Envisioning structural transformation - lessons from a foresight project on the future of innovation

Elna Schirrmeister, Philine Warnke

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung


The paper aims to contribute towards building foresight capacities for systemic and structural transformations. Experiences from a foresight project exploring future innovation patterns (www.innovation-futures.org) are discussed. Four specific features were applied in order to underpin the recognition of structural transformation: . Inductive foresight approach with an emphasis on capturing indications for extra-systemic change at a micro level instead of extrapolating seemingly dominant macro-trends. . Visual inspiration, tomobilise tacit knowledge, support a creative spirit and an easy exchange of ideas among people with different disciplinary backgrounds. . Rigorous assessment of coverage of dimensions of change, to foster the explicit consideration of possibly unrecognised/hidden structural changes . Extended openness for diversity, to avoid the exclusive interpretation of weak signals only in the context of the existing structures. The findings of the project indicate interesting changes in the nexus of innovation demand and innovation supply. A wide variety of hybrid value creation models with novel configurations of innovation actors emerged. We explain the approach and findings of the project and discuss in particular the implications for foresight methodology. We argue that all four innovative methodological features contributed in a specific way to opening up new perspectives on the future of innovation and potential structural transformation of innovation processes.
Seiten (von - bis)453-466
FachzeitschriftTechnological Forecasting & Social Change
PublikationsstatusVeröffentlicht - 2013

Research Field

  • Ehemaliges Research Field - Innovation Systems and Policy


  • Vision
  • Structural transformation
  • Inductive approach
  • Foresight methodology
  • Innovation pattern
  • Visualisation
  • Scenarios
  • Weak signals


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