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Science and technology policy-making and the study of its effects on innovation are requiring a “more sophisticated understanding of the ways on which science and technology interact” (to quote, as an example, N. Rosenberg, Science and Public Policy, vol 18, number 6, pages 335-346, 1991). The exploration of these relations has been and continues to be at the core of the models that, along the period initiated after the Second World War, have been used to promote and analyse the science and technology activities and their outcomes. The “science model” left pace to the “science push-market pull – R&D model”, inspired on linearity, a model that represented the technological change leading to innovation as closely dependent and based essentially on scientific results. More recently, after acknowledgement of the insufficiencies of the linear model, models have evolved considering that science and technology and innovation are part of a system, a “social” system, whose essential activity is learning and which is also “dynamic”. This orientation has corresponded with the idea that biology, and not physics, ought to inspire the economics of technology and innovation (application of the theory of Darwinian evolution, see for a review, J. Mokyr, Bulletin of Economic Research, vol 43, number 2, pages 127-149, 1991). The microeconomics view has been at the onset of recognising the limitations of the dominant neoliberal theory based on the concept of a stable and unique equilibrium. An important lesson that has been learned from the use of evolutionary, biology based, models is that history – and culture – matters. As Mokyr has stated (see reference cited above) “... It is simply impossible to understand longterm economic growth without some kind of Schumpeterian theory of technological creativity and innovation. The neoclassical equilibrium paradigm seems singularly unsuited to that task”. |
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