Approaches to factor assessment of innovation environment at the stage of initiating projects and strategies to enhance competitiveness of higher education, under which regional governments and universities can cooperate to obtain additional federal resources, remain poorly investigated. The purpose of the article is to evaluate the development level of regional higher education systems using the case study of two constituent territories of the Russian Federation – the Novosibirsk and Nizhny Novgorod regions, as well as to identify barriers hindering the transfer of innovations from universities to regional economy. The work draws upon the institutional provisions of public strategic planning. The research methods include SWOT and PESTEL analysis, correlation analysis, content analysis of regulatory acts, etc. The information base covers data from a survey of 477 respondents on the influence of macro-environment factors on administrative staff of universities, as well as reports of the Ministry of Education and Science of the RF, the Federal State Statistics Service (Rosstat), and the Federal Service for Intellectual Property (Rospatent). Comparison of government regional programs for scientific and technological development in the two territories with the results of analysis of the innovation level and the state of higher education revealed imperfections in procedures for registration of intellectual activity results, as well as the lack of coordination between regional authorities’ formal approaches to selecting indicators for stimulating R&D and actual activities to improve competitiveness and innovation activity of universities. The screening of the development level and the innovation environment of the two regional higher education systems, reinforced by the dynamics of statistical data and processed in Python with weighted coefficients, helped identify and rank five key factors having a potentially negative impact on the competitiveness of regional universities: a decline in the number of universities in the region; failure to meet federal project targets; reorientation of universities towards the secondary vocational education sector; critical wear of infrastructure; insufficient integration of university project management as a channel of interaction with the state. The enhanced methodological framework for factor assessment of the innovation environment provides greater authority for managerial decisions in setting goals, defining project measures, and formulating development strategies for universities based on identification of key barriers.
Introducing digital solutions in production and management has become a priority growth strategy for industrial enterprises that is driven primarily by current sectoral and market dynamics rather than internal goals. The article provides theoretical and empirical foundations for typologization and identification of generic digital transformation strategies used by Russian industrial firms. The research methodology builds on the theories of industrial organization and strategic management, as well as the concept of digital maturity. Dynamic, statistical, and industry analyses were used as research methods. The empirical evidence is comprised of data on industrial sectors provided by the SPARK-Interfax system and the Russian State Industry Information System (GISP) of the Ministry of Industry and Trade of the Russian Federation. The article proposes and theoretically substantiates a two-dimensional model for identifying industrial enterprises’ generic digital transformation strategies relying on the composite indices of structural pressure and digital maturity. By integrating their values, we present a matrix and distinguish between four generic digital transformation strategies: catch-up digital modernization, inertial digitalization, proactive digital leadership, and the transformation strategy. The empirical analysis demonstrates that only two of these strategies are currently implemented in practice: the strategy of catch-up digital modernization is characteristic of enterprises in the radio-electronics, chemical, and pharmaceutical industries, while the strategy of inertial digitization is typical of firms in agricultural machine building, machine tool engineering, and heavy engineering industries. Identifying generic strategies will enable industrial enterprises to determine priority directions of digital transformation, while allowing executive authorities to design support and incentive programs at the sectoral level.
In the context of the ongoing transformation of the Russian cosmetics market shaped by geopolitical factors and import substitution policy local producers increasingly face the need to comprehend unconscious mechanisms of consumer decision-making. The article presents experimental research on consumer behaviour when choosing cosmetic products using neuromarketing technologies. Methodologically, the study relies on the concept of sensory marketing and neurophysiological approaches to examining consumers’ cognitive-affective responses during visual product evaluation. The research used neuromarketing tools (eye tracking, the Facial Action Coding system (FACS), electroencephalography (EEG)) and SPSS Statistics 23.0 software for statistical analysis. Empirical data were obtained from three laboratory experiments on the packaging of seven facial cream brands by local Crimean producers, carried out from September to December, 2025 with 48 participants. Analysis of eye movement patterns revealed that the logo as a key brand identifier attracts only limited visual attention, which indicates that local brands are scarcely recognizable. A positive purchase decision is determined by consumers’ integrated emotional response to the packaging (a positive vector, high valence, and arousal) triggered by visual attention patterns, which together form a predictive model of choice. Using the case study of locally produced facial cremes, the paper proposes a methodology for ranking products by neurophysiological metrics. The findings allow evaluating the attitude towards local brands, predicting consumer choices based on responses to packaging, and optimizing products assortment, packaging design, and promotional strategies.
The rationale of this paper is that AI-enabled digital banking applications enhance consumer experiences and customer relationships; however, holistic findings on the impact of these applications on customer satisfaction and loyalty, beyond their benefits and adoption, are limited. The study aims to reveal the impact of AI-powered digital banking applications on customer loyalty by examining consumer adoption, experience, and satisfaction levels. The theoretical basis is grounded in an integrated research model that correlates variables from the technology acceptance model and the expectation confirmation model. The data and research methods comprise 510 participants using AI-enabled banking applications in Türkiye, employing a quantitative research design and an online survey technique. The data obtained were analysed using structural equation modelling (PLS-SEM). The findings indicate significant effects of perceived ease of use on perceived usefulness, as well as the relationship between perceived usefulness and confirmation on satisfaction. Furthermore, significant effects of satisfaction on continuance intention and continuance intention on customer loyalty were found. However, the direct effect of satisfaction on customer loyalty is not significant. This result suggests that satisfaction plays an indirect role in the formation of customer loyalty through continuance intention. Therefore, satisfaction and continuance intention are critical variables in strengthening customer loyalty in AI-enabled digital banking. Increasing customer satisfaction may not be sufficient for enhancing customer loyalty: banks must devise strategies to support customers’ intentions to use applications regularly
Post-growth as a set of conditions for the economic activity constitutes an important factor in municipal strategic planning. The study aims to assess the practice of strategic planning of municipalities’ development at the post-growth stage. Methodologically, the research rests on the theories of strategic planning and management, and the concept of sustainable development. The methods include semantic mapping, synthesis, comparative, structural, and content analysis. The evidence base consists of the 2010 and 2015–2024 socio-economic indicators, as well as strategic planning documents of the Sverdlovsk oblast’s municipalities. The article proposes a method for evaluating the municipalities’ socio-economic development strategies, which involves five elements: the main goal in the context of post-growth; the use of the economic growth premise; the consideration of municipal resource deficits; mechanisms for overcoming resource constraints; and the integration of the principle of responsibility into municipal governance. Results of testing the method, using data from six territories, showed that the strategizing of the municipalities under a post-growth scenario – where resource constraints lead to a decrease in quality of life and standard of living – is characterized by the introduction of elements that mitigate negative consequences. At the same time, the strategizing of the municipalities with a reproduction base that allows them to maintain the achieved quality of life in the long term is characterized by inertia. The paper concludes that the strategies of the municipalities under post-growth should consider resource shortages, formulate goals in qualitative rather than quantitative terms, focus on the territory’s fundamental problems and ways to overcome them, and provide for the integration of the principle of responsibility into municipal governance
