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On Foresight Design and Management: A Classification Framework for Foresight Exercises

  • Totti KönnöläEmail author
  • Toni Ahlqvist
  • Annele Eerola
  • Sirkku Kivisaari
  • Raija Koivisto
Chapter
Part of the Complex Networks and Dynamic Systems book series (CNDS, volume 1)

Abstract

The gradual paradigm shift in innovation research and policy from linear to systemic innovation models has also challenged also the conventional technocratic technology-driven forecasting practices and called for new participatory and systemic foresight approaches (Smits and Kuhlmann 2004). In the 1980s, publicly funded foresight activities were commonly seen as an instrument for assisting in the development of priorities for research and development (R&D) resource allocation (Irvine and Martin 1984). Later on, stakeholder participation and networking have been regarded as increasingly important elements of foresight activities for ‘wiring up’ the multilayered innovation systems both in the public (Martin and Johnston 1999) and private sectors (e.g. Salmenkaita and Salo 2004). Reports from recent foresight projects have, in turn, emphasized the importance of common vision building as a step towards the synchronization of the innovation system (Cuhls 2003). In these developments, the locus of foresight activities has tended to shift from positivist and rationalist technology-focused approaches to the recognition of broader concerns that encompass the entire innovation system, including its environmental, social and economic perspectives. The High Level Expert Group appointed by the European Commission crystallized these trends by defining foresight as follows (European Commission 2002): ‘A systematic, participatory, future intelligence gathering and medium-to-long-term vision-building process aimed at present-day decisions and mobilizing joint action’.

Keywords

Innovation System Priority Setting Modular Design Stakeholder Engagement Stakeholder Participation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Totti Könnölä
    • 1
    Email author
  • Toni Ahlqvist
    • 2
  • Annele Eerola
    • 3
  • Sirkku Kivisaari
    • 3
  • Raija Koivisto
    • 4
  1. 1.Impetu Solutions, Palacio de MirafloresMadridSpain
  2. 2.VTT Technical Research Centre of FinlandTurkuFinland
  3. 3.VTT Technical Research Centre of FinlandVTT, EspooFinland
  4. 4.VTT Technical Research Centre of FinlandTampereFinland

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