Accelerating Low-Carbon Innovation
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Date
2020-11-18
Publication Type
Review Article
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yes
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Abstract
Accelerating innovation in low-carbon technologies is fundamental to achieving global climate targets. However, only few technologies, such as solar PV, LEDs, and electric vehicles, are currently on track to meet these targets. In contrast, many other technologies, such as nuclear power, biomass power, and carbon capture and storage (CCS) are not on track. In this perspective, we conduct a thorough review of experience rates of low-carbon technologies that have been reported in the existing literature. We also draw on complexity theory, evolutionary economics, and cybernetic theory to develop a technology typology that helps explain systematic differences in technologies’ experience rates by distinguishing between technologies on the basis of (1) their design complexity and (2) the extent to which they need to be customized. Based on this typology, we derive implications for policy makers and climate and energy modelers. We argue that the Paris Agreement's reliance on the nationally driven green industrial policy only suits innovation in certain types of technologies, and thus, should be complemented by top-down measures to coordinate R&D, demonstration, deployment, and regulations across countries. We suggest that integrated assessment modelers and policy scholars concerned with the political feasibility and dynamics of interventions should take caution with respect to technologies with high design complexity and need for customization, where global experience rates might be substantially lower than what can be expected from the diffusion in current localized niche markets. Finally, while several approaches for measuring the design complexity and need for customization of technologies exist in the literature, innovation scholars should direct their efforts toward improving our understanding of how these approaches differ and toward characterizing different technologies along the two dimensions in a systematic and replicable manner.
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published
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Journal / series
Volume
4 (11)
Pages / Article No.
2259 - 2267
Publisher
Elsevier
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Software
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Subject
Technological innovation; Experience rates; Knowledge spillovers; Green industrial policy; international coordination
Organisational unit
09550 - Schmidt, Tobias / Schmidt, Tobias
02890 - Albert Einstein School of Public Policy / Albert Einstein School of Public Policy