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Learning pathways for energy supply technologies: bridging between innovation studies and learning rates

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Mark Winskel
  • Nils Markusson
  • Henry Jeffrey
  • Chiara Candelise
  • Geoff Dutton
  • Paul Howarth
  • Sophie Jablonski
  • Christos Kalyvas
  • David Ward
<mark>Journal publication date</mark>01/2014
<mark>Journal</mark>Technological Forecasting and Social Change
Pages (from-to)96–114
Publication StatusPublished
Early online date2/01/13
<mark>Original language</mark>English


Understanding and supporting learning for different emerging low carbon energy supply technology fields is a key issue for policymakers, investors and researchers. A range of contrasting analytical approaches are available: energy system modelling using learning rates provides abstracted, quantitative and output oriented accounts, while innovation studies research offers contextualised, qualitative and process oriented accounts. Drawing on research literature and expert consultation on learning for several different emerging energy supply technologies, this paper introduces a ‘learning pathways’ matrix to help bridge between the rich contextualisation of innovation studies and the systematic comparability of learning rates. The learning pathways matrix characterises technology fields by their relative orientation to radical or incremental innovation, and to concentrated or distributed organisation. A number of archetypal learning pathways are outlined to help learning rates analyses draw on innovation studies research, so as to better acknowledge the different niche origins and learning dynamics of emerging energy supply technologies. Finally, a future research agenda is outlined, based on socio-technical learning scenarios for accelerated energy innovation.