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The use of the industrial Modbus network in control and measurement systems of laboratory stations
No full textThis article presents the potential of using the Modbus TCP industrial computer network in measurement tests of electrical machines and devices used in laboratory stations. The Modbus interface is the primary communication channel for most measuring equipment for reading electrical parameters, such as current, voltage, and power, as well as mechanical parameters, such as rotational speed and torque at the shaft of the tested machine. The measurement system is designed to acquire data in steady states of the electric drive assembly, where the measured parameters indicate approximately the same value. The article presents the tasks and role of the measurement system in a modern approach to collecting and processing measurement data using intelligent communication devices
Wpływ inflacji na wzrost gospodarczy w wybranych krajach świata
Full text linkWpływ inflacji na wzrost gospodarczy jest częstym tematem badań. Obserwacje te pozwalają wyznaczyć odpowiedni poziom inflacji dla danego kraju, który maksymalizuje tempo wzrostu gospodarczego oraz czy występuje dodatnia czy ujemna zależność między tymi zmiennymi.
Celem pracy jest ustalenie zależności pomiędzy wzrostem gospodarczym a inflacją. Artykuł analizuje zależność między inflacją a wzrostem gospodarczym, koncentrując się na danych empirycznych z krajów rozwiniętych i rozwijających się w okresie ostatnich lat. Autorzy przedstawiają teoretyczne podstawy relacji inflacja–wzrost, na podstawie nowoczesnych i klasycznych modeli makroekonomicznych, odwołując się do klasycznych i nowoczesnych modeli makroekonomicznych, takich jak test przyczynowości Grangera, model Solowa czy krzywą Phillipsa. Wyniki badań wskazują, że umiarkowana inflacja nie jest niekorzystna w niektórych warunkach instytucjonalnych. Niestabilna, wysoka inflacja ma negatywny wpływ na realne dochody, wydajność i inwestycje, prowadząc do spowolnienia wzrostu gospodarczego
Inability to face unexpected expenses and monetary poverty in Poland: Are these two faces on the same coin?
No full textResearch background: The economic literature often states that monetary poverty does not coincide with other types of poverty. The paper examines monetary poverty and financial distress, which refer to distinct aspects of poverty. It addresses the issue by explaining how the same household characteristics affect these different types of poverty.
Purpose of the article: The paper aims to identify socioeconomic variables influencing financial distress and monetary poverty in Poland. In addition, the relative contribution of household-level variables in explaining McFadden’s R2 for the financial dimensions under consideration is assessed.
Methods: The study relies on data from the EU Statistics on Income and Living Conditions (EU-SILC) survey in 2022. Logistic regression analysis empirically tests the impact of socioeconomic variables on financial distress and income poverty. Moreover, the relative importance of regressors is determined using the Shapley-Owen decomposition analysis.
Findings & value added: The results have revealed that the smallest group consisted of only monetary poor households, followed by both monetary poor and financially distressed. The largest group was made up of households that experienced only financial distress. Such an incomplete overlap in experiencing the examined types of poverty implies the importance of studying financial distress alongside traditional income indicator. The study indicated a statistically significant role for characteristics such as disability, unemployment, education, the burden of the repayment of debts, household type, and tenure status in experiencing all the types of poverty considered. Furthermore, it was observed that the explanatory power of the models varied depending on the types of poverty under consideration. The results also revealed a substantial relative contribution of education to McFadden’s R2 in all models, indicating that education level substantially explains vulnerability to financial fragility. The contribution of other regressors varied among the models describing the types of poverty analyzed. These findings should stimulate policymakers, as effective policies are needed to alleviate different types of poverty
Effect of corporate sustainability performance on the changes in payout policy of the top global companies
No full textResearch background: Corporate sustainability is currently one of the most popular issues in theoretical and empirical research. It generally focuses on identifying the relationship between corporate sustainability performance (CSP) and corporate financial performance (CFP), although the CSP-CFP link is not investigated enough in the context of changes in dividend payments.
Purpose of the article: The paper aims to identify the relationship between CSP and changes in dividend payouts. To do this, a research hypothesis was formulated, stating that improving CSP in environmental, social, governance, and economic dimensions increases the propensity to pay stable dividends.
Methods: The main empirical research method is the panel logistic regression model, which includes variables of corporate sustainability. Additionally, descriptive statistics and the Pearson correlation coefficients are analyzed. The empirical research was conducted using data on the top global companies listed in the Global 500 of 2021 from the period of 2011–2021. All required data were retrieved from the Refinitiv (Thomson Reuters) Eikon database.
Findings & Value added: The main conclusion of the paper is that when all dimensions of corporate sustainability are integrated in the long run, only the strong effectiveness of corporate systems and processes inside a company make board members maintain dividends at the previous levels. It means that the research hypothesis cannot be confirmed for all corporate sustainability dimensions considered together. The value added of the paper is that the authors considered the long-term returns pillar score as one of the independent variables, which is not a commonly used approach, although economic sustainability is a key corporate sustainability dimension
Greenwashing in the context of responsible consumption and production (SDG 12): A cross-sectoral analysis of sustainability
No full textResearch background: Responsible consumption and production, articulated in Sustainable Development Goal 12 (SDG 12), has heightened global expectations for credible sustainability disclosure. Despite this, firms across sectors continue to use selective, vague, or unverifiable environmental claims that contribute to greenwashing. Although research on greenwashing has expanded, consolidated knowledge on how misrepresentation patterns vary across industries and how these practices undermine SDG 12 objectives remains limited. A clearer understanding of sector-specific disclosure behaviors is essential for strengthening accountability and supporting responsible production–consumption transitions.
Purpose of the article: This study aims to provide a cross-sectoral synthesis of greenwashing mechanisms and sustainability misrepresentation, examining how disclosure tactics differ across the manufacturing, energy, fast-moving consumer goods (FMCG), automotive, technology, and service sectors. The objective is to map these practices against SDG 12 expectations and highlight how they hinder progress toward responsible production and consumption.
Methods: Using a PRISMA-based systematic review of Scopus-indexed studies, the analysis applies thematic coding and comparative sectoral assessment to identify patterns of misrepresentation. The review integrates evidence across multiple industries to highlight differences in performance-based, claim-based, symbolic, and impression-management tactics.
Findings & value added: The results show that manufacturing and energy firms predominantly engage in performance-related sustainability misrepresentation, whereas FMCG and service firms more frequently employ claim-based, symbolic, and impression-management approaches. Across all sectors, recurring practices include overstated certifications, selective reporting, and ambiguous SDG commitments, which collectively impede transparency and weaken the achievement of SDG 12. By offering one of the first comprehensive cross-industry evaluations of greenwashing within an SDG framework, the study advances the theoretical understanding of sustainability misrepresentation and identifies sector-specific risks relevant for regulators and policymakers. It also provides actionable insights into enhancing reporting integrity and accountability aligned with SDG 12
Harnessing artificial intelligence to strengthen green innovation capacity in pursuit of sustainable development goals: Evidence from Taiwan’s manufacturing sector
No full textResearch background: Artificial Intelligence (AI) is becoming a revolutionary ability that can speed up the shift towards sustainable production through re-source efficiency, optimization of processes, and low-carbon innovations. Consistent with the United Nations Sustainable Development Goals (SDGs), SDG 9 (sustainable industrialization), SDG 12 (responsible consumption and production), and SDG 13 (climate action), AI is becoming a driver of green innovation, as well as a facilitator of the same.
Purpose of the article: This paper examines how AI applications affect organizational performance (OPE) in the Taiwanese manufacturing industry with a special emphasis on the mediating effect of GIC. Based on the Dynamic Capabilities Theory (DCT), the paper constructs and empirically validates a structural model that elucidates how AI adoption increases sustainable competitiveness through the development of innovation-oriented capabilities.
Methods: The research used a cross-sectional, quantitative study design and gathered data on 270 professionals in the Taiwanese manufacturing sectors. The AI applications, GIC, and OPE were measured using a structured questionnaire to measure them using multi-item Likert scales. Hypotheses were tested using the Partial Least Squares Structural Equation Modeling (PLS-SEM).
Findings & value added: The study shows that Artificial Intelligence (AI) adoption plays a significant role in enhancing both green innovation capabilities (GIC) and overall organizational performance (OPE). More importantly, GIC emerges as a key mechanism through which AI applications are translated into measurable sustainability outcomes, underscoring its role as a strategic bridge between digital transformation and environmental performance
Gold-backed cryptocurrencies in cryptocurrency portfolios: Evaluating their hedging capabilities and safe-haven characteristics during extreme market conditions
No full textResearch background: This paper explores the hedging and safe-haven properties of gold-backed cryptocurrencies within the context of conventional cryptocurrencies such as Bitcoin, Ethereum, Tether, and Binance. With the rise of blockchain technology, cryptocurrencies have gained recognition as alternative investment assets, drawing comparisons to traditional safe-haven assets like gold. However, the risk management potential of crypto gold, especially during periods of extreme market volatility, remains under-examined.
Purpose of the article: The purpose of this article is to assess the effectiveness of gold-backed cryptocurrencies as hedging instruments and safe havens for investors in conventional cryptocurrencies. By analyzing their tail dependence during extreme market fluctuations, the study aims to determine their risk management utility.
Methods: To achieve this, we employ a Student’s t copula structure integrated with an ARMA-GJR-GARCH model to measure the time-varying tail dependence between gold-backed and conventional cryptocurrencies. This approach allows for a comprehensive analysis of both normal and extreme market conditions. We use the Digix Gold Token (DGX) as a representative of gold-backed cryptocurrencies. The study examines four major conventional cryptocurrencies — Bitcoin (BTC), Ethereum (ETH), Tether (USDT), and Binance (BNB) — by analyzing daily closing prices from May 14, 2018, to January 31, 2023, which comprise 1702 observations. The dataset, sourced from coincodex.com, includes periods of significant market stress, such as the COVID-19 pandemic and the Russian-Ukrainian conflict.
Findings & value added: The findings reveal a weak association between gold-backed cryptocurrencies and conventional cryptocurrencies, resulting in medium-to-low hedging effectiveness during the sample period. Nevertheless, during crisis periods, a negative association is observed, indicating that gold-backed cryptocurrencies act as effective safe havens in times of market distress. The study contributes to the literature by providing empirical evidence on the risk management benefits of crypto gold, particularly during financial crises, and highlights its potential inclusion in portfolios with cryptocurrency investments to enhance resilience
Energy-agriculture market linkages: Asymmetric effects in the context of the Russia-Ukraine conflict
No full textResearch background: The study examines the impact of geopolitical tensions, in particular the Russia-Ukraine conflict, on agricultural commodity markets at a global level. The research focuses on the period from February 2021 to February 2024, a period characterized by significant economic instability due to the ongoing conflict. The research covers global agricultural commodity markets, focusing on three main categories: soft commodities, grains and livestock.
Purpose of the article: The purpose of this paper is to examine the asymmetric interactions between crude oil and gas prices and agricultural commodity yields from February 2021 to February 2024. The study aims to analyze these interactions on a global scale, encompassing the world markets for soft commodities, grains and livestock. The research aims to provide insights into how geopolitical tensions, in particular the Russia-Ukraine conflict, are affecting these global agricultural markets and their linkages to energy prices.
Methods: This study uses the Nonlinear Autoregressive Distributed Lag (NARDL) model to analyze the asymmetric interactions between crude oil and gas prices and agricultural commodity yields, capturing both short-run and long-run asymmetries. The study divides the sample period into three distinct sub-periods of the Russia-Ukraine conflict, allowing for a detailed examination of how energy price fluctuations affect agricultural commodities under different economic conditions.
Findings & value added: Our main findings are the following: (1) positive correlations with oil and gas prices for soft commodities and grains; (2) weaker but significant relationship for livestock; (3) short-term asymmetries are particularly pronounced during periods of high economic turbulence (e.g. Russia-Ukraine conflict); (4) grain and livestock yields show stronger responses to negative oil price shocks; (5) no long-run equilibrium relationship found by cointegration tests. The present paper is unique in combining the Nonlinear Autoregressive Distributed Lag (NARDL) model with a detailed analysis of the Russia-Ukraine conflict, providing unprecedented insights into the asymmetric impact of geopolitical tensions on agricultural commodity markets, which is essential for understanding market dynamics during crises
Boosting IT companies’ performance through corporate governance standards: An empirical analysis
No full textResearch background: In the process of global economic development, the Information Technology (IT) sector has acquired a vital role. Digital transformation drives economic growth, making IT support essential for the efficient functioning of any state, company, or public institution. The IT industry is not only the primary source of innovation, but has also become a key provider of security in the current geopolitical context marked by unexpected challenges. Governance in IT companies is essential to ensure alignment of technology with business objectives, risk management and regulatory compliance. It contributes to transparency, accountability and cost optimization, thereby ensuring process quality and the long-term sustainability of the organization.
Purpose of the article: The research focuses on the empirical study of the impact of corporate governance on the financial performance of the IT companies in the United States of America (US). The econometric analysis database includes 877 companies over a period of 7 years, from 2016 to 2022. This period is characterized by the mass development of emerging technologies, the increasing capabilities of artificial intelligence and adaptation to global crises—with the most relevant example being the Covid-19 pandemic. In the context of the pandemic, the need for digitalization became imperative, particularly in ensuring continuity in online education, e-commerce, and remote work. These developments underscore the growing importance of IT governance and strategic digital capabilities in shaping resilient, future-ready organizations. This study provides valuable insights into the intersection of corporate governance and organizational performance within the dynamic and rapidly evolving IT industry. By adopting an empirical approach, it goes beyond theoretical models to offer evidence-based analysis on how governance structures and standards can enhance operational efficiency, financial results, and strategic resilience.
Methods: There are estimated multiple linear regression models using unbalanced panel data, with pooled OLS, cross-section random effects, cross-section fixed effects, cross-section, and time fixed effects. The dependent variables are represented by return on assets and return on equity, the independent variables capture the characteristics of the board of directors, while company-specific indicators are used as control variables. For each dependent variable, 24 econometrical models were performed.
Findings & value added: The main findings of the research disclose a positive influence of the remuneration and audit committees, board independence, board gender diversity, liquidity, and company size, while board meetings frequency and indebtedness have a negative impact on the financial performance of the IT companies. The added value of this study lies in its interdisciplinary approach, combining principles of corporate governance with performance metrics specific to the digital economy. The findings have practical implications for executives, investors, and policymakers aiming to foster transparency, accountability, and innovation within technology
Digital revolution meets ESG: Can AI, blockchain and cloud computing enhance ESG performance?
No full textResearch background: In today’s digital age, traditional environmental, social, and governance (ESG) development paths are gradually facing challenges, including from digital technologies. In particular, the potential roles of artificial intelligence (AI), cloud computing (CC), and blockchain (BC) in the ESG market have not been fully explored.
Purpose of the article: This study explores the deep integration of digital technology and ESG by evaluating the correlation and spillover effects among AI, CC, BC, and eight global ESG indices.
Methods: This study explores the spillovers between AI, CC, BC, and eight global ESG indices by cross-quantilogram and quantile time-frequency connectedness approaches.
Findings & value addition: The lower quantile of ESG returns has a weak positive (strong negative) correlation with the lower (upper) quantile of digital technology. Next, the spillover effects vary with time, frequency, and quantile levels. Meanwhile, the North America and Asia-Pacific developed ESG indices serve as the transmitter and receiver of spillover effects, respectively. Furthermore, the dependence between digital technology and ESG returns is insignificant before the COVID-19 crisis but increases after it. This quantile-dependent asymmetry fundamentally challenges linear assumptions prevalent in current ESG-technology integration theories. Overall, this study contributes by integrating AI, CC, BC, and ESG into a unified framework, and analyzing their interaction mechanisms. Furthermore, it dynamically analyzes the asymmetry over long and short-term horizons, and highlights the hedging role of digital technology in stabilizing ESG markets. Moreover, we provide novel insights about the interconnectedness between these markets, offering valuable guidance on risk management. Consequently, regulators should urgently explore the development of digital asset-based ESG derivatives as targeted risk mitigation tools. Positioned at the cutting-edge, this work sets a methodological benchmark for analyzing non-linear, frequency-sensitive interdependencies within the rapidly evolving ESG-digital nexus, transforming the theoretical framework from static linearities to dynamic non-linearities. Finally, this study proposes some reasonable suggestions, including raising risk awareness, promoting digital transformation, building integration and innovation platforms, and leveraging ESG’s diffusion role