The shadow economy (SE) is a global phenomenon that affects every country. However, its forms and mechanisms may differ depending on a country's socio-economic characteristics. The major characteristic is a country’s economic system. Hence, market and transition economies can be affected differently. Given that the size of the SE directly affects the level of tax revenue, it is particularly important to investigate the factors of the SE during the post-crisis period, when policymakers need sufficient budgetary funds to implement anti-crisis measures. In that sense, this paper aims to identify the differences in the factors that boosted the SE in 17 market and 19 transition economies in Europe between 2009-2014. The research is based on the PLS-SEM method. A country’s wealth and development, market openness, tax system and political environment are employed as the major SE factors. These factors are the most common in previous literature when investigating the issues of the shadow economy and are most appropriate for this research. The results suggest that particular factors of the SE differently affect market and transition economies. In transition economies, a favourable political environment, greater wealth and development, as well as a lower tax burden contribute to a smaller size of the SE, whereas greater market openness and a higher tax burden lead to a larger size of the SE. The links between market openness, tax system and the SE are not, however, statistically significant. Like transition economies, market economies are characterized by the positive impact of political environment and wealth and development when combating the SE. Unlike in transition economies, the size of the SE in market economies is reduced by a high tax burden and greater market openness. In the latter case, there is only one statistically insignificant path coefficient – it represents the relationship between the SE and market openness. The Multi-Group Analysis (MGA) method was employed to compare the path coefficients estimated for the country groups under consideration. The results indicate that the only difference in the path coefficients representing the relationship between market openness and the SE is not statistically significant. Based on the research results, some recommendations for policymakers in transition and market economies are provided in the conclusion.

In this paper, seven hypotheses are defined, on the basis of which a theoretical model is developed to examine how different sources of enterprise risk affect

It is logical to assume that knowledge, as the most valuable resource in an organization, has an important role in achieving the goals of corporate sustainable development (CSD). However, not many studies have tried to uncover the true relationship between knowledge management practice and CSD. In that sense, this study aims to analyze the connection between these two variables. The study was conducted during the first quarter of 2024. The sample size used for the analysis consists of 84 managers from different hierarchical levels employed in Serbian companies which have already implemented knowledge management principles. The Partial Least Squares Structural Equation Modeling (PLS-SEM) technique is adopted to explore complex relationships among variables. In addition, the mediation analysis was performed to investigate the mediating role of green innovation practice in the relationship between knowledge management and CSD. The results suggest that the total effect of knowledge management on CSD is significant (b = 0.670, p = 0.000), indicating a positive relationship between these variables without considering the mediator. When mediator green innovation was included, the direct effect of knowledge management on CSD became very low and statistically insignificant (b = 0.022, p = 0.934), suggesting that the variable green innovation fully mediates the relationship between them.

High unemployment rate, low level of economic activity and low living standards are some of the most significant problems that the Republic of Serbia has been facing in the last few years. The development of small and medium enterprises and entrepreneurs as great potential to solve these problems to some extent is still not sufficiently exploited. Keeping in mind the importance of the development of this economy segment, this paper analyses the business economy of entrepreneurs by economic activities in 2018 in the Republic of Serbia to determine the economic activities that have the greatest prospects for entrepreneurship development in the future. The ratio analysis of operations was used as a starting point for comparative analysis. It was conducted using the data obtained from the Annual Bulletin of Financial Statements published by the Business Registers Agency for ten economic activities where entrepreneurs reordered the highest profitability in 2018. Using the entropy method and PROMETHEE method, the ranking of entrepreneurs according to economic activities was performed. The obtained results indicated that in 2018, the best-ranked entrepreneurs were those operating in Professional, Scientific, Innovative and Technical Activities, while the worst-ranked are entrepreneurs operating in Accommodation and Food Services.

A large number of studies have examined the effect of air pollution on mortality and morbidity. However, the most of those studies have investigated associations between air pollution and only one or two specific diseases such as cardiovascular, pulmonary and mental diseases or pregnancyrelated problems. This study aimed at exploring the risk effect of particulate matter air pollution on the emergency room visits for all these diseases in the city of Bor, Serbia. The data on daily emergency room visits between April 2014 and December 2018 as well as daily measurements of PM10 from 4 stations were collected. The Generalized-Additive Model (GAM) with quasi-Poisson regression was applied to assess the connection between daily PM10 and emergency room visits for each outcome. Calendar time, temperature and relative humidity were incorporated as confounding variables. Each 10 μg/m3 increase in PM10 at lag 0:3 day was associated with 0.33% (95% CI: 0.11, 0.54) and 1.22 % (95% CI: 0.73, 1.71) increments in admission for cerebrovascular diseases and pregnancy-related problems, respectively.