Larysa Rybina

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).

Successful achievement of the 17 Sustainable Development Goals (SDGs), including SDG 7: Affordable and Clean Energy, is impossible without proper financial support, especially after the devastating impact of the COVID-19 pandemic. Despite more than million academic papers related to SDG 7, only very few of them address the financial aspects of achieving SDG 7. To test the hypothesis, “SDG 7 related academic studies ignore the issue of investment in general and responsible investment in particular”, a meta-analysis is performed that includes a number of specific instruments and technics such as SciVal by Elsevier, VosViewer, Google trends, Google Books Ngram Viewer and Google Data. The results show a lack of appropriate academic support (methodology, empirical results, econometric models etc.) for practitioners to fill the existing financial gap and successfully achieve SDG 7. Among 1.2 million SDG 7 related papers, less than 100 deal with the financial gap problem measured by trillions of dollars in achieving SDG 7. This paper identifies the most promising and relevant topics for study related to SDG 7 and investment: the impact of the pandemic on decisions in the energy sector; efficiency of SDG 7 investment support and methodology for its assessment; green bonds, green loans, sovereign green bonds as responsible investment tools to advance SDG 7.

Acknowledgments
Inna Makarenko gratefully acknowledges support from the Supreme Council of Ukraine (0122U201796).
The research was supported by the Scientific Grant Agency of the Ministry of Education, Science, Research, and Sport of the Slovak Republic and the Slovak Academy Sciences (VEGA), project No 1/0364/22: Research on eco-innovation potential of SMEs in the context of sustainable development.

Russian aggression adversely affected the economy of Ukraine and emphasized the need to adapt the best practices of EU countries to determine steps to restore the country’s competitiveness. This study aims to determine the influence of the innovative development of countries on their competitiveness and identify prospects for Ukraine’s post-war economic recovery. The study constructed neural networks to assess the relationships between the factors of innovative development and the competitiveness of the EU countries and Ukraine. Six main factors of innovative development of countries are identified: “innovations in business (S1),” “intellectual property (S2)”, “innovations in industry (S3),” “eco-innovations (S4),” “innovation management (S5),” and “digital innovations (S5).” Groups of factors are determined by the strength of influence (strong, moderate, or weak). For Ukraine, S1 and S6 have a strong effect (33.3%), S5 shows moderate (16.7%), S2, S3, and S4 show weak effects (50%). For EU countries, S1 and S6 have a strong influence, S2 and S3 – moderate, S5 and S4 – weak. This comparative analysis concluded that EU countries consider intellectual property, green economy, and state innovation policy as key components of their competitiveness. The results discovered a weak relationship between intellectual property protection, innovation in industry, and competitiveness of Ukraine compared to EU countries. However, digital innovations significantly and positively affect Ukraine’s competitiveness.