Lithuanian Social Research Centre

Purpose This study analyses the potential and emerging risks of blockchain technology in several financial and non-financial industries. The ability of blockchain technology to comply with the Corporate Sustainability Reporting Directive is also analysed. Design/methodology/approach A systematic bibliometric analysis was carried out based on the PRISMA 2020 methodology, reviewing 43 articles, all peer-reviewed and indexed in the Web of Science database. Subsequently, a meta-analysis was conducted to assess how blockchain technology can provide advances and improvements. Findings Seven research questions were answered to highlight the ability of blockchain technology to automate data verification, data immutability and align corporate reporting with International Financial Reporting Standards. Blockchain technology has the potential to enhance corporate risk management strategies and promote cross-industry collaboration. Research limitations/implications We found that technology can act as an enabler for achieving sustainability goals and more effective corporate governance in increasingly changing environments. Practical implications In addition to the ability to automate traceability and strengthen regulatory compliance in sectors such as finance, tourism and agribusiness. Blockchain technology has the potential to improve environmental, social and governance auditing and facilitate verification processes. The findings focus on its role in enhancing transparency, risk management and cross-industry collaboration, leading to more reliable and sustainable corporate reporting. Originality/value A combined approach is offered by bibliometric analysis and meta-analysis to assess the role of blockchain technology in Corporate Sustainability Reporting Directive compliance. Theoretical frameworks such as institutional, stakeholder and corporate governance theories are integrated from a sustainable and technological perspective.

Type of the article: Research ArticleAbstractFinancial inclusion has become increasingly central to the European Union’s social policy agenda amid digital transformation, recurrent economic shocks, and persistent poverty and inequality concerns. This study aims to assess the impact of financial inclusion on poverty risk and income inequality in the European Union, with particular attention to non-linear and long-run effects. The analysis uses annual aggregate EU-level data for 2004–2023. It applies time-series econometric methods, including correlation analysis, unit root and Granger causality tests, linear and quadratic regressions, and Error-Correction Models. The results indicate that financial inclusion does not exert a uniform direct linear effect on social outcomes. Correlation analysis shows a strong association between digital financial use and income inequality (e.g., card transactions and the Gini coefficient: r = −0.69; internet banking use and the Gini coefficient: r = −0.63), while correlations with poverty risk remain weak. Regression results confirm that most financial inclusion indicators have no statistically significant linear effect on poverty risk. However, a significant non-linear (inverted U-shaped) relationship is identified between card payment transactions and poverty risk, indicating that poverty risk declines once digital payment usage exceeds a threshold. In contrast, income inequality is significantly and negatively associated with traditional financial access, as increases in bank branch density per 100,000 inhabitants reduce the Gini coefficient in both the short and long run. Overall, the findings show that the social effects of financial inclusion in the EU are outcome-specific and depend on the form and intensity of inclusion rather than access alone.

Abstract Research examining micro-level factors in European countries is well-established. However, little research explores how macro-level factors, such as institutional settings or labour market structures, shape working poverty. After reviewing the literature on macro-level determinants of in-work poverty, we classified these factors into two broad categories—institutional and structural—and examined their impact on in-work poverty rates across the EU. We conducted a panel regression analysis using data from 27-EU countries over the period 2009–2022. The results indicate that in-work poverty in the EU-27 is shaped by both institutional and structural macro-level factors. Fluctuations in the employment rates of specific population groups influence working poverty. The in-work poverty rate declines as youth employment rates increase, whereas higher employment rates among non-EU nationals, low-skilled individuals, and those employed in agriculture, forestry, and fishing are associated with an increase in in-work poverty in the EU. The part-time employment rate was found to be a contributing factor to the increase in in-work poverty. A larger share of the population leaving education early contributes to rising in-work poverty. Finally, our findings highlight that public expenditure on disability benefits has a positive effect on alleviating in-work poverty by providing crucial financial support to vulnerable households.

Abstract People's life trajectories and family dynamics have become increasingly complex, bringing shifts in fertility, gender equality, work-life balance, and economic stability. The scientific challenge is to capture these complexities and understand their causes and consequences. The Generations and Gender Survey (GGS) provides key insights into these developments, serving as a vital resource for researchers and policymakers. The GGS is a cross-national longitudinal survey collecting data on individuals aged 18 to 79 across topics such as union formation, fertility, household dynamics, work, well-being, and gender attitudes. Its key strengths include cross-national comparability, a panel design with prospective and retrospective data, large sample sizes, and multi-mode data collection. The GGS consists of two rounds: GGS-I, launched in the early 2000s in over 20 countries, established a foundation for comparative research, while GGS-II, started in 2020, builds on GGS-I with methodological innovations such as mixed-mode data collection and refreshed samples. This data brief provides an overview of the GGS, outlining its development, design, implementation, and key features. It also highlights the survey's contributions to demographic and social research, and explores the new research opportunities emerging with GGS-II.

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