GRF · Innovation Nexus
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.
How the work runs.
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: example names and illustrative values, not a record or a live system.
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.
Connected activity in China.
Night lights, population density and active fires over China, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Connected activity, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · 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.
Connected activity, framed on China.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA/NOAA VIIRS · U.S. Geological SurveySources 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 hexagonal 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- 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 hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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 hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Observed (EO): NASA/NOAA VIIRS (Suomi NPP). 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).
- Live: NASA EONET Events are indicative, not authority warnings.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- NASA GIBS: 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).
- Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
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
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
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 | Published statistics |
| 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 | Published statistics |
| Enterprises with fast broadband | percent of enterprises | annual | Enterprise ICT usage surveys | Published statistics |
| Absorption of regional innovation funds | percent of allocation committed and paid | annual | Fund management data | Published statistics |
| Smart specialisation priority domains | count of registered domains | per programming period | Smart specialisation strategies | DECLARED |
Exercise a cascade in regional innovation systems with the people who decide.
Assembled from the Nexus Standards area profile Frontier technology risk standards: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. To model a place of your own choosing, open the full System Builder.
Hazards
- Cryptographically relevant quantum computer
- Dam failure
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Data breach (set off downstream)
- Mass account takeover (set off downstream)
- Harvest-now, decrypt-later collection (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H104Hazard family: Quantum technology and cryptographic transition (NHS-1 tech.quantum)NRS-T9Quantum technology and cryptographic transition riskNRS-T0Exponential technology risk and responsible innovationNRS-H109Hazard family: Energy-transition technology failures (NHS-1 tech.energy-transition)NRS-M19Method fabric: Cyber, AI and frontier technologyNRS-U12Universe platform profile: Foresight Nexus
Observation
- Our World in Data datasets (listed for reference)
- World Bank Open Data and World Development Indicators API (listed for reference)
- Research and development expenditure as a proportion of GDP
- Researchers per million inhabitants
Example geography
- North America: 243 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
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 |
How regional innovation systems is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Policy instrument matrix
The kinds of instrument available on regional innovation systems, by level of government and cooperation.
| Instrument type | Local | National | Regional | Global |
|---|---|---|---|---|
| Regulatory | Zoning, building codes | Laws, standards, licensing | Harmonised rules | Conventions and treaties |
| Economic | Local levies, grants | Budget lines, taxes, insurance schemes | Risk pools, regional funds | Financing mechanisms |
| Information | Local warnings | Disclosure, early warning, statistics | Data sharing arrangements | Global monitoring and reporting |
| Institutional | Local committees | Lead agencies, coordination councils | Regional bodies and secretariats | Multilateral mandates |
| Cooperative | Community agreements | Partnership compacts | Memoranda and joint programmes | Agreements and joint commitments |
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, specialisations 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, specialised 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 specialisation, 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.
Why now: regions are competing for strategic industries and talent, and resilience depends on whether regional systems can absorb shocks to supply chains and skills. Innovation Nexus compares regional arrangements and offers reviewed findings to the Regional Systems series of Reports.
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 specialisation 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.
- 01Policy, institutional and decision scienceMandate and gap mapping · Programme evaluation design · Comparative regulatory analysisApplied here
- 02Systems engineeringRequirements traceability for AI governance · Readiness gates for transfer programmesApplied here
- 03Artificial 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?
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