Technological Learning in the Energy Sector

Technological Learning in the Energy Sector

Lessons for Policy, Industry and Science

Edited by Martin Junginger, Wilfried van Sark and André Faaij

Technological learning is a key driver behind the improvement of energy technologies and subsequent reduction of production costs. Understanding how and why production costs for energy technologies decline, and whether they will continue to do so in the future, is of crucial importance for policy makers, industrial stakeholders and scientists alike. This timely and informative book therefore provides a comprehensive review of technological development and cost reductions for renewable energy, clean fossil fuel and energy-efficient demand-side technologies.

Chapter 4: Putting Experience Curves in Context: Links to and between Technology Development, Market Diffusion, Learning Mechanisms and Systems Innovation Theory

Martin Junginger, Roald Suurs, Geert Verbong and Gerrit Jan Schaeffer

Subjects: economics and finance, energy economics, environment, energy policy and regulation, innovation and technology, technology and ict


Martin Junginger, Roald Suurs, Geert Verbong and Gerrit Jan Schaeffer 4.1 INTRODUCTION As far as the experience curve approach goes, the focus is mainly on quantifying the cost reductions of the technological artefact (e.g. a wind turbine or biomass power plant) due to technological development. However, the experience curve by itself offers no explanation why costs should decline in the first place. As illustrated in the previous chapter, circumstances such as market developments, knowledge diffusion, sector and geographical system boundaries all can have an impact on (the applicability of) the experience curve approach. Yet, many studies (both historical and prospective) do not place experience curves in a broader context. In this chapter, we point out some issues of the experience curve approach from an innovation studies perspective; we take a look at how far theories on learning mechanisms and innovation systems can contribute to a better understanding of technological learning (and associated cost reductions); and we discuss whether and how these concepts could be used to complement the experience curve approach. 4.2 EXPERIENCE CURVES, STAGES OF TECHNOLOGY DEVELOPMENT AND MECHANISMS OF LEARNING The learning curve was first observed in the mass production of cars. Researchers found a clear relation between unit cost and number of units 36 Putting experience curves in context 37 produced. They explained this empirical observation by assuming that numerous repetitions of the various operations in a production process triggered the gradual improvement and acceleration of this process, hence the name ‘learning curve’. Later, researchers expanded this...

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