Basic research →Applied research →Development →(Production and) Diffusion

A traditional method of analysing innovation policy is through the lens of the Linear model of innovation…

• due to it’s… simplicity and its ability to provide a sense of orientation for administrators, simplifying complex processes to aid decision-makers in allocating funding to research and development (Godin, 0000).
• It is a straightforward framework (theoretical construction as a result of industrialisation and increasing mathemtisation of economics). 1. Basic Research 2. Applied Research 3. Development 4. Diffusion
• Assigns role of the state, strengths and weaknesses - directly lends itself to the market failure narrative of the pharma health innovation system.

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A traditional method of assessing an innovation policy is with the linear model of innovation; a framework that XYZ…

The linear model of innovation is, at best, a practical way of understanding the innovation process. At worst, it;s a rigid template for academics to assess things through proxy.

It is, rather, a theoretical construction of industrialists, consultants, and business schools, seconded by economist.

The model is a rhetorical entity. It is a thought figure that simplifies and affords administrators and agencies a sense of orientation when it comes to thinking about allocation of funding to R&D. However, official statistics are, in fact, more important in explaining the continued use of the linear mode.l

The model has been very influential. Academic organizations as a lobby for research funds (National Science Foundation 1957a) and economists as expert advisors to policy makers (Nelson 1959) have widely disseminated the model, or the understanding based thereon, and have justified government support to science using such a model. As a consequence, science policies carried a linear conception of innovation for many decades (Mowery 1983).

“Everyone knows that the linear model of innovation is dead,” claimed N. Rosenberg (1994)

The article also argues that the long survival of the model despite regular criticisms is because of statistics. In fact, statistics on the three components of research were for a longtime (and still are, for many) the only available statistics allowing one to understand the internal organization of research, particularly in firms.

Furthermore, as innovation came to define the science-policy agenda, statistics on R&D were seen as a legitimate proxy for measuring technological innovation because they included development (of new products and processes).