, and FYR of Macedonia. The results of path analyses of Structure Equation Modelling indicate a positive direct and indirect impact of entrepreneurial intentions on cooperation and internationalization of a new venture. Results also indicate that the usage of new technologies, as a moderator variable, strengthens the relationship between cooperation and internationalization of a new venture.

This research aimed to determine whether and how financial analysis combined with machine learning can support decision-making for sustainable business growth. This study was conducted using a sample of 100 Serbian companies whose bankruptcies were initiated between 2019 and 2021 to identify key factors that distinguish solvent from insolvent companies. Two neural networks (NNs) were trained and tested to predict these discriminating factors one year (Y-1) and two years (Y-2) before bankruptcy initiation. Initially, a total of 37 predictor variables were included, but prior to modeling, variable reduction was performed through VIF analysis and t-tests. The training dataset comprised 70% of the sample, while the remaining 30% was used for testing. Both NNs utilized a softmax activation function for the output layer and a hyperbolic tangent for the hidden layers. Two hidden layers were included, and training was conducted over 2000 epochs using the gradient descent algorithm for optimization. The research results indicate that poor cash management is the first sign of possible insolvency one year in advance. Additionally, the findings reveal that retained earnings management can serve as a reliable bankruptcy predictor two years in advance. The overall predictive accuracy of the NN models is 80.0% (Y-1) and 73.3% (Y-2) for the testing dataset. These findings demonstrate how selected ratios can support bankruptcy prediction, providing valuable insights for company proprietors, management, and external stakeholders.