Learning pathways for energy supply technologies: Bridging between innovation studies and learning rates
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Authors:
Mark Winskel Nils Markusson Henry Jeffrey Chiara Candelise Geoff Dutton Paul Howarth Sophie Jablonski Christos Kalyvas David Ward |
Original Language
Pages Number of Pages Journal Journal publication date Volume Early online date DOIs State |
English
96-114 19 Technological Forecasting and Social Change Jan 2014 81 5/11/13 http://dx.doi.org/10.1016/j.techfore.2012.10.015 Published |
Abstract
Supporting innovation and 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 used, often with little cross-over between them. Energy systems 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 evidence 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, and so better acknowledge the different niche origins and learning dynamics of energy supply technologies. Finally, future research issues are outlined.
Supporting innovation and 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 used, often with little cross-over between them. Energy systems 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 evidence 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, and so better acknowledge the different niche origins and learning dynamics of energy supply technologies. Finally, future research issues are outlined.
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