Deliverable D6.1
Classification of ERA Hub schemes
EXECUTIVE SUMMARY
This deliverable presents a comprehensive framework for classifying ERA Hub schemes across the European Research Area, developed within the ERA_FABRIC project. The ambition of ERA Hubs is not to prescribe a single model of ecosystem organisation, but rather to support the emergence of context-sensitive, place-based innovation ecosystems capable of addressing regional needs while contributing to EU-wide objectives such as open science, green and digital (twin) transitions, and societal resilience. Against this backdrop, the document addresses a central challenge: how to systematically classify the variety of ERA Hub schemes operating across Europe in a way that reflects their core logic, stakeholder dynamics, and operational characteristics.
The classification developed in this deliverable is grounded in a structured yet flexible methodological approach that draws upon multiple sources collected along the ERA_FABRIC implementation, including the ERA_FABRIC stakeholder survey, regional partner profiling, the catalogue of measures and tools, and previous analytical work on research and innovation ecosystems and territorial governance. The classification is constructed using an ideal-type methodology, which enables the development of conceptual archetypes that help to structure and interpret the complex and hybrid reality of ERA Hubs. This approach does not aim to rank hub types or to prescribe uniform models, but rather to provide a heuristic tool that supports reflection and strategic development. The typology identifies four dominant logics – civic-driven, cluster-driven, research-driven, and policy-driven – each corresponding broadly to one of the four components of the quadruple helix innovation model: civil society, business, academia, and public authorities.
Civic-driven hubs are ecosystems anchored in civil society organisations and local communities. They prioritise inclusivity and public value, often using participatory tools such as citizen labs or co-creation spaces.
Cluster-driven hubs are steered by the private sector, particularly by business associations and industrial consortia. Their focus is on competitiveness, applied innovation, and value chain integration. These hubs tend to be agile and demand-driven, but may require policy support to enhance inclusiveness and long-term impact.
Research-driven hubs, meanwhile, are orchestrated by universities, RTOs, and other knowledge-producing institutions. They function as engines of knowledge production and transfer, leveraging their participation in European research programmes and advanced infrastructures. However, they may need targeted mechanisms to strengthen societal engagement and ecosystem integration.
Lastly, policy-driven hubs are initiated and governed by public authorities and policy bodies. Their role is to align research and innovation activities with regional strategies, coordinate actors across sectors, and provide long-term institutional support through instruments such as RIS3 strategies and public-funding programmes.
Each of these hub types is analysed across five core dimensions: knowledge ecosystem functionality, stakeholder engagement, governance structure, cross-regional connectivity, and human-centric orientation. In addition, each hub type is associated with a set of typical tools and instruments, recurrent strengths, and common challenges. The analysis confirms that while each archetype has distinctive features, most real-world hubs operate in hybrid configurations, combining elements from multiple logics to meet their objectives. For instance, policy-driven hubs often incorporate research institutions as coordinators; research-driven hubs include civic engagement components; and cluster-driven hubs may evolve into platforms for policy experimentation or social impact innovation.
This report also presents a comparative synthesis and a consolidated typology matrix that allows stakeholders to assess their positioning within the broader ERA Hubs landscape. These resources are intended to serve as practical tools for policy learning and strategic alignment. The classification facilitates the tailoring of support mechanisms and the design of appropriate instruments for Knowledge ecosystem development.
This deliverable contributes to the ERA_FABRIC project’s objective of operationalising the ERA Hubs concept in a way that is empirically grounded, strategically actionable, and sensitive to Europe’s rich territorial diversity. It offers a common vocabulary and analytical scaffold for understanding the evolving role of ERA Hubs, helping regional and national stakeholders to navigate their development trajectories and enhance their contribution to a more open, inclusive, and interconnected ERA.
ABBREVIATIONS
CSOs Civil Society Organizations
DIH Digital Innovation Hub
EDIH European Digital Innovation Hub
EIT European Institute for Innovation and Technology
ERA European Research Area
ESF European Social Fund
ESG Environmental Social Governance
EU European Union
IP Intellectual Property
NEB New European Bauhaus
NGOs Non-Governmental Organizations
RTOs Research and Technology Organizations
R&D Research and Development
R&I Research and Innovation
RIS3 Research Innovation Smart Specialisation Strategy
RIS4 Research Innovation Smart Sustainable Specialisation Strategy
SDG Sustainable Development Goals
SMEs Small and Medium Enterprises
1. INTRODUCTION
The ERA_FABRIC project aims to operationalize the ERA Hubs concept through an empirical and conceptual deepening of its components. One of the key tasks within this effort is to understand and classify the variety of ERA Hub models that exist or could be developed across European regions. This report directly contributes to this objective by offering a structured classification framework of ERA Hub schemes, based on their principal governance logic and their stakeholder configuration.
This classification is not intended as a rigid taxonomy, but rather as a heuristic and strategic tool for ecosystem actors. It enables stakeholders to better identify their own hub model, reflect on their strengths and challenges, and explore how specific measures and tools may be more or less appropriate depending on their hub type. Furthermore, it serves to support inter-regional learning by making visible the diversity of legitimate approaches to ERA Hub development, avoiding a “one-size-fits-all” paradigm.
The need for a typology classification arises from several converging observations within the ERA_FABRIC project:
- The heterogeneity of European territories means that ERA Hubs manifest in very different ways depending on the local institutional, economic, and social context.
- Previous ERA_FABRIC surveys and analyses -showed that while certain factors are common to high-performing research and innovation ecosystems, their combinations and manifestations vary.
- There is currently a lack of a shared language or framework for distinguishing between ERA Hub models in a systematic way. This acts as an obstacle for cross-regional comparison and the tailoring of support mechanisms at EU level.
Therefore, this document has the following specific objectives:
- To propose a coherent typology of ERA Hubs schemes rooted in the findings of the ERA_FABRIC project.
- To characterize each hub type according to a common set of dimensions.
- To link each hub type to specific tools, instruments, and policy measures, drawing from empirical use cases.
- To provide a navigational aid for stakeholders to better position their hub within this typology and reflect on potential directions for development.
- To inform European and national policymakers about the variety of support needs across different hub types.
2. METHODOLOGICAL APPROACH
The development of the ERA Hubs classification framework presented in this deliverable is the result of a multi-layered and iterative research process, embedded within the analytical activities of the ERA_FABRIC project. The methodology integrates empirical analysis and stakeholder co-creation, reflecting the project’s broader commitment to evidence-informed and participatory research and innovation policy design.
The starting point for the methodological design was the recognition that ERA Hubs, as envisioned in the renewed European Research Area, are not a “standardized” institutional form but a multi-dimensional and context-sensitive construct. Their manifestations vary across regions, depending on governance structures, dominant actors, policy legacies, and socio-economic conditions.
To support the operationalization of the ERA Hub concept in such a diverse landscape, a typology was needed – one that could:
- Identify archetypal hub configurations based on observable characteristics;
- Allow regions to recognize themselves within the typology and benchmark their position;
- Serve as a navigational compass for designing and selecting tools, support instruments, and governance modalities;
- Enable cross-comparison and learning between territories with similar or complementary models.
This required a methodology that was both structured and flexible, capable of integrating diverse qualitative and quantitative inputs, and able to reflect the complexity of real-world ecosystems without oversimplifying. Thus, this deliverable draws from a broad range of interlinked project activities, including (but not limited to):
- ERA_FABRIC Stakeholder survey (Deliverable D2.3): Quantitative insights into perceived success factors and challenges in regional R&I ecosystems;
- Partner regional profiling (Deliverable D2.4): Comparative views on regional strengths, gaps, and governance structures;
- Catalogue of measures and tools (Deliverable D4.1): Empirical mapping of tool deployment and alignment with different ecosystem types;
- Literature review and policy documents: Including the European Commission’s ERA Communication, Smart Specialisation strategies, and European Innovation Scoreboard methodologies;
- Internal workshops: Discussing with project partners and regional stakeholders on civic engagement, collaborative research, industrial innovation, and policy integration.
Drawing from these sources, after recognizing recurring structural logics around dominant actors, four recurring “hub logics” were identified:
- Civic-driven
- Cluster-driven
- Research-driven
- Policy-driven
These four logics coincide with each of the aspects of the Quadruple Helix I System: Society, Business, Academic research, and Government, respectively. For each of these hub types, five key analytical dimensions were defined to allow comparison:
- Knowledge ecosystem functionality
- Stakeholder engagement
- Governance
- Cross-regional connectivity
- Human-centricity
In addition to these analytical dimensions, each hub type was then analysed in terms of typical tools and instruments used, potential strengths and potential weaknesses inherent in their typology.
It must be noted that this methodology adopts an “ideal-type” approach, meaning that the categories represent stylized constructs that help organize reality but are not expected to exist in pure form. Ideal types are heuristic tools, not empirical classifications; thus, real-world ERA Hubs will often combine features from multiple types. It must be noted that this classification does not aim to rank or evaluate hub types hierarchically. All types are considered legitimate, with specific strengths and limitations.
2. METHODOLOGICAL APPROACH
The development of the ERA Hubs classification framework presented in this deliverable is the result of a multi-layered and iterative research process, embedded within the analytical activities of the ERA_FABRIC project. The methodology integrates empirical analysis and stakeholder co-creation, reflecting the project’s broader commitment to evidence-informed and participatory research and innovation policy design.
The starting point for the methodological design was the recognition that ERA Hubs, as envisioned in the renewed European Research Area, are not a “standardized” institutional form but a multi-dimensional and context-sensitive construct. Their manifestations vary across regions, depending on governance structures, dominant actors, policy legacies, and socio-economic conditions.
To support the operationalization of the ERA Hub concept in such a diverse landscape, a typology was needed – one that could:
- Identify archetypal hub configurations based on observable characteristics;
- Allow regions to recognize themselves within the typology and benchmark their position;
- Serve as a navigational compass for designing and selecting tools, support instruments, and governance modalities;
- Enable cross-comparison and learning between territories with similar or complementary models.
This required a methodology that was both structured and flexible, capable of integrating diverse qualitative and quantitative inputs, and able to reflect the complexity of real-world ecosystems without oversimplifying. Thus, this deliverable draws from a broad range of interlinked project activities, including (but not limited to):
- ERA_FABRIC Stakeholder survey (Deliverable D2.3): Quantitative insights into perceived success factors and challenges in regional R&I ecosystems;
- Partner regional profiling (Deliverable D2.4): Comparative views on regional strengths, gaps, and governance structures;
- Catalogue of measures and tools (Deliverable D4.1): Empirical mapping of tool deployment and alignment with different ecosystem types;
- Literature review and policy documents: Including the European Commission’s ERA Communication, Smart Specialisation strategies, and European Innovation Scoreboard methodologies;
- Internal workshops: Discussing with project partners and regional stakeholders on civic engagement, collaborative research, industrial innovation, and policy integration.
Drawing from these sources, after recognizing recurring structural logics around dominant actors, four recurring “hub logics” were identified:
- Civic-driven
- Cluster-driven
- Research-driven
- Policy-driven
These four logics coincide with each of the aspects of the Quadruple Helix I System: Society, Business, Academic research, and Government, respectively. For each of these hub types, five key analytical dimensions were defined to allow comparison:
- Knowledge ecosystem functionality
- Stakeholder engagement
- Governance
- Cross-regional connectivity
- Human-centricity
In addition to these analytical dimensions, each hub type was then analysed in terms of typical tools and instruments used, potential strengths and potential weaknesses inherent in their typology.
It must be noted that this methodology adopts an “ideal-type” approach, meaning that the categories represent stylized constructs that help organize reality but are not expected to exist in pure form. Ideal types are heuristic tools, not empirical classifications; thus, real-world ERA Hubs will often combine features from multiple types. It must be noted that this classification does not aim to rank or evaluate hub types hierarchically. All types are considered legitimate, with specific strengths and limitations.
3. COMPARATIVE ANALYSIS OF THE FOUR ERA HUB TYPES
The following comparative analysis provides an in-depth examination of the four ideal-type ERA Hub schemes – civic-driven, cluster-driven, research-driven and policy-driven – along a shared set of analytical dimensions. This section aims to uncover the distinctive characteristics and structural configurations that define each model, while also illuminating their respective strengths and limitations. This analysis builds upon the methodological framework outlined earlier, drawing from empirical observations, use case mapping, and strategic insights gathered throughout the ERA_FABRIC project. It serves a dual purpose: first, to facilitate a nuanced understanding of how ERA Hubs function under different governance and stakeholder constellations; and second, to enable stakeholders to identify patterns of convergence and divergence that can inform the design of tailored support instruments and collaborative partnerships. While each hub type reflects a dominant institutional driver and logic of coordination, this section also acknowledges the permeability between types, encouraging a flexible and reflexive reading of the classification. The section will analyze each Hub type separately for the ease of the reader; a comparative matrix compiling and summarizing all the information can be found in the Annex of the present document.
3.1 Civic-driven Hubs
Civic-driven ERA Hubs are fundamentally shaped and activated by civil society organisations (CSOs), local communities, citizen initiatives, or social economy actors. Their primary rationale is to generate bottom-up, inclusive, and mission-oriented innovation that responds to local needs and enhances public value and democratic participation in science, technology, and innovative applications.
These hubs emerge from a logic of social transformation rather than a technological competition. They challenge traditional models of innovation governance by centering community empowerment and societal challenges. Civic-driven hubs often operate at the intersection of social innovation and participatory governance and are key enablers of human-centric R&I systems as envisioned in the renewed ERA.
The governance of these hubs is typically collaborative and deliberative, blending formal and informal structures and relying heavily on co-creation. Civic-driven hubs are particularly relevant in regions that face socio-economic marginalisation or innovation exclusion, prioritise participatory democracy and sustainability and/or host a dense fabric of local associations and active citizens.
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Key characteristics |
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|
Dimension |
Characteristics |
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Knowledge ecosystem functionality |
Moderate to high. Strong focus on non-technological innovation, service co-design, and bottom-up experimentation. Less emphasis on high-tech R&D. |
|
Stakeholder engagement |
Very high. Civil society, citizens, NGOs, minority groups, and local collectives are deeply involved as agenda-setters and co-creators. Facilitators’ commitment enhances this process. |
|
Governance |
Deliberative, bottom-up governance. May lack formal structures but strong in distributed agency. Partnerships with public institutions are often essential. |
|
Cross-regional connectivity |
Moderate. Often place-bound but can scale via civic networks. Increasing role in translocal knowledge exchange. |
|
Human-centricity |
Extremely high. Driven by societal challenges, NEB values, and SDG alignment. |
Table 1: Key characteristics of Civic-driven Hubs
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Typical tools and instruments |
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Category |
Tools and instruments |
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Citizen engagement |
Participatory budgeting, open assemblies, citizen juries, digital engagement platforms, etc. |
|
Co-creation & Living Labs |
Urban or rural living labs, testbeds for public services, community innovation hubs, open hackathons, etc. |
|
Social innovation finance |
Community funding schemes, ethical investment funds, social innovation challenge calls, etc. |
|
Knowledge sharing |
Civic data commons, open access libraries, informal learning networks, community science labs, etc. |
|
Policy influence |
Public-civic pacts, co-governance agreements with municipalities, civic councils on R&I, etc. |
Table 2: Typical tools and instruments of Civic-driven Hubs
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Strengths and Challenges |
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|
Strengths |
Challenges |
|
Deep societal relevance and legitimacy |
Often underfunded and institutionally fragile |
|
High inclusivity and democratic innovation capacity |
Limited access to technical R&I infrastructures |
|
Strong capacity for trust-building and ownership |
Risk of marginalization from mainstream research and innovation policies |
|
Agile in responding to local needs and crises |
Difficulties in sustaining long-term impact without institutional anchoring |
Table 3: Strengths and challenges of Civic-driven Hubs
Policy and design implications
Civic-driven hubs often require enabling conditions and intermediary support to connect with formal research and innovation infrastructures. Social and community-based innovation must be recognized and funded in regional strategies and cohesion policies. Civic research and innovation intermediaries, such as public innovation labs or community innovation brokers, should be created. Blended governance models are advised, allowing for shared leadership between municipalities and community actors, which should be complemented with capacity-building programmes so they can engage in policy design.
3.2 Cluster-driven Hubs
Cluster-driven ERA Hubs are research and innovation ecosystems primarily steered by the private sector, with a central role played by industry clusters, business associations, and innovation-oriented firms. These hubs are rather rooted in market logic and emphasize competitiveness and value creation through collaborative innovation.
Rather than being coordinated by public or academic actors, cluster-driven hubs evolve from the self-organization of enterprises, often around a shared value chain or industrial domain. Their collaborative structure fosters open innovation and trust-building among firms, especially SMEs, enabling them to co-develop new products, access new markets or co-invest in infrastructure/training.
Cluster-driven hubs are well-aligned with the entrepreneurial discovery process central to Smart Specialisation Strategies and often emerge in regions with established sectoral strengths or a history of industrial cooperation.
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Key characteristics |
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|
Dimension |
Characteristics |
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Knowledge ecosystem functionality |
High. Strong capacity to translate needs into solutions through market mechanisms. Value chains are central, and innovation is applied and incremental. |
|
Stakeholder engagement |
Strong in private sector engagement, especially among SMEs and large companies. Collaboration with academia and public actors is pragmatic, often project-based. |
|
Governance |
Industry-led governance via cluster associations or business consortia. Public authorities may play a supporting role, but governance is often bottom-up. |
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Cross-regional connectivity |
Moderate. Strong participation in interregional partnerships, S3 platforms, value chain collaborations, and EU industry networks. Often internationally oriented. |
|
Human-centricity |
Moderate. Focus is on economic growth, competitiveness, and job creation, with growing interest in social and green transition when incentivized. |
Table 4: Key characteristics of Cluster-driven Hubs
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Typical tools and instruments |
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Category |
Tools and instruments |
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Business development |
Cluster facilitation, joint branding and marketing, matchmaking events, innovation scouting services, etc. |
|
R&D & innovation |
Collaborative R&D projects, applied research platforms, technology demonstrations, cross-sector pilots, etc. |
|
Financial instruments |
Innovation vouchers, co-investment funds, corporate venture, business angel platform, etc. |
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Capacity building |
Sector-specific training programs, peer-learning networks, talent mobility schemes, etc. |
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Infrastructure |
Shared prototyping spaces, labs, logistic platforms, pilot production lines, etc. |
Table 5: Typical tools and instruments of Cluster-driven Hubs
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Strengths and Challenges |
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|
Strengths |
Challenges |
|
Close link to market needs and technological demands |
May overlook societal and environmental considerations unless incentivized |
|
Agile and demand-driven collaboration models |
Risk of exclusivity – less accessible to civil society or academia |
|
Peer-based governance enhances trust and commitments |
Short-term business logic may limit engagement in long-term missions or basic R&D |
|
Strong drivers of regional economic development |
Dependence on external support for pre-competitive collaboration |
Table 6: Strengths and challenges of Cluster-driven Hubs
Policy and design implications
Cluster-driven hubs require specific policy support mechanisms and governance facilitation strategies. For instance, there is a need for support for cluster organisations as coordination nodes through core funding and operational capacity building, and a need for incentives for mission-aligned business innovation (such as green transition challenge calls or ESG-oriented procurement). Clusters must be connected with academia and civil society through brokerage services for inclusive research and innovation agendas. Also, businesses must participate in the co-design of RIS3 strategies to ensure relevance and uptakes and recognize cross-regional cluster collaborations in cohesion policy and ERA instruments.
3.3 Research-driven Hubs
Research-driven ERA Hubs are anchored in universities, research and technology organizations (RTOs), or public research institutes. Their central logic is the generation, valorisation, and transfer of scientific knowledge, which they aim to translate into technological innovation and policy insights.
These hubs are often embedded within regional research and innovation ecosystems where academic institutions act as conveners and orchestrators. They are particularly relevant in regions with strong higher education institutions, established research infrastructures, and access to national or European funding streams that support science and technology. The research-driven hub model emphasizes:
- Scientific excellence as a public good.
- The production and dissemination of frontier knowledge.
- Collaboration with the other asps of the Quadruple Helix in research and knowledge transfer.
- Capacity building through education.
They tend to be strongly integrated into the European Research Area, with a high rate of participation in European-funded projects (Horizon Europe, Marie Sklodowska-Cure Actions, European Research Council grants, etc.).
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Key characteristics |
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|
Dimension |
Characteristics |
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Knowledge ecosystem functionality |
High. These hubs often host advanced R&D infrastructures, scientific clusters, open science initiatives, and IP generation capabilities. |
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Stakeholder engagement |
Moderate to high. Engagement is typically stronger with students, researchers, and R&I-driven firms. Civil society and SMEs may be less involved unless specific outreach mechanisms are in place. |
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Governance |
Led by universities or consortia of research actors; governance structures may be formal (university alliances) or informal (research collaboration networks). Strong in strategy but may face coordination issues across public-private boundaries. |
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Cross-regional connectivity |
Moderate to high. High participation in EU research programmes and networks. |
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Human-centricity |
Variable. Some hubs engage in mission-driven research and citizen science, but others are more technocratic or disconnected from public concerns unless funded to do so. |
Table 7: Key characteristics of Research-driven Hubs
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Typical tools and instruments |
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Category |
Tools and instruments |
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Infrastructure |
R&D facilities, FabLabs, testbeds, digital and physical research infrastructures, high-performance computing centers, etc. |
|
Collaboration platforms |
University-industry collaboration offices, public-private labs, research consortia, co-publication networks, etc. |
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Transfer and valorisation |
Technology Transfer Offices, IP portfolios, licensing agreements, spin-off incubators, proof-of concept funding, etc. |
|
Human capital development |
Interdisciplinary graduate schools, innovation PhDs, EIT-labelled master programmes, research mobility schemes, etc. |
|
Outreach and engagement |
Living labs, citizen science platforms, science festivals, policy advisory roles, etc. |
Table 8: Typical tools and instruments of Research-driven Hubs
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Strengths and Challenges |
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|
Strengths |
Challenges |
|
Strong knowledge production and transfer capacities |
May be disconnected from non-academic actors (e.g. SMEs, citizens) |
|
Access to international research networks and funding |
Risk of fragmentation between scientific excellence and regional relevance |
|
High innovation potential in deep tech and advanced sectors |
Dependence on public and competitive project funding |
|
Potential talent attraction in certain regions |
Governance dominated by academic logic may limit agility |
Table 9: Strengths and challenges of Research-driven Hubs
Policy and design implications
To support the development of research-driven hubs within the ERA, policymakers should consider incentivizing civic and industry engagement through targeted funding and facilitating governance integration, including shared strategies between universities, regional governments, and business associations. Policymakers should also pay attention to ensuring access to research infrastructures for non-academic users (especially SMEs, CSOs). It is also important to support career development pathways for research in both academic and non-academic settings to guarantee talent attraction and retention. Finally, it would be important to monitor societal impact of academic innovation, using metrics that go beyond publications and patents.
3.4 Policy-driven Hubs
Policy-driven ERA Hubs are primarily initiated and orchestrated by public institutions – typically regional governments, managing authorities, innovation agencies, or national ministries. These hubs reflect a strategic and programmatic orientation, where public authorities act as system conveners and enablers, leveraging policy instruments and funding to structure collaboration and ecosystem alignment.
The core logic of policy-driven hubs is territorial coordination. Their objective is to align place-based assets and actors with long-term policy goals – such as green and digital transitions or smart specialization policies – while enhancing institutional coherence and governance capacity.
Unlike cluster- or research-driven models that emerge organically from industrial or academic activity, policy-driven hubs are often deliberately created through policy planning and public investments and contemplated in documents such as regional innovation roadmaps or operational programmes.
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Key characteristics |
|
|
Dimension |
Characteristics |
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Knowledge ecosystem functionality |
Moderate to high. Strong in ecosystem orchestration and infrastructure funding. May depend on effectiveness of stakeholder mobilization. |
|
Stakeholder engagement |
Variable. Engagement mechanisms are usually formalized but may lack depth or continuity unless reinforced. |
|
Governance |
Strong institutional anchoring. Multi-level governance frameworks are often in place. However, risk of fragmentation between policy areas (e.g. R&I and economic development) |
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Cross-regional connectivity |
High. Often aligned with EU programmes, interregional partnerships, and national innovation strategies. Act as policy nodes in larger territorial innovation networks. |
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Human-centricity |
Variable. Depends on political priorities and integration of participatory or mission-oriented approaches. Increasing relevance due to NEB and mission-driven policy logics. |
Table 10: Key characteristics of Policy-driven Hubs
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Typical tools and instruments |
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Category |
Tools and instruments |
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Strategic planning |
Smart Specialisation Strategies (RIS3, RIS4), Regional development plans, innovation roadmaps, etc. |
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Public funding |
RDF/ESF+ programmes, regional innovation vouchers, pre-commercial procurement, co-financing of DIHs or EDIHs, etc. |
|
Infrastructure investment |
Research centres, shared testing facilities, science parks, digital connectivity, etc. |
|
Monitoring & evaluation |
Territorial foresight, policy intelligence dashboards, regional observatories, etc. |
|
Stakeholder governance |
Quadruple Helix councils, regional innovation boards, interdepartmental task forces, etc. |
|
EU integration |
Participation in European projects (Interreg, Horizon), European Innovation Valleys, WIDERA actions, etc. |
Table 11: Typical tools and instruments of Policy-driven Hubs
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Strengths and Challenges |
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Strengths |
Challenges |
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Strong ability to align policy instruments, funding, and institutional support. |
Risk of over-engineering or excessive bureaucracy. |
|
Capacity to mobilise public investment at scale. |
Limited agility compared to private or civic-driven models (including siloed departments). |
|
Legitimacy to convene diverse actors and create long-term frameworks. |
Stakeholder participation may be tokenistic if not well designed. |
|
Fostering Alignment with national and EU strategies. |
Potential disconnection from experimentation or grassroots dynamics. |
Table 12: Strengths and challenges of Policy-driven Hubs
Policy and design implications
To increase their effectiveness and relevance, policy-driven hubs benefit from a combination of institutional capacity-building and ecosystem-responsive tools. Thus, it is necessary to strengthen civic and SME participation mechanisms, going beyond consultation and co-creation formats and making them active participants of the hubs. For this, it would be advisable to create flexible public-private-civic governance bodies, able to act across sectors and funding schemes. In this context, policy intelligence tools (e.g. dashboards, foresight…) would be useful to inform adaptative governance and avoid policy inertia. Last but not least, it would be essential to facilitate connectivity with other hub types through coordinated funding and shared pilot initiatives.
Conclusions and recommendations
The classification of ERA Hub schemes developed in this report has sought to bring clarity and structure to the evolving landscape of regional research and innovation ecosystems in Europe. The typology suggested, comprising civic-driven, cluster-driven, research-driven and policy-driven hubs, offers a lens through which to understand the plurality of research and innovation pathways emerging across territories. However, as we mentioned before, this classification must not be interpreted as a rigid taxonomy. Rather, it constitutes a heuristic tool designed to assist stakeholders in navigating complex realities, fostering reflection, and informing decision-making.
One of the most salient insights that emerged during the typology development process is that hybridization is, in practice, the prevailing condition across European research and innovation ecosystems. Although each hub type reflects a dominant logic – be it civil society mobilization, market-driven collaboration, academic leadership, or public sector orchestration – real-world hubs rarely conform exclusively to a single model. It is increasingly common to observe regional ecosystems that blend elements from multiple types. For example, a research-driven hub may integrate strong civic engagement components through participatory research and co-creation platforms, while a cluster-driven hub may rely on public co-financing mechanisms and alignment with regional policy priorities to scale innovation. Similarly, policy-driven hubs often partner with academic institutions or grassroots initiatives to enhance legitimacy and capacity to address societal challenges. This hybrid nature suggests that policy and programmatic support must allow for flexibility, rather than encouraging conformity to prescriptive models.
Another cross-cutting finding relates to the centrality of governance maturity as a critical determinant of ERA Hub performance. Regardless of the dominant model, the capacity of a hub to articulate a clear strategic vision, engage relevant stakeholders in meaningful ways, and coordinate activities across multiple levels of decision-making is essential. Governance maturity encompasses both the formal structures that shape decision-making processes and the informal practices that enable collaboration, negotiation, and learning. In cluster-driven hubs, this governance maturity often takes the form of peer-based structures rooted in trust and reciprocity among businesses, while civic-driven hubs rely on distributed leadership and participatory decision-making. In research-driven hubs, governance typically follows institutional logics anchored in academia, and in policy-driven hubs, governance frameworks are anchored in administrative structures and public mandates. The effectiveness of each of these models depends not only on their formal architecture but also on their capacity to align interests and adapt over time.
A third insight concerns the uneven levels of inclusivity observed across hub types. While inclusiveness is a normative goal enshrined in the ERA policy agenda, its operationalization varies considerably. Civic-driven hubs place inclusivity at the center of their mission, often working proactively to involve underrepresented groups. By contrast, research- and cluster-driven hubs tend to focus on more specialized forms of participation, typically involving actors who already possess the capacities and resources to engage. Policy- driven hubs occupy a middle ground, with inclusivity depending largely on the design of participation mechanisms and the political will to ensure democratic accountability. These differences suggest that inclusivity cannot be assumed; it must be designed, resourced, and continuously monitored. Policies aimed at supporting ERA Hubs should therefore integrate explicit mechanisms to deepen and broaden stakeholder participation, including those actors that are structurally disadvantaged or historically excluded from research and innovation processes.
An additional insight relates to the tension between place-based specificity and translocal connectivity. ERA Hubs are, by design, rooted in the unique needs and institutional configurations of their respective territories. Their strength often lies in their capacity to mobilise local knowledge, respond to contextual challenges, and build trust among local actors. However, this embeddedness does not preclude broader connectivity. On the contrary, the most dynamic and impactful hubs are those that manage to combine deep local roots with strong linkages to European and global innovation networks; thus, ERA Hubs can thrive when they operate as nodes in a distributed and collaborative research and innovation system. The implication for policy is clear: support mechanisms must reinforce both territorial anchoring and outward-facing connectivity, enabling hubs to learn from one another and scale successful practices across borders.
A final transversal finding concerns the critical role of toolkits and instruments tailored to the specific logics and needs of each hub type. The analysis undertaken in this deliverable has shown that civic-driven hubs often require participatory design platforms, social innovation funding streams, and mechanisms for community empowerment. Cluster-driven hubs, by contrast, benefit from business services, value chain coordination tools, and access to investment. Research-driven hubs require support for interdisciplinary collaboration, infrastructure sharing, and incentives for societal engagement, while policy-driven hubs need governance intelligence tools, foresight capacities, and alignment with regional development frameworks. A generic or uniform policy approach would fail to capture this diversity. Instead, ERA Hubs support must be modular and adaptable, enabling regions to assemble toolkits that are responsive to their evolving ecosystems and strategic ambitions.
In conclusion, the typology and analysis presented in this deliverable offer a grounded and flexible framework to guide the development, support, and evolution of ERA Hubs. The four archetypes – civic-driven, cluster-driven, research-driven, and policy-driven – are not intended as fixed categories but as orienting concepts to help stakeholders understand their ecosystem’s dominant logics and make informed choices about future directions. The typology also enables policymakers to design and implement differentiated support instruments that reflect the diversity of regional realities while contributing to the shared goals of the European Research Area.
ANNEX
Consolidated comparative matrix
Dimension | Civic-driven hubs | Cluster-driven hubs | Research-driven hubs | Policy-driven hubs |
Ecosystem functionality | Moderate. Bottom-up innovation, societal needs focus, often non-technological | High. Market-oriented, tech development and commercialization capacity | High. Strong R&D, advanced knowledge production, IP generation | Moderate to high. Public coordination of R&I, depends on institutional efficiency |
Stakeholder engagement | Very high. Citizens, CSOs, local communities, underrepresented groups deeply involved | High in the private sector. SMEs and industry consortia actively engaged | Moderate to high. Strong with academia and researchers, less so with SMEs/citizens | Variable. Formal stakeholder mechanisms; depth of engagement depends on design |
Governance structure | Collaborative, deliberative, distributed. Often informal or experimental. | Business-led governance through cluster bodies. Trust-based and peer-driven | Academic or research-institution-led; governance reflects institutional hierarchies | Public-sector driven. Based on strategies, steering groups, and institutional mandates |
Cross-regional connectivity | Moderate. Place-based but networked | High. Value chains and interregional cooperation | Moderate to high. Strong participation in Horizon Europe and transnational projects | High. Formal links with EU/national policy frameworks |
Human-centricity | Very high. Equity, inclusion, SDGs, well-being are central | Moderate. Indirect benefits via job creation or CSR, increasing attention to ESG | Variable. Dependent on project orientation; can be strong in mission-driven labs | Variable. Depends on integration of civic priorities a participatory/mission-oriented approaches |
Table Annex A: Consolidated comparative dimensions matrix
Hub type | Typical tools and instruments |
Civic-driven | Citizen labs, participatory budgeting, digital democracy platforms, social innovation accelerators, civic data commons… |
Cluster-driven | Innovation vouchers, business matchmaking, industrial pilots, shared facilities, value chain roadmaps, sector-focused training… |
Research-driven | Living labs, technology transfer offices, doctoral schools, Horizon Europe R&I projects, open science platforms, interdisciplinary centers… |
Policy-driven | RIS3/RIS4 strategies, regional observatories, public procurement for innovation, quadruple helix councils, foresight dashboards… |
Table Annex B: Consolidated tools and instruments matrix
Hub type | Main strengths | Key challenges |
Civic-driven | Societal legitimacy, inclusivity, adaptability, mission-alignment | Underfunding, institutional fragility, lack of formal recognition |
Cluster-driven | Market relevance, SME support, agility, export capacity | Risk of exclusivity, short-term focus, limited societal perspective |
Research-driven | Scientific excellence, talent development, EU integration | Disconnection from non-academic actors, dependency on grants |
Policy-driven | Institutional coherence, resource mobilisation, long-term vision | Bureaucracy, variable participation quality, siloed departments |
Table Annex C: Consolidated strengths and challenges matrix