The implementation of information and communi- cation technologies (ICT) requires a strategic purpose for the achievement of business objectives. In this context, the absorption capacity, that is, the way in which knowledge is identified, processes and good practices are assimilated, business models are transformed and therefore performance is achieved, becomes an alternative for the implementation of these new technological tools by management. This research explores how the effective implementation of digital technologies modulates the connection between organizational capacities to assimilate knowledge and innovation achievements within the business context. The analysis was based on 487 managers from multiple economic sectors, processed by modeling structural equations with SmartPLS. The findings highlight a direct and statistically significant impact of digital technologies on two critical dimensions: the potential capacity to internalize external knowledge (PACAP) and concrete indicators of innovation performance. From praxeology, the results suggest that technological adoption acts as a catalyst in the transition between the identification, assimilation of external knowledge and incorporation of good practices towards reflection processes within organizations that allow progress in the transfor- mation of business models and therefore influence organizational performance. These practices suggest that digital technologies strengthen the organizational mechanisms for processing external knowledge, thus facilitating its conversion into innovations. In addition, the sustained improvement of innovation performance includes not only absorption capacities, but also their strate- gic articulation with appropriate technological infrastructures. Therefore, organizations that consciously integrate digital tools into their knowledge management processes are suggested that they could be more effective in transforming information inputs into innovative results. This synergistic effect highlights the need to align iteration processes in the implementation of new techno- logical tools with the development of organizational competencies to acquire, process, interpret and apply knowledge.
Financial sustainability in Turkish foundation universities is examined through the interaction of revenue diversification, cost management, and enterprise risk management (ERM). It addresses how universities sustain financial viability under funding constraints and institutional uncertainty. Drawing on resource dependence theory and the resource-based view, the study develops and tests an integrated model in which ERM operates as a mediating mechanism linking external resource strategies and internal organizational capabilities. Data were collected from senior administrators in foundation universities and analyzed using partial least squares structural equation modeling. Results show that revenue diversification has a positive direct effect on financial sustainability, while cost management has no significant direct effect. Both strategies influence financial sustainability indirectly through ERM. These findings indicate that financial strategies do not independently generate sustainability outcomes but require integration within structured risk governance systems. ERM emerges as a central mechanism enabling coordinated financial decision-making under resource constraints and uncertainty. The study contributes to higher education literature by highlighting risk governance as a linking mechanism between strategy and performance and extends understanding of financial management in non-Western higher education contexts. It offers practical implications for strengthening institutional resilience through embedded risk management in financial planning.
The literature examining the impact of artificial intelligence (AI) on higher education often boils down to the question of whether AI will replace teachers. This study examines the issue more broadly — through the lens of the diverse nature of academic tasks. A multidimensional analysis is conducted to show how academic work is being redistributed among tasks that AI can replace, augment, or cannot meaningfully displace. The study uses qualitative content analysis on a purposive corpus of 46 documents, including scientific papers, reports, policy and practitioner texts, and higher education commentary published between 2020 and 2026. A 3×3 analytical matrix was developed, reflecting the degree of distribution of functions between humans and AI ("Replace," "Augment," or "Human-dominant") across three basic dimensions of academic activity (teaching, research, and socio-technical work). The findings show that AI is strongest in codifiable and routine tasks such as basic educational content generation, objective grading, literature processing, drafting, and administrative support. By contrast, tasks involving judgment, ethics, interpretation, mentoring, relationship-building, assessment design, governance, and public trust remain human-dominant. The research concludes that AI does not eliminate academic work; it reorders it, shifting value from content transmission toward learning design, interpretive expertise, and institutional stewardship.
The transition to a knowledge-based economy increasingly depends on the accumulation and effective use of regional intellectual capital (RIC). This challenge is particularly acute for resource-oriented countries seeking to reduce their dependence on natural resources and achieve sustainable long-term development. However, its immediate economic effects of RIC remain unclear. The paper examines whether regions that accumulate RIC are able to convert it into short-term economic dynamics and whether such accumulation creates the foundations for long-term regional transformation. Using panel data for regions of Kazakhstan, the empirical strategy distinguishes between two complementary dimensions of RIC impact. The structural effect of RIC is estimated using a two-way fixed-effects panel model, while the short-term conversion effect is operationalized through a novel indicator - the Regional Intellectual Capital Conversion Elasticity (RICCE_Elasticity). The results show that RIC functions primarily as an accumulated institutional resource whose development impact depends not only on its stock, but also on regional mechanisms that enable its economic conversion. By distinguishing between accumulation and conversion effects, the paper contributes to the literature on intellectual capital and regional development.
Technological development dynamics underscore the relevance of a comparative analysis of national priorities in science and innovation. The article identifies and typologizes promising technologies enshrined in the development strategies of 19 countries: technological leaders—the United States, Japan, Germany, the United Kingdom, South Korea, Canada, Australia, Spain, and Italy—and countries of the Global South—Brazil, India, China, South Africa, the United Arab Emirates, Egypt, Ethiopia, Indonesia, Iran, and Saudi Arabia. It tests two hypotheses: whether a universal “core” of promising technologies exists and whether stable groups of countries with similar innovation profiles emerge. The empirical base comprises two to five strategic documents for each country, dating from 2018 to 2026. The analysis employs frequency, semantic, and content analysis; calculation of the Revealed Comparative Advantage (RCA) index across 12 thematic sections and 86 subsections; and k-means clustering. The analysis confirmed both hypotheses: despite a shared core of priorities, countries differ in their modes of strategic concentration, forming several types of profiles. Although the study is limited to declared rather than actual outcomes, its contribution lies in the systematic comparison of the strategies of advanced economies and Global South countries, the identification of specialization models, and the development of conceptual approaches to assessing technological sovereignty in a multipolar world.
