Alla Polyanska

Purpose. The purpose of this study is to examine the structure of the energy mix as a prerequisite for diversifying energy resources, which determines the resilience of the energy system to external shocks and shapes its internal energy supply potential, and to assess this structure empirically through a comparative analysis of Ukraine and Poland. Methodology. The assessment of energy mix diversification and resilience is based on the integrated application of entropy-based and concentration-based indices, which are widely used in contemporary energy system studies. Shannon entropy is employed to evaluate the degree of structural diversity and balance of the energy mix, reflecting the level of dependence on dominant energy sources. An increase in entropy values indicates a reduction in concentration risks and an improvement in the structural resilience of the energy mix under energy transition conditions. The Herfindahl–Hirschman Index (HHI) is applied as a complementary indicator to validate and interpret the results of the entropy analysis. The consistent dynamics of increasing Shannon entropy and decreasing HHI values confirm a stable trend toward energy mix diversification and reduced concentration risks. Findings. Using the cases of Ukraine and Poland, the study substantiates the structural characteristics and dynamics of the energy mix over the period 2013–2024. The analysis identifies key trends in energy supply transformation and highlights critical turning points that significantly influenced structural changes in the energy mix. The main constraints and drivers of energy resource diversification that determine the resilience of the energy mix under energy transition conditions are identified, providing an analytical basis for energy policy design and managerial decision-making. Originality. The proposed analytical framework, combining Shannon entropy with the Herfindahl–Hirschman concentration index, enables a systematic assessment not only of the structure and evolution of the energy mix but also of the risks associated with excessive reliance on dominant energy sources, accounting for their advantages and limitations. Practical value. The study identifies key directions for energy policy transformation in Ukraine and Poland during 2013–2024, and substantiates the effectiveness of energy resource diversification in enhancing the resilience of the energy mix. The results may support strategic planning and evidence-based management in the energy sector.

Purpose: This paper aims to investigate the evolving residential preferences of Generation Z (Gen Z) consumers in the context of global urban transformations and socio-economic uncertainty. This study examines the role of rational and behavioural considerations in shaping preferences for traditional, sustainable, digital and smart housing attributes and explores whether these preferences differ between Gen Z consumers in Ukraine and Poland. Design/methodology/approach: This study integrates a literature review of residential preferences, behavioural economics, sustainable housing and smart-home technologies with an empirical survey of residential real estate consumers in Ukraine and Poland. Exploratory factor analysis was applied to identify the latent dimensions of residential preferences; Cronbach’s alpha was used to assess their internal consistency; and comparative statistical analysis was conducted to examine cross-country differences. The empirical findings were subsequently translated into a conceptual design of a smart and sustainable apartment, linking identified consumer preferences with relevant residential design solutions. Findings: The results of this study indicate that Gen Z residential preferences are predominantly associated with rational considerations, particularly safety, comfort, housing quality, family-oriented functionality, energy efficiency and digitalisation, while smart and sustainable technologies complement rather than replace traditional housing attributes. Importantly, no statistically significant differences were identified between Ukrainian and Polish respondents across any of the four latent dimensions. Despite substantial differences in the current socio-economic, institutional and security contexts of the two countries, this convergence suggests that common generational values may contribute substantially to residential preferences alongside country-specific conditions. Practical implications: The findings of this study provide practical guidance for developers, architects, urban planners and policymakers by indicating that smart and sustainable housing solutions should be integrated with fundamental residential attributes such as safety, comfort, functionality and housing quality. Energy-efficient technologies, digital systems, environmental monitoring and smart-home solutions should, therefore, be designed and communicated through their practical contribution to everyday residential needs rather than technological novelty alone. The proposed apartment concept illustrates how empirically identified Gen Z preferences can be translated into user-centred sustainable residential design. Originality/value: This study contributes to residential consumer behaviour research by integrating behavioural interpretation with traditional, sustainable, digital and smart-housing preferences and by examining their cross-country convergence among Gen Z consumers. The absence of statistically significant differences between the Ukrainian and Polish samples provides initial empirical support for an emerging supranational model of Gen Z residential preferences, in which shared generational values may transcend national differences. Rather than claiming universal applicability, this study introduces this model as an empirically grounded concept requiring further validation across larger samples and a broader range of national contexts.

The article explores the evolution of energy transition research through a bibliometric co-occurrence analysis of author keywords extracted from 146 scientific publications. The analysis reveals a shift from the technical aspects of energy systems and traditional decision-support approaches (2014–2018) towards climate change, decarbonization, renewable energy, investments, and energy policy (2018–2021). Recent studies (2022–2024) increasingly emphasize renewable energy, sustainable development, and intelligent decision-support systems, reflecting the growing digitalization of energy systems and the transition towards intelligent energy management. Based on these findings, the study develops a Digital-Twin-Oriented Techno-Economic Decision-Support Framework (DTOTEDSF) for optimizing and managing carbon-reduction strategies under dynamic energy transition conditions. Rather than representing a fully implemented digital twin (DT), the proposed framework constitutes the analytical foundation for its future development. It integrates techno-economic modeling, optimization, scenario analysis, and sensitivity assessment into a unified decision-support methodology. To demonstrate its practical applicability, the framework was applied to four industrial CCS case studies in the cement sector using publicly available technical and economic data. Its analytical core combines technical, economic, and optimization models to evaluate CCS performance under alternative operating conditions. Consequently, the proposed framework provides a methodological basis for the future implementation of fully operational DTs and contributes to the development of intelligent decision-support tools for industrial decarbonization and the sustainable energy transition.

Recent studies indicate that regional disparities and differences in policy effectiveness have increased the importance of behavioural factors, including awareness, social norms, motivation, and cultural practices, in shaping energy transition outcomes. This study adopts an interdisciplinary framework that integrates behavioural, socio-technical, and regional development perspectives to explain household energy consumption behaviour and to translate behavioural evidence into policy recommendations. The study aims to identify and empirically assess the profiles of household energy consumption behaviour during the energy transition, examine how these profiles shape behavioural patterns, and develop differentiated policy recommendations. The empirical analysis is based on a survey of 997 household representatives from different regions of Ukraine. Exploratory factor analysis was applied to identify the main behavioural dimensions, K-means cluster analysis was used to classify respondents into behavioural profiles, and Pearson’s χ² test was employed to examine the association between categorical characteristics and cluster membership. The findings reveal three distinct behavioural clusters characterized by different levels of awareness, engagement, and readiness to adopt energy-efficient practices. The identified clusters represent individual-level behavioural profiles rather than territorial categories. Although the region of residence was significantly associated with cluster membership, regional characteristics should be interpreted as associated with the socio-economic, climatic, and infrastructural context in which different behavioural profiles emerge rather than determining individual behaviour directly. The findings provide evidence for integrating behavioural segmentation with regional characteristics when designing energy efficiency and demand-side management policies, thereby supporting more targeted and effective energy transition strategies in Ukraine.

The article explores the evolution of research on the energy transition through a biblio-metric co-occurrence analysis of author keywords extracted from 146 scientific publica-tions. Rather than analysing publication content directly, the study examines the rela-tionships among keywords related to the energy transition and intelligent deci-sion-support technologies. Recent research (2022-2024) increasingly focuses on renewable energy, sustainable development, and intelligent systems, which reflects the shift towards the digitalization of energy systems and the growing importance of sustainable develop-ment. Between 2018 and 2021, research shifted toward a broader understanding of the en-ergy transition, emphasizing climate change, decarbonization, renewable energy, invest-ments, and energy policy within the context of sustainable development. In contrast, pre-vious studies (2014-2018) have mainly focused on the technical aspects of energy systems and traditional decision-support approaches. The study focuses on demonstrating the outcomes of such evolution and considers the decision-making process for building an methodological concept integrated with expert systems to optimize and manage car-bon-reduction strategies under dynamic energy transition conditions. In this study, the concept of a DT is considered as a methodological direction for extending the capabilities of modern expert systems rather than as a fully implemented digital twin. Accordingly, an algorithmic model of an expert system is proposed, in which the analytical core is based on engineering (η), economic (F), and optimization models that are consistent with the digital twin concept. Particular emphasis is placed on the economic module, which ena-bles the assessment of the economic value of CO₂ capture, break-even carbon price, mini-mum functional point, optimal operating conditions, and the sensitivity of results to key economic parameters. The proposed approach contributes to the development of intelli-gent tools to support decarbonization and the transition to sustainable energy supply.

The study focuses on models of environmentally oriented development to support decision-making in business ecosystems (BE). The goal is to show the relationship between technical greening measures and BE performance results. The study's stages include the characteristics of BE; evaluation of greening measures and their impact on functioning; construction of factor-analysis models of technical greening and BE efficiency; determination of validation criteria based on elasticity indicators; and justification of the feasibility of the proposed methodology for decision support in BE. The methodology is based on the conceptualisation of BE, the construction of “input-output” models, the calculation of the integral indices ITGI and IBEEEI, factor/regression analysis, and elasticity assessment (point and arc). For an energy company, the most significant ITGI parameters are the share of new equipment with reduced noise and lower water discharge. The results of BE greening depend significantly on environmental costs and payments to support the ecobalance. The average annual growth rate of ITGI exceeds that of IBEEEI, indicating a lag between implementation and results; the nonlinear nature of the relationship is confirmed. The arc elasticity index indicates a moderate average sensitivity of IBEEEI to changes in ITGI, while the point elasticities reflect greater volatility in response to shocks. The study confirmed the presence of a measurable, but lagging and nonlinear relationship between technical greening and the results of greening the business ecosystem. This makes the constructed models an effective tool for supporting management decisions in sustainable development. The practical value lies in the proposed methodology for assessing internal drivers of business ecosystem efficiency in alignment with external challenges, enabling the systematic evaluation of environmental initiatives, their effectiveness, and their integration into digital decision-support systems for monitoring sustainable transformations.

The article focuses on the changing paradigm that the energy transition is increasingly shifting from a purely technological domain toward a socio-political and behavioral process shaped by regional disparities and social conditions. Recent studies indicate that regional disparities and differences in policy effectiveness have increased the importance of behavioral factors, including awareness, social norms, motivation, and cultural practices, in shaping energy transition outcomes. This study is grounded in an interdisciplinary framework combining behavioral theories, socio-technical transition approaches, and regional development concepts. It aims to investigate the role of consumer behavior in shaping energy transition outcomes, with a particular focus on regional and educational factors. An empirical survey of 997 respondents across different regions of Ukraine was conducted. Using cluster analysis, three distinct groups were identified, reflecting different levels of awareness and engagement with energy transition issues. Factor analysis revealed that region and education are the most significant determinants of cluster formation. The results confirm that behavioral patterns are strongly influenced by socio-regional characteristics and cannot be explained solely by traditional energy indicators. Based on these findings, the study validates the need for region-sensitive energy policies and provides recommendations for designing targeted interventions that account for regional context and educational level to enhance the effectiveness of energy transition strategies.

Modification of the properties of caking coals through the methods of their treatment is of practical interest, especially in the context of deterioration of the raw material source for coke production and high requirements for the quality of coke. Considering the hydrophobicity of coals and their relatively high porosity, vapor treatment can be an effective method of influencing coal properties. Research on the properties of coal treated with water vapor and crude benzene vapor was conducted using different caking ability methods. Coal moistened to 10%wt. was also investigated for comparison. Four coal samples with varying degrees of coalification, ranging from medium to high rank (R_o = 0.76–1.50%) and characterized by volatile matter (V^daf = 20.24–37.42%), were investigated. The mechanisms of interaction between coals and water in liquid and vapor form were determined. The results demonstrate that the treatment with water vapor and crude benzene significantly affects the properties of coal A. Specifically, under the influence of water vapor, there is a decrease in the period before the formation of plasticity and an increase in the caking properties of coal A. Coal B and C have good caking ability, so the effect of treatment is less noticeable. The treatment of the coal D leads to an increase in the viscosity of the plastic mass and a decrease in the caking properties. The approaches used in the study of the impact on coal properties can be effectively implemented in production conditions.

У статті розглянуто поняття енергоефективності як інструменту забезпечення енергетичного переходу. Узагальнено та систематизовано підходи міжнародних організацій до трактування поняття «енергоефективність», що дало змогу виявити концептуальні відмінності між інтерпретаціями визначень. Сформовано узагальнене визначення енергетичної ефективності, яке відображає комплексний, вимірюваний та міждисциплінарний характер даного поняття. Для дослідження динаміки та трансформації наукової активності у сфері енергетичної ефективності здійснено бібліометричне дослідження наукових публікацій, представлених у базі Scopus. Використання спеціалізованого програмного забезпечення VOSviewer дало змогу виокремити ключові наукові кластери та актуальні напрями розвитку досліджень, а також проаналізувати структуру міжнародної наукової кооперації у зазначеній тематиці.