Artsrun Avetikyan

Type of the article: Research Article

Understanding the alignment between public interest and academic research is increasingly relevant in the context of global sustainability challenges. This study aims to investigate the relationship between societal attention, as measured by Google Trends, and scholarly output on renewable energy and the shadow economy. Using bibliometric data from Scopus and Web of Science alongside global Google Trends data from 2004 to 2025, the analysis employed Pearson and Spearman correlation coefficients, Granger causality, and distance correlation to assess the strength, direction, and form of association between public search trends and academic activity. The results reveal a significant Granger-causal relationship from public searches on “renewable energy” to academic publications, with F-statistics above 5.2 (p < 0.01), and strong positive correlations (Pearson r = 0.72; Spearman ρ = 0.69; distance correlation = 0.63). In contrast, the terms “informal economy” and “feed-in tariff” demonstrated weak or inconsistent associations, with correlations below 0.25 and statistically insignificant causality tests (p > 0.1). Cross-country comparisons further highlighted uneven alignment, with India showing high search intensity (Google Trends index > 75) but relatively low publication volume (< 2% of global output). At the same time, South Africa displayed closer coherence, with both indicators moving in tandem (r ≈ 0.61). These findings underscore scholarly research’s partial and asymmetric responsiveness to public demand, varying significantly by topic and geographic context. Moreover, while Google Trends offers robust signals of societal interest, disparities in digital access and literacy reduce its universality, pointing to critical underexplored research gaps with direct policy relevance.

Acknowledgment
This study was prepared as part of the project supported by the National Scholarship Programme of the Slovak Republic, the project 101127491-EnergyS4UA-ERASMUS-JMO2023-HEI-TCH-RSCH. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or European Education and Culture Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. This research was funded by the grants VEGA 1/0689/23 “Sustainable growth and the geopolitics of resilience in the context of crisis prevention” and VEGA 1/0254/25 “Artificial Intelligence and FDI-invested Business Service Centers: Selected Macroeconomic and Corporate Aspects”.

Type of the article: Research Article

AI is widely regarded by the IMF and the World Bank as a catalyst for growth. AI should be understood as a multidimensional socio-technical system embedded across institutions, industries, and society. Its economic contribution depends on which pillars of the national AI system expand (e.g., R&D capacity, infrastructure, governance, or social acceptance). For this reason, the seven pillars of AI development are measured by the AI Vibrancy subindices, which help avoid reliance on a single composite indicator that may conceal offsetting effects. This study examines how different pillars of the national AI ecosystem shape the architecture of the knowledge economy and its economic outcomes by estimating heterogeneous within-country associations between GDP per capita and seven AI ecosystem pillars, operationalized through AI Vibrancy subindices, using a balanced panel of 36 countries with complete data over the period 2020–2023. Fixed- and random-effects models are estimated using heteroskedasticity-robust and Driscoll-Kraay standard errors. The results indicate that, within countries over time, the R&D (β = –5.676, p < 0.001) and Infrastructure (β = –16.306, p < 0.001) subindices have strong and statistically significant negative associations with GDP per capita, while Public Opinion shows an adverse effect that is significant at the 5% level under heteroskedasticity-robust inference (β = –9.126, p = 0.040) and marginally significant under Driscoll-Kraay inference (p = 0.054). Responsible AI exhibits a marginally positive association (β = 5.773, p = 0.065) in the Driscoll-Kraay specification, whereas Economy, Education, and Policy & Government show no significant within-country effects.

Type of the article: Research Article

Abstract
Global account ownership rose from 51 to 76 percent of adults between 2011 and 2021, much of it through digital channels, yet the depth and innovativeness of national financial systems vary sharply across economies. This study quantifies how the rule of law and the model of digital government relate to two dimensions of financial-sector development, banking-sector depth and digital financial innovation, across developed, developing, and transition economies, and tests whether digital government can substitute for institutional quality. Using a panel of 183 economies over 2000–2021 (estimation window 2003–2021) and a four-wave Global Findex panel, the analysis applies two-way fixed-effects and pooled wave-fixed-effects models with country-clustered standard errors. The rule of law is positively associated with banking-sector depth, but the association is heterogeneous: it is largest and most robust in transition economies (β = 22.17, p = 0.020) and insignificant in developing economies. Digital government, by contrast, is not significantly related to banking-sector depth (p = 0.322) yet is strongly associated with digital financial innovation, where the rule of law also matters; the e-government association is strongest for digital-payment adoption (β = 51.99, p < 0.001). In these cross-country estimates, the rule-of-law × e-government interaction is negative and significant (β = −10.69, p = 0.018), and the marginal association of the rule of law declines by almost half as digital government expands, a pattern consistent with partial substitution. These findings are robust to the 2025 revision of the governance data and to extending the sample through the 2024 Findex wave.

Acknowledgments
This article was prepared based on the results of a study funded by the Ministry of Education and Science of Ukraine entitled “GovTech for Ukraine: A Digital, Secure, Transparent, and Equitable State in Times of War and Post-War Reconstruction” (registration number: 0126U000544).