The article aims to find out the perception of human capital issues by entrepreneurs of small and medium-sized enterprises within the V4 countries, who implement the concept of CSR in their managerial praxis. The paper is based on a questionnaire survey with data collection from September 2019 to January 2020 with a total of 1585 respondents. Statistical methods of Pearson's chi-square and z-score were used to test the hypotheses. The results revealed differences between countries in terms of employees' turnover, perception of employees as the most important corporate capital, or the implementation of participatory management style. On average, 93% of respondents consider employees the most important company capital across the countries. There is also a strong consensus on the necessity of evaluating employee performance and motivation to innovate work practices.On the contrary, differences in the opinion on staff turnover were found among researched countries. The highest rate of turnover is among Polish entrepreneurs, and the lowest is in Hungary. With the growing company's size, the turnover of employees is getting higher. A participative management style is mainly implemented in the praxis by Slovak entrepreneurs (90%) and least by Hungarian (68%). However, Hungarian entrepreneurs are highly aware of the fact that their employees try to increase their performance, and healthy competition prevails among them (74%). The results may be interesting for those who promote or implement CSR in the conditions of the researched countries.
Research background: It does not matter if the company is operating in the domestic or in the international environment; its failure has serious impact on its environment. Because of this fact it is not surprising that not only owners of the companies, but also another interested groups are focused on the prediction of the company´s financial health. Purpose of the article: The first studies concerned with this issue are dating back to 1930 but from this time a hundreds of bankruptcy prediction models have been constructed all over the world. Some of them are known world-wide and some of them are known only on the national level. Many researchers share their opinion, that it is not appropriate to use foreign models in the domestic conditions non-critically, because they were constructed in the different conditions. One of the main problems are used variables. Methods: We mention three studies which were focused on the used variables in the bankruptcy prediction models. Our comparative study was concerning with 42 models constructed in the seven chosen transit economics with the aim to realize which variables are relevant and which could be reduce from the bankruptcy prediction models. We focused only on the used variables and abstracted from the used methodology, the date of their construction or the model´s power of relevancy. Findings and Value added: The result of our comparative study is the identification of 20 variables, which were used in three or more prediction models, so we assume that these variables have the best prediction ability in the condition of transit economics and their application should be consider in the construction of new models.
The financial health of enterprises and their continued profitability and competitiveness in the market are influenced considerably by the level of earnings achieved. Enterprises are forced to report the best possible results to demonstrate financial strength and competitiveness and to provide a good accounting for investors and creditors. Thus, the main objective of the study is to investigate whether there is any mutual dependence between corporate financial stability and earnings management. To measure these categories, Altman’s Z score was used to determine the financial health of enterprises, and the Beneish M-score and modified Jones model were applied to detect earnings manipulation. Using the chi-square test, the results revealed a statistically significant dependence between financial distress and earnings manipulation. Then, a multivariate statistical technique of correspondence analysis was applied to the categorical data to find categories of factors that are mutually correspondent. Based on a dataset of 11,105 enterprises operating in the Visegrad countries, the results found that enterprises that are threatened by bankruptcy or located in the gray zone tend to manipulate their earnings to maintain credibility, creditworthiness, and competitiveness. Because the financial health of an enterprise provides a potential incentive for earnings manipulation, state authorities, regulators, and policy-makers may benefit from the findings of the study.
The present time is constantly evolving, advancing and bringing new challenges and threats that may have an adverse impact on individuals and organizations. Each organization must adapt its activities to the current situation. It must also take care of its security, which it needs to ensure its existence, successful functioning and continuous improvement of its position within the global environment. Security must therefore be part of the organization’s main strategies. Therefore, appropriate attention should be paid to security and the organization should regularly allocate sufficient resources to ensure its security. The aim of this article is to point out the possibilities of using the CBA method in the framework of security management in the concept of socially responsible business. The CBA method provides scope to develop and incorporate its methodological framework into standard risk management practices within a company by assessing the costs and benefits of the proposed preventive measures related to ensuring the required level of security within the organization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.