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News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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AI Implementation by Small Entrepreneurs in Russia: Flowers Grow also on Stones

Central European Business Review. 2026. Vol. 15. No. 2. P. 69–90.
Dormidontova Y.

This study examines the individual factors of artificial intelligence (AI) implementation by small and medium-sized enterprise (SME) owners, based on a survey of 499 respondents in Russia. Drawing on Innovation Diffusion Theory, the Technology Acceptance Model (TAM), and stakeholder-oriented sustainability approach, the analysis shows that SME owners who already use AI for private purposes are more likely to implement it in their businesses. Owners who see AI as potentially damaging to their businesses are also more likely to adopt it. Those who believe AI will harm the economy overall are less likely to use it. Younger entrepreneurs are more inclined to adopt AI. Education is not significant. Owners of larger SMEs and those in urban areas are more likely to adopt it. The findings challenge TAM based evidence regarding the role of hedonic motivation: in this post-transitional economy, expected damage to one’s own business emerges as a key driver of AI implementation by SMEs. Implications for Central Eastern European audience: As AI penetration grows in CEE, SME owners with personal AI experience should be more likely to implement AI in business, with younger entrepreneurs expected to lead adoption, similar to Russia. However, unlike Russia, urban-rural differences in CEE may be less pronounced due to a closer distances between cities and rural areas, potentially diminishing the role of settlement in AI adoption. Policies emphasizing practical, experiential learning opportunities may be more effective than formal education, given the limited additional technical skills required for AI implementation in SMEs.

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: English
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Keywords: small and medium-sized entrepreneurshipInnovation adoptionArtificial intelligence (AI)
Publication based on the results of:
Russian small business under external shocks: dynamics of adaptation (longitudinal study) (2024)
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