The presented paper focuses on the possibility to group countries by the cluster method in terms of assessing the sustainable competitiveness of European countries. Our calculation is based on HDI (Human Development Index) and EPI (Environmental Performance Index) indices. We also tried to show the differences in HDI and EPI index of the Slovak Republic and the Netherlands. The aim of this paper is to evaluate the global competitiveness regarding the environmental economics model, considering all three levels: economic, social, and environmental. We measure the socio-economic dimension using HDI according to the health and education areas, then we measure the environmental dimension using EPI, which monitors the behaviour of countries in the field of human health protection and ecosystem protection. Our question is whether there is an appropriate classification for the development of these countries that could help to reduce the differences between the average countries and the EU 27 average. The approach to this topic began with the question whether these countries, which have high values of economic growth, have a high level of EPI or HDI. The intention is to look for the possible existence of a gradual rapprochement of countries belonging to the same group.

The aim of this paper is to assess the reliability of alternative default prediction models in local conditions, with subsequent comparison with other generally known and globally disseminated default prediction models, such as Altman’s Z-score, Quick Test, Creditworthiness Index, and Taffler’s Model. The comparison was carried out on a sample of 90 companies operating in the Slovak Republic over a period of 3 years (2016, 2017, and 2018) with a narrower focus on three sectors: construction, retail, and tourism, using alternative default prediction models, such as CH-index, G-index, Binkert’s Model, HGN2 Model, M-model, Gulka’s Model, Hurtošová’s Model, Model of Delina and Packová, and Binkert’s Model. To verify the reliability of these models, tests of the significance of statistical hypotheses were used, such as type I and type II error. According to research results, the highest reliability and accuracy was achieved by an alternative local Model of Delina and Packová. The least reliable results within the list of models were reported by the most globally disseminated model, Altman’s Z-score. Significant differences between sectors were identified.

The subject of this study is an oligopolistic market in which three firms operate in an environment of quantitative competition known as the Cournot oligopoly model. Firms and their production are differentiated, which brings the theoretical model closer to real market conditions. The main objective was to expand the Cournot duopoly and add another firm, resulting in an oligopolistic market structure assuming a partially differentiated production and coalition strategy between two firms. This article contains an oligopolistic model specifically designed for three different types of expectations, and has been applied to find and verify the stability of the net equilibrium of oligopolists. The market of telecommunication operators in Slovakia was selected as a real market case with accessible data on an oligopoly with three companies and partial differentiation. There are studies in which the authors limit their considerations to a certain number of repetitions of oligopolistic games. An infinite time interval is considered here. Three types of future expectations were considered: a simple dynamic model (or naïve expectations) in which the oligopolist assumes that its competitors will behave in the future based on their response functions, an adaptive expectations model in which the oligopolist considers a weighted average of the quantities offered by its competitors, and real expectations in which firms behave as rational players and do not have complete information about demand and offer output based on expected marginal profit. While the presented model proved to be stable under naïve and adaptive expectations, no stable equilibrium was found under real expectations and further results indicate a chaotic behavior.

This study delves into the impact of visual marketing stimuli on consumer response times, focusing on the complexity and subjectivity of the questions posed. Conducted in Slovakia, the research involved 40 participants (20 men and 20 women, aged 30 to 50 years), all holding university degrees in economics to ensure consistent decision-making experience. Participants were presented with visual stimuli representing four well-known FMCG brands. The stimuli included simple brand preference questions and complex evaluative judgments of offer efficiency. Response times were measured in milliseconds and analyzed using statistical methods, including the Mann-Whitney U test and one-way ANOVA. Results revealed that responses to simple stimuli averaged 1212 ms, while complex stimuli elicited slower responses, averaging 2504 ms. A significant difference was observed for “No” answers in the offer evaluation tasks, with correct “No” responses taking 3000 ms compared to 2297 ms for incorrect ones (p < 0.05), highlighting the cognitive load involved in accurate decision-making. These findings provide valuable insights into the cognitive processes driving consumer decision-making and contribute to the theoretical understanding of how question complexity and subjectivity influence response times. AcknowledgmentThis paper was funded by research grant VEGA 1/0462/23 entitled “Circular economy in the context of societal demands and market limitations“ (100% share).

Type of the article: Research ArticleAbstractArtificial intelligence (AI) is reshaping how firms design work, yet firm-level evidence compresses employment implications into a single net figure that hides simultaneous hiring and cutting within one firm. The study examines how AI adoption stage, self-assessed AI maturity, orientation, and ownership are associated with the incidence and co-occurrence of realized or planned job creation and elimination. The analytical sample is 693 AI-engaged Slovak firms from a cross-sectional survey (351 current users, 211 pilot firms, 131 planning adoption). Two binary items record whether AI-related positions have been introduced or are planned, and whether AI has led or is expected to lead to layoffs. Each item merges realized with planned or expected action, so the outcomes indicate the incidence of an actual or anticipated event, not the number of positions. We applied exact tests, logistic and multinomial logistic regression, and a bivariate probit model with Benjamin-Hochberg false-discovery-rate (FDR) adjustment. Reported or planned creation was more frequent than elimination (18.0% vs. 9.2%; p < 0.001), and the two co-occurred well beyond chance (odds ratio 7.23; ρ = 0.54). A more advanced adoption stage was associated with a higher incidence of creation (OR 1.49; FDR-adjusted p = 0.004), and employee job-threat concern was associated with a higher incidence of elimination (OR 1.58; p = 0.014). Foreign ownership was associated with joint occurrence of both outcomes in an exploratory model only (RRR 2.29; unadjusted p = 0.027). The study contributes a descriptive typology of four incidence patterns; the cross-sectional design supports associational reading only.AcknowledgmentsThe authors thank the AI-ImpactSK project team and all responding firms.This paper was supported by the European Union – NextGenerationEU through the Recovery and Resilience Plan for Slovakia under project No. 09I05-03-V02-00003/2025/VA (AI-impactSK); 100% share.