Technology transfer
Technology transfer is the movement of knowledge, inventions and capability from where they are made to where they are used: from universities and public laboratories to firms, from large firms to suppliers, and across borders. Much transfer fails not for lack of an invention but for lack of absorptive capacity, finance, standards or skills on the receiving side. This page sets out the conditions for adoption, how transfer is measured, and the institutional choices that shape it.
Regulatory sandbox board
Technology transfer · Regulatory sandbox · Cohort 6
Cohort
| Parametric micro-cover | Insurance | Agreed | 5 of 12 | Testing |
| Flood sensor data market | Data | Partial | 4 of 12 | Conditions |
| AI permit triage | Public service | Agreed | 9 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.
Technology transfer is the movement of knowledge, inventions and capability from where they are made to where they are used: from universities and public laboratories to firms, from large firms to suppliers, and across borders. It often fails for lack of absorptive capacity, finance, standards or rules of ownership rather than lack of invention.
Connected activity in North America.
Night-time lights and population density, the footprint of electrified, connected activity, framed on North America 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
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Night-time lights and population density, the footprint of electrified, connected activity, framed on North America.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
Technology transfer: how the risk develops.
Adoption conditions and capacity. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Absorptive capacity
A firm can only use what it can understand. Without engineers, managers and in-house development able to adapt a technology, licences and grants produce little on the receiving side.
The valley of death
Between a laboratory demonstration and a market-ready product lie costly validation, scale-up and certification. Public research funding often ends before private investors are willing to begin.
Rules of ownership
Who owns publicly funded inventions, on what licence terms and with what government rights sets the incentives of universities, inventors and licensees. Rules that suit one sector can block another.
Diffusion is uneven
Adoption spreads from leading firms to the rest slowly, and productivity gaps widen in the meantime. Small firms, lagging regions and low-income economies often adopt only after standards and prices settle.
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 |
|---|---|
| Absorptive capacity | A firm's or country's ability to recognise, assimilate and apply external knowledge. |
| Valley of death | The funding and capability gap between a research result and a product ready for investment. |
| Invention disclosure | A researcher's formal report of an invention to their institution's technology transfer office. |
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 |
|---|---|---|---|---|
| Invention disclosures from public research organisations | count per year | annual | Technology transfer office surveys | REPORTED |
| Licences and options executed | count per year | annual | Technology transfer office surveys | REPORTED |
| Licensing income of public research organisations | national currency per year | annual | Technology transfer office surveys | REPORTED |
| Spin-off companies formed and surviving | count by cohort | annual | Institutional records and business registers | REPORTED |
| Enterprises using AI, cloud or robotics | percent of enterprises by size class | annual | Enterprise ICT usage surveys | OFFICIAL |
| Patent families filed by public research organisations | count of patent families | annual | Patent databases | OFFICIAL |
| Technology readiness level at programme entry and exit | level on the readiness scale | per project | Programme monitoring records | 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 |
|---|---|---|
| AUTM Licensing Activity Survey | Disclosures, licences, start-ups and income for North American institutions | Licensed, AUTM terms |
| HESA Higher Education Business and Community Interaction survey (UK) | Contract research, consultancy, licensing and spin-off data by institution | Open, attribution |
| Eurostat ICT usage in enterprises | Adoption of AI, cloud, robotics and data analytics by firm size and sector | Open, attribution (Eurostat reuse policy) |
| WIPO IP Statistics Data Center | Patent, utility model and design filings by office and origin | Free, WIPO terms |
| EPO PATSTAT | Patent families, applicants and citations for linking inventions to institutions | Licensed by the European Patent Office |
| CORDIS (European Commission) | Projects, participants and results of EU research and innovation programmes | Free reuse, attribution |
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 |
|---|---|---|
| Ministries of science and higher education | Who owns publicly funded inventions and what licensing and access terms apply | Comparative reviews of ownership regimes and their documented effects |
| Technology transfer offices and university governing bodies | Which inventions to protect, license or release openly, and on what terms | Disclosure and licensing records; sector-specific adoption conditions |
| Innovation agencies and national development banks | How to finance validation and scale-up between research and market | Readiness gates by programme; funding-stage gap analyses |
| Patent offices and WIPO member states | How patent and licensing rules support access and diffusion as well as reward | Filing and licensing statistics; treaty frameworks and their flexibilities |
Outputs this topic produces
- Adoption-condition assessments covering skills, finance, standards and infrastructure
- Comparative reviews of ownership and licensing rules for publicly funded inventions
- Readiness gates for transfer programmes using technology and adoption readiness
- Evaluation guides for transfer offices that look beyond counting licences
What experts ask.
Transfer questions focus on the receiving side.
- Does the receiving organization or country have the skills, infrastructure and finance to use the technology?
- Is the technology suited to local conditions, or does it need adaptation?
- Who owns the relevant intellectual property, and on what terms can it be used?
- How is tacit know-how, which is not written down, transferred alongside formal knowledge?
- Does transfer build lasting local capability, or create dependence?
Mechanisms and drivers.
Much of what makes a technology work is tacit: the experience of the people who built and operate it. Transfer therefore depends heavily on people moving, training and collaborating, not only on documents or licences. Absorptive capacity, meaning the ability to recognize, assimilate and apply external knowledge, determines how much benefit a recipient gains.
Intellectual property arrangements, standards, market size and regulatory approval all shape whether transfer is worthwhile for the parties. International transfer adds questions of equity and dependence, particularly for climate, health and digital technologies where access affects public welfare.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Licensing and spin-out data | Formal transfer from research institutions | Misses informal and collaborative transfer |
| Absorptive capacity indicators | Readiness of recipients | Proxies such as research spending are imperfect |
| Programme evaluation | Whether transfer programmes changed outcomes | Attribution is difficult; time lags are long |
| Case studies | How transfer worked in practice | Context-specific |
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.
Why is licensing income a weak measure of success?
What is a technology readiness level?
Does Innovation Nexus value patents or broker licences?
Why do so many transfer efforts fail?
Is open access enough for transfer?
Does Innovation Nexus broker licences?
Around Innovation Nexus.
Bring your expertise to this field.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.