Oleksandr Kubatko

This paper examines the economic relationships between oil price volatility and socially-economic development of 14 Organization of the Petroleum Exporting Countries (OPEC) using the annual panel data for the period 1990–2014 obtained from the World Bank (WB) statistical data sets. Hausman specification test has been performed to choose the method of panel data analysis, and the results were in favor of fixed effects estimation. The main findings indicate the direct relationship between economic growth and oil price volatility. The research supports the hypothesis that an increase in crude oil prices is positively related to GDP, and a 10% increase in oil prices correlates with 0.6-4% GDP improvements. Structural changes in employment in favor of service sector are negatively correlated with GDP per capita. Changes in GDP structure in favor of oil rents on 10% lead to the shrinking of GDP on 1%. Life expectancy at birth, as an indirect indicator of health, positively influences the economic growth indicators and an improvement in life expectancy on one percentage leads on average to 1% growth in GDP and 0.5-1.33% growth in GDP per capita. Energy efficiency improvements are positive drivers of GDP values at OPEC, and our findings suggest that a 10% increase at GDP per unit of energy use leads to 3% increase of GDP itself. The study recommends investing in energy efficiency, human capital, and capital formation to guarantee long-run economic development and prosperity of OPEC counties.

The development of human civilization is related to the constant change of economic formations, and the current social and economic situation is determined by such concepts as Society 5.0, Fourth, and Fifth Industrial Revolutions (FIR, FiIR). The paper aims to estimate the change of human role in each economic formation caused by industrial revolutions. A structured review methodology with a focus on biological, labor, and personal entity of human within the industrial revolutions is used. The description of the changes between the biological, labor, and personality entities of human in various socio-economic formations is discussed. The human as a biological entity is not changed in the first four industrial revolutions, while the FiIR tries to change the biological entity through augmenting the physical capacity. The human as a labor entity is not changed in the first three industrial formations, while the FIR tries to replace the majority of physical human jobs and opens the gate for creative economy and decisions-making. The direct labor participation is minimized within FIR since the economic systems move to the transition to the dominant role of cyber-physical systems. The personal human development is triggered within the FiIR, since informational diversity in economic systems is actualized, and conditions for creative jobs within the creative economy are formed. The biological, labor, and personality entities of human are sequentially actualized within the economic formation caused by industrial revolutions.

The study’s relevance relates to the transformation of the human capital reproduction during the transition to a new socio-economic model and changes (digitalization, cyberization, customization, etc.) that are now taking place within Industries 4.0 and 5.0. The purpose of the study is to formulate the content and key directions of learning processes based on modeling and the formation of digital twins for the production and consumption of goods. The research method is based on the analysis of structural links in socio-economic systems, where the potential of human capital is realized. The study describes a trialectic model for the system development mechanism, which gives grounds to distinguish three types of essential components of implementing the specialists’ competencies (material, information, and communication). Based on the concept of “system of systems”, the necessity of multifunctional training of specialists for socio-economic systems is substantiated and shown on the list of personal knowledge/skills in the renewable energy sector. Recent trends in the reproduction of human capital, such as intellectualization, increased communication, internationalization, acquisition of skills, customization, and communication with consumers, are stated in line with Industries 4.0 and 5.0. The potential for future research is aimed at harmonizing relations between humans and cyber-physical systems, motivating the needs for self-development, and using disruptive technologies in the reproduction of human capital.

Acknowledgment
The publication contains the results of research of the European Commission grants “Jean Monnet Chair in EU Economic Policies and Civil Society” (619878-EPP-1-2020-1-UA-EPPJMO-CHAIR) and EU legislative, economic and social transition to sustainable society within Industry 4.0 and 5.0 (619997-EPP-1-2020-1-UA-EPPJMO-CHAIR).
The paper is prepared within the scientific research projects “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy” (No. 0121U100470) and “Fundamentals of the phase transition to the additive economy: from disruptive technologies to institutional socialization of decisions” No. 0121U109557), funded by the general fund of the state budget of Ukraine.

This paper investigates the effect of the Brexit vote on the connection between UK stock market expectations and US stock market returns. To gauge UK stock market expectations, the option-implied volatilities of the FTSE 100 index are calculated in the period starting five months before and ending four months after the Brexit referendum. To keep the analysis “clean”, it stops right before the 2016 US presidential elections. It uses an OLS regression to estimate the change in the relationship between US and UK stock market expectations.
The main findings show that the US and UK stock markets became somewhat less integrated four months after the Brexit referendum compared to the five months before it. The S&P 500 Index returns have a statistically significant impact on implied volatilities of the FTSE 100 only before the Brexit referendum. However, the British risk-free rate (LIBOR) became a statistically significant factor affecting FTSE 100 implied volatilities only after Brexit. This analysis may be used by decision-makers in the money management industry to act appropriately during Black Swan events. When UK citizens unexpectedly voted in favor of Brexit, the risk-free rate dropped, making it cheaper to invest, increasing the Sharpe ratios of equity portfolios. Coupled with increased uncertainty, this caused portfolio reallocations. In turn, expected volatility measured by options-implied volatility increased.

Acknowledgment
The authors would like to thank Olesia Verchenko for critique, a KSE M.A., external defense reviewer for helpful comments.

Digitalization, dematerialization of production and consumption, and structural shifts in the direction of service economy forming do promote to reduction of material use and sustainable development. The paper aims to investigate the role of digital, structural, economic, and social factors in sustainable development promotion in OECD countries. The paper uses the data on digital achievements, social and economic development of OECD member states from World Bank data sources for the period 2007–2018. The random-effects GLS regression model is used, and empirical regression models to estimate the influence of key factors related to digital transformation on GDP per capita and CO2 emissions per capita are constructed. The results of the regression analysis show that using the number of Internet users as an indicator for achievement in digitalization has a positive and statistically significant influence on GDP per capita due to lower transaction costs and higher share service economy. An increase in urbanization rates (as an indicator of capital concentrations and labor specialization) by one percent promotes a GDP per capita increase of 299 USD. Also, an increase in Gini coefficient by one percentage point correlates with decrease in GDP per capita on 196 USD and the reduction of CO2 per capita by 0.12 tones due to the structural shifts in aggregate demand. Still, improvements in digital transformations have no significant environmental effect in OECD members, while processes related to urbanization, income inequality, and share of industrial output are important drivers for CO2 per capita reduction.

Acknowledgments
The paper contains the results of a study conducted within the framework of research projects: “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy” (No. 0121U100470); “Fundamental bases of the phase transition to an additive economy: from disruptive technologies to institutional sociologization of decisions” (No. 0121U109557).

The disruptive technologies and cyber-physical production systems are important factors that bring transformations to socio-economic formations. The paper aims to formulate the content, key directions, positive and negative effects of additive economy (AE) in the current transition phase to Industry 4.0. The research method is based on the analysis of structural links in socio-economic systems, where the additive economy potential is realized. The additive economy is treated as a new approach to production technological aspect based on the additive principle of manufacturing and aimed at minimizing the use of primary natural resources for dematerialization of social production. AE is the antithesis of the subtractive economy, which dominates today and uses only a tiny proportion of extracted natural resources. Among the positive effects of AE, there are the reduction in energy intensity of products, dematerialization of production, solidarity of society, economic systems sustainability, and intellectualization of technologies and materials. Among the negative expectations of AE, there are increased information vulnerability of production, risk of losing control over cyber-physical systems, expanding the unification of individuals, and increasing psychological stress. The additive economy is more sustainable than the subtractive economy since it does not require extra components to the production spheres, reduces the resource scarcity, and could satisfy more economic agents’ needs. Therefore, improved production efficiency due to AE promises economic growth acceleration, environmental burden and social risk reduction.

Acknowledgment
The publication was prepared in the framework of the research projects “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy” (№ 0121U100470); Fundamental bases of the phase transition to an additive economy: from disruptive technologies to institutional sociologization of decisions (No. 0121U109557).

The Covid-19 pandemic changes people’s behavior, determines the interpersonal distance of communication, and deepens the digitalization processes of public life. This paper aims to establish the social trust impact on the social sustainability of Ukrainian territorial communities in the Covid-19 pandemic. For an empirical study, four territorial communities of Ukraine were taken, which geographically represent the whole of Ukraine. It used the online survey method based on Google forms. A randomly selected 1530 respondents aged 18+ were interviewed in 2021, where the quota sampling by gender, age, and territorial community has been preserved. The study proves that the family remains the basis of social stability for Ukrainians. In difficult situations, the population expects help from their relatives and is ready to help themselves. However, institutional social trust is highly deficient, with only 5.8% of citizens wishing for help from local authorities in the face of the pandemic. The survey shows that the poorest part of the population is prone to atomization and demonstrates the lowest interpersonal and institutional trust level, weakening social stability due to the risks of numerous divorces, labor migration, and the problems of family members’ isolation during the Covid-19 pandemic. The pandemic has widened the gap between the poorest and wealthiest groups. Therefore, social resilience management should aim to improve institutional and interpersonal social trust. Furthermore, public authorities should unite the community using economic, social, cultural, and religious instruments since atomized individuals cannot withstand local and global challenges efficiently.

Acknowledgment
The paper was prepared in the framework of the research project “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy” (№ 0121U100470) and “ Jean Monnet Chair in EU Economic Policies and Civil Society” (619878-EPP-1-2020-1-UA-EPPJMO-CHAIR).

A full-scale Russian invasion in Ukraine changes people’s behavior and determines the current person’s resilience/vulnerability in society. This paper aims to estimate individual resilience/vulnerability and its factors in the community during wartime. It used the online survey method based on Google Forms and online focus-group interviews during May-August 2022 at four territorial communities in Kyiv, Lviv, Mykolaiv, and Sumy regions, which geographically represent the whole of Ukraine. A randomly selected 468 respondents were interviewed, including 139 internally displaced persons and refugees and 329 who did not consider themselves in any vulnerable category. The survey shows that according to the “Well-being and baseline status” factor, 66.3% of respondents confirmed an increase in their activity in response to the war.
Along with a high level of trust in their family during wartime, indicators of social atomization (broken social ties, isolation of people from each other) are high. Thus, 37.4% of respondents noted that they rely only on themselves and solve their problems independently, without anyone’s help. Using the Connor-Davidson Resilience Scale, it was found that the social resilience of the Ukrainian population is mainly based on individual resilience rather than on the resilience of mechanisms. For almost 50% of the respondents, there are manifestations of atomized sustainability and vulnerability, which increase the likelihood of post-traumatic stress disorder. Therefore, the control over disaster management processes should be based not only on data monitoring but also on training and innovativeness to increase social resilience.

Acknowledgment
This study was funded by a grant “Restructuring of the national economy in the direction of digital transformations for sustainable development” (No. 0122U001232).

The additive economy should be the productive basis toward which the national economies aspire. This paper aims to deepen the theoretical issues of the additive economy forming and its key components: additive technology and additive manufacturing. Additive technology is defined as a set of methods and tools based on which the production of products occurs by adding only the useful part of natural substances to the final commodity and creating no waste. Additive manufacturing is a system of interconnected processes of transforming natural substances into finished products based on additive technology. The additive economy is a system of trade and industries based on additive manufacturing. The study analyzes competitive advantages (direct prototyping, saving materials and energy, the ability to work without human participation, dematerialization of transportation and storage of products) and challenges of the additive economy (building an organizational network of production systems; forming solidarity economy; developing new social institutions; social development of a person). The paper formulates the key directions of economic systems restructuring to an additive economy formation, including restructuring energy production types, energy networks, and interface sphere and change of the structure of primary resources. The general debatable problem of the economic systems restructuring to the additive economy is the formation of new social institutions capable of providing necessary solutions.

Acknowledgment
The study is prepared in the framework of the research project “Restructuring of the national economy in the direction of digital transformations for sustainable development” (№0122U001232), funded by the National Research Foundation of Ukraine.

Over the years, technological progress has accelerated highly, and the speed, flexibility, human error reduction, and the ability to manage the process in real time have become more critical and required production companies to adapt production and business models according to the needs. The demand for real-time decision support systems adapted to these raising business needs is continuously growing. Nevertheless, businesses usually face challenges in identifying new indicators, data sources, and appropriate financial modeling methods to analyze them. This paper aims to define and summarize the main financial/economic forecasting methods for production companies in the context of Industry 4.0. Main findings show forecasting accuracy of up to 96% when combining economic and demand information, optimal forecasting period from 10 months to five years, more frequent use of soft indicators in forecasting, the relationship between company’s size and production planning. Four groups of indicators used in financial modeling, such as (I) production-related, (II) customers’ and demand-oriented, (III) industry-specific, and (IV) media information indicators, were separated. The analysis forms a suggestion for decision-makers to pay more attention to the forecasting object identification, indicators’ selection peculiarities, data collection possibilities, and the choice of appropriate methods of financial modeling.

Acknowledgment
This work was partly supported by Project No. 0121U100470 “Sustainable development and resource security: from disruptive technologies to digital transformation of Ukrainian economy”.

The full-scale russian invasion of Ukraine led to numerous physical and moral challenges. The paper aims to estimate the role of family as a social resilience driver in managing wartime challenges on a regional level. It used the online survey method based on Google Forms and online focus-group interviews in September-November 2022. Household members (1,089 respondents) of Kyiv, Lviv, Zakarpattia, Mykolaiv, Sumy, Chernihiv, and Dnipropetrovsk territorial communities were surveyed. Most respondents generally positively assess Ukraine’s prospects; 59% believe that the situation in the country will most likely improve. During war escalation, 67.2% of respondents waited for family support, and 48.8% helped their relatives, but relying on family support did not increase their safety expectations. In communities that did not increase their activity level in response to the war by one percentage point, the “feeling unsafe” responses increased by 1.8 percentage points, which means that an active civil position is also responsible for feeling safe (other things being equal) and increasing society’s resilience. At the same time, even in wartime, the indicators of social atomization are quite high, as 46.2% relied only on themselves and solved their problems independently, without anyone’s help. Therefore, developing family relations is one of the effective mechanisms for raising internal human resources to manage wartime challenges.

Acknowledgment
This study was supported by a project “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (№0124U000549) and “Economic and energy security of Ukraine in the conditions of war and post-war reconstruction: disruptive technologies for sustainable development” (№0123U103593).

The rise of local and global challenges (such as COVID-19, wars, natural disasters, etc.) requires advanced communication and information technologies to support economic development. The study aims to form a theoretical basis and practical tools for creating and functioning of wiki communities. Wiki communities are a new form of social association based on Internet communications of socio-economic subjects (individuals and organizations), in which each participant has equal rights to receive information, exchange opinions, and generate solutions. The theoretical basis involves substantiating the key principles on which wiki communities are formed, e.g., decentralization, openness, peering, sharing, and mass nature of activity. Wiki communities are represented by a set of specific types, such as professional, academic and research, custom, creative, public and non-commercial communities. The specific managing activities of wiki communities are described by several classification levels, such as operational activities, ensuring security, quality assurance, and motivation. The wiki community management toolkit includes a goal-setting algorithm, decision-making procedures, communications, rules of operation, typical tasks, areas of application, the operation and development cycle, and functional capabilities. It allows effective transfer of information, communication in real-time, and mutually enriching each other in forming knowledge and innovation.

Acknowledgment
The publication was prepared in the framework of the research project “Restructuring of the national economy in the direction of digital transformations for sustainable development” (№0122U001232) from National Research Foundation.

Type of the article: Editorial

Acknowledgments
The paper is prepared within the scientific research projects “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (No. 0124U000549) and “Fundamental grounds for Ukraine’s transition to a digital economy based on the implementation of Industries 3.0; 4.0; 5.0” (No. 0124U000576).

The modern industrial revolutions have significantly influenced social and political landscapes, prompting critical inquiries into the security and integrity of socio-economic systems, particularly in the context of military confrontation. This paper investigates the role of disruptive technologies associated with Industries 3.0, 4.0, and 5.0 in safeguarding socio-economic systems amid the ongoing russian war against Ukraine. The paper highlights how modern technologies have bolstered system resilience and adaptability by examining progress in green energy, transport transition, and the development of digital infrastructure and services before the war. Green energy and transport technologies have been instrumental in decentralization, energy networking, compensating for energy losses, and mitigating disruptions caused by the war. The proliferation of electric vehicles and the expansion of charging infrastructure have significantly reduced the potential impact of aggression, facilitating evacuations and supporting essential services during fuel shortages. Digital technologies have played a crucial role in ensuring continued access to education, employment, and communication, thereby strengthening societal resilience and reinforcing human capital, a key factor in socio-economic system security. This marks a shift from a technocratic to a system-synergistic, human-centered security model, where human capital becomes a core determinant of resilience, and technologies evolve from mere tools into integral elements of a sustainable socio-economic structure. Nevertheless, challenges related to technological dependencies, such as supply chain vulnerabilities and cyber threats, require further investigation in future research.

Acknowledgments
The paper is prepared within the scientific research projects “Digital Transformations to Ensure Civil Protection and post-war Economic Recovery in the Face of Environmental and Social Challenges” (No. 0124U000549) and “Fundamental Grounds for Ukraine’s transition to a digital economy based on the implementation of Industries 3.0; 4.0; 5.0” (No. 0124U000576).

Type of the article: Research Article

Abstract
The interaction of humans with artificial intelligence and cyber-physical systems opens the way to understanding the role of humans in modern industrial ecosystems. The research purpose is to examine the roles and functions of humans in implementing Industry 5.0 through the analysis of personality transformations in social and labor entities. A structured review methodology that synthesizes existing research on Industry 5.0 as a human-centric direction using systematic and transparent procedures (framing the question, identifying relevant publications in the Scopus database, summarizing the evidence, and interpreting the findings) is used. Within Industry 5.0, the physiological needs of a bio-human (needs for food, water, living conditions, etc.) and the technocratic interests of a labor-human (the desire to earn money, career growth, prestige, etc.) are overwhelmed in terms of time and effort by the socio-human personality needs (intellectual development, the realization of creative abilities, and obtaining knowledge). In complex technical tasks and strategic decision-making processes, humans continue to play a key role, emphasizing that full automation is not possible in all areas, and a human-centric approach remains the basis of production systems. Among the key personality skills needed for Industry 5.0 are analytical and creative thinking, the ability to design technology, critical thinking, ability to solve complex problems, leadership skills, emotional intelligence, and generating new ideas. Industry 5.0 promotes the consumption of mainly information and services dictated by the informational (spiritual) nature of the personality and relatively depresses the use of materials and services, dictated by the material nature of the human-bio.

Acknowledgments
This study is conducted within the project “Restructuring of the national economy in the direction of digital transformations for sustainable development” (№0122U001232) from the National Research Foundation of Ukraine.

Type of the article: Research Article

Abstract
The significance of green economic growth opens up a new space for studying cyclical development processes, raising the issue of coexistence between sustainable development and the cyclical features of economic growth. The purpose of this study is to identify statistically significant relationships between cyclical components (fluctuations) of economic growth and environmental consequences within national economic systems. The paper utilizes Hodrick–Prescott and Butterworth bandpass filters to detrend dynamic series of ecological and economic development, highlighting cyclical components (fluctuations) that are analyzed for the presence of correlation in the referenced and lag periods (to identify procyclical and lag dynamics). The analysis uses statistical data from the World Bank for Ukraine and Hungary for 1991–2022. The results prove that for Ukraine with an increase in the cyclical component of GDP per capita there is a cyclical increase in pollution indicators, according to the Butterworth filter for NOx emissions from industrial combustion (correlation coefficient 0.72), F-gases emissions from industrial processes (correlation coefficient 0.77), CO2 emissions excluding LULUCF (correlation coefficient 0.70). The situation with Hungary is different, and the business cycle is not correlated with pollution fluctuations. The paper does not find a statistically significant relationship between the business cycle and fluctuations in methane (CH4) emissions from waste (Mt CO2e). Overall, most economic and environmental components are procyclical in nature, with the strongest correlation in the reference period for a developing industrial economy (Ukraine). In contrast, there is no such link within a more developed economy (Hungary).

Acknowledgments
This research was conducted within the project “Restructuring of the national economy in the direction of digital transformations for sustainable development” (№0122U001232) funded by the National Research Foundation of Ukraine.

Type of the article: Research Article

Profound ecological and technological shifts are transforming the foundations of global development and redefining the trajectory of contemporary globalization. The study aims to investigate the role of the sustainable economy in shaping a new globalized development model in the context of disruptive technologies and Industry 4.0. The results demonstrate that sustainability and advanced digital-cyber-physical technologies act as mutually reinforcing drivers of structural change, enabling the transition toward circular production systems, intelligent resource management, and human-centered industrial paradigms. The study confirms that sustainability becomes the new logic of globalization, in which additive production, renewable energy, cyber-physical systems, and intelligent networks form disruptive trends reshaping political and economic relations. Recent market assessments indicate that the global Industry 4.0 sector has already reached a value of USD 180–200 billion, with projections ranging from USD 600–900 billion by 2034. Within a sample of developed economies, an increase in the Globalization Index by one point decreases the Sustainable Development Index by 0.68 points. The scientific novelty lies in the conceptualization of the sustainable economy through both classical and globalization approaches: the former focuses on additive, resource-efficient production, while the latter interprets sustainability as a new organizing logic of globalization that reshapes geopolitical interactions, redistributes technological power, and embeds ecological constraints into global governance. The study concludes that the sustainable economy represents a new globalization reality in which ecological principles, digital intelligence, and technological sovereignty jointly define long-term development trajectories.

Acknowledgments
The paper is prepared within the scientific research projects “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (№0124U000549).

Type of the article: Research Article

The relevance of the study stems from the transformation of modern work models from the technologically oriented Industry 4.0 paradigm to the human-centric Industry 5.0, where employee autonomy is emerging and becoming established as a global trend. The paper aims to conceptualize employee autonomy as an economic resource by optimizing work–life balance and assessing its impact on productivity and population well-being. For the analysis, panel data were collected for 123 countries over the period 2005–2023. The methodological basis of the study is the Levin–Lin–Chu unit root test, the Breusch–Pagan Lagrangian multiplier test, the Hausman specification test, and GLS regression estimation. The study found that, on average, in the group of accessible countries, each additional 100 hours worked per year reduces labor productivity by USD 2 per hour. An increase of one hour in the working year reduces GDP per capita by USD 28.48 per person.

Furthermore, a one percent increase in the length of the working year is associated with a 2.71 percent drop in GDP per capita per hour. Thus, productivity in the Industry 5.0 paradigm at the global level is predominantly qualitative and is shaped by focus, intrinsic motivation, and decentralized decision-making, rather than by increasing working hours. It is concluded that worker autonomy is an economically significant factor in enhancing productivity, innovation potential, and contributing to the geopolitical and geoeconomic sustainability of societies in the era of globalization.

Acknowledgments
The paper is prepared within the scientific research projects “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (No. 0124U000549) and “Fundamental grounds for Ukraine’s transition to a digital economy based on the implementation of Industries 3.0; 4.0; 5.0” (No. 0124U000576).

Type of the article: Research Article

Abstract
The freelance economy opens new ways for direct interaction between freelancers and customers without intermediaries. This study aims to systematize the forms of the freelance economy in the context of Industry 5.0. A structured review methodology focusing on technological progress and human-centric solutions of the freelance economy is used. Freelancing and Industry 5.0 are closely intertwined and complement each other, forming new economic models and work processes. Their relationship lies in the combination of technological development and human creativity, which allows for the formation of efficient and flexible economic structures. Personalization and customization of consumption within Industry 5.0 promote the freelancing (individualization) of the production sphere, building a win-win strategy both for consumers and producers. Freelancing economy focuses on information processing of work, enables remote communications, promotes creativity of work, provides opportunities for the synergistic combination of human cognitive abilities with AI, ensures the development of personalization and customization of consumption, and contributes to the social development of workers. The structure of the forms of the freelance economy is characterized by the integration of decentralized financial systems, the use of artificial intelligence and blockchain, and the transition to new forms of labor organization based on global digital platforms and self-regulated organizations. One of the key barriers to the freelance economy is the lack of legal regulation of cryptocurrencies and decentralized autonomous organizations (DAOs), as well as the associated cybersecurity risks. To summarize, the significance lies in creating a more adaptive, flexible, and decentralized labor market that meets the challenges of today’s digital world.

Acknowledgments
This research was funded by a grant “Fundamental grounds for Ukraine’s transition to a digital economy based on the implementation of Industries 3.0; 4.0; 5.0” (No. 0124U000576) and “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (No. 0124U000549). 

Rapid economic reforms and proper GDP growth in China has affected the regional development of Chinese provinces. This study aims to estimate the degree of economic and environmental disparities within Chinese provinces for developing policy recommendations of regional transformation. The reduced log-linear specification of endogenous growth model is used for the estimation of convergence rates within Chinese provinces. The empirical results prove that an increase of 1% in GDP per capita basic year reduces the economic growth rate by 0.1% in the reference year. Thus, the ratio of the average per capita income in the wealthiest group to poorest provinces accounted for the factor 9.6 in 1995 and factor 4.1 in the year 2015, which means a reduction of disproportionate development. Environmental convergence trends were also found and less polluted provinces eventually increase emissions at higher rates than the initially polluted ones. With the pass of time, all provinces do move to the same steady state in environmental parameters. The speed of the economic and environmental convergence in China provinces is rather slow, and the economic growth was achieved by great sacrifices of an environment, since all provinces are striving to the same steady state in terms of pollution increase. The industrialized regions due to the presence of significant financial resources should pay more attention to the protection of the environment using all the available economic potential. At the same time, both initially poor provinces and rich have to develop more profoundly agriculture, tourism, recreation, and other environmentally friendly industries to improve economic performance.

Type of the article: Theoretical Article

Abstract
National cybersecurity opens new opportunities for digital transformation and helps counter the growing threat of cyberattacks. The purpose of this study is to develop a methodology and identify the most influential predictors of national cybersecurity in global competitiveness, utilizing the data mining approach. To assess the impact of cybersecurity characteristics, modern machine learning methods were implemented in the Salford Predictive Modeler software environment, including Classification and Regression Trees, Random Forest, Stochastic Gradient Boosting, Multivariate Adaptive Regression Splines, Generalized Path Seeker, and classical regression. Data mining was conducted using the World Competitiveness Ranking (WCR) indicators, constructed by the Institute for Management Development, and the National Cybersecurity Index (NCSI), constructed by the e-Governance Academy, for 64 countries as of 2024. Three groups of countries were identified with different predicted levels of competitiveness, underscoring the importance of balancing the development of both external and internal components of cyber defense. The empirical results demonstrate that countries with strong cybersecurity management capabilities achieve higher competitive positions, even with limited participation in global cyber initiatives. At the same time, active global involvement without sufficient internal readiness does not create sustainable competitive advantages. The regression tree provided a transparent allocation of key subfactors, with global cybersecurity contribution and cybersecurity management playing leading roles. The significance of the study lies in shaping methodology and state policy in cybersecurity, human resource development, regulatory framework enhancement, and digital ecosystem strengthening.

Acknowledgments
The paper is prepared within the scientific research projects “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (№0124U000549) and “Drivers and barriers to human capital transformation for a circular and green economy” (No. 0126U001080).

Type of the article: Theoretical Article

Abstract
The shift towards the “product as a service” paradigm requires adaptive pricing tools. The article aims to conceptualize AI-driven algorithmic pricing methods for short-term rentals and to validate them through simulation modelling as a synthetic proof of concept. The methodology distinguishes conceptual evaluation – structural-functional and SWOT analyses – from empirical simulation. The proposed framework of the actual demand-probability model uses a logistic function as a deep learning-based predictive model (MLP) within an explicit revenue-maximization procedure. While the MLP is trained to minimize prediction error in latent demand, the forecast WTP serves as a critical input to a bounded search module that calculates the revenue-maximising price. The algorithmic model demonstrates a significant uplift in simulated gross booking revenue relative to the Static, Rule-Based, and Random Forest benchmarks, based on 100 Monte Carlo repetitions. A deep learning-based predictive model with an average cumulative revenue of USD 7,307.42 outperforms the Random Forest model with high statistical significance and achieves a high win rate across simulated scenarios. Probability-based algorithmic pricing mitigates the risks of resource downtime. The sensitivity analysis confirms MLP model stability across varying consumer price elasticities. AI-driven pricing is positioned as a scalable, systemic digital technology for coordinating economic processes in modern platform industries.

Acknowledgments
This research was funded by a grant from the state budget of Ukraine, “Fundamental grounds for Ukraine’s transition to a digital economy based on the implementation of Industries 3.0; 4.0; 5.0” (No. 0124U000576) and “Digital Economy and Renewable Energy: Building Sustainable Business Models for Ukraine’s Post-War Reconstruction” (No. 0126U000877).