Regional innovation systems
Innovation is concentrated in place. A regional innovation system is the set of firms, universities, public bodies and intermediaries within a region and the rules that link them, and it shapes whether new technologies are created, adopted or passed by. This page sets out how regional capacity builds and diverges, how technology diffuses between leading and lagging regions, and what evidence the regional, national and supranational institutions that fund place-based policy can use.
Regulatory sandbox board
Regional innovation systems · Regulatory sandbox · Cohort 4
Cohort
| Parametric micro-cover | Insurance | Agreed | 3 of 12 | Testing |
| Flood sensor data market | Data | Partial | 4 of 12 | Conditions |
| AI permit triage | Public service | Agreed | 4 of 12 | Testing |
| Drone deliveries, medical | Logistics | Agreed | 12 of 12 | Exit test |
Exit criteria
- Consumer harm
- none recorded
- Evidence
- independent evaluation
- Rule change
- regulator decides
- Wind-down
- plan on file
Sandbox cycle
- Applyeligibility
- Admitsafeguards
- Testbounded
- Evaluateindependent
- Exitor rule change
- Publishlessons
Fig.Regulatory sandbox board. Design wireframe with placeholder names and illustrative values, not a record or a live system.
The short answer.
A regional innovation system is the set of firms, universities, public bodies and intermediaries within a region and the rules that link them. It shapes whether new technologies are created, adopted or passed by. Capacity concentrates through agglomeration and related variety, and diffusion lags with distance, so copying leading regions rarely works.
Connected activity in the contiguous United States.
Night-time lights and population density, the footprint of electrified, connected activity, framed on the contiguous United States as an example geography for this subject; each layer is a dated NASA product.
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Connected activity
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Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Night-time lights and population density, the footprint of electrified, connected activity, framed on the contiguous United States.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Data: NASA GIBS · ASTER GDEM · Natural EarthSources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). CC BY 4.0
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
Layers and dates
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
Regional innovation systems: how the risk develops.
Regional capacity and technology diffusion. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Agglomeration
Skilled people, specialised suppliers and investors cluster where others already are. The returns to concentration are real, and they pull capacity away from smaller and peripheral places.
Related variety
Regions diversify most easily into activities close to what they already know. Policy that leaps to unrelated frontier sectors often lacks the skills and suppliers to take hold.
Diffusion lags with distance
Technologies reach lagging regions late, through supply chains, branch plants and returning graduates. Weak broadband, thin advisory services and small firms slow adoption further.
Governance capacity
Regions differ in their ability to design, co-fund and evaluate programmes. Funds allocated to places without that capacity are often underspent, or spent on what is easy rather than what is needed.
Terms used on this page.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Smart specialisation | An EU approach in which regions choose research and innovation priorities that build on their existing strengths. |
| Agglomeration economies | Benefits firms gain from locating near each other, such as shared labour pools and knowledge spillovers. |
| Related variety | Diversity of industries that share skills or technologies, which helps regions diversify. |
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| R&D expenditure by region and sector | percent of regional GDP | biennial | Regional R&D statistics | OFFICIAL |
| Regional innovation performance group | category relative to the EU average | biennial | Regional Innovation Scoreboard | ESTIMATED |
| Patent applications by inventor region | count per million inhabitants | annual | Regionalised patent data | ESTIMATED |
| Employment in knowledge-intensive services and high-technology manufacturing | percent of regional employment | annual | Labour force surveys | OFFICIAL |
| Enterprises with fast broadband | percent of enterprises | annual | Enterprise ICT usage surveys | OFFICIAL |
| Absorption of regional innovation funds | percent of allocation committed and paid | annual | Fund management data | OFFICIAL |
| Smart specialisation priority domains | count of registered domains | per programming period | Smart specialisation strategies | DECLARED |
From sources to decisions.
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Eurostat regional science and technology statistics | R&D, human resources in science and technology and patents at NUTS level | Open, attribution (Eurostat reuse policy) |
| European Commission Regional Innovation Scoreboard | Comparative regional innovation performance | Free reuse, attribution |
| OECD Regional Database and OECD REGPAT | Regional economic indicators and patents linked to regions | Open, attribution (OECD terms); REGPAT on request |
| JRC Smart Specialisation Platform | Regional priorities, strategies and peer reviews | Free reuse, attribution |
| European Commission Cohesion Open Data Platform | Planned and spent cohesion funds by programme and theme | Free reuse, attribution |
| US National Center for Science and Engineering Statistics (NSF) | State-level R&D, workforce and innovation indicators | Public domain |
Who decides, and what the evidence serves.
Innovation Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Regional governments and regional development agencies | Which domains to prioritise in a smart specialisation or regional innovation strategy | Capability profiles with related activities; priority choices of comparable regions |
| National ministries responsible for regional policy | How to allocate national innovation funding across regions without hollowing out lagging places | Regional indicators with their uncertainty; diffusion analyses |
| European Commission (DG REGIO and the Joint Research Centre) | What conditions to attach to cohesion funding for innovation and how strategies are reviewed | Absorption data; peer reviews; evaluation designs |
| Managing authorities of structural funds | Which calls to run and how to build the capacity to spend well | Governance capacity assessments; programme designs |
Outputs this topic produces
- Regional capability profiles showing related activities and gaps
- Diffusion analyses tracing how technologies reach lagging regions
- Programme designs for place-based innovation with governance capacity assessed
- Peer-learning formats linking regional authorities across borders
What experts ask.
Regional questions ask why capacity concentrates and how it spreads.
- What are the region's strengths, specializations and gaps?
- How quickly do new technologies reach firms and public services in the region?
- Do regional institutions, such as universities and development agencies, connect to local firms?
- How do national policies affect regions differently?
- Can lagging regions build capability, or does policy reinforce existing leaders?
Mechanisms and drivers.
Innovation tends to cluster because of shared labour pools, specialized suppliers and knowledge spillovers between nearby firms. These advantages compound, so leading regions pull further ahead. Diffusion to other regions depends on their absorptive capacity, infrastructure, skills and the links between local firms and outside sources of knowledge.
Regional strategies often build on existing strengths, a principle sometimes called smart specialization, rather than copying leading regions. Their success depends on regional institutions with the capability to design and sustain them, which is itself unevenly distributed. Regions that depend on a single industry are especially exposed when a technology shift erodes it, which links regional innovation to economic resilience.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Regional innovation indicators | Comparative performance across regions | Composite indices hide specific weaknesses |
| Technology adoption surveys | Diffusion among firms and services | Periodic and often national rather than regional |
| Economic complexity and specialization analysis | Capabilities and related diversification opportunities | Based on trade and employment data that miss services |
| Policy evaluation | Effects of regional programmes | Long time lags and many confounding factors |
How it is studied, and what the methods cannot say.
- Policy, institutional and decision scienceMandate and gap mapping · Programme evaluation design · Comparative regulatory analysisApplied here
- Systems engineeringRequirements traceability for AI governance · Readiness gates for transfer programmesApplied here
- Artificial intelligence and machine learningCoding policy and legal texts · Mapping patents and papers to technologiesApplied here
Questions and answers.
What is smart specialisation?
Why not copy the policies of leading regions?
Is this evidence only for European regions?
Why does innovation concentrate in a few places?
Can lagging regions catch up?
Does Innovation Nexus work with specific regions?
Around Innovation Nexus.
Bring your expertise to this field.
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