Abstract
Foresight is a powerful tool that is frequently applied in response to major challenges facing science, technology, and innovation policy. With the use of Foresight studies, policy makers give a clear indication to the science, technology, and innovation community that policy making is considering a bottom-up approach rather than a purely top-down one. Foresight exercises go beyond simple predictions to become anticipatory intelligence, based on a wide diversity of viewpoints, and knowledge sources. Due to the varying nature and characteristics of Foresight studies, there is no “one indicator that fits all” – different motivations and objectives, different methods and techniques, imply different outputs and outcomes. Hence the indicators we use to describe the studies may take on different meanings – even quantitative indicators can require a great deal of interpretation. Furthermore, the longer-term impacts of the work cannot be assessed in the immediate aftermath of the work. But while many indicators are tailor-made for specific Foresight studies, and are not necessarily fully comparable with those of other different Foresight studies, it is possible to learn from experience and use the indicators and indicator frameworks of earlier Foresight exercises in later ones.
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Meissner, D. (2013). Instruments to measure Foresight. In: Meissner, D., Gokhberg, L., Sokolov, A. (eds) Science, Technology and Innovation Policy for the Future. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31827-6_4
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DOI: https://doi.org/10.1007/978-3-642-31827-6_4
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