Background: The rapid development of artificial intelligence is transforming business operations, work processes, and organizational structures. Companies increasingly rely on data-driven decision-making and automation to enhance efficiency and competitiveness. However, the successful integration of artificial intelligence does not depend solely on technological readiness, but also on employees' perceptions, attitudes, and adaptability. Previous studies suggest that educational level, type of work, and hierarchical position may influence how individuals perceive technological change and its consequences. Purpose: This study examines how employees in Slovak enterprises perceive the future impact of artificial intelligence on business operations. It investigates whether educational background, type of work, and job position influence workplace attitudes toward artificial intelligence. Studydesign/methodology/approach: A quantitative survey was conducted among employees of Slovak companies in 2024. Data were collected through an online questionnaire using Likert-scale statements. After data cleaning, 260 responses were analyzed. The hypotheses were tested using non-parametric statistical methods to examine differences between groups. Findings/conclusions: The results indicate that educational level has only a limited effect on perceptions of artificial intelligence, with significant differences appearing mainly in relation to decision-making and data analysis. In contrast, clear differences were found between employees performing mental and physical work, with mental workers expressing more positive attitudes. Differences were also found across hierarchical positions, with managers reporting more favorable expectations regarding efficiency, innovation, and organizational change. The findings highlight that the integration of artificial intelligence is not only a technological issue but also a managerial and organizational challenge. Limitations/future research: The study is based on a convenience sample and a cross-sectional research design, and it represents an investigation limited to Slovakia. Therefore, the findings should be interpreted as exploratory and may not be fully generalizable. Future research should examine larger and more diverse samples and explore the long-term organizational and psychological effects of artificial intelligence adoption.
Background: Tax revenue performance is a central indicator of fiscal capacity and macroeconomic stability, particularly in small and open transition economies. While existing research highlights that macroeconomic volatility can weaken revenue mobilization, empirical evidence on the fiscal consequences of exchange rate volatility in European transition countries remains limited and fragmented. Given rising external exposure, evolving monetary regimes, and ongoing institutional reforms, understanding how exchange rate instability affects tax revenues is of growing policy relevance. Purpose: The purpose of this study is to examine whether exchange rate volatility undermines tax revenue performance in selected European transition economies. To this end, the paper evaluates the magnitude and robustness of this relationship, while accounting for macroeconomic, fiscal, and structural determinants of tax revenues. Study design/methodology/approach: The analysis employs a two-way fixed-effects panel framework using annual data for ten European economies over the period 2006-2024. The sample includes Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Hungary, Montenegro, North Macedonia, Romania, Serbia, and Slovenia. Exchange rate volatility is measured using an integrated annual indicator derived from daily conditional variances estimated through a volatility model. The empirical specification controls for economic development, growth dynamics, inflation, government expenditure, public debt, trade openness, and production structure. To ensure reliable inference, robust standard errors are applied to address heteroskedasticity, serial correlation, and cross-sectional dependence. Findings/conclusions: The results indicate a statistically significant and negative relationship between exchange rate volatility and tax revenue performance. Specifically, a 1% increase in exchange rate volatility is associated with an approximate 0.034 percentage-point decline in the tax revenue-to-GDP ratio. This demonstrates that higher exchange rate instability is associated with lower tax revenues relative to economic output, suggesting that currency volatility acts as a source of fiscal fragility rather than a stabilizing mechanism. Ultimately, the findings underscore the importance of exchange rate stability and coordinated monetary-fiscal frameworks for ensuring predictable and sustainable revenue mobilization in transition economies. Limitations/future research: The study is limited by its small country sample and the static nature of the empirical framework. Future research could extend the analysis to a broader set of countries, apply dynamic modeling techniques, and explore the asymmetric or nonlinear effects of exchange rate volatility on tax revenues.
Background: Digital transformation has become a central process in contemporary business environments, as organizations increasingly integrate advanced technologies into their operations and business models. While digital transformation is widely recognized as a driver of organizational change and innovation capacity, its direct effect on competitive advantage remains unclear, as the mechanisms through which digital investments translate into strategic outcomes are not yet fully understood. Purpose: The aim of this research is to examine how digital transformation influences innovation and competitive advantage, and to assess whether innovation performance mediates this relationship. Study design/methodology/approach: Data were collected through a structured survey in which 53 representatives of companies from Split, Croatia participated. The response rate was 31.2%. Empirical analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed relationships between digital transformation, innovation performance, and competitive advantage, which is particularly appropriate for small samples and exploratory research designs. Findings/conclusions: The results indicate that digital transformation positively influences innovation performance, which in turn positively influences competitive advantage. Innovation performance fully mediates the relationship between digital transformation and competitive advantage, with the direct path becoming insignificant once the mediator is included. These findings suggest that digital transformation generates competitive advantage primarily through its capacity to enhance innovation performance, rather than through direct technological adoption. Limitations/future research: The study is limited by a small convenience sample drawn from a single geographic area, which restricts generalizability. Future research should examine different institutional, sectoral and national contexts, incorporate objective performance measures, and apply longitudinal designs to better establish causality.
Background: Sustainability reporting has increasingly become a regulated and strategically significant component of corporate governance, while digital platforms play a growing role in shaping how such information is searched for, accessed, and interpreted within a strategic management context. Purpose: The aim of this study is to examine the semantic and behavioural structure of online search queries related to sustainability reporting and to identify dominant patterns of digital informational demand. Study design/methodology/approach: The study applies qualitative thematic content analysis and digital search analytics using data from AnswerSocrates and AnswerThePublic. A set of interrogative queries was coded into thematic categories, and cross-platform comparison was conducted across search engines, AI environments, and social media platforms. Findings/conclusions: The findings show that Google search queries related to sustainability reporting are predominantly framed as a regulatory and compliance-driven issue, accompanied by strong implementation and professional orientations. AI-mediated prompts (ChatGPT, Gemini) connected with sustainability reporting demonstrate a more solution-driven and market-oriented character. Social media queries (YouTube, TikTok, Instagram) further indicate the dual role of these platforms as spaces for showcasing corporate sustainability practices and exploring career opportunities. Limitations/future research: The study is limited by country-specific focus, potential subjectivity in coding, and the static nature of search data. Future research may expand geographical scope and explore longitudinal developments.
Background: generating business model thus plays the role of an intermediary between companies and customers, effectively harmonising the degree of correspondence between what the company creates and offers and what the customer appreciates. Purpose: The aim of the presented article is to examine the potential determinants of the value bearer in business models from the perspective of young adults. Study design/methodology/approach: The paper is supported by a primary survey (n=504), which was conducted in the first half of 2025. The data were processed with an emphasis on exploration, primarily using frequency analysis, contingency tables, the x2 test and its effect size, and Multiple Correspondence Analysis. Findings/conclusions: The results are focused on examining two retail chains. The results emphasise price as a purchase motivator and highlight how individual elements of customer value are interdependent. Additionally, they show that, from a market perspective, consumers perceive retailers differently based on their strategic positioning. Limitations/future research: It is worth noting that the study focuses on only one segment. However, in the future, it would be appropriate to expand the research to other segments. This study is limited to two retail chains, leaving opportunities for future research to investigate a wider range.
