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
International markets offer significant appeal for small and medium-sized enterprises (SMEs) seeking to scale their businesses. However, there are often numerous obstacles to this journey, especially complex for companies lacking the experience of international expansion. The purpose of the article is to fill the existing gap in the literature by thoroughly analysing the institutional factors influencing SME internationalization and identifying emerging trends that shape strategic decision-making in foreign markets. The research combines institutional theory and resource-based view, acknowledging regulatory structures and cultural norms in SMEs’ global expansion. To address the research problem, bibliometric and co-citation analyses were performed, accompanied by topic modelling to classify key topics and pinpoint areas for further research. The empirical evidence base of the study was compiled using the Scopus database. The initial search query yielded 1,272 publications, which were then sequentially screened against predefined criteria. After applying Scopus Metrics source filters (Top-10 journals) and a final keyword refinement, the final sample comprised 188 peer-reviewed journal articles. The findings indicate that SMEs adapt market entry strategies to institutional influences while leveraging resources and structures. The current trends in digital transformation and the impact of social capital are highlighted as essential factors that play a crucial role in the internationalization of small and medium-sized enterprises. The proposed conceptual framework aims to integrate institutional determinants with the internal capabilities and strategic decisions of SMEs, providing a comprehensive understanding of their operations in foreign markets.
Establishing entrepreneurial management systems to enhance corporations’ innovation performance requires appropriate design methodologies to be developed. The initial stage of the design process involves creating a method for assessing stakeholders’ potential within corporate entrepreneurial networks as the primary mechanism for managing the composition of actors, which constitutes the purpose of this study. The methodological framework is grounded in the theories of entrepreneurship, networks, and potentials. The methods of comparison, analysis, and synthesis, along with cartographic visualization tools, were applied. The study relies on data from SPARK-Interfax, the Federal State Statistics Service of Russia (Rosstat), the Agency for Strategic Initiatives, and the Presidential Grants Foundation. The authors’ method for assessing entrepreneurial potential of actors in the national economy is based on comprehending entrepreneurship through its distinctive characteristics (innovativeness, creativity, openness to knowledge sharing, and rational risk-taking) and centers around designing and reconfiguring the composition of actors within large corporate entrepreneurial networks. Empirical testing with data from 83 Russian regions reveals that entrepreneurial potential is highly differentiated across the territories in terms of both integral indicators and actor groups. The study identifies regions leading in specific components of entrepreneurial potential: the highest potential of infrastructural business is observed in Moscow; the potential of civil society institutions that promotes the development of distinctive entrepreneurial characteristics is the greatest in the Magadan oblast; the Republic of Kalmykia excelled in the population’s educational and communicative levels; and the Republic of Tatarstan exhibited the most effective public administration practices for implementing innovation-driven strategies. The results confirm that combining the potentials of actors from various groups yields the highest systemic entrepreneurial capacity, which underscores the effectiveness of a network approach to organizing corporations’ entrepreneurial and innovation activities
Industrial companies’ strategic management increasingly faces a gap between declared technology priorities and the practical capability to convert external technological signals into decisions on R&D portfolios, investment allocation, and technology roadmaps. This study develops a comprehensive tech mining approach that turns patent analytics into an operational tool for strategic forecasting. The methodological basis combines the principles of the tech mining concept as an instrument for integrating text analysis with strategic technology management, technology roadmapping structured according to the multi-level architecture of “market–product–technology”, as well as the technology readiness level (TRL) model used to assess the maturity of technological solutions. Among the research methods are topic modelling (LDA) of a patent corpus, qualitative interpretation, multi-criteria ranking of technological niches, and content analysis of patent wording to infer technology maturity when direct stage information is unavailable. The evidence base comprises patent documents from the WIPO PatentScope database related to microalgae-based technologies. The study identifies 11 thematic clusters structured around the value creation core (biomass and biofuel production) and establishes infrastructure areas, growth points, and blind spots of the industry. Of five areas of the roadmap, the greatest maturity and commercial potential are characteristic of integrated solutions (bioremediation, CO₂ utilization). The proposed map links the results of patent analytics with R&D prioritization and investment decisions over short, medium, and long terms.
The geopolitical situation and external shocks of 2020 and 2022 significantly altered the development of Russia's industry, intensifying the need to analyze organizational change as a key instrument of adaptation. The article examines the impact of structural and strategic organizational change on the growth of Russian industrial enterprises in both the market (revenue dynamics) and social (employment dynamics) contexts. The theories of organizational change, as well as the concepts of competitive advantages and business resilience under external shocks constitute the methodological basis of the research. Econometrics methods were used, including the assessment of the ordinal logit model revealing the direction and significance of the effect that various types of change exert on enterprises' performance. The evidence base contains data from the fifth round of the survey "Russian Enterprises in Value Chains - 2022" by the Institute for Industrial and Market Studies, HSE University, covering 1,879 manufacturing companies located in 71 regions of Russia. Over the period under review, investments in fixed assets were a stable driver of growth, structural change exerted a more predictable impact on employment, while strategic change were associated with heterogeneous effects. Our analysis highlighted differences in the response of revenue and employment to the changes implemented during the pandemic, the recovery, and the onset of large-scale sanctions, yet the impact of the firms' investment projects proved to be the most pronounced and stable. Product innovations and switching to new Russian suppliers had a positive influence on growth in 2020 and a negative effect in 2022. The raw-materials exporter status boosted the companies' growth during the pandemic, while the importer status did so during the sanctions period. Under sanctions, radical managerial decisions gain greater significance, while the impact of gradual organizational transformations diminishes. The research results clarify the mechanisms of industrial firms' adaptation to crises and provide a basis for devising comprehensive approaches to managing organizational change.
Management problems when creating specific types of goods (products, services) differ from those emerging in the technological sphere, since technology is a special product representing a method of influencing or changing the state of an object to achieve specific goals. In this regard, technology competition and the processes of adding or substituting technologies create a range of special tasks and generate original effects that are not typical of purely consumer goods. The paper centers on core management objectives within a specific management object, namely technologies, which forms the independent research area “economics of technology”. The relevance is attached to the effect of technological dualism and the processes of substituting and adding technologies. The research methodology includes the elements of control theory for large-scale systems, technological development theory and the concept of technological modes. The empirical evidence is comprised of data on technology development retrieved from the Federal State Statistics Service of Russia (Rosstat). The research methods are typification, generalization, structural and statistical analyses. The study formulates the main theoretical objectives of technology management (substitution, overcoming technological dualism, developing the core and the periphery of technology, etc.) and presents different approaches in the field of macromanagement with reference to the technological modes and the coordinate system “creative destruction – combinatorial build-up”. We have singled out the management modes of technological development with an emphasis on technological substitution or addition to attain the goals of technological renewal using the case of the Russian economy. The paper outlines an option for differentiating technology policy tools to secure technological sovereignty and leadership and shows that the objective of optimal control must be revised in light of the considerable uncertainty inherent in technological competition.
While traditional emotional intelligence (EI) models have laid a strong foundation, they fall short in capturing the emotional demands of hybrid work, where adaptability, empathy and digital trust are not optional but crucial for an organization’s performance. The study explores the emotional landscape of hybrid IT work settings, where employees handle the invisible boundaries of remote communication, digital overload and limited face-to-face cues. Methodologically, the study is guided by established perspectives on competency-based theory and socio-technical systems theory in the context of hybrid work. The paper explores the behavioural foundations that shape the four core components of EI – self-awareness, self-management, social awareness and relationship management – using exploratory and confirmatory factor analyses applied to 422 responses from Indian IT professionals. Six distinct factors (empathy, self-expression, interpersonal influence, emotional clarity, trustworthiness, adaptability) emerged as critical drivers shaping the emotional competence in this evolving workspace. To understand how these factors interact, network analysis was conducted, revealing two interrelated clusters: intrapersonal drivers, supporting self-regulatory competencies, and interpersonal drivers, shaping social capabilities. Self-expression emerged as the central factor, bridging the two clusters and shaping the overall emotional effectiveness. The findings extend EI theory into the digital age and provide a tailored and practical framework for organizations to develop emotionally sustainable workplaces and guide future leadership development
Geopolitical changes have transformed retail trade in Russia, while strengthening the role of local brands and private labels (PLs) amid limited access to international markets, which necessitates a rethinking of consumer loyalty factors. The study aims to identify and systematize key factors affecting consumer loyalty to brands, retail chains, and PLs, as well as to determine their differences. The theory of customer loyalty constitutes the methodological foundation of the research. The information base consists of 6,615 articles from Scopus and Dimensions databases, covering the period from 1994 to 2025. The key research method is content analysis of scientific publications following the PRISMA standard. The review of academic sources confirmed significant differences in consumer loyalty factors: brand loyalty is primarily determined by emotional factors (love for brand, trust); retail chain loyalty relies on functional factors (perceived quality, loyalty programmes) integrated with omnichannel strategies; private label loyalty combines emotional and functional factors (perceived quality, price sensitivity, trust in the retailer), thus fostering utilitarian loyalty. The research identified gaps in the academic literature on the following topics: the integration of emerging technologies (artificial intelligence) for brands, digitalization and omnichannel strategies for retail, and emotional evolution for PLs. To address the methodological gaps, mixed empirical research is recommended, aimed at incorporating loyalty to brands, retail chains, and PLs within a unified model.
The active implementation of intelligent decision support systems (IDSSs) entails changes in management practices. The article aims to assess the systemic impact of technological, organizational, and human factors of IDSSs implementation on the transformation of management methods in Russian companies. The research methodology resides in a systems approach to management. Regression analysis was used as the research method. To verify the robustness of the results, the study relies on the method of sequential construction of four nested multiple linear regression models with the addition of control variables. The evidence base consisted of data from an online survey of 104 executives and employees of Russian companies, who are experienced in implementing or operating intelligent systems. The paper identifies statistically significant systemic relationships between the factors under consideration and the transformation of management practices. The organizational factor was proven to contribute the most to the management system's transformation. The research results establish the robustness of the statistical relationships to the influence of the company size, industry, and regional specificity and empirically confirm the importance of a comprehensive approach to the digital transformation of management. The findings provide a basis for developing IDSSs implementation strategies. Prospects for further research involve conducting longitudinal analysis to clarify the cause-and-effect relationships between the use of these systems and the transformation of management methods.
Job burnout, becoming increasingly widespread lately, reduces employee productivity, which has an adverse impact on global economy.The article presents an analysis of academic publications on the economics and management ofjob burnout, reveals key topics and shapes the agenda for future research. It builds on a review of over 650 scholarly works addressing burnout syndrome within business, economics, and decision-making theory. Topic modelling based on the BERTopic tool was applied, followed by a subsequent qualitative analysis of the identified themes. We distinguish between 14 topics categorized into three groups: general issues, specific issues, and industry-specific aspects. Most publications focus on the prerequisites and outcomes of burnout in the field of education. Experts adhere to three theoretical frameworks: job demands and resources, conservation of resources, and the multidimensional model of burnout. Research into fundamental burnout mechanisms is of the greatest academic influence, though there is a growing relevance of digitalization issues. According to the studies reviewed, job burnout arises from the imbalance between resources and demands. Measures to prevent this syndrome should be multi-level and aimed at strengthening individual, work-related, and organizational resources. The identified topics revolve around academic, geographical, and industry-specific clusters, which is attributable to the dominant social and economic discourse.
Amid current demographic pressures, the Russian economy faces the need to integrate national working-parent support policies into corporate HR management practices.The study seeks to provide an empirical evaluation of both effects and barriers to the implementation of family-oriented flexible work arrangements within corporate standards for supporting employees with parental responsibilities. The research methodology builds on role theory, rational choice model, and new institutionalism. At the empirical level, we carried out an expert survey involving representatives of 641 companies in the Ural economic region. Expert assessments were analysed using the methods of descriptive statistics, such as mean values and the Kruskal-Wallis test. Narrative analysis was applied to cluster the expert recommendations by areas of support. The findings reveal that employers are poorly informed about the provisions of the national Corporate Demographic Standard. Corporate initiatives to support staff with family responsibilities are more prevalent in large companies compared to medium-sized and small firms. Implementing flexible schedules, part-time work, and remote work offers several advantages, namely reduced employee turnover, increased staff loyalty, and improved labour productivity. The results show that flexible work arrangements have a limited, though still positive, impact on fertility motivation. Among the barriers to implementing family-oriented practices are: difficulties in organising individual work schedules, technological constraints, and potential increased dissatisfaction among employees without parental responsibilities. The proposed model for integrating family-oriented work arrangements into HR management policy can be used in corporate social programmes.
Ideology is an integral part of modern economics that reflects the use of appropriate mental models and shapes the vision of economic processes. However, existing academic literature lacks analysis of dirigisme as an economic ideology. The purpose of the paper is to analyze the position of dirigisme in Russian economic science. Methodologically, the research rests on the narrative economics approach that facilitates the identification of concise theoretical narratives focusing on the relationships between events, facts, and their interpretations. The authors applied the methods of quantitative and qualitative text analysis through machine learning: classification using vector representations (embeddings), and analysis of relevant n-grams. Empirical data cover a corpus of 40,045 Russian-language scientific articles on economics published between 1992 and 2023 that are attributed to the ideology of dirigisme. According to machine analysis, dirigisme is the most prominent ideology in contemporary Russian economics. Having considered the most common bigrams and trigrams, we identified three stages – early, intermediate, and modern – in the development of this ideology in Russian economics. The paper also formulates three its theoretical narratives: “dirigisme and technocracy”, “dirigisme and eternal lag (catching-up)”, and “manageability of economy”. The findings demonstrate that dirigisme’s elements are formalized through strategic and indicative planning in the Federal Law “On Strategic Planning in the Russian Federation” and related bylaws. The research results contribute to a better understanding of dirigisme as an economic ideology and can be used to analyze public economic policy in Russia
At present, domestic cosmetic companies in Russia lack effective mechanisms for overcoming consumer distrust and adapting to new market conditions created by the departure of leading foreign brands after 2022. This study addresses the need to develop adaptive business models and marketing strategies for local Russian cosmetic brands to cope with consumer distrust and effectively respond to the market turbulence. The research methodology is based on the theories and concepts of business models, marketing strategies and consumer behaviour. The study was conducted as an ad-hoc investigation employing a mixed-methods design. The qualitative exploratory phase included 10 in-depth interviews with consumers, which provided a detailed understanding of their motivations and perceptions of beauty products. The main quantitative phase was carried out through an online survey with 456 respondents. To analyse data, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were applied, which ensured the reliability and validity of the identified factors. The paper highlights key determinants of beauty consumers' behaviour towards Russian local brands, such as a mandatory sensory experience and emotional connection with the client, and presents recommendations for formulating adaptive marketing strategies under current market conditions, namely ensuring close integration of the business model's elements, where environmental and social agendas are not auxiliary, but core components. These findings significantly expand practical knowledge in the field of cosmetic industry in Russia. A comprehensive approach was implemented to explore consumer behaviour under turmoil, employing a mixed-methods methodology to produce recommendations that address the existing theoretical and empirical gaps.
Extraordinary situations such as the COVID-19 crisis affect various financial indicators of companies, including profitability, indebtedness, and liquidity. This study aims to examine the impact of the pandemic on the financial performance of the global aviation industry. The methodological foundation is based on the prospect theory of Kahneman and Tversky. The sample consists of 20 internationally operating airline companies. The analysis covers two periods: the five years preceding the pandemic (2015–2019) and the two-year pandemic period (2020–2021). Fifteen financial ratios, grouped under liquidity, profitability, financial structure, and activity, were calculated and used as data. The data were first weighted using the entropy method, followed by analysis through the TOPSIS and PROMETHEE which are multi-criteria decision-making methods. Additionally, performance rankings for the pre-pandemic and pandemic periods were compared using Spearman rank correlation, revealing consistency between TOPSIS and PROMETHEE results. Both methods indicate that the pandemic generally had a negative effect on financial performance. According to TOPSIS, the most adversely affected companies were Air China, British Airways, LATAM Airlines Group, and Southwest Airlines. According to PROMETHEE, these were Aeroflot Russian Airlines, Air China, Air France, and Alaska Airlines. However, both methods also identified Emirates and Delta Airlines as companies whose financial performance improved during the pandemic. These improvements may be attributed to timely adjustments in financial strategies, enhanced operational efficiency, and agile responses to emerging opportunities. Furthermore, the findings suggest that companies with strong prepandemic performance did not necessarily retain their leading positions during the pandemic, highlighting the disruptive and unpredictable nature of such extraordinary events.
Social and environmental corporate responsibility is becoming increasingly important in organizational operations and production processes. This is due to increased consumer awareness about the importance of ESG factors. Meanwhile, there is the aspect that celebrities play crucial role in influencing purchasing behaviours of the younger generations. The study is devoted to investigating the mediating influence of celebrity endorsement on ESG-oriented purchase. The methodological basis of the study is an integrative approach following stakeholder theory, generational theory, and the meaning transfer model. The data were assessed using econometric methods namely regression analysis. The study used primary data obtained through an online survey of 384 respondents belonging to Generation Z and Millennials. The research findings demonstrate a significant positive impact of ESG-factors awareness and celebrity endorsements on consumer purchase decisions. The study confirmed that celebrity endorsements of ESG-related products significantly influence purchase decisions among Gen Z and Millennials. The empirically proven results confirm the need for not only implementing ESG practices, but also to disseminate consumer awareness about that. Celebrity endorsement significantly mediated the relationship between awareness of ESG practices and purchase decision. The results may be useful in developing strategies to build ESG awareness to stimulate purchase among millennial and Gen Z consumers.
Algorithmic pricing poses challenges of price non-transparency and dynamics. The paper identifies and classifies the mechanisms of consumer adaptation to algorithmic pricing through integration of motives, practices, and contextual factors, as well as segments consumers based on the patterns revealed. The methodological framework incorporates a comprehensive examination of adaptation from the perspectives of economic theories (Becker’s rational choice, Monroe’s price sensitivity), psychological concepts (Bolton’s fairness theory, Lally’s habits theory), and sociological approaches (Bourdieu’s social capital). The study employs the survey method, latent class analysis (LCA), ANOVA, and multinomial logistic regression. The information base consists of primary survey data obtained in the period of April–May, 2025 from 313 Russian consumers. We have identified three consumer segments with unique adaptive strategies: “digital rationalists” (36%) focused on savings and convenience; “controlling optimizers” (30%) sensitive to prices and striving for fairness; and “discount enthusiasts” (34%), who turn saving into a socialgamifying practice and are motivated by psychological reward. Key determinants of the segmentation include age, income level, place of residence, and digital literacy. The findings contribute to the understanding of non-linear adaptation mechanisms and can be used by companies to adjust pricing algorithms considering consumers’ adaptive practices; by consumers – to enhance awareness and make informed decisions in the digital environment; and by government regulators – to develop measures that protect consumer rights from algorithmic discrimination.
