Abstract
The diffusion of cost-effective energy-efficiency measures (EEMs) in firms is often surprisingly slow. This phenomenon is usually attributed to a variety of barriers which have been the focus of numerous studies over the last two decades. However, many studies treat EEMs homogenously and assume they have few inherent differences apart from their profitability.
We argue that complementing such analyses by considering the characteristics of EEMs in a structured manner can enhance the understanding of EEM adoption. For this purpose, we suggest a classification scheme for EEMs in industry which aims to provide a better understanding of their adoption by industrial firms and to assist in selecting and designing energy-efficiency policies.
The suggested classification scheme is derived from the literature on the adoption of EEMs and the related fields including the diffusion of innovations, eco-innovations and advanced manufacturing technology. Our proposed scheme includes 12 characteristics based on the relative advantage, the technical and the information context of the EEM. Applying this classification scheme to six example EEMs demonstrates that it can help to systematically explain why certain EEMs diffuse faster than others. Furthermore, it provides a basis for identifying policies able to increase the rate of adoption.
We argue that complementing such analyses by considering the characteristics of EEMs in a structured manner can enhance the understanding of EEM adoption. For this purpose, we suggest a classification scheme for EEMs in industry which aims to provide a better understanding of their adoption by industrial firms and to assist in selecting and designing energy-efficiency policies.
The suggested classification scheme is derived from the literature on the adoption of EEMs and the related fields including the diffusion of innovations, eco-innovations and advanced manufacturing technology. Our proposed scheme includes 12 characteristics based on the relative advantage, the technical and the information context of the EEM. Applying this classification scheme to six example EEMs demonstrates that it can help to systematically explain why certain EEMs diffuse faster than others. Furthermore, it provides a basis for identifying policies able to increase the rate of adoption.
| Original language | English |
|---|---|
| Pages (from-to) | 502-513 |
| Number of pages | 12 |
| Journal | Energy Policy |
| Volume | 51 |
| DOIs | |
| Publication status | Published - Dec 2012 |
Bibliographical note
CIER-E-2012-73UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 13 Climate Action
Keywords
- Energy efficiency
- Adoption of energy-efficient technology
- Classification of energy-efficiency measures
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