Foresight and STI Governance

Efficiency Assessment of the Artificial Intelligence Market: Exploring the Limits

Yaroslav Kouzminov — 2025-12-17

The development of Artificial Intelligence (AI) is significantly impacting the global economy, transforming corporate strategies and enhancing operational efficiency. This study aims to analyze the relative efficiency of the Generative AI (GenAI) market, considering the market size of chips, servers, and data center infrastructure required for its operation, and comparing these market sizes with the market size of AI solutions. The study hypothesizes that the current AI market, despite its rapid development, is characterized by a catching-up nature compared to the component market and does not yet fully reflect the proportional relationship between the volumes of these markets (the hardware market and the AI solutions market).

It is emphasized that the capital expenditures of technology giants on the creation of AI infrastructure have significantly increased, which may require decades to achieve a balance between the size of the hardware market that supports AI and the size of the AI solutions market itself. To assess the efficiency of the AI market, the Data Envelopment Analysis (DEA) methodology is applied, considering «inputs» (the market size of components) and "outputs" (the market size of AI solutions). The results of the DEA analysis of the GenAI market dynamics from 2016 to 2024 reveal a non-linear nature of development, starting in 2021, with a trend reversal and a decrease in efficiency indicators, which confirms the hypothesis of the catching-up nature of AI technologies compared to the component market. It is shown that fluctuations in efficiency begin three years after the deployment of the first large language models, indicating their significance for the demand for hardware, but not yet demonstrating sufficient returns in the form of a comparable growth of the AI solutions market.

The limitations of the study are associated with the time interval of analysis (2016-2024) and the composition of the companies included in the analysis, which covers a majority, but not the entire, market. The novelty of the study lies in the application of DEA analysis for a comprehensive assessment of the AI market considering, but divides the component market and the technological solutions market of AI usage. The results obtained provide a critical assessment of the prospects for the development of the AI market and identify an imbalance between the «soft» (technological solutions) and «hard» (components) markets, identifying the potential for more efficient exploration and use of generative models. However, the results require further development in terms of describing the effects in different sectors of the economy.

Transformational Urban Transitions towards a New Type of Sustainability

Michinaga Kohno — 2025-12-17

The need to comply with new economic models (Industry 4.0 and 5.0) is driving countries, organizations, and sectors toward technological transformation. The implementation of such large-scale projects requires a certain level of maturity and a special resource base to overcome various obstacles. The article analyzes the key components of specific potential for such initiatives based on the experience of urban transformation, which can serve as a model for other socio-economic systems. Empirical data from Japanese and European cities reveal key patterns that influence the outcomes of the transition. The role of narrative tools in building consensus among all participants is emphasized, without which transformational projects risk adding to the dominant statistics of failures.

The analysis of factors presented in the article enriches our understanding of the specifics of transformational transitions, not so much from the point of view of technological capabilities, but rather from the perspective of contextual and cultural differences and a certain degree of maturity of urban management teams and the population. Its results may be useful for leaders initiating long-term radical transformations in various sectors to transition to sustainability and a new quality of development.

Towards Innovative Production Model: Digital Transformation in Small and Medium Enterprises

Nicola Magaletti — 2025-12-17

The transformational transition towards Industry 4.0 poses a particularly challenging task for companies of all sizes, especially if their level of digital maturity is low. This is especially true for small and medium-sized businesses facing resource constraints. Even with the availability of advanced technologies such as the Internet of Things, artificial intelligence, and big data analytics, digital transformation may not happen if the company’s management models, strategy, and culture are not adapted to the increasingly complex context.
This article presents a unique and rare transformation pathway in extremely unfavourable conditions. The case of Tecnomulipast (Italy) challenges established ideas about how to overcome structural constraints, demonstrates the possibility of breaking the old paradigm and escaping “path dependency,” and reveals a changing nature of potential for sustainable development. The study fills managerial, technological, and contextual gaps in research on the digitalization of SMEs and offers conclusions that are of practical use in shaping regional innovation policy.

Beyond compliance: evaluating the governance capacity of public digital platforms in sustainable supply chains

Paolo Pariso — 2025-12-17

This article examines how national digital platforms support the governance of sustainable and resilient public service supply chains. While digital infrastructures are central to procurement and investment planning, their role in enabling value co-creation and policy integration remains underexplored. Drawing on Public Service Logic, Public Service Supply Chain Management, and Procurement 4.0, the study analyzes five Italian platforms—ANAC, OpenCUP, MePA, Italia Domani, and ReGiS—through an eight-indicator evaluative framework. Based on document analysis and maturity modeling, results reveal divergent levels of interoperability, traceability, and strategic alignment. ReGiS shows high technical maturity but limited transparency; Italia Domani aligns with policy goals but lacks operational integration. Overall, platforms exhibit a procedural focus with limited systemic coordination. The findings highlight the persistence of compliance-driven digitalization and call for modular governance, citizen-oriented design, and predictive data ecosystems. This study contributes to understanding how digital infrastructures shape public value through supply chain reform.

Rethinking Global Education for Sustainability: Learning from East Asia’s Relational Turn

Marcus Anthony — 2025-12-17

Global development programs focused on addressing major challenges and achieving sustainability have revealed a systemic gap between the production of academic knowledge and real social transformation. This paper argues that the dominant twentieth-century model of higher education, rooted in disciplinary silos, objectivity, and linear knowledge transfer, cannot adequately address the complex, interdependent crises. A logical question arises: how are the education systems of leading countries today accumulating transformative potential to gain a real ability to contribute to universal prosperity?

In response, the paper explores the educational paradigms of China, Japan, and South Korea, illustrating how East Asian philosophies, particularly Confucianism, Daoism, and Buddhist humanism, offer alternative ontological and pedagogical foundations for transformation. These traditions emphasize relationality, ethical self-cultivation, and self-emptying as modes of transformative engagement. By integrating these cultural resources with the practical frameworks of Causal Layered Analysis (CLA), the paper assesses how current East Asian reforms reflect different depths of change across structural, paradigmatic, and mythic layers.

Ultimately, the study proposes that sustainable educational transformation requires more than policy reform; it demands a civilizational shift from mechanistic cognition toward metamorphic learning, wherein education fosters planetary wisdom, systemic awareness, and compassion as the basis for sustainable human futures.

This article is a part of the special issue “Transforming Education in the 21st Century: Foresight and Sustainable Development”
Guest Editors: Asad Abbas (Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Monterrey, Mexico), Ahsan Ali (Zhejiang Sci-Tech University, Hangzhou, China), Jose Luis Martin-Nuñez (Instituto de Ciencias de la Educación, Universidad Politécnica de Madrid, Madrid, Spain), Mehul Mahrishi (Swami Keshvanand Institute of Technology, Management & Gramothan, Jaipur, India)

Cutting-edge Technologies for Analyzing Student Feedback to Inform Institutional Decision-making in Higher Education

Sabur Butt — 2025-12-17

Aspect-Based Sentiment Analysis (ABSA) has emerged as a powerful tool for deriving actionable insights from qualitative feedback in education. This study presents a multitask learning framework to analyze student evaluations of teaching (SET) by extracting and classifying opinions on specific aspects of teaching performance. Leveraging a novel and first open-sourced dataset of 6,025 Spanish-language comments, the proposed framework integrates opinion segmentation and multi-label classification to capture nuanced feedback on nine predefined aspects, such as "Teaching Quality" and "Classroom Atmosphere." Applications of this approach extend beyond SET analysis, offering valuable insights for course improvement, faculty assessment, and institutional decision-making in higher education. The paper compares the performance of fine-tuned transformers (BERT and RoBERTa) with large language models (LLMs), including GPT-4o, GPT4o-mini, and LLama-3.1-8B, using both fine-tuned and Few-shot Chain of Thought (CoT) methodologies. Evaluation results reveal that fine-tuned GPT-4o outperformed all other models, achieving a weighted F1-score of 0.69 for positive aspects and 0.79 for negative aspects, while Few-shot CoT approaches demonstrated competitive performance with greater scalability and interpretability. Our findings demonstrate the framework's potential to transform unstructured feedback into structured insights, aiding educators and institutions in enhancing teaching quality and student engagement.

Imagining the Digital University: Infrastructural Logics and Institutional Futures in the Global South

Olga Ustyuzhantseva — 2025-11-12

The article examines how national digital transformation strategies in higher education articulate divergent institutional futures in India, China, and South Africa. A comparative analysis of policy documents from 2013–2024 demonstrates how governance rationalities and infrastructural designs redefine the epistemic role, operational logic, and autonomy of universities. Digital transformation is conceptualized not as technical modernization but as a socio-political project encoding institutional imaginaries and normative frameworks. Three dominant models are identified: the Chinese model—a technocratic centralized strategy with algorithmic monitoring and STEM prioritization; the Indian model—open digital architectures preserving institutional discretion within a federal governance structure; the South African model—flexible decentralization emphasizing equity and epistemic decolonization.

These models reveal contradictions between strategic coordination and autonomy, equity and efficiency, infrastructural control and pedagogical reflexivity. The study demonstrates that digital infrastructures determine not only access to education but also academic temporality, agency, and epistemic authority. The proposed understanding of digital transformation as an infrastructural imaginary contributes to critical debates on higher education reform and global governance under conditions of systemic uncertainty.