Alvina Oriekhova

This study aims to investigate whether corporate social responsibility activities are associated with more or less tax avoidance by focusing on this interrelationship in mandatory vs. voluntary regulatory regimes. The sample includes 6,668 firm-year observations of Chinese A-share firms listed on the Shanghai and Shenzhen stock exchanges over 2011–2019. The study uses corporate culture and risk management theories to develop the hypotheses. Regression analysis and various robustness tests are employed to test the hypotheses. The data are retrieved from the HEXUN CSR system and CSMAR and WIND databases.
Consistent with the predictions of corporate culture theory, which argues that aggressive tax avoidance cannot be synchronously coupled with corporate social responsibility, the paper finds that notwithstanding regulatory regime, when the level of corporate social responsibility increases, the level of tax aggressiveness decreases. Thus, the results show that firms reporting corporate social responsibility tend to be less tax aggressive. Firms that engage in more corporate social responsibility activities are less likely to be tax aggressive, irrespective of regulatory regimes in place. Moreover, pollution indicators have little effect on corporate social responsibility and tax aggressiveness in Chinese institutional settings. The study contributes to the business ethics literature by implying the role of tax avoidance as a part of CSR and not as a separate non-CSR element of companies’ activities.

Acknowledgment
This paper is co-funded by the European Union through the European Education and Culture Executive Agency (EACEA) within the project “Embracing EU corporate social responsibility: challenges and opportunities of business-society bonds transformation in Ukraine” – 101094100 – EECORE – ERASMUS-JMO-2022-HEI-TCH-RSCH-UA-IBA/ERASMUS-JMO-2022-HEI-TCHRSCH https://eecore.snau.edu.ua/

The paper delves into the relationship between accounting conservatism, valued by financial stakeholders, and corporate social performance (CSP), esteemed by non-financial stakeholders. This study assesses the potential impact of financial reporting practices, specifically accounting conservatism, on a firm’s CSP activities, which has significant implications for diverse stakeholders. Employing an accrual-based proxy for accounting conservatism and the social contribution value per share from the Shanghai Stock Exchange as a proxy for CSP, the study utilizes a sample of 25,490 year-company observations of A-share listed companies on China’s Shanghai and Shenzhen stock exchanges spanning from 2008 to 2019. Empirical findings indicate a negative correlation between accounting conservatism and CSP. The study suggests that higher levels of social performance are associated with reduced conservatism in financial reporting, indicating that firms prioritize CSP over the interests of financial stakeholders by adopting less conservative financial reporting policies. Aligned with agency theory, these results underscore that socially responsible firms are less inclined to employ accounting conservatism in reporting earnings. This study establishes a connection between firms’ unconventional and less traditional activities, such as CSP, and conservative financial reporting, offering valuable insights for investors, analysts, and regulators.

Acknowledgment
This paper is co-funded by the European Union through the European Education and Culture Executive Agency (EACEA) within the project “Embracing EU corporate social responsibility: challenges and opportunities of business-society bonds transformation in Ukraine” – 101094100 – EECORE – ERASMUS-JMO-2022-HEI-TCH-RSCH-UA-IBA / ERASMUS-JMO-2022-HEI-TCHRSCH https://eecore.snau.edu.ua/

Type of the article: Research Article

Abstract
Global progress toward universal access to affordable, reliable, and clean energy has stalled, with over two billion people still lacking access to clean cooking, and affordability pressures are rising. AI is emerging as an energy-intensive technology and a potential enabler of more equitable energy systems. This paper assesses whether AI vibrancy contributes to advancing energy equity across countries while accounting for differences in economic capacity. The study employs a balanced panel of 36 countries from 2017 to 2023 (252 observations), drawing on the Global AI Vibrancy Tool, World Bank Open Data, and the World Energy Council’s Energy Trilemma Index. Box–Cox transformations were applied to address skewness, and panel econometric models (fixed and random effects) with robust standard errors were estimated. The FE model shows no significant within-country effect of AI vibrancy on energy equity (R² = 0.012). The RE model indicates a positive association: a one-unit increase in the AI vibrancy score results in an improvement of 0.00165 in the energy equity index (p < 0.01). At the same time, GDP per capita exerts a strong and highly significant effect (p < 0.001). The RE model explains 12.4% of the overall variation in energy equity. After correcting for heteroscedasticity and cross-sectional dependence, GDP per capita remains significant, whereas the effect of AI vibrancy weakens to marginal significance (p ≈ 0.09). Country-specific effects further reveal systematic over- and under-performance beyond what AI vibrancy and income predict, underscoring the critical role of governance and institutional quality in shaping energy equity outcomes.

Acknowledgment
The article was prepared as a part of the MSCA4Ukraine project 06030419, European Union’s Horizon 2020 Research and Innovation Programme. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union, the European Research Executive Agency, or the MSCA4Ukraine Consortium. Neither the European Union nor the European Research Executive Agency, nor the MSCA4Ukraine Consortium as a whole, nor any individual member institutions of the MSCA4Ukraine Consortium can be held responsible for them.

Type of the article: Research Article

Artificial intelligence has become a driver of knowledge transformation, skills renewal, and institutional change, making lifelong learning increasingly important for adapting to AI-driven labor markets and societies. This study aims to examine whether national AI development indicators are associated with realized participation in education and training across different adult age groups in European countries, and to discuss what these associations may imply for lifelong learning and knowledge transfer policies. The analysis is based on a panel of 18 European countries for 2017–2024 and applies two-way fixed-effects models with country and year effects, contemporaneous, one-year, and two-year lag specifications, and Driscoll–Kraay robustness checks. The results show that the total AI Vibrancy Score is not a statistically significant predictor of participation in education and training: the contemporaneous coefficients are 0.4822 for adults aged 18-74, 0.1054 for those aged 45-54, and 0.5006 for those aged 50-74. Descriptive statistics indicate that average lifelong-learning participation declines with age, from 20.09% among adults aged 18-74 to 14.82% among those aged 45-54, and 9.34% among those aged 50-74. The lagged structural models show that AI-related R&D is negatively associated with subsequent participation, with one-year lag coefficients of −1.2310, −0.9392, and −0.8911 for the three age groups, respectively. In contrast, AI-related Policy and Government activity has a positive two-year lagged association for adults aged 18-74 and 45-54, with coefficients of 0.6064 and 0.7346. This suggests that policy-related AI development, rather than national AI development alone, may be more relevant for observed adult participation in education and training.

Acknowledgments
This research was funded by an EU grant “Immersive Marketing in Education: Model Testing and Consumers’ Behavior” under project No. 09I03-03-V04-00522/2024/VA and by the Ministry of Education and Science of Ukraine “Modeling and forecasting of socioeconomic consequences of higher education and science reforms in wartime” (No. 0124U000545).

Type of the article: Research Article

Abstract
The transition toward climate neutrality is reshaping economic systems and increasing the importance of human capital in green modernization. However, a significant gap persists between technological advances and the strategic management of the workforce. This study aims to systematize and conceptually map the contemporary scholarly landscape of human capital management research within the renewable energy transition. Using the PRISMA 2020 protocol, the study analyzed 2,258 Scopus-indexed documents published between 1994 and 2026 through bibliometric and science mapping methods. The methodology combined descriptive statistics, keyword frequency analysis, multiple correspondence analysis (MCA), and network co-occurrence cluster analysis using the Bibliometrix R-package and VOSviewer. The results show a rapid increase in publication activity, with an annual growth rate of 18.01%, with China, the United States, and India leading global output and the international collaboration rate reaches 28.6%. Science mapping showed that the term “human capital” entered this field more actively only after 2020 (297 occurrences), still lagging behind technological topics. MCA indicated a clear conceptual separation between knowledge domains: the relative distance between the educational and workforce clusters suggests that these themes are still weakly integrated in the literature. Network analysis identified five thematic clusters: the technological and educational foundation, macroeconomic environment and resources, strategic management and innovative transformation, the socio-labor dimension and labor market, and eco-technological regulation. These results point to the need for a more integrated approach to adaptive human capital development that connects technological change, professional mobility, and institutional learning and strengthens the role of human capital in supporting green transformation.

Acknowledgment
This paper was supported by the Ministry of Education and Science of Ukraine as part of the research project Adaptive Human Capital Management in the Renewable Energy Sector: Synergy of Innovation and Social Sustainability” (Grant/Project No. 0126U000453).