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Wired for stability: The role of infrastructure and Fintech in migrant employment
No full textResearch background: Migration has become a pivotal factor in Slovakia\u27s economic and social environment, particularly as the country faces labor shortages and an aging workforce. Ensuring employment stability for migrant workers is essential for sustaining economic productivity and addressing demographic challenges. Investments in infrastructure and fintech-based remittance services are increasingly seen as crucial in mitigating employment volatility.
Purpose of the article: This study examines the impact of investments in transportation, housing, and telecommunications infrastructure, along with fintech-based remittance services, on the employment stability of migrant workers in Slovakia. The research aims to identify strategies that promote job retention by addressing both structural and financial factors.
Methods: The study employs a panel dataset spanning 2013 to 2023, applying the System Generalized Method of Moments (GMM) estimator to mitigate endogeneity issues. Diagnostic tests, including AR(2) and Hansen tests, confirm the robustness and reliability of the model\u27s results.
Findings & value added: Results indicate that investments in transportation and housing infrastructure exert the strongest positive influence on migrant employment stability. Telecommunications infrastructure also plays a meaningful role, albeit with a smaller effect. Fintech-based remittance services further enhance financial security, reduce economic stress, and improve job retention rates. These findings highlight the significance of combining physical, digital, and financial infrastructures to foster stable employment conditions. The study integrates insights from Human Capital and Social Integration theories, providing a comprehensive framework for understanding the mechanisms that support employment stability. The research offers valuable guidance for policymakers, emphasizing the need for targeted infrastructure investments and fintech solutions to improve labor market resilience and economic integration in Slovakia and similar Central and Eastern European economies
EU decarbonization and industrial export competitiveness in a small open economy: A surprising resilience
No full textResearch background: The competitiveness of the EU and its position in international trade have declined significantly, while the massive, unprecedented decarbonization of European industry has brought another challenge. Examining the impact of strict European decarbonization on the export competitiveness of European producers is not only a necessary indicator for setting appropriate policy design, but also a useful lesson for other countries in the fight against the climate crisis through proper policies.
Purpose of the article: This study evaluates the impact of stringent decarbonization on the export competitiveness of industrial producers within a small open economy, using Slovakia as a representative case study. Specifically, the authors analyse the effects of substantial renewable energy sources (RES) financing—mediated through feed-in tariffs—and investigate the causal relationship between export dynamics and higher electricity bills.
Methods: Based on data from Eurostat (energy prices, value-added) and Prodcom (export flows), the authors examine the impact of EU decarbonization measures on the competitiveness of Slovak industrial exporters within energy-intensive industries using Error Correction Models (ECM).
Findings & value added: In their research, the authors did not confirm the negative impact of decarbonization in a small open economy on the export of energy-intensive products. Among several factors explaining the finding, the Porter Hypothesis might be a possible explanation. The authors identified imported capital (investment) goods containing innovative technologies from multinational companies as a possible dominant factor. Finally, demanding decarbonization policies might not automatically be harmful to the internal and external competitiveness of domestic companies. Innovation policies and targeted stimulation measures (incentives and foreign trade measures) can be prerequisites for maintaining export competitiveness of industrial production. These findings from Slovakia serve as a useful representative case for the design of decarbonization policies—particularly in export-oriented countries implementing feed-in tariffs to support RES—and may guide managerial decisions in companies within energy-intensive industries in the CEE region and in a broader international context
The rise of international, digital, and sustainability-driven ventures: Rethinking entrepreneurship in the global economy
No full textA new model to identify factors affecting sustainable performance of sports business: The role of technology intelligence, sustainable manufacturing, green HR management, CSR and resource management
No full textResearch background: The global movement around issues such as sustainability the offers an opportunity to create context for corporate social responsibility. On the other hand, the effective management of sports organizations necessitates a well-defined business model, with a comprehensive understanding of the value creation process being paramount for its successful implementation. By integrating critical criteria into a holistic framework, sports enterprises can systematically identify and address key factors influencing their sustainable success. This approach fosters long-term viability and resilience in the competitive sports industry by enhancing both environmental and operational efficiencies while cultivating a sustainability-oriented organizational culture.
Purpose of the article: The present study aims to investigate the impact of several factors on the sustainable performance of sports firms, including technology intelligence, sustainable manufacturing methods, green human resource management, corporate social responsibility, and waste, energy, and resource management.
Methods: A quantitative approach was adopted, utilizing a descriptive-survey methodology to examine the proposed model. The research population comprised managers and professionals within the sports industry. The minimum sample size for Partial Least Squares Structural Equation Modeling (PLS-SEM) was determined using the 10-times rule of thumb.
Findings & value added: The findings corroborated the model\u27s efficiency in assessing sustainable performance within sports businesses. Furthermore, the results demonstrated that the five aforementioned variables (technology intelligence, corporate social responsibility, sustainable manufacturing practices, green human resource management, and waste, energy, and resource management) exerted a statistically significant influence on the sustainable performance of sports enterprises. This model proposes a framework to unravel how these factors interact and influence sustainable performance of sports business, thus aiding sports businesses in optimizing their strategies for sustainable success
Immersive collaborative business process and extended reality-driven industrial metaverse technologies for economic value co-creation in 3D digital twin factories
No full textResearch background: Internet of Things devices and sensors, artificial intelligence-based digital asset trading and digital twin-based extended reality technologies, and autonomous robotic and enterprise resource planning systems can be leveraged in 3D semantic scene completion and metaverse-based commercial transactions across Internet of Things-based business environments. Distributed ledger and enterprise business technologies, shop-floor digital twin synthetic data, and 3D simulation and visualization systems configure integrated multi-physics workflows in hyper-realistic immersive industrial environments for artificial intelligence-based business value. Digital twin-based Internet of Robotic Things, robotic swarm and multi-modal machine learning algorithms (with regard to enterprise total factor productivity), and virtual and augmented reality simulation technologies are pivotal in spatial planning processes. Industrial product data and manufacturing value chain management support digital twin-based virtual factory modeling in collaborative immersive 3D visualization environments.
Purpose of the article: We show that interconnected business process management and metaverse economic organizational structures, immersive economic and entrepreneurial knowledge image-based modeling (for big data-driven product development processes), and remote autonomous equipment control and monitoring integrate digital twin-enabled 6G Tactile Industrial Internet of Things, deep reinforcement learning and image processing algorithms, and event-driven signal processing for collaborative economic value co-creation. Deep learning-based visual recognition and industrial extended reality technologies, 3D production management modeling, and Internet of Things industrial and mobile sensing networks are pivotal in production operation management, as deep learning-based multi-source data fusion assists autonomous industrial manufacturing processes across interactive 3D immersive business and synthetic manufacturing environments. Collaborative robotic cyber-physical production and generative Artificial Intelligence of Things-based systems (in terms of managerial business value), artificial intelligence-based perceptual and cognitive technologies, and spatial mapping and machine intelligence algorithms enhance manufacturing process visualization, as industrial big data sharing and interoperability are functional in 3D semantic scene completion for sustainable business and economic growth across big data-driven immersive virtual industrial manufacturing environments.
Methods: We inspected Tracxn (the Industrial Metaverse section) for the first 100 companies in terms of Tracxn score for X-corn status (i.e., Minicorn, Soonicorn, or none), total equity funding (USD), and company stage (i.e., Seed, Funding Raised, Unfunded, Public, Acquired, Acqui-Hired, and Series A, B, C, D), and identified three main topics for analysis that would lead to tangible business outcomes. We examined the performance management of shop floor virtualization: connected digital twins increase production and logistics process optimization in production environments across the industrial metaverse, facilitating photorealistic production system 3D modelling and simulation. We appraised integrated diagnostic functionalities of real-time simulation implementation for error elimination and machine parameter adjustment in immersive planned production lines by synthetic image data sets and collaborative workflows. We determined digital twin-based data synthesis operational procedures and interconnected use cases across industrial scalable infrastructures for value chain efficiency.
Findings & value added: We identified the specific integrated operational simulation functions and production tasks, key performance indicators of shop floor autonomous and value creation systems, and industrial process parameters for predictive quality and fault detection, resulting in production loss reduction by use of industrial metaverse technologies. By use of operational data with regard to the technological management of the selected companies, quantitative analysis determines how immersive collaborative business process and extended reality-driven industrial metaverse technologies lead to economic value co-creation across 3D digital twin factories and cyber-physical manufacturing enterprises. The main value added derived from our research is that cloud-based collaborative 3D visualization and neuromorphic computing systems, 6G sensing and holographic simulation technologies, and machine intelligence and environment awareness algorithms (for business performance and productivity) can be leveraged in machine vision-based defect prediction, detection, diagnosis, and management. Virtual reality space convergence and object connection operate in Internet of Things-based sensing device performance monitoring across Internet of Things-based business environments. Virtual assembly lines and manufacturing enterprises necessitate machine learning-based production forecasting techniques, 3D object detection and tracking, and industrial autonomous and cyber-physical production systems, supporting spatial computing and predictive maintenance algorithms in collaborative immersive virtual environments
Energy consumption and savings behavior under the pressure of energy security, sustainability and cleaner energy transition: The case of Romania
No full textResearch background: Romania is in a profound process of transformation of its energy sector, with sustainability, security, and alignment with the European Union standards as the main factors. The ability of consumers to make energy consumption more efficient and to improve their energy use habits is therefore a major input to strengthen the Romania and EU\u27s energy independence and fight climate change.
Purpose of the article: In this article, the authors are studying the ability of Romanian citizens to make energy consumption more efficient, and also the direct and indirect effect on their real contribution to saving energy.
Methods: The data was gathered through a questionnaire and the respondents are citizens from Romanian households. The analysis was carried out through an econometric model by applying the PLS-SEM technique. The objective was to identify and investigate the elements that impact the contribution to saving energy of Romanian citizens.
Findings & value added: The findings of the article confirm the study hypotheses crafted in the literature review section and demonstrate that the real contribution to saving energy of Romanian citizens is directly caused by various determinants, such as: being aware and informed about energy saving processes, being responsible about the energy consumption, the choice of energy provider and devices and the social/ community influence. Identifying the independent variables with relevant influence on the citizens’ contribution to saving energy could help the stakeholders within the energy sector to implement measures that could help citizens use energy more efficiently and reduce environmental impacts. Studying the independent variables that have considerable influence on the citizens’ contribution at saving energy through their ability to make energy consumption more efficient could assist the stakeholders from the energy sector to outline and improve their capabilities in meeting the needs of the energy consumers of the future
Assessment of municipal waste management in the selected EU countries
No full textThe aim of this study was to conduct an assessment of municipal waste management systems in selected European countries. Used research methods were comparative and statistical analysis. The research was conducted in May 2024.
The theoretical part contains the basics of the concept and definitions of waste management and municipal waste systems. Moreover, it provides information connected with waste management among benchmark countries in the European Union.
The empirical part of the article describes the results of the conducted research. Based on the Global Waste Index 2022, Denmark and Germany emerged as the most efficient waste management systems, with recycling rates of 35.6% and 47.8%, respectively. These countries were assigned to the first cluster of waste management systems. In contrast, Poland and the Czech Republic, with recycling rates of 26.6% and 22.0%, respectively, were categorized in the third cluster. According to Global Waste Index 2022, the best waste management systems are characterized by a high share of recycling and other beneficial waste management methods. In the second part of the study, the authors presented a graphical comparison of the Danish and Polish municipal waste management system. Denmark, with a waste market value of 139.45 million per 1 billion of population, slightly outperforming Poland’s $131 million per 1 billion.
The work concludes with a summary that includes the most important elements of the described waste management analysis and trends in the European Union. It highlights the effectiveness of policy interventions and technological advancements in optimizing waste management practices. Furthermore, an example of a research gap present in economic literature is provided. These insights deliver a data-driven foundation for policymakers to enhance sustainability strategies across Europe
How does the digital economy drive CO2 reduction in China? Evidence from a novel decomposition model and scenario analysis
No full textResearch background: Increasing CO2 emissions place considerable strain on environmental performance, whereas the digital economy, as a transformative economic paradigm, has been identified as an essential catalyst for mitigating environmental effects. However, the inherent limitations of conventional decomposition models have led previous decomposition analyses to overlook the driving effect of the digital economy on CO2 emissions.
Purpose of the article: Examining the impacts of the digital economy within the framework of CO2 emissions disaggregation and subsequently projecting the future pathways of CO2 emissions. Ultimately, the research aims to offer scientific insights and recommendations for achieving low-carbon development through digital economic support.
Methods: The actual contribution of the digital economy to CO2 emissions is assessed through a novel Generalized Divisia Index (GDI) model. Further, the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model is extended to project the CO2 trajectories across distinct scenarios.
Findings & value added: The results unveil that the digital economy plays a weaker driving force in cutting CO2 emissions. Carbon intensity and energy intensity within the digital economy show substantial potential to deliver CO2 emission abatement, especially in the provinces of eastern and western regions. The carbon factor is manifested as the main accelerator of increasing CO2 emissions. Under the low-CO2 scenario, CO2 emissions driven by the digital economy will meet the emission goals ahead of schedule, while reductions will suffer constraints in the baseline and high-CO2 scenarios. The findings provide an empirical basis and scientific reference at the factor decomposition level for the digital economy to support CO2 reduction
Renewable energy and sustainable development: Evidence from lower middle-income countries
No full textResearch background: Renewable energy (REN) is considered a crucial part of building a foundation for sustainable development (SUD) and is a solution to many environmental and social challenges that countries around the world are facing. In lower-middle-income countries (LMICs), the increasing energy demand, coupled with the pressure to mitigate environmental impacts, has created favorable conditions for transitioning to sustainable energy sources. However, this process faces numerous barriers, including limitations in financial resources, technology, and infrastructure. To overcome these challenges, it is essential to understand the role and impact of REN on various aspects of SUD in this group of countries.
Purpose of the article: This study aims to analyze the impact of REN on SUD in LMICs while examining the influence of nonrenewable energy and other socioeconomic factors.
Methods: The study employs the ordinary least squares (OLS) method, the random effects model (REM), the fixed effects model (FEM), and the generalized method of moments (GMM) estimation technique. Data for 51 LMICs were collected from the World Development Indicators (WDI) database of the World Bank and the International Energy Agency (IEA).
Findings & value added: REN contributes positively to SUD. However, in some countries, fossil fuels remain integral to economic development, as REN sources have yet to fully replace them. Furthermore, socioeconomic factors such as economic growth, education, and urbanization also affect SUD in LMICs. This finding reinforces and expands prior studies by clarifying the dual role of REN in promoting economic growth and mitigating environmental pollution among LMICs. This subject has received limited attention in the existing literature. Concurrently, this finding provides a scientific basis for policy formulation, investment orientation, and the modernization of energy systems, aimed at building long-term SUD strategies.
