Abstract
One of the major policies for improving industrial energy efficiency is networking companies by region and industrial sector to encourage them to share energy efficiency-related experiences and learn from one another and providing them with necessary support for energy efficiency investment. This method facilitates network management, but its effectiveness may be undermined by the heterogeneity of barriers perceived by the networked companies in the course of energy efficiency investment. Accordingly, this study proposes effective strategies for constructing energy efficiency networks with special reference to the main drivers of corporate investment in energy efficiency improvement for companies in South Korea, which is preparing to introduce related policies. We identified and quantified the major drivers of decision-making on energy efficiency investment in 32 Korean companies, using a hybrid method combining an analytic hierarchical process (AHP) and k-means clustering. The companies were divided into three subgroups with similar investment drivers. Significant differences existed in the decision-making steps of energy efficiency investment and major drivers considered important by the companies depending on corporate characteristics. Results also verified that classifying companies into homogeneous subgroups with similar investment drivers greatly contributes to constructing more effective networks and providing customized policy packages.
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The authors gratefully acknowledge the support of the KU-KIST School Project (Korea University).
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Jiyong Park: conceptualization, formal analysis, writing—original draft preparation
Taeyoung Jin: methodology, formal analysis, writing—original draft preparation
Sung-Eun Chang: formal analysis, writing—original draft preparation
JongRoul Woo: conceptualization, methodology, formal analysis, writing—reviewing and editing
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Park, J., Jin, T., Chang, SE. et al. A needs-based approach to construct an industrial energy efficiency network: a case study of South Korea. Energy Efficiency 16, 30 (2023). https://doi.org/10.1007/s12053-023-10110-y
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DOI: https://doi.org/10.1007/s12053-023-10110-y