This study explores the impact of environmental, social, and governance (ESG) factors on profitability and market capitalization within the European automotive industry. Since the industry is confronted with environmental and regulatory challenges, ESG contributions are valuable to know for strategic decision making and investor attitude. With panel data from 60 automotive firms listed on the Eurostoxx 600 index from 2011 to 2022, the research utilizes panel regression techniques, such as the generalized method of moments, to control for possible endogeneity. The findings show that the social aspect of ESG has a positive effect on return on assets (ROA), illustrating that socially responsible efforts can strengthen operating performance. In contrast, environmental performance weakly negatively affects ROA, probably because substantial sustainability-related expenses are incurred. Governance has no significant impact on profitability. For market valuation, as captured by Tobin’s Q, social factors are negatively correlated, indicating investor doubt regarding quick returns on social investments, while governance is positively but weakly correlated. These results highlight the multifaceted nature of ESG integration in the automotive industry, with the implication that firms need to delicately trade off between sustainability initiatives and profitability and investor expectations.

Small-sized and medium-sized enterprises (SMEs) are vital to global economies but remain highly vulnerable to cyber threats due to limited resources, technical capacity, and awareness. This bibliometric study analyzes 245 peer-reviewed documents on SME cybersecurity published between 2005 and 2025, mapping the field through keyword co-occurrence, author productivity, citation patterns, and collaboration networks. Results show steady growth, with research output increasing at 16.7% annually. Core themes include awareness, governance, risk management, digital adoption, and Industry 4.0 integration, with a clear shift from technical toward strategic and human-centered approaches. Lotka's Law indicates fragmentation, as most authors contribute only once, underscoring the need for academic continuity. The United States, the United Kingdom, and South Africa dominate in volume, while France and Australia stand out for international collaboration. Influential contributors such as Spruit M and De Arroyabe JCF emphasize regulatory compliance and resilience. The literature highlights persistent challenges for SMEs in adopting standards like ISO 27001 and emerging technologies such as machine learning. Promising interventions include gamified training tools like CySecEscape 2.0 to strengthen awareness. This study advances understanding of SME cybersecurity research and calls for tailored, interdisciplinary strategies to enhance resilience, offering insights for policy, scholarship, and practice. The bibliometric evidence also reveals a growing recognition of the role of public policy and regulation in shaping SME cybersecurity practices. Highly cited works such as Kabanda et al. (2018), Heidt et al. (2019), Kljucnikov et al. (2019), and Tamvada et al. (2022) emphasize that national and European regulatory frameworks, including the NIS2 Directive and the Cyber Resilience Act, significantly influence SMEs' readiness, compliance behavior, and investment in security. These findings underline that effective cybersecurity strategies for SMEs require not only technological and organizational measures but also coherent public policy support and accessible institutional mechanisms.

This research provides a comprehensive analysis of the state of readiness assessment for enterprises in the context of Industry 4.0. It examines the most influential authors, countries, and journals in this field, identifies key research themes, and explores the evolving landscape of Industry 4.0. By bibliometric analysis, this study uncovers the intricate network of co-authorship and co-citation among researchers, journals, and countries. The analysis underscores the dominance of China in terms of both publication volume and citation impact, driven by its strategic "Made in China 2025" plan. The United States and India also make substantial contributions, reflecting the global nature of Industry 4.0 research. The key themes in this area include digital transformation, IT innovations, production, and supply chain management. This study pinpoints three distinct clusters of journals, demonstrating the multidisciplinary nature of Industry 4.0. In addition, a co-occurrence analysis of keywords highlights the most prevalent themes, including Industry 4.0, frameworks, big data, and performance. This research offers valuable insights into the research landscape, informing scholars and industry stakeholders of key players, trends, and emerging areas in assessing enterprise readiness for Industry 4.0.

This study examines the relationship between environmental, social, and governance (ESG) performance and firm valuation, with a particular emphasis on distinguishing between causal effects and predictive relevance. Using a panel dataset of publicly listed firms, the analysis combines panel econometric models, including pooled OLS, fixed effects, dynamic specifications, and System GMM estimators, with machine learning techniques to provide a comprehensive assessment of ESG valuation dynamics. The econometric results consistently show that ESG does not exhibit a statistically significant or robust linear effect on firm valuation across model specifications. This suggests that previously documented ESG–value relationships may be driven by cross-sectional differences rather than within-firm causal effects. In contrast, the machine learning analysis demonstrates that ESG variables improve out-of-sample predictive performance, particularly when included in lagged form, indicating that ESG contains incremental predictive information. Further evidence points to a nonlinear, threshold-like relationship between ESG and firm valuation. ESG appears to have limited relevance at lower levels but becomes positively associated with predicted valuation at higher levels of ESG performance. At the same time, firm valuation is primarily driven by persistence and traditional financial fundamentals, with ESG playing a secondary and context-dependent role. Overall, the findings highlight a fundamental distinction between explanatory and predictive modeling in ESG research. While ESG does not emerge as a robust determinant of firm value, it contributes to prediction through nonlinear and interaction-based mechanisms. These results provide a more nuanced perspective on the financial relevance of ESG and carry important implications for both research and practice.

This study examines the financial performance of ESG and non-ESG portfolios between 2020 and 2024 using monthly data from ten major US exchange-traded funds (ETFs). Leveraging the Capital Asset Pricing Model (CAPM) and Modern Portfolio Theory (MPT), we assess annualized returns, volatility, Sharpe ratios, and maximum drawdowns. The results show that ESG portfolios perform comparably to traditional portfolios in terms of both returns and risk-adjusted efficiency. While the non-ESG portfolio posted slightly higher returns, the difference was statistically insignificant. CAPM estimates revealed betas near unity and no evidence of abnormal returns (alpha), supporting the neutrality hypothesis. These findings suggest that investors can pursue ESG strategies without compromising financial outcomes. From a policy perspective, the results underscore the need for robust ESG disclosure frameworks to support market transparency and efficiency.Copyright© 2025 The Author(s). This article is distributed under the terms of the license CC-BY 4.0., which permits any further distribution in any medium, provided the original work is properly cited.Article’s history: Received 25th of October, 2025; Received in revised form 19th of November, 2025; Accepted 14th of December, 2025; Available online: 30th of December, 2025. Published as article in the Volume XX, Winter, Issue 4(90), December, 2025.

This study examines the relationship between environmental, social, and governance (ESG) principles and corporate tax behavior through a comprehensive bibliometric analysis of publications from 2000 to 2025. Using the Bibliometrix R package and following PRISMA guidelines, the analysis identifies influential authors, journals, countries, and thematic clusters shaping the ESG–taxation research landscape. The findings reveal a significant shift from viewing taxation as a compliance-oriented financial decision to understanding it as an integral part of sustainable governance and ethical corporate conduct. Keyword networks and thematic evolution maps highlight growing attention to tax transparency, green fiscal instruments, and ESG-related policy interventions. The study contributes to conceptualizing taxation within modern sustainability frameworks and outlines key research gaps, including limited evidence from developing economies and the need for causal analyses.