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Digital transformation of the energy industry: Use of digitalisation and modern technologies in customer service systems as exampled by Tauron Polska Energia S.A.
No full textThis article presents the role of digitalization and modern technologies, including artificial intelligence, in customer service in the energy sector, using the example of TAURON Polska Energia S.A. The theoretical section discusses the relationship between digitalization, digitization, and digital transformation, and highlights the importance of AI tools such as chatbots, RPA, and recommendation systems. The empirical section presents TAURON\u27s activities, including the development of self-service services, a mobile application, digital notifications, e-invoices, and e-contracts using blockchain, the digitization of connection processes, the expansion of ICT infrastructure, and "barrier-free" initiatives. The analysis shows that digitalization increases the efficiency and accessibility of services, but also poses organizational and social challenges
Customs duties and common customs tariff as an instrument for the protection of the European Union internal Market: An economic and financial dimension
No full textCustoms duties and common tariffs remain a traditional instrument for protecting the European Union (EU) common market. The customs tariff embraces the customs nomenclature (a systematised list of goods) with the applicable duty rates, on the basis of which the duty payable on imports into the European Union is calculated. The customs tariff and the customs duties it contains not only have a protective function, but also possess an economic and fiscal dimension, as they ensure the EU budget revenue. The main objective of this study is to show the role played by customs duties and tariffs in the protection of the internal market and EU producers, including the economic and fiscal dimension of these market protection tariff instruments. The specific objective is to verify the research hypothesis that the role of customs duties and the common customs tariff in the protection of the EU common market is decreasing. The analysis of the level, types and changes of customs duties in the EU customs tariff confirmed the research hypothesis that customs duties generally no longer play a major role in the protection of the internal market. For more than twenty years, they showed a downward trend, starting in the mid-1990s. However, for some goods, mainly agricultural ones (dairy products, sugar and confectionery, cereals), but also textiles, clothing and motor vehicles, customs duties are still a barrier to access to the EU market, so they perform an important protective function and have a significant fiscal dimension. The study relies on traditional research methods: deductive reasoning and comparative analysis. For the purpose of the analysis, various sources were used, such as domestic and foreign literature, legal acts of the EU secondary legislation in the form of regulations, statistical data of the Eurostat, the World Trade Organization and the World Bank
Automation of work supervision as an element of ensuring safety of heating material transfer for a selected heating station
No full textThe paper addresses the issue of pipeline transport safety using the example of automation of the supervision of the operation of a selected heating plant. Presents in it the process of automatic control and supervision of the operation of a heat exchanger substation. Initially operated by humans, these substations have transformed into fully automated devices, the operation of which is managed by SCADA master systems. An analysis of the correctness of the operation of the heat substation was carried out using remote supervision systems, which offer a number of functionalities allowing remote control of the most important parameters of the heat transfer process to the end user. The benefits resulting from the appearance of automatic supervision and regulation devices in heat substations were presented, as well as the possibilities of using IT systems for remote analysis of the correctness of the course of the substation operation control process
The influence of natural environment on the operation of selected elements of fire signalling systems - limiting the number of false alarms
No full textThis paper presents the influence of selected natural environment parameters, i.e. temperature, relative humidity, electromagnetic interference and pressure on the operation of detectors used in fire signalling systems (FSS). Continuous diagnostics of environmental parameters, in particular their changes over time, may contributed to the lower numbers of false alarms in FSSs. Thus, development of an operating procedure for such elements in the continuously changing environment is an important functional issue related to operation of selected FSS detectors. Fire detector sensors detect various characteristic parameters of fire (CPF), such as smoke, temperature or electromagnetic radiation. The values of CPF depend on the changing environmental parameters - rooms, traffic routes, warehouses, etc. where detectors reacting to various test fires TF1 to TF9 are present
Design of application for vehicle classification with queue detection using deep learning
No full textThe aim of the study was to create a solution that would enable the detection of a queue of vehicles before an intersection with traffic lights in the Matlab programming environment. The work focuses on designing an application for detecting a queue of cars, using the YOLO algorithm and developing a mechanism for changing lights based on the detected queue. The solution presented in the paper can be applied in practice and contribute to increasing safety, traffic flow and efficiency of urban traffic management
Zielone finansowanie w gminie
Full text linkW artykule omówiono ideę zielonego finansowania oraz oceniono jego zastosowanie na poziomie lokalnym na przykładzie Gminy Góra Kalwaria i Gminy Piaseczno. Przedstawiono definicje, instrumenty oraz rolę samorządów w transformacji energetycznej. Część empiryczna oparta została na analizie inwestycji środowiskowych finansowanych z funduszy krajowych i lokalnych. Studium przypadku ukazało różnice i podobieństwa w podejściu obu gmin do zielonego finansowania
AI governance in higher education: A meta-analytic thematic review of current research trends, policy initiatives and knowledge gaps
No full textResearch background: Artificial Intelligence (AI) is rapidly transforming higher education, presenting both opportunities and challenges for institutions. AI improves education through personalized learning, adaptive assessments, virtual tutoring, and generative support. However, these advancements also bring challenges that require vigilant governance to uphold academic integrity and ethical standards.
Purpose of the article: Given the complexities and potential impacts of AI in higher education, this study aims to provide a thematic review by synthesizing the available literature to shed light on research trends, initiatives, and knowledge gaps in AI governance. The literature also explores the background of AI integration into higher education, focusing on its applications, benefits, challenges, and implications for students, educators, and institutions.
Methods: This study followed PRISMA guidelines and used the Scopus database for data collection. After rigorous screening, 142 papers were selected for the final review. The bibliometric analysis was conducted using the R Studio Bibliometrix package, which generates various indicators like publication trends, author collaborations, keyword co-occurrences, and citation patterns. This approach offers a different perspective on data representation and analysis compared to VOSviewer.
Findings & value added: The study highlights that AI governance in higher education involves establishing guidelines, data protection, and privacy policies. Institutions like Swansea University and government agencies like the European Commission and the US Department of Commerce are adopting ethical frameworks to guide AI development and reserving funds for AI governance research. The research concluded that governments worldwide had recognized the need for AI integration in academic research and higher education for sustainable growth and had implemented comprehensive regulations
Towards sustainable labour market: Spatial analysis of the differences in the employment of women and men across the EU regions
No full textResearch background: Reducing the gender employment gap (GEG) is a key challenge in the context of achieving the Sustainable Development Goals (SDGs), particularly in the area of decent work and equal opportunities (SDG8, decent work and economic growth and SDG5, gender equality). This multidimensional problem plays a critical role in regional policy, which is reflected in the legislative and executive measures taken at the level of the European Union (EU).
Purpose of the article: The aim of this article is to analyse the relationship between the employment gap and selected socio-economic factors in the regions of the EU at NUTS 2 level, with a particular focus on spatial interactions. This is particularly important for regional policy and the creation of a sustainable labour market.
Methods: The analysis is based on aggregated Eurostat data at NUTS 2 level. The statistical and spatial econometric tools used for the empirical part are the spatial correlation coefficients of Moran’s I and Geary’s C, local Moran’s I, and two spatial econometric models (Spatial Durbin Model, SDM, and Spatial Durbin Error Model, SDEM).
Findings & value added: Using spatial regression models, the study identifies key labour market factors affecting GEG. A higher share of part-time workers and longer working hours per employee are linked to increased GEG, while a greater share of women with higher education and a higher old-age dependency ratio (ODR) correlate with a reduction in this gap. In turn, industrialisation impacts GEG indirectly, influencing neighbouring regions. These findings highlight the systemic nature of the GEG, emphasising its economic, educational, and demographic drivers. The study underscores the need for regionally coordinated policies to address gender disparities in the labour market and support the achievement of the sustainable development goals (SDG4, SDG5, SDG8)
The impact of significant macroeconomic turbulence on corporate debt levels: A case study of Visegrad Group countries during COVID-19 pandemic
No full textResearch background: Macroeconomic volatility leads to increased corporate indebtedness, ultimately undermining the broader economic environment and firms’ competitiveness across all industries. The COVID-19 pandemic, among all recent disruptions, was a profound systemic shock with enduring effects on the economy, offering a valuable case study for analysing its wide-ranging impact on corporate financial stability. The pandemic’s spread significantly influenced corporate debt levels, and while this was a common issue for the corporate sector, its impact on financial performance varied considerably across industries.
Purpose of the article: The consequences of the pandemic are evident from various perspectives, and it is essential to monitor and evaluate the changes caused by the COVID-19 pandemic, not only for immediate understanding but also for their long-term and universal implications on economic and social systems worldwide. The main intention of this study is to describe and quantify the impact of the COVID-19 pandemic, examine changes in the growth of critical determinants and identify new trends in enterprises operating in Visegrad Group countries, providing insights that may be valuable for broader contexts and future crises.
Methods: Friedman test results indicate a principal distinction between groups but do not identify which pairs of groups differ. However, as the monitored indebtedness indicators exhibit significant differences, we employ the Bonferroni correction to determine which monitored periods had the largest disparities in the individual indicators. This study employs panel data from 12816 firms from Visegrad Group countries covering 2018–2022.
Findings & value added: This study provides a detailed and subtle explanation of corporate debt dynamics during the pandemic years, revealing considerable differences beyond direct effects. Based on the most recently available financial data, we present valuable long-term insights concerning enterprises’ resilience and flexibility and enrich the theoretical knowledge concerning financial stability under crisis. Moreover, the findings offer actionable advice for business leaders and policymakers seeking to enhance corporate debt management and economic competitiveness in a globalising and turbulent world. These findings are of worldwide applicability and will undoubtedly remain so for practice and scholarship in the forthcoming few years
How industrial robots affect energy intensity: Empirical evidence from Chinese firms
No full textResearch background: While prior research has examined multiple determinants of energy intensity (EI), firm-level impacts of industrial robots (IR) remain under-explored. As IR technologies witness exponential growth, not only in China but across advanced and emerging economies, their potential to reshape production efficiency and energy consumption patterns at the firm level is increasingly critical. This study addresses a global policy and scholarly imperative: understanding how automation interacts with environmental performance amid accelerating climate goals. Given China’s dual commitment to carbon neutrality by 2060 and its status as the world’s largest IR market, this context offers unique empirical research—the findings have broad relevance for countries navigating digital transformation and decarbonization simultaneously.
Purpose of the article: This study aims to dissect the direct, indirect, and non-linear impacts of IR adoption on firm-level EI using a sample of 1,286 listed manufacturing enterprises in China from 2011–2022.
Methods: The empirical strategy integrates fixed effects to control for time-invariant firm heterogeneity and year-specific shocks, and panel quantile regression to capture distributional heterogeneity.
Findings & value added: Findings show IR adoption significantly reduces firm-level EI, with IR’s squared term exhibiting a threshold effect: EI declines substantially only after IR reaches a developmental threshold. Environmental regulations moderate this relationship, diminishing and even reversing IR’s effect to positive. Panel quantile regression results show these effects are significant mainly at medium-high EI levels, absent at low levels. Heterogeneity analysis further indicates that threshold and moderating effects are pronounced in high-energy-consuming and state-owned firms at medium-high EI, but nonexistent in low-energy-consuming and non-state-owned firms. This study advances the theoretical understanding of technology-environment interactions by demonstrating that the energy-saving potential of automation is conditional on scale, institutional context, and baseline energy use—offering a universal framework applicable beyond China to inform sustainable industrial policy and corporate investment strategies worldwide