Denis Juracka

Over the past few decades, globalisation, digitalisation, and social transformation have fostered the emergence of the sharing economy as a new economic model. This article examines consumer behaviour in the Slovak sharing economy, with a particular emphasis on the accommodation sector. The main objective of the study is to map consumer behaviour in the area of the sharing economy in the Slovak Republic and to determine the factors influencing this consumer behaviour in the accommodation sector. A questionnaire survey of 385 respondents was used to conduct quantitative research, with statistical validation using Pearson's test and a proportional agreement test. According to the findings, the majority of consumers, particularly those in the younger and higher income groups, have positive experiences with shared accommodation platforms. The most influential elements in accommodation selection were found to be price, location, and user reviews. From a theoretical approach, the study contributes to the small body of research on sharing economy adoption in smaller European Union countries, highlighting the relevance of socioeconomic considerations in shaping consumer preferences. In managerial terms, the research underlines the need for platforms to improve trust, openness, and flexibility, particularly in terms of service quality and cancellation rules. Furthermore, the findings emphasise the need to increase public knowledge of the benefits of the sharing economy through focused media efforts and government backing. The study's novelty stems from its contextual focus on Slovakia and its integration of consumer satisfaction data with strategic recommendations for sustainable tourism development and regulatory legislation.

Research background: Digital transformation across the European Union (EU) has become a critical driver of economic competitiveness and societal development. However, there are still notable differences in member states’ infrastructure, governance, and level of digital preparedness. Interest in setting the primary factors that determine digital maturity and understanding the structural disparities in the EU’s digital landscape is developing as a result of Industry 5.0, which places a high priority on human-centricity, sustainability, and resilience. Purpose of the article: The objective of this article is to evaluate the digital preparedness of EU member states by using the most recent Network Readiness Index (NRI) data for 2024. It aims to determine the factors that have the most significant impact on the overall digital performance, evaluate the disparities between countries in the quartiles of the NRI rankings, and visualize the current status of digital transformation throughout the EU. This research further contextualizes the findings within the shift from Industry 4.0 to Industry 5.0. Methods: The study applies a combination of multivariate and inferential statistical techniques. A segmentation map is used to visually group countries by digital performance. Stacked bar graphs illustrate the importance of specific NRI components to overall scores. An independent sample t-test is performed to assess significant differences between high-performing and moderately performing countries. A regression study determines the primary predictors of overall digital readiness. Findings & value added: The study indicates significant variability in the structure and determinants of digital readiness among EU nations. Research and development (R&D) investment, household Internet access, and GDP per capita in purchasing power standards (PPS) are considered the most reliable indicators of digital success. Statistically significant differences were established between the first and second quartiles across various parameters of the NRI. This study improves the literature by delivering a thorough empirical evaluation of the 2024 NRI data and presenting practical recommendations for policymakers aiming to promote fair and sustainable digital transformation in accordance with Industry 5.0 principles.

This study examines small and medium-sized enterprises (SMEs) in the European Union (EU) and their openness to circular economy practices. A cross-section of European SMEs is evaluated using data for the EU-27 taken from the Euroflash Barometer 549 (SMEs, resource efficiency, and green markets). The aim of this study is to reveal the relationship between various circular economy activities within the European Union. This objective is accomplished by means of the statistical technique known as principal component analysis (PCA), which involves the categorization of variables into dimensions. The analysis pointed to two categories of circular economy activities. According to the research results, up to 93% of SMEs implement at least one circular economy activity. SMEs that adopt strategies for the efficient use of environmental resources, particularly in water conservation, also employ energy-saving measures. PCA identified a second group prioritizing modular architectures, environmentally benign materials, and recurrent resource use. Notably, businesses focusing on water conservation appear to prioritize sustainable product design the least. In contrast, those incorporating circular economy principles into product design and manufacturing also tend to emphasize recycling and reuse.

Artificial intelligence (AI) is becoming a significant driver of transformation in the business environment, particularly for startups, which are characterised by high levels of adaptability, innovation orientation and strategic flexibility. Startups that incorporate artificial intelligence into their structures and processes are reshaping traditional approaches to value creation. This study aims to explore how artificial intelligence influences the formation and evolution of business models in startups across different industries. The analysis draws on academic literature, case study evidence and current market observations in order to identify key areas where artificial intelligence may affect fundamental business model components. The comparative part of the study focuses on differences between AI-driven startups and traditional companies that did not emerge as startups and do not rely on artificial intelligence as a core strategic technology. The comparison is carried out within three selected industries, namely banking, automotive manufacturing and retail. The study applies the Business Model Canvas (BCM) as a conceptual tool to evaluate the configuration of business models in both categories of companies. The results of the analysis indicate that startups using artificial intelligence are creating new types of business models in which AI plays a significant role in shaping the value proposition, sales channels, and revenue streams. Traditional companies, on the other hand, are not transforming their business models radically but are integrating artificial intelligence mainly in support areas. Building on these findings, this research contributes to the broader understanding of business model innovation under the influence of artificial intelligence and outlines the analytical foundations for identifying structural distinctions between AI-driven startups and traditional companies.

Research background: Every business activity involves the business environment. The faster rate of technology development has an impact on innovation management roles within the company as well as innovation approach methods. For these reasons, it is necessary to analyze innovation management in individual countries because it includes decisions made and actions done in relation to creating and implementing an innovation strategy. Every business operates in a certain atmosphere that is dynamic and has a constant impact on the business. Therefore, it is important to analyze and predict the development of the business environment. Purpose: The aim of this paper is to specify and identify the development of scientific articles dealing with innovation management and processes that are closely related to the topic of innovation. Research methodology: Within this study, through quantitative-mathematical bibliometric analysis, the prevalence of innovation and innovation management in scientific articles is analyzed. Results: The results of the research point to the fact that dealing with innovation management and innovation processes in the corporate environment has its importance not only in the present, but also in the past because authors’ pointed out in their scientific studies the need for continuous progress, namely in a linear course with the development of science. Novelty: The examination of innovations is frequently a complex phenomenon that needs to be investigated within the particulars of a given country, which is one of the study’s limits. The amount of money spent overall on research and development (R&D) and the level of support for innovation vary per nation. The added value of the study consists in a comprehensive analysis of scientific articles dealing with the topic of innovations, their development and importance in business processes.

Research background: In terms of evaluating the financial health and stability of the entire industry, the financial and economic analysis of individual companies is among the most critical. It is a composite of numerous fragmentary components that collectively convey information regarding individual activities. Purpose of the article: The energy industry is assessed from the perspectives of profitability, debt coverage, equity, and efficient asset utilization through the use of individual indicators to determine the changes and impacts of recent crisis. The purpose of this paper is to assess the extent to which the financial health and stability of the selected industry have been impacted by a diverse array of economic factors. Methods: The subsequent section of the paper is dedicated to the examination of individual relative financial indicators within the designated sector of the national economy. The industry selected for this project is classified as section D - Supply of electricity, gas, steam, and cold air by the Statistical Office of the Slovak Republic and the SK-NACE classification of economic activities. The ratio analysis is the most critical component of the paper when analyzing the economic effects on the energy industry. The optimal values are then contrasted to the resultant values, which are evaluated based on the trend of positive or negative development. Findings & Value added: In summary, the design phase assesses computed indicators in the context of external factors during the monitored period, while the industry anticipates its future using the data. The profitability indicator was most significantly impacted by the aforementioned factors in 2022, as the sector experienced a decline. Additionally, liquidity increased until 2021. In 2022, it experienced a slight decline as a result of economic pressures. The indebtedness analysis indicated that the property could be funded by personal capital, as evidenced by the substantial self-financing. The energy sector's financial status was consistent, as evidenced by the stabilization of critical financial ratios and its resilience in the face of significant external disruptions.

Sustainability is about intergenerational solidarity in finding solutions to ensure the continued growth that allows organizations and companies to be proactive. In the context of contemporary technology, the fourth industrial revolution, i.e., the widely accepted notion of Industry 4.0, and swift corporate growth; the effects of industry, transportation, and urbanization on climate change; and the preservation of the environment in its entirety are becoming more and more significant. The primary objective of this study is to evaluate the eco-innovation performance of European nations, comparing their evolution from 2013 to 2022, in order to identify patterns, leaders, and opportunities for improvement in the implementation of eco-innovation strategies. This study includes the analysis of the Eco-Innovation Index as well as other studies carried out at the European Union level in the field of sustainability and sustainable innovation through the graphic maps, cluster analysis, and correspondence analysis in the statistical program SPSS. Different approaches to development are taken by the EU’s member states. Even though some countries have achieved significantly lower results than the average of the Eco-Innovation Index or significantly higher results than the average, overall, all countries (except Romania) have improved their point evaluations when compared to the year 2013 when the Eco-Innovation Index started to be reported. The nations in the Northern European region produce consistent, long-term outcomes, and these countries have emerged as leaders in innovation in recent years. The countries of Luxembourg, Austria, Finland, Sweden, and Denmark have the best long-term outcomes. On the contrary, Bulgaria has ranked last for a long time, with the least-rated eco-innovation activities.

Innovation is a critical element in numerous domains, especially when it comes to determining the course of business success via efficient innovation management systems. The objective of this study is to determine which innovation category has the greatest impact on the effectiveness of innovation management by analyzing the correlation of innovation and its associated activities on the innovation performance of companies. This study synthesizes empirical research findings regarding the relationship between management and innovation performance through the utilization of meta-analysis. In recent decades, meta-analysis has gained significant prominence as a method to improve the precision of results by integrating multiple studies into a comprehensive analysis. Systematic reviews and meta-analyses enhance the credibility of research outcomes due to their status as the most dependable forms of evidence. A noteworthy correlation is observed between innovation performance and innovation categories, with small and medium-sized enterprises (SMEs) exhibiting the strongest correlation. Significantly, organizational innovations demonstrate the strongest correlation coefficient, indicating that they have the greatest impact on innovation performance. This research highlights the significance of innovation management in effectively addressing enterprise challenges and promoting business success. It specifically emphasizes the critical role that organizational innovations play in facilitating innovation performance.

The sharing economy, as a developing business model, is becoming more and more popular. This phenomenon can be observed in many countries. The sharing economy, as a part of human life in its essence, has existed for a long time. In general, the sharing economy is considered an economic model where individuals or organizations share a certain type of property or, in this way, provide services for a financial reward. One of the most used sectors, where there is constant interest, is the shared transport of people, goods, and services. However, platforms operating in the shared transportation segment should be analysed from various points of view, such as their financial results and overall economic stability. The study is primarily focused on the sector of shared transport and transport services. The chief objective of the study was to demonstrate the impact of the COVID-19 pandemic on shared transport and transport services within the territory of the Slovak Republic. The analysis included ride-hailing platforms such as Bolt Services SK as well as food and dining delivery platforms such as Wolt Slovakia. Through appropriately chosen methods of financial and economic analysis, the situation of the platforms before and during the COVID-19 pandemic was determined. We also performed an analysis of the development of the number of cars and the related level of automobilization in the territory of the Slovak Republic, since the shared economy represents an alternative to conventional economic models.

This paper deals with the comparison of differences in the levels of the application of executives and managers´ competences in companies divided by the number of employees and the line of business and identifies the differences based on this classification. Research data were collected via a questionnaire survey administered to 610 small and medium-sized enterprises in the Czech Republic. The subsequent analysis of the responses showed that it is possible to work with complete data from 581 companies. The data were then subjected to statistical calculations according to statistical methods, specifically, the general linear model (GLM), two-way ANOVA, and regression analysis. These methods were used for calculating the results and compiling auxiliary tables and graphs. The results show that in terms of the classification of the companies by their size (the number of employees), it is statistically clear that with the growing number of employees and thus the size of companies, the level of application of the competencies of managers and executives increases as well. The highest level was identified in companies with 150 or more employees, while the lowest was identified in small companies with no more than 9 employees. In terms of the classification of companies by line of business, there were no significant differences in the application of competences; therefore, it cannot be confirmed that any specific line of business shows a higher level of applying managers´ and executives´ competences. The results obtained can help small companies realize that although the application of competences is more typical for large enterprises, small companies must also pay attention to this topic if they want to grow in the future and increase their turnover. The results are limited by the methods chosen for the achievement of the objectives and data collection. Finally, the results were compared with the findings of other authors.