Background The circular economy is implemented at different levels from Urban Industrial Symbiosis to Hubs4Circularity proposing systemic solutions, integrating multiple regional stakeholders, and introducing a variety of operational models to different regional settings and sectoral needs. Previous work has been conducted within Horizon Europe projects, creating matchmaking frameworks that use multicriteria methods, mainly focusing on waste streams and stakeholder compatibility to create efficient collaboration and valorization paths. Most of these frameworks were dedicated to specific resources such as water, technical specialties and technological processes. However, to support Hubs4Circularity concept materialization, there is a need to align symbiosis synergies identification and implementation not only with technical aspects, but also with locality and spatial patterns, considering local strategies, economy, society, and authorities, using regional science methods. Methods This study focuses on the integration of regional settings and dimensions, including regional characteristics, spatial patterns, local and national strategies, resources and waste status, infrastructure and capacity, social, environmental, and economic status, and other special needs or local challenges -all these named as “Regional Scenery”- into the matchmaking framework. The collected information about the regions is translated into tables that encode them into quantitative parameters, so to prioritize the identified synergies according to their significance, value, and impact to each different area. Results The result is a detailed framework to prioritize all the identified symbiosis synergies, and therefore enable decision-making features for local industries, businesses, authorities, and policy makers according to regional needs and priorities. This framework will be validated via the digital platform of IS2H4C Horizon Europe project. Conclusions This research sets a baseline and creates a pathway for further specialization and improvements, by expanding this regional context, including more regional aspects and parameters, while maintaining an equilibrium between the quality of granular data and practical issues on availability of data.
Manousiadis et al. (2026) studied this question.