Mr Stefan Rehak, Mr Juraj Šimčisko (p)

A well-established empirical regularity in urban science is that innovation outputs such as patents scale superlinearly with city size. While this relationship is typically summarized by a single scaling exponent, its structural interpretation remains unclear. This paper examines whether urban scaling operates directly through population size or indirectly through mediating mechanisms.
Using data on 606 European Functional Urban Areas in 2020, we test whether inventor sorting and collaboration-network structure mediate the population–innovation relationship. Innovation is measured using fractional patent counts from the European Patent Office, and collaboration structure is captured by the External–Internal (E–I) index derived from co-inventor networks. We estimate a structural equation model to decompose total scaling effects into sorting and network components.
Results show strong mediation through the number of inventors, consistent with a sorting mechanism. Larger cities also exhibit more internally oriented collaboration structures. Once inventor concentration and collaboration orientation are accounted for, population size no longer has a statistically significant direct effect on patenting. These findings suggest that urban scaling of innovation reflects the joint effect of inventor accumulation and collaboration structure rather than a direct impact of population size.

Dr. Valentina Diana Rusu (p), Prof Angela Roman

In the era of digitalisation, the accelerated development of Artificial Intelligence (AI) is profoundly changing the way businesses operate, regardless of their size. While AI adoption offers substantial opportunities for improving operational efficiency, innovation capacity, and market competitiveness, small and medium-sized enterprises (SMEs) face considerably greater structural and resource-related constraints compared to large firms. This study aims to examine the extent to which small and medium-sized enterprises in EU member states use AI-based tools. More specifically, it provides a comparative analysis of the degree of use of AI by businesses, depending on their size and sector of activity, highlighting structural disparities both within and between countries. Based on information obtained from the Eurostat database, the paper uses a research methodology that combines analysis based on key indicators on the use of AI with cluster analysis to highlight progress in the use of AI, discrepancies in the use of AI by categories of enterprises, and to identify both similarities and differences between EU member states. In addition, through our analysis, we comparatively identify how EU countries position themselves from the perspective of the use of AI by SMEs. The findings reveal significant cross-country heterogeneity in AI uptake, alongside persistent gaps between SMEs and large enterprises within the same national contexts. The results demonstrate that AI diffusion in the EU remains uneven, reflecting differences in digital maturity, sectoral structure, and national innovation ecosystems. By systematically mapping these disparities, the study contributes to the literature on digital transformation by offering an updated, comparative, and data-driven perspective on SME AI adoption at the EU level. Given the central role of SMEs in the EU economy, the paper argues that targeted policy interventions at European, national, and regional levels are essential to reduce structural barriers and accelerate AI diffusion. Strengthening SME access to AI capabilities is critical not only for firm-level performance but also for enhancing overall EU competitiveness in the global digital economy.

Dr. Carmen Beatrice Pauna (p), Dr. Yana Tsvetanova Kirilova

Context and Motivation:
Rural areas in Romania and Bulgaria are at a critical juncture, caught between the pressure of depopulation and the need to adapt to Green Deal standards. While agriculture remains the economic backbone, long-term sustainability requires diversification towards high value-added activities. This paper investigates the mechanisms that allow rural communities to remain economically viable without compromising natural resources, such as by transforming biomass and local resources into value-added chains.
Objective of the Study:
The research aims to identify and compare good practices of economic sustainability in rural communities in both countries.
This paper analyses economic sustainability strategies in rural areas of Romania and Bulgaria, assessing the impact of roadmaps developed within the framework of European initiatives. We aim to identify how the sustainable valorisation of specific resources (e.g. agricultural residues in the Vidin region-BG or biomass in the Centru Region-RO) contributes to local resilience.
Methodology:
The research uses an approach based on “Open Innovation Platforms” (OIP), a concept developed in the methodology of the BE-Rural project. We analyze good practices through:
- SWOT analysis of the bioeconomy potential in the selected regions.
- Assessment of local policy co-creation, involving actors from the quadruple helix (administration, academia, business, civil society).
- Benchmarking between bio-based business models implemented in both countries (e.g. pellet production, medicinal plant processing, etc.).
Expected Results:
We appreciate that the results indicate that rural economic sustainability in RO and BG does not depend only on subsidies, but on the creation of local innovation ecosystems. The paper tries to demonstrate that “bottom-up” strategies, which emphasize bioeconomy education and local processing, reduce dependence on external markets and increase the attractiveness of rural areas for young entrepreneurship. The paper provides a set of policy recommendations for regional authorities in order to replicate successful models in other similar areas of the EU.
Conclusions:
- In the studied regions of Bulgaria and Romania there is an untapped potential of biomass (agricultural and forestry residues).
- It is found that the "Triple Helix" Model is insufficient, and it is necessary to switch to the "Quadruple Helix", which involves the involvement of local actors in producing systemic change.
- In order to overcome the "Knowledge Gap" barrier, it is proven that investment in human capital (workshops, transfer of good practices) is more urgent than investment in the technological infrastructure itself.