Inproforum, 2025 (roč. 19), číslo 1

The concept of wellness is traditionally understood within a holistic, multidisciplinary framework (Hettler, Dunn), where the psychological and mental components are key to achieving maximum potential. Despite this theoretical consensus, in practice, wellness on the Czech market, and especially in the accommodation sector, is predominantly reduced to the physical dimension (swimming pools, saunas, massages). This article aims to explore the discrepancy between the theoretical holistic concept of wellness and the practical services offered in the Czech Republic and to identify gaps in the mental health care segment.
The methodology combines systematic literature research with an analysis of the content of the websites of 50 selected luxury accommodation facilities (N=50) in the Czech Republic and an exploratory qualitative survey of demand (structured interviews with clients).
The results show that the vast majority (92%) of the facilities surveyed offer only one-dimensional, physically focused services, while comprehensive mental health care packages (including retreats, meditation, and yoga with an instructor) are offered by only 8% (4 facilities). The results also show that although client demand is primarily directed towards traditional services (swimming pool, sauna), respondents actively express interest in expanding the offer to include relaxation and meditation exercises as a counterbalance to a stressful lifestyle.
Based on data triangulation, the article confirms a significant gap in the offer of holistic wellness stays (retreats) on the Czech market. It formulates recommendations for tourism entities that want to take advantage of the growing trend of mental health care.

Customer retention and loyalty are paramount in the restaurant industry, especially in the fast-food sector. Although customer loyalty in the fast-food industry has received extensive attention from practitioners and academics worldwide, researchers have yet to establish the critical factors of fast-food customer loyalty. This paper aims to reveal the antecedents of fast-food customer loyalty by synthesizing the results of recent studies. Methodologically, this research develops a systematic literature review following the PRISMA framework. Thirty-one publications available on Scopus and Web of Science databases were included in the review and analyzed to identify the most researched antecedents of fast-food customer loyalty in recent years. Overall, this research provides valuable insights for academics and practitioners interested in fast-food customer loyalty.

The goal is to define the essence, basic characteristics and relationships of retail, as well as the basic aspects of the business model in retail. To fulfill the article’s objective, secondary data was gathered for an overview of different authors’ opinions on the subject, which were then compared and evaluated.  The potential contribution of the article’s approach lies in the fact that it explains the fundamental changes in retail, which also strengthens the importance of the supply and demand side in the consumer market. Turbulent changes occur in the environment in which retail units carry out their economic activities. These changes are reflected in the value proposition by speed and adaptation of the product and business models to the customer’s requirements. In the conclusion, some suggestions resulting from the characteristics of the retail trade and the business model in the retail trade are presented. To fulfill its mission, retail must make the best use of its capabilities supported by digital solutions.

The aim of this article is to identify and analyze the main research directions and thematic areas within the field of cognitive ergonomics, focusing on its impact on employee performance and well-being. The study aims to provide a comprehensive understanding of how various ergonomic factors contribute to organizational outcomes and employee well-being. The analysis was compiled based on sources available in the Web of Science, Scopus, and Google Scholar databases, published mainly after 2015. The selection criteria were clearly defined and included: publication type – peer-reviewed articles and conference papers; year of publication – 2015 to 2025; relevance to the work environment and cognitive ergonomics; focus on psychological, cognitive, or acoustic factors related to employee well-being. Studies focused exclusively on medical or clinical ergonomics were excluded. The results point to the main research clusters: physical work environment and productivity, acoustic ergonomics and noise factors, psychosocial factors and organizational context, experimental and application approaches. The findings confirm the interdisciplinary link between cognitive ergonomics, the working environment, and subjective well-being, and emphasize the importance of researching this issue not only from the perspective of health protection, but also in terms of maintaining work performance and the long-term competitiveness of organizations. The article also discusses practical and managerial implications that stem from the identified clusters, particularly in relation to workplace design and management strategies that promote sustainable productivity.

This paper explores perspectives of regional DMOs (Destination management organizations) from selected regions of the Czech Republic on competencies, collaboration, and barriers in selected Czech destinations, linking empirical evidence with contemporary literature in destination management. The study aims to identify the most critical factors that enable or hinder cooperation with an emphasis on destination offer development. By combining recent theoretical insights with data from the questionnaire among DMOs, the research contributes to a deeper understanding of collaborative governance in tourism. It provides practical implications for DMOs, policymakers, and practitioners.

Sustainable consumption is currently one of the key topics in social and economics discourse, especially in the context of growing environmental awareness among consumers. Young generations, particularly Generation Z, represent a significant consumer group whose purchasing behavior is influenced by environmental values, digital communication, and an emphasis on authenticity. This work focuses on the role of green marketing, transparency, brand credibility, emotional appeals, and digital media – including influencer marketing – which significantly support the shift from environmental attitudes to actual behavior. The influence of environmental knowledge and social factors on purchasing intentions is also important. The analysis further highlights the growing importance of modern technologies such as artificial intelligence, which enhances the effectiveness of green marketing tools. The findings emphasize the need for a comprehensive approach that combines education, authentic communication, and technological innovation to promote sustainable consumption among the younger generation.

The world economy is a dynamic entity that is constantly changing. Part of these changes has been the process of internationalization, which reflects closer economic connections between individual countries. International ties are thus transforming from exclusively trade exchange to increasingly integrated components. This is a phenomenon that has a multidimensional level and is characterized by the growing complexity of trade exchange. Bilateral trade relations are one of the most widespread forms of cooperation, where integration leads to the harmonization of regulatory frameworks and the strengthening of strategic ties. The aim of the article is to describe the level of cooperation between Australia and South Korea. This research paper will attempt to examine the impact of the KAFTA trade agreement on selected sectors of the economy - meat and sugar, as strategic trade items.

Music is a significant component of the shopping environment that can affect consumer behavior on both conscious and subconscious levels. The objective of this study is to examine the correlation between musical stimuli and consumer experience in retail food stores. An online questionnaire survey from various age groups and locations in Slovakia forms the foundation of the research.
Two hypotheses were developed based on the existing data. The first looks at how the level of the music and how sensitive a person is to noise affect how likely they are to leave the business early. The second one looks at how the chosen and perceived tempo of music match up and how it affects how much fun shopping is and how annoyed people are. The investigation included regression models that accounted for sociodemographic characteristics, including generation, settlement size, and cultural practices. The anticipated outcomes suggest that consumers with heightened noise sensitivity are more inclined to exit a store when the music volume is excessive. It is also thought that when the preferred and actual tempo of the music are the same, it makes the shopping experience seem better and less irritating.
The study enhances comprehension of the effects of auditory stimulation in a retail context and facilitates practical recommendations in sensory marketing, while also addressing subliminality and consumer variability.

Growing concerns in the tourism industry have brought community tourism to the forefront as a potential solution. Community tourism emerges as one of the possibilities for mitigation of tourism´s negative externalities: mitigation of poverty by creating local jobs and income, cultural degradation by enabling communities to preserve and showcase local traditions, environmental damage by placing residents as stewards of their environment, and the economic imbalance of mass tourism by ensuring benefits stay within the community. This approach offers a framework for local communities to take ownership and control of their tourism development. By empowering residents, community-based tourism seeks to ensure that the benefits of tourism remain within the local area. This study includes a preliminary analysis of a small-town community tourism potential based on three semi-structured interviews with community leaders in Římov, followed by a review of existing literature on community tourism to establish a foundation for future research. 

An important driver of success, according to several scientists, is Business Process Management (BPM), which represents a structured holistic management discipline focused on improving the performance of enterprises through the management of their business processes. BPM includes various methods, techniques and tools to support the identification, design, mapping, modelling, implementation and optimization of processes in order to support business goals. Business process mapping, as an integral and primary part of BPM, plays a fundamental role in the identification, analysis and design of processes. The digitalization of business process mapping supported by BPM software tools and standards fundamentally changes the means of documenting and managing processes. The scientific article includes: theoretical definition of basic concepts in the field of BPM, analysis and development of business process mapping and management also in the context of digitalization, synthesis of findings from expert sources and surveys, identification of barriers to implementing BPM, overview of BPM software tools and formulation of recommendations for enterprises in the field of BPM, including the digitalization of business process mapping. The main findings indicate that companies have low levels of digitized processes, 70% of companies use at least one BPM tool, only 3% of companies do not model or map processes at all, and up to 82% of companies use paper or manual process mapping. These findings are critical in the context of Industry 4.0, where the current emphasis is on digital innovation and thus on a high level of automation of business processes.

The research investigates how artificial intelligence (AI) reshapes labour markets, focusing on job composition, evolving skill demands, and changes in HR practices. The analysis reveals that AI can simultaneously promote efficiency and the creation of new high-skill positions while exacerbating labour market polarization and eroding stable employment forms. The scope and intensity of these effects vary significantly across sectors, occupational categories, and institutional environments. The results highlight that techno-logical progress is not inherently inclusive; rather, its impact depends on how technology is integrated into organisational and social frameworks. Employee involvement, training and retraining systems, and effective social dialogue emerge as key determinants of equitable adaptation. The study concludes that the governance of technological change, rather than technology itself, will shape the future configuration of labour markets.

The exploitation of artificial intelligence (AI) seems to be limitless and has therefore increasingly become a top trend topic in research and practice. This article deals with AI in the field of compliance and corporate governance. Since the topic of AI and compliance has hardly been addressed in the literature to date, the authors approach the subject by examining AI and corporate governance, another sensitive business management topic. Using the Gioia methodology, this article analyzes the current state of AI in corporate governance literature. While the possibilities and advantages of AI are often highlighted, there are also a number of open questions, risks associated with AI and, consequently, essential conditions that must be met for the successful use of AI. The results indicate that the risks and concerns of AI applications currently appear to predominate, which is why it must be the task of research and practice to find ways to address the doubts to exploit the full potential of AI also in sensitive business areas such as corporate governance.

The empirical literature has identified dozens of specific factors, such as organizational and technical readiness and many others, which positively influence the implementation of artificial intelligence (AI) in innovative businesses. The aim of this article was to compile a theoretical review of measurement instruments for these factors and to discuss their qualities, strengths, and weaknesses. Using a systematic literature review approach, we identified dozens of articles describing the factors in question, within which we analyzed specific measurement instruments and compiled a systematic overview of them. We found that the methods of measurement, the instruments, and the indicators used to describe and assess the status and level of these factors differ in nature and design and vary in their explanatory value and measurement validity. Self-report questionnaires and subjective expert assessments are combined with objective financial indicators. A systematic and comprehensive overview of measurement tools will provide managers with a practical aid in the process of implementing AI, thereby increasing the likelihood of successful AI implementation. At the same time, it will enable researchers to improve the existing framework and help create better, more informative measurement instruments.

Digital twins (DTs) are an emerging technological innovation in healthcare, enabling real-time simulation and optimization of clinical and operational processes through the integration of AI, IoT, and data-driven modeling. While initially adopted for clinical prediction and treatment planning, their broader economic implications for healthcare management remain underexplored. This paper presents a scoping review of recent research (2023–2025) examining the cost-effectiveness and economic value of digital twins in healthcare. The review synthesizes evidence from fifteen international studies indexed in the Web of Science database, focusing on both implementation costs and potential financial benefits for healthcare providers and systems. Findings show that DTs are most cost-effective in operational and infrastructural applications such as hospital logistics, energy management, and digital hospital ecosystems where cost reductions are directly measurable through improved resource utilization and process efficiency. In contrast, clinical and population-level twins demonstrate mainly conceptual or long-term economic potential, constrained by limited empirical data and methodological heterogeneity.
Overall, the review identifies digital infrastructure maturity, interoperability, and workflow integration as key enablers of financial sustainability. It also highlights the lack of standardized economic evaluation methods, underscoring the need for consistent reporting frameworks to inform evidence-based investment decisions in healthcare digitalization.

The main aim of this paper is to examine the application of artificial intelligence in small and medium-sized enterprises and to investigate whether the adoption of AI in enterprises across the V4 countries varies not only by country but also by enterprise size. The analysis is based on the latest available Eurostat data and combines descriptive statistics with chi-square tests: (i) a goodness-of-fit test to assess whether AI adoption rates differ across countries, and (ii) an independence test to verify the relationship between company size and AI adoption. The results show statistically significant differences across V4 countries and size categories: larger enterprises show higher adoption than SMEs, and there are significant disparities between countries, with some lagging behind. The findings confirm that structural factors (company size, national context) play a key role in AI deployment. The study provides practical recommendations for policymakers and SME managers: to develop competencies and infrastructure in a targeted manner, to focus support on overcoming identified barriers to adoption, and to monitor the effect of company size on the return on AI implementation. 

This paper examines regional disparities in research and innovation (R&D) expenditures across Slovakia, with particular emphasis on differences between the Bratislava Region and the remaining NUTS 2 regions. The aim of the study is to identify the extent of these disparities and to assess whether they are statistically significant. The analysis is based on secondary data obtained from the Regional Innovation Scoreboard (RIS) 2023, compiled by the European Commission in cooperation with Maastricht University. Using descriptive statistics and inferential analysis, including independent samples t-tests, the study compares public and private R&D expenditures as a percentage of GDP across Slovak regions. The results reveal that the Bratislava Region significantly outperforms other regions in both public and private R&D investment, confirming the presence of pronounced regional disparities in innovation financing. These findings highlight the need for targeted, region-specific innovation policies aimed at strengthening R&D capacity in less developed regions and supporting more balanced regional development in Slovakia.

Innovation and the introduction of new processes are an essential part of the functioning of enterprises. The main aim of this paper is to evaluate the position of enterprises from the Czech Republic within Central Europe in terms of innovation and the introduction of new business processes, and to identify whether there are significant differences between enterprises from individual countries. To achieve this aim, harmonized secondary data from the CIS 2022 survey and descriptive statistics, together with the chi-square test of independence, are used. The Oslo Manual is used to classify particular types of innovation. The results show the dominance of Germany, both in absolute terms and in intensity. Slovakia lags significantly behind other Central European countries. Process innovations are most often represented in all countries, while Czech enterprises are well above average in marketing innovations, and they also stand out in product innovations. It is recommended to strengthen organizational and process innovations, in particular in order to create a suitable innovation mix leading to increased competitiveness.

Stress in the workplace is currently on the rise, and it is company employees who encounter stress daily. Companies should therefore actively address this issue. However, the starting point for an optimal solution to stress in the workplace lies in monitoring stressors, which is often overlooked by companies. The main objective of this article is to identify the current state of stressor monitoring in manufacturing companies in the Czech Republic. Data was collected using a questionnaire survey and then processed using descriptive statistics, logistic regression and Fisher's exact test. The analysis found that the state of stressor monitoring in the workplace is critical. The most frequently monitored stressors are workplace relationships, overtime and high workloads. Statistically significant factors influencing the introduction of stressor monitoring in the workplace are the company's participation in a foreign group and the recent introduction of digitalisation elements in the workplace.

Machine learning (ML) represents one of the most transformative technologies shaping modern business environments. Its ability to process large volumes of data and generate predictive insights offers new opportunities for data-driven decision making and strategic management. However, despite its growing potential and benefits, the actual adoption of ML in enterprises remains relatively limited. The aim of this paper is to explore the current state of ML adoption across enterprises in the European Union and to synthesize existing research on how ML is applied in different business functions. Using secondary data from Eurostat and a structured literature review, the study identifies key areas of implementation, major benefits, and persistent barriers that influence the adoption and effective use of ML in organizations. Findings suggest that while ML enhances accuracy, efficiency, and strategic agility, its diffusion in European enterprises is still constrained by data related challenges, implementation costs, and shortages of skilled professionals. The paper underscores that closing widening cross-country gaps and moving beyond pilot stages will require stronger data pipelines and stewardship, practical model explainability, and change management to scale ML across enterprises, especially in lagging sectors such as manufacturing and transportation.

Music is a key atmospheric element that significantly shapes the retail experience by enhancing emotional engagement, increasing dwell time, and improving overall customer satisfaction. In fashion retail, where sensory cues are central to brand identity, well-selected background music—considering genre, tempo, and familiarity—can influence consumer attitudes and behavior. This study explores the impact of auditory environments in fashion stores, focusing on how music affects consumer experience and emotional responses at the point of sale. The research was conducted across 90 fashion retail stores using mystery shopping, with data collected by an external agency. Observations were structured into three main components: evaluation of customer impressions, store managers’ assessments, and in-store audio recordings from three spatial zones—entrance, main shopping area, and checkout zone. Findings reveal that background music has a measurable impact on consumer cognition, affect, and behavior—including time spent in-store, willingness to spend, and the overall perception of the store environment. A relationship between musical preferences and fashion sensibilities was observed, with specific genres evoking distinct emotional and behavioral responses. Fashion settings appear to reflect and amplify emotional atmospheres generated by music. Although the study relies on self-reported data, its results underscore the strategic value of music in retail marketing. Future research should explore these dynamics in controlled environments, using both explicit and implicit tools to assess emotional impact more precisely. These insights offer practical implications for fashion retailers, suggesting that tailored music strategies can enhance customer engagement, shape brand perception, and contribute to a more immersive shopping experience.

Digital transformation is increasingly influencing the way universities deliver administrative and support services. AI-powered chatbots are emerging as promising tools to enhance communication, efficiency, and user experience in student–university interactions. However, their successful implementation requires not only technological preparedness but also thoughtful change management to align organizational culture, stakeholder expectations, and service workflows. This paper presents a qualitative study exploring how university students perceive the planned introduction of an AI chatbot at a faculty’s student administration office. Using semi-structured interviews, the research examines expectations, perceived benefits, and concerns related to the chatbot’s integration into academic service processes. The analysis will be grounded in the theoretical framework of change management and institutional adaptability. The study aims to contribute to a deeper understanding of how students conceptualize AI-driven change in university administration, offering practical insights for managing digital transformation in higher education institutions.

The article compares the participation of the Czech Republic, Slovakia, and Portugal in Horizon Europe (HE), the EU’s main funding program for research and innovation. While the Czech Republic and Slovakia share a common historical and institutional background, Portugal serves as a comparable yet distinct reference case. Based on 2021–2024 data, the article assesses funding uptake, engagement capacity, and territorial imbalances. It highlights low absorption rates and failure to meet the 3% GDP target for R&D. Reflecting on warnings from the Draghi report about structural weaknesses in the EU’s innovation framework, it proposes reforms to enhance efficiency and support place-based excellence.

Recently, interactions between the Czech Republic and Taiwan in the business, tourism, and academic spheres have intensified following joint efforts by the governments of both countries. The article aims to evaluate the collaboration of Czech universities with their Taiwanese university partners. Specifically, the analyses focus on the intensity and forms of the collaboration and interrogate whether there are patterns regarding the type and size of the Czech universities. Forms of collaboration are defined as exchange of students, exchange of academics and joint projects. The dataset was derived from published long-term plans, internationalisation strategies, action plans, and university websites of 26 Czech public universities. The results indicate that student exchange is the most common form of cooperation between Czech and Taiwanese universities, followed by academic exchange. Joint projects appear to be a challenging and less frequent form of cooperation. Compared to other Czech universities, technical universities cooperate more intensively with Taiwanese partners (in all areas). Large and medium-large sized Czech universities intensively collaborate in all areas with Taiwanese universities. The intensity of collaboration between small and small-medium sized Czech universities and Taiwanese universities in rather low, except of the exchange of students that is moderate. These results can guide the policy makers when designing better internationalisation policies in higher education.

The aim of this article is to present the results of a bibliographic and conceptual analysis in the field of artificial intelligence (AI) and business economics, focusing on its impact on innovation, efficiency, and enterprise competitiveness. The analysis is based on recent scientific sources from databases such as Web of Science, Scopus, and Google Scholar, published mainly after 2020. The findings highlight the main research areas: AI as a driver of innovation and productivity, the transformation of business models and cost structures, and the role of aI in sustainable technologies. In recent years, AI has also entered areas that were once considered purely biological. Significant advancements have been achieved in the development and genetic editing of living organisms, particularly yeasts, which play a key role in producing biofuels. These applications illustrate how AI can connect digital and biological innovation, fostering progress in renewable energy and the broader bioeconomy. The results confirm the growing interconnection between AI, innovation management, and sustainable development, underlining the importance of further research on AI integration to strengthen long-term competitiveness and digital transformation of enterprises. 

This study examines how monetary policy influences corporate investment in China, emphasising how firm characteristics shape heterogeneous investment responses. Using a panel of 5,440 firms from 2000 to 2024, we analyse how interest rates, inflation, and firm-level attributes—such as size, leverage, and liquidity—interact to determine capital expenditure decisions. The results show that both interest rates and inflation exert positive and significant effects on investment, reflecting structural features of China’s financial system and firms’ adaptive behaviour under macroeconomic fluctuations. Larger and more leveraged firms invest significantly more, while liquidity has a negative effect, suggesting precautionary savings motives. Subsample regressions reveal meaningful heterogeneity: large firms respond more strongly to interest rates, while small firms face internal financial constraints and show minimal responsiveness to inflation. These insights highlight the importance of firm-level characteristics in understanding monetary transmission and corporate resilience.

The economic drivers of today's enterprises include the efficient use of resources (natural and other), while maintaining good economic results. This perspective is essential today for maintaining corporate competitiveness within the industry and internationally. This paper focuses on assessing the relationship between economic value added (EVA) and resource productivity. The textile industry is one of the most resource-intensive and globally interconnected industries. This industry is also facing growing pressure to integrate sustainability. An empirical analysis of companies in the textile industry in the Czech Republic has shown  that companies with positive economic value added (EVA) not only achieve higher profitability but also exhibit a more sustainable long-term management style, as measured by resource productivity. Although average resource productivity values indicate different levels depending on EVA creation, this fact could not be statistically confirmed.

The inflationary burden and inflationary potential of a currency can be estimated either by analysing monetary policy and other macroeconomic data, or by using comparative analysis procedures in the case of identifying past inflationary burdens and estimating them on the basis of recent monetary policy actions in the case of future developments. This paper follows the latter method. Data for the Czech koruna compared to the Polish zloty, the Hungarian forint and the euro are used as comparative bases, and the US dollar and the Swiss franc are also examined in a partial way. The paper is designed as a set of notes on the subject. It cannot be seen as a comprehensive analysis based on sufficient research. However, it concludes that the Czech koruna has historically been burdened with an inflationary potential of roughly 0.5 to 1.5 percentage points relative to the major currencies. Thus, with the same monetary policy, inflation on the koruna reaches the higher values described above. The explanation for this phenomenon is historical and relates to the structural fundamentals of the Czech economy.

This paper revisits the long-standing debate on whether fiscal redistribution hinders or supports economic development. Utilizing data from a diverse sample of more than 70 countries over the last three decades since 1993. The analysis explores the relationship between redistribution policies and national income levels, which represents the material basis for human development and its sub-aspects. Contrary to traditional efficiency-loss arguments, the findings suggest a positive and statistically significant association between higher redistribution rates and higher per capita income. In addition to income levels, the study examines how redistribution relates to income inequality and to migration. While initial correlation analysis suggested that countries with more migrants tend to be more equal, panel regression reveals a reversed relationship: an increasing migrant population is associated with rising inequality in host countries. Ultimately, the impact of migration on inequality, as well as on other aspects of economic development, depends on how well destination countries are able to integrate migrants into their social and economic systems.

: Defense expenditures in the Czech economy reached 1.5% of GDP in 2023 and 2.08% of GDP in 2024, amounting to approximately CZK 160 billion. Meeting the new commitment to allocate 5% of GDP to defense (3.5% for military spending and 1.5% for support expenditures) would require over CZK 450 billion annually, placing significant pressure on the state budget and the economy. In this context, it is advisable to direct part of the funds toward security projects based on the principles of the Copenhagen School of Security Studies. These projects integrate sustainability with state security, encompassing environmental protection, energy self-sufficiency, transport infrastructure, and other strategic sectors. The goal is to develop a comprehensive approach that combines military readiness with the long-term resilience of the state against risks related to climate, energy, and infrastructure, while minimizing negative impacts on the economy.

Nonprofit organizations constitute an integral part of civil society, as they contribute to the provision of public services, the promotion of social cohesion, and the representation of disadvantaged groups. In recent years, however, they have faced increasing economic pressures that threaten their stability and long-term sustainability. Rising inflation, growing labor and energy costs, limited availability of public funding, and changes in the structure of private donors create an environment in which nonprofit organizations must fundamentally redefine their financial and organizational strategies. This article analyzes the institutional responses of the nonprofit sector to these challenges, with particular emphasis on resource diversification, internal process optimization, and strengthening strategic management. It also discusses the risks associated with reliance on limited funding sources and presents examples of best practices that can enhance sector resilience. The study aims to deepen understanding of the dynamics of nonprofit organizations in a changing economic context and to highlight factors that may support their long-term institutional sustainability.

The aim of this article is to describe the transparency of enterprises regarding their environmental impacts in the context of ESG implementation. The research was conducted through a quantitative questionnaire survey at the enterprise level. In total, 78 valid responses were collected across various sectors, providing a diverse empirical basis. The study is structured around three research questions: (1) How do enterprises approach transparent monitoring of their environmental impacts? (2) What is the effect of having a clearly defined strategy for reducing the environmental impacts of enterprises’ activities on transparent monitoring of environmental impacts? (3) What is the effect of the perceived barriers to ESG implementation on transparent monitoring of environmental impacts? The findings contribute to a better understanding of the relationship between the level of transparency in monitoring and communicating environmental impacts and selected variables such as enterprise size, environmental impact reduction strategies, and perceptions of barriers to ESG implementation.

This article builds on the previous contributions presented at the INPROFORUM conferences, which focused on the application of functional time series analysis to assess sustainability through selected indicators. The aim of the present study is to compare two human development indicators applicable to the assessment of sustainability at the regional level: the Regional Human Development Index (RHDI), developed for the European Commission, and the Subnational Human Development Index (SHDI), based on the UNDP methodology and compiled by the Global Data Lab. The analysis covers EU regions at the NUTS 0, NUTS 1, and NUTS 2 levels over the period 2000–2020, corresponding to three programming periods of EU cohesion policy. Descriptive statistics and functional time series analysis were used. Although the two indices differ in their construction, they exhibit similar trends. The RHDI provides a more detailed regional perspective, whereas the SHDI allows for broader international comparability. This study is among the first to systematically compare these indicators in the context of European regions and highlights their potential for evaluating the impacts of European policies, as well as their practical application within the framework of cohesion policy.

The integration of Micro, Small, and Medium Enterprises (MSMEs) into the sustainability agenda is crucial for sustainable development, yet remains poorly understood in resource-constrained contexts. This study explores the complex interplay between sustainable practice adoption and perceived barriers among MSMEs in Zimbabwe. Through a cross-sectional survey of 312 enterprises, we identified a distinct hierarchy in the adoption of sustainable development practices: solar energy leads significantly (62.18%), substantially outdoing waste recycling (41.67%), water conservation (42.31%), and sustainable packaging (40.06%). While financial constraints (high costs: 50.3%; limited financing: 48.1%) and knowledge gaps (technical: 40.4%; information: 38.5%) were prevalent, the most critical finding reveals a central paradox: a strong positive correlation (r ≈ 0.98) between adoption intensity and barriers reported. High adopters (averaging 5.47 practices) cited significantly more obstacles than low adopters (0.64 barriers), particularly in technical knowledge (76.7% vs. 9.5%) and limited finance (73.3% vs. 30.5%). This suggests that barrier recognition and navigation are essential to the adoption process, not simply deterrents. The study concludes that standard intervention models are inadequate. We recommend a multifaceted strategy: leveraging solar energy as a strategic entry point, shifting training from theory to practical implementation support, developing integrated financial products, and implementing tiered support systems tailored to different adoption stages. These findings provide a comprehensive framework for policymakers and practitioners to bridge the intention-action gap and accelerate sustainable development in emerging economies.

In the face of growing global uncertainty, ranging from climate change to geopolitical instability, regional resilience depends increasingly on the ability of local governments to coordinate, adapt, and act collectively. Intermunicipal cooperation (IMC) provides a governance mechanism through which municipalities can pool resources, enhance administrative capacity, and jointly deliver essential services. As such, IMC not only promotes efficiency, but also strengthens the institutional and social fabric necessary for regional sustainability and resilience. This paper analyzes inter-municipal cooperation (IMC) in Slovakia and its crucial role in improving the quality and availability of public services, particularly in the context of enhancing regional resilience. The study aims to identify the specific benefits, prevalent challenges, and untapped potential of IMC within the Slovak local government landscape and to propose concrete measures to enhance its efficiency and effectiveness. The methodology is based on a comprehensive questionnaire survey conducted among Slovak municipalities. The results show that IMC brings significant benefits, such as cost savings and improved service quality, which directly contribute to regional robustness. However, it also faces persistent challenges like administrative complexity and lack of stable funding. The paper provides strategic recommendations for future cooperation and emphatically underscores the need for systemic legislative and financial changes at the state level to fully realize IMC's potential for sustainable and resilient regional development.

The study analyzes the system of subsidies for affordable housing in the Czech Republic in the context of economically and socially disadvantaged regions. The main objective is to assess the extent to which the current public support framework fulfills its declared purpose of ensuring affordable housing for low-income households and to identify the institutional and economic factors influencing its effectiveness. The research uses qualitative comparative analysis of academic studies, statistical data, and strategic documents from 2012–2025. An interdisciplinary approach combines insights from economics, regional development, and public administration theory to critically evaluate the institutional framework of housing policy in the Czech Republic. The findings point to persistent systemic shortcomings, insufficient coordination between levels of public administration, fragmentation of competences, and a strong dependence on market mechanisms in addressing the issue of housing affordability. These factors contribute to the residualization of the public housing sector, which is narrowing to narrowly defined groups of the population and losing its stabilizing and developmental function. The study concludes that housing policy should be seen as a long-term and institutionally anchored tool for regional development, linking public investment, regulatory frameworks, and local capacity building to promote social cohesion and economic resilience.

ESG reporting is becoming more prevalent in practice. More and more companies are creating and monitoring environmental, social and governance indicators. This gives them a better chance of succeeding not only on the domestic market but also on international markets. A company’s activities also have an impact on its surroundings and strong relationships are important for the successful development of business operations. A positive assessment of a company contributes to its long-term stability. Current ESG reports are undergoing a process of development and therefore differ from company to company. In our research, we focused on the trends, challenges and opportunities associated with the implementation of ESG in the agricultural sector. This study presents relevant taxonomy and legislation from the perspective of the European Union and Slovakia. We also focused on the implementation of ESG in the business environment and the reporting process. In the near future, agricultural enterprises can expect changes and adjustments to ESG reporting requirements. They should use the current transition period to adapt their enterprise information systems and create the necessary processes and tools for effective ESG reporting.

The paper examines the development of corporate taxation in the Visegrad Group (V4) countries—Slovakia, the Czech Republic, Poland, and Hungary. The main objective is to analyse how the tax policies of these countries have evolved over time, to identify the key drivers behind these changes, and to assess their impact on businesses and the broader economy. The study also compares the corporate tax systems of the V4 countries with those of other EU member states and explores how global trends, such as tax harmonization and the digitalization of taxation, have influenced their fiscal frameworks. The study offers a comprehensive examination of the evolution of corporate taxation within the Visegrad Group (V4) countries—Slovakia, the Czech Republic, Poland, and Hungary—by combining both theoretical and analytical approaches. It explores fundamental concepts of corporate taxation and outlines the policy frameworks that have shaped tax systems in these economies. Furthermore, the analysis focuses on the broader economic and fiscal environment of the region, identifying the main factors that have influenced tax reforms, and the differing approaches each country has adopted in response to domestic and international challenges. The paper evaluates how changes in corporate tax structures and rates have affected business activity, investment levels, and overall economic performance. Building on the empirical findings, the study formulates policy recommendations aimed at improving the efficiency and fairness of corporate taxation. It emphasizes the need for balanced tax policies that stimulate entrepreneurship, attract foreign investment, and support sustainable economic growth while maintaining fiscal stability. Overall, the paper provides a valuable overview of corporate tax developments in the V4 countries and contributes to the broader discussion on tax competitiveness and harmonization within the European Union. Its conclusions and recommendations may serve as a useful resource for policymakers, economists, and legislators engaged in shaping future fiscal strategies.

: Household financial stability is a fundamental pillar of overall economic well-being, especially during periods of uncertainty and crisis. Maintaining adequate precautionary wealth not only mitigates financial stress but also fosters more confident financial decision-making. Households with sufficient reserves are less dependent on credit, better protected against debt accumulation, and more capable of preserving long-term savings and investment strategies during short-term disruptions. This paper investigates the key determinants of precautionary wealth held by Slovak households. The study aims to identify and quantify the influence of wealth-related, demographic, and financial variables on the formation of precautionary wealth. We hypothesize that wealth-related factors, particularly the capacity to accumulate personal financial assets (PFA) play the dominant role. Using data from the Slovak sample of the Household Finance and Consumption Survey and employing ordinary least squares (OLS) regression, we estimate four models (full, preferred, factor, and simplified). The preferred model reveals that PFA has the strongest positive effect on precautionary wealth. Together, PFA and income account for over 56% of the total explained variance. Among financial indicators, ECB policy rates show a positive association, while real deposit rates have a negative effect, suggesting behavioral biases in household responses. Demographic variables, such as age, gender, and education, play a comparatively smaller role. The findings emphasize the dominant role of wealth-related and financial variables in precautionary wealth accumulation.

The main aim of this paper is to determine whether the analysed groups of family business units differ significantly in their financial indicators. We examined a selected sample of family businesses based on data from their financial statements for the period 2020–2022, obtained from the Albertina database. Our analysis included almost 500 family companies in the Czech Republic that provided data to Albertina for all three years under review. Family companies were identified according to typical approaches to family business financing in the Czech Republic. The monitored indicators include debt ratio, return on equity (ROE), and personnel costs as a percentage of total costs.
The cluster analysis identified three clusters of family firms. Each cluster was described according to reported accounting data, size, and sector of the main activity of the grouped enterprises. It is evident that family businesses listed in the Czech family business register are micro, small, and medium-sized enterprises; large businesses are not included in the register. The highest representation is in the manufacturing industry, mainly metal processing, which applies to all three clusters. In the cluster analysis, we focused on centroids (typical average companies in the cluster), which represent typical approaches to corporate financing. The approach of family firms to debt financing is crucial, as most firms are risk-averse and primarily use their own capital for financing.

This article examines the growing role of artificial intelligence (AI) in accounting auditing, the opportunities it presents, methodologies, and challenges encountered from an academic perspective. With the proliferation of Industry 4.0 and big data, sampling-based approaches used in traditional auditing are becoming insufficient, creating a need to analyze the entire data universe. In this context, AI provides auditors with unprecedented capabilities to detect fraud, errors, and irregularities within large data sets, forming the basis of the “Audit 4.0” paradigm. The article addresses the three main areas of AI application in auditing—process automation, risk assessment, and decision support systems—within a theoretical framework. Anomaly detection-focused unsupervised learning methodologies, particularly clustering analysis and deep learning-based autoencoder architectures, are examined at a technical level. However, the practical application of AI also brings significant challenges, such as data imbalance, the interpretability of complex models (the “black box” problem), and potential biases in algorithms. As solutions to these challenges, Explainable Artificial Intelligence (XAI) techniques and the concept of “Trustworthy Artificial Intelligence” are discussed. In conclusion, it is emphasized that AI is not a technology that eliminates the auditor, but rather an “augmented intelligence” tool that enhances their capabilities. It is noted that the auditor's role is transforming from manual data verification to that of an expert who interprets AI models and oversees algorithmic systems. This transformation will shape the future of the auditing profession.

Developed dairy farms face increasing turbulence from climate change, market volatility and rapid digitalization. While strategic analysis is widely promoted, its systematic use, and the strategic integration of smart technologies, remains limited. This qualitative pilot study, grounded in strategic management and innovation literature, explores these challenges by combining a targeted review with ten semi-structured interviews involving farmers (3), consultants (4), a veterinarian specialized in data-driven farming, a policymaker, and a professor of strategic analysis. Across this diverse group, seven interrelated barriers emerged: constrained information use, low digital readiness, behavioural resistance, weak entrepreneurial orientation, institutional uncertainty, underused advisory support and fragmented decision routines. The findings highlight a persistent gap between established strategic tools (SWOT, PESTEL, scenario planning) and their practical application: digital investments are often reactive rather than strategically embedded. The contribution lies in framing digital transformation as a strategic capability challenge, not only a technological one, and translating the barrier set into actionable levers for managers, advisors and policymakers. As a pilot, the study also sets out a research agenda for broader comparative analysis of strategy and digital adoption in agriculture, providing both immediate insights and directions for future work.

: This study investigates the predictive ability of financial and area-related ratios in forecasting future asset profitability. The predictive modelling was conducted using the Random Forest algorithm. The analysis encompassed both conventional financial ratios and their modified counterparts. Specifically, the following indicators were examined: profit-to-assets ratio, profit per hectare, sales-to-assets ratio, sales per hectare, debt-to-assets ratio, debt per hectare, fixed asset ratio, assets per hectare, and labour productivity. Empirical results indicate that profitability ratios, particularly the profit-to-assets ratio, exhibit strong predictive performance. Furthermore, area-related variants—such as profit per hectare and debt per hectare—demonstrated enhanced accuracy in certain scenarios. Nonetheless, the practical applicability of these area-related indicators is constrained by challenges related to data availability and consistency.

The agricultural sector plays a pivotal role in global economic development by ensuring food security, contributing to GDP growth, and supporting other industries through resource transfer and trade. However, it is characterized by high volatility due to climatic uncertainty, market fluctuations, and global crises such as the COVID-19 pandemic and the war in Ukraine. These events have triggered significant increases in food prices, intensifying inflationary pressures and reducing welfare, particularly in developing countries. As a result, state intervention in agriculture has regained prominence, with policymakers applying diverse protectionist and redistributive measures, such as subsidies, tax incentives, and direct payments, to stabilize markets and support producers. In the European Union, the Common Agricultural Policy (CAP) remains a cornerstone of this intervention, yet it faces criticism for inefficiency, uneven redistribution, and inadequate targeting of vulnerable groups. Empirical studies demonstrate mixed results: while some confirm the positive effects of agricultural support on productivity and poverty reduction, others reveal inefficiencies, reverse redistribution, and fiscal burdens. This review highlights the complex relationship between agricultural protection, price stability, and social welfare, emphasizing the need for targeted, evidence-based policies that balance economic efficiency, fairness, and sustainability in both developed and developing economies.

Partial agri-environmental measures and ecological management schemes should provide adequate compensation for the implementation of specific practices or ecological commitments regarding land management by business entities under EU Common Agricultural Policy. The agricultural output of such production-related enterprises is commonly achieved with reduced input consumption and lower pressure on the environment. In addition, such production of agricultural primary production enterprises may come from marginal areas that could be left without economic utilisation without financial support, including the associated potential for the provision of ecosystem services, as an additional dimension of social benefits in the framework of landscape management, and the associated potential for the development of biodiversity of the area concerned. This article aims at exploratory study of available secondary data of EU Farm Accountancy Data Network on diversity in agricultural land usage among farms in order to identify relationship between development of their economic performance  and structure of land use.

The aim of the study is to analyze the predictive capabilities of changes in working capital as an indicator of impending insolvency of companies in the Czech Republic. The research uses empirical data from the financial statements of companies that entered insolvency proceedings between 2019 and 2024 and compares them with a control sample of financially stable entities. The analysis was performed using logistic regression and additionally verified using ROC analysis. The results confirm that selected working capital indicators, in particular current liquidity and the ratio of working capital to total assets, have a significant ability to predict financial instability. The findings highlight the practical importance of effective working capital management for the early identification of insolvency risk and provide a basis for the development of early warning models in the corporate sector.
 

School catering is an important element of the public food service system and represents a stable market with high and consistent demand for food. In recent years, increasing academic and political attention has focused on the inclusion of regional food into school canteens. Such an initiatives are also linked to sustainability goals, regional economic support, and reduction of environmental impact of food system. This study investigates the relationship between school canteen size (measured by the number of meals served per day) and the share of regional food used in daily operations. A data from a survey among primary schools in Brno (Czech Republic) revealed no significant correlation between canteen size and the use of regional food in school canteens. These results contribute to understanding factors that are important for designing more sustainable food systems.