Abstract
The increasing complexity of the relations between technologies and economics combined with more social pressure, global competition, technological change, as well as national budget restrictions, imply new challenges for public policies. Thus, to be able to forecast the development of knowledge and technological change in some well-known trajectories could be one of the major stakes for science technology and industrial policies. It is then not surprising that recent years have brought a significant revival of public foresight activities in many countries. The purpose of the paper is precisely to propose a new foresight method in order to obtain a taxonomy of the future technologies, and consequently to provide a better understanding of industrial dynamics. We present a statistical analysis of a Delphi investigation, based on scientific and technological knowledge complementarities, in order to obtain coherent clusters, which may be looked upon as a theoretical tool for political decisions. Our methodology is then applied to French and the German sectors of life sciences, elementary particles, energy, environment and natural resources.
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