Monika Kot (p), Katarzyna Kopczewska

Arian Osroosh

The modern economy relies heavily on innovation, especially in high-technology firms (medium-high-tech, high-tech and high-tech knowledge-intensive services). Understanding the socio-economic environment in which these firms operate is crucial to fostering innovation and creating a supportive business climate. While high-tech firms are typically thought to cluster in metropolitan areas, close to similar firms, recent trends suggest that many are also thriving in peripheral locations, outside densely populated business centres.

The aim of this research is to explore the spatial factors that support the establishment and growth of high-tech firms. Key questions include whether proximity to other technology firms, to firms in different sectors, or to urban centres influences innovation and business success. The study also seeks to identify which sectors foster collaboration and clustering with technology firms, and where these clusters come from. All spatial factors are examined in the context of the socio-economic drivers of entrepreneurship and innovation, including supply and demand factors.

Preliminary results indicate a significant increase in high-tech firms in Poland between 2012 and 2021, from 4.3% to 6.08% of all firms, with knowledge-intensive services experiencing the most pronounced growth. Notably, almost a third of these firms operate in low to medium density areas, challenging the assumption that high-tech firms only thrive in metropolitan clusters. Using innovative methods tailored to high-granularity data (point and grid data), this research captures spatial phenomena at a highly localised scale. We apply spatial statistics, spatial econometrics and spatial machine learning to quantify the spatial relationships and identify the drivers of high-tech business location.

This research contributes to a deeper understanding of the spatial dynamics of high-tech firms and provides insights into the development of innovation-driven business environments. The study provides insights to further understand the spatial dimension of entrepreneurial ecosystems.

Arian Osroosh (p), Jan Zenka

Diego Chavarro

Peripheral manufacturing plays a crucial role in regional development across Europe. However, such contexts have traditionally been overshadowed by urban agglomerations and are perceived as less favorable for firms in terms of economies of scale, particularly in knowledge generation and production. While recent studies have begun to address this urban-centric bias by recognizing the distinct characteristics and diversity of peripheral regions as well as their potential advantages for firms, there remains a lack of integrated understanding regarding the knowledge dynamics and supplier–customer linkages of manufacturing firms operating in peripheries. This study aims to address this gap by drawing on both theoretical and empirical research in economic geography to examine the factors influencing local and regional knowledge linkages and supply–demand linkages across three interrelated scales: the firm (including history, and position in GVC), the industry (including product standardization, tech intensity, and knowledge bases), and the region (including industrial structure, path dependency, periphery varieties and strategic coupling). Most importantly, factors that affect both the geographies of supplier and knowledge linkages are identified.

Diego Chavarro (p), Tommaso Ciarli, Bernardo Caldarola

Monika Kot

This study investigates the dynamics of economic convergence and divergence across European NUTS3 regions, emphasizing the role of innovation and rural-urban distinctions within innovation clubs. Building on prior research on regional inequalities and European convergence policies, the study identifies four distinct innovation clubs—Core-Core, Core-Periphery, Periphery-Core, and Periphery-Periphery—based on regional innovation and economic performance, as well as centrality in knowledge networks. Using network analysis, clustering techniques, and regression models, the research examines inter- and intra-club convergence patterns and the influence of rurality, urbanization, and geography on economic growth.

Key findings demonstrate that convergence is not uniform across regions but primarily occurs within similar clubs, such as rural-to-rural or urban-to-urban. Rural regions exhibit higher growth rates compared to urban areas but face stronger diminishing returns, reflecting faster convergence. However, these dynamics are more strongly influenced by core-periphery structures and geographic factors than rural-urban distinctions. Core regions, often concentrated in economically dominant countries like Germany, France, and Italy, exhibit high centrality in knowledge exchange, while peripheral clusters are slightly more balanced in their composition and reflect lower innovation capabilities. Rural regions are predominantly located in the least integrated and lowest-performing Periphery-Periphery club, while urban areas are concentrated in the Core-Core and Periphery-Core clusters.

Contrary to aggregate analyses, within-club regressions reveal that rurality has minimal influence on growth dynamics after accounting for club membership and geographic location. Geographic disparities are evident, with Eastern European regions experiencing stronger convergence and catch-up effects compared to their North-Western and Southern counterparts.

This research underscores the importance of tailored regional policies that address local conditions, spatial heterogeneity, and the complex interplay between innovation, geographic context, and economic growth. Future work aims to expand the analysis by incorporating additional science, technology, and innovation indicators to further explore the role of innovation in driving convergence and to refine the characterization of regional dynamics across the rural-urban and core-periphery spectra.