R&D Public Policy Strategies: A simplified model

Public policies on R&D and innovation have proved to make a considerable impact on economy in most countries. The range of strategies adopted by governments is so wide and complex that it is difficult to establish a comparison among them, or to make a forecast on the potential outcomes from adopting one or other strategies. Thus, to ease the policy design process there is a need to outline a model that allows visualising the possible strategies and instruments available.

The model presented here (see figure below) provides a generic overview of strategies that may be adopted when making R&D policy, attending to two key parameters: the degree of interventionism, and the level of risk assumed by the managing government. As a results, there are four type of strategies that may be adopted:

Figure showing a model to define R&D and Innovation Public Policy Strategies, designed by Francisco Velasco and licensed under CC BY-NCSA 4.0. Blog de Francisco Velasco: www.fvelasco.com

An attempt has been made to map some of the most common instruments (Di Comite & Kancs, 2015) in the proposed matrix as shown below. This mapped model is yet to be developed further and there is a likely misreading of some of the instruments. I will be happy to listen your views!

Figure showing a model mapping instruments of R&D Public Innovation Policies, prepared by Francisco Velasco and licensed under CC BY-NCSA 4.0. Blog de Francisco Velasco: www.fvelasco.com

An explanation both figures above is provided:

  • Enabling Strategy. Is characterised by low government interventionism and high-risk aversion (understood primarily as financial risk). This strategy is characteristic from economies based on primary industry and with a reduced and unsophisticated innovation ecosystem. Some typical instruments implemented under this strategy are: training programmes to raise the innovation profile of professional staff, promotion and marketing actions to raise public awareness on innovation, or the launch “innovation voucher” programmes that provide a small financial contribution for SMEs to hire external consultants to develop new products, conducting market research, or improving internal processes.
  • Dynamic Strategy. This strategy requires governments to take an innovation facilitator roll and take actions towards fostering R&D collaboration; the most typical instrument in this case is the implementation of funding programmes to R&D projects. The level of risk taken is variable and depends on the level of funding committed to such purposes; and the degree of government interventionism is relatively low, because policies focus on rewarding R&D activity, and not on influencing how such activity shall be conducted.
  • Regulated Strategy is characterised by a high interventionism to define the “game rules”, that is, regulation and legislation that obliges meeting certain standards concerning R&D directly or indirectly. Public Administrations taking this approach assumes relatively low risks, since no great sophistication is required on the design of specific instruments; however, a relatively high investment is required in the preparation of regulatory and tax-related measures. Some common instruments adopted with the regulated strategy are the introduction of corporate tax discounts on R&D, the implementation of ISO standards related to R&D management practice, or the application of green-related normative (such as CO2 emissions requirements, which pushes companies developing novel technological solutions)
  • Open Systemic Strategy. This strategy assumes innovation as an intrinsic part in the way government manages office (the government innovates itself). Such approach implies a high interventionism under the premise of having a good understanding on innovation and R&D strategy, and places the government as a key stakeholder in the country´s innovation agenda. Government thus assumes a high level of risk in the design of new instruments that usually involve participative and co-creative processes with the private sector. This model requires highly qualified personnel with world-class knowledge on innovation and R&D processes, and takes place in the most advanced economies in the world. Some of the usual instruments adopted with this strategy are the public procurement of innovation, technology foresights, or the long-term transformation of the educational system itself to ensure the creation of an innovative culture.

The proposed model is subject to discussion and has no scientific grounds. However, it is based on fieldwork observation and provides the advantage of being simple and building on two solid parameters (interventionism and risk). The model may aid the strategy design process because allows understanding some underlying implications of adopting specific strategies, and designing the appropriate instrument policy mix for each country. I am intending to refine and improve some of the assumptions, and I will be happy to hear your comments!



Di Comite, F., & Kancs, D. (2015). Macro-Economic Models for R&D and Innovation Policies.


Re-thinking Technology Transfer

Since Henry Chesbrough originated the term “Open Innovation” (Chesbrough, 2003), technology transfer has been often understood as a lineal process, where one side represents the “supply of technology” (technologies and know-how resulting from R&D activity and typically developed by universities, technological institutes and other knowledge generators), and the other side the “demand of technology” (normally represented by the enterprises, the market). This vision assumes that working on the prioritisation and evaluation of technology portfolios, allows to identify potential applications, and by setting the right protection mechanisms a researcher may be able to find potential buyers of the technology.

The reality beyond this model is that results are poor, and according to some estimates only 1% to 5% of R&D results reach the market and remains as a viable product/process for a period of 2-5 years.

The big issue lies in assuming that technology transfer is a lineal process addressed from the “supply” side (i.e., the technologies that are to be sold), while technology transfer should be understood as a circular process, where the focus shall be placed on the “demand” side, the market needs. The figure below explains this approach:

Figure showing the Pull Technology Transfer Model designed by Francisco Velasco and licensed under CC BY-NC-SA 4.0. Blog de Francisco Velasco: www.fvelasco.com


Following the proposed model above, technology transfer shall start with co-creative field work conducted with enterprises and assisted by experts, to re-evaluate their value chains, their products and their business models, aiming at defining specific industry challenges or needs. Such “needs”, shall be marketed adopting appropriate communication strategies, targeting technology suppliers that are able to provide incremental solutions and get involved in a participative process with the buyer to adapt the solution to the specific need.

This approach challenges the settled logic of starting technology transfer work with the categorisation and prioritisation of technology portfolios, and the design of technology catalogues; and suggest to take a similar approach with the “needs”, thus conducting a categorisation and prioritisation of product/process improvement needs, and developing needs catalogues, that shall be framed in a form that the scientific community is able to understand.

I believe that the greatest mistake in the technology transfer business, has been assuming that is ruled under the same logic than traditional product sale (if I am willing to sell a product, I prepare some advertising material and target potential customers –sometimes with some previous user research-). However, technology and innovation requires a different approach because the purchasing driver is not emotional or physical, but a business need. Thus the sales cannel cannot be a catalogue that explains the technology, but a working process with the company to understand how they could earn more or avoid losing money by acquiring a new technology; and the greatest challenge lies in translating this information into a language that is understood by knowledge generators. This way, we are able to focus marketing on finding “sellers” (technology suppliers) instead of finding “buyers” (companies willing to buy technologies), thus simplifying and improving success probabilities. A basic principle to continue developing and investigating further!



Chesbrough, H. W. (2003). The era of Open Innovation. MIT Sloan Management Review, 44(3), 35–41.