Skip to main content

Advertisement

Log in

A needs-based approach to construct an industrial energy efficiency network: a case study of South Korea

  • Original Article
  • Published:
Energy Efficiency Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2

Similar content being viewed by others

References

  • Apostolou, B., & Hassell, J. M. (1993). An empirical examination of the sensitivity of the analytic hierarchy process to departures from recommended consistency ratios. Mathematical and Computer Modelling, 17(4–5), 163–170. https://doi.org/10.1016/0895-7177(93)90184-Z

    Article  Google Scholar 

  • Barelli, L., Desideri, U., & Ottaviano, A. (2015). Challenges in load balance due to renewable energy sources penetration: The possible role of energy storage technologies relative to the Italian case. Energy, 93, 393–405. https://doi.org/10.1016/j.energy.2015.09.057

    Article  Google Scholar 

  • Chu, P., & Liu, J. K. H. (2002). Note on consistency ratio. Mathematical and Computer Modelling, 35(9–10), 1077–1080. https://doi.org/10.1016/S0895-7177(02)00072-9

    Article  MATH  Google Scholar 

  • Glowik, M., Bhatti, W. A., & Chwialkowska, A. (2022). A cluster analysis of the global wind power industry: Insights for renewable energy business stakeholders and environmental policy decision makers. Business Strategy and the Environment, 1–12. https://doi.org/10.1002/bse.3268

  • IEA. (2015). Energy and climate change. In World energy outlook special report. IEA. https://doi.org/10.1038/479267b

    Chapter  Google Scholar 

  • IEA. (2019). Energy efficiency is the first fuel, and demand for it needs to grow. Paris: IEA publishing.

    Google Scholar 

  • IEA. (2021a). Net zero by 2050 - A road map for the global energy sector. Paris: IEA publishing.

  • IEA. (2021b). Driving energy efficiency in heavy industries. Paris: IEA publishing.

  • Ilbahar, E., Kahraman, C., & Cebi, S. (2020). Risk assessment of renewable energy investments: A modified failure mode and effect analysis based on prospect theory and intuitionistic fuzzy AHP. Energy, 239, 121907. https://doi.org/10.1016/j.energy.2021.121907

    Article  Google Scholar 

  • Jalo, N., Johansson, I., Kanchiralla, F. M., & Thollander, P. (2021). Do energy efficiency networks help reduce barriers to energy efficiency? -A case study of a regional Swedish policy program for industrial SMEs. Renewable and Sustainable Energy Reviews, 151, 111579. https://doi.org/10.1016/j.rser.2021.111579

    Article  Google Scholar 

  • Jin, T., & Choi, B. (2020). Sectoral decomposition of Korea’s energy consumption by global value chain dimensions. Sustainability, 12(20), 8483. https://doi.org/10.3390/su12208483

    Article  Google Scholar 

  • Kodinariya, T. M., & Makwana, P. R. (2013). Review on determining number of cluster in k-means clustering. International Journal of Advance Research in Computer Science and Management Studies, 1, 90–95.

    Google Scholar 

  • The Government of Korea. (2020). Carbon neutrality strategy of the Republic of Korea 2050. The Government of Korea.

    Google Scholar 

  • Krarti, M., & Aldubyan, M. (2021). Role of energy efficiency and distributed renewable energy in designing carbon neutral residential buildings and communities: Case study of Saudi Arabia. Energy and Buildings, 250, 111309. https://doi.org/10.1016/j.enbuild.2021.111309

    Article  Google Scholar 

  • Liu, G., Yang, J., Hao, Y., & Zhang, Y. (2018). Big data-informed energy efficiency assessment of China industry sectors based on K-means clustering. Journal of Cleaner Production, 183, 304–314. https://doi.org/10.1016/j.jclepro.2018.02.129

    Article  Google Scholar 

  • Lu, J., Ren, L., Yao, S., Rong, D., Skare, M., & Streimikis, J. (2020). Renewable energy barriers and coping strategies: Evidence from the Baltic States. Sustainable Development, 28(1), 352–367. https://doi.org/10.1002/sd.2030

    Article  Google Scholar 

  • Marchesani, F. (2012). Drivers for industrial energy efficiency: An innovative framework. [Doctoral Dissertation. Polytechnic University of Milan].

    Google Scholar 

  • Miremadi, I., Saboohi, Y., & Jacobsson, S. (2018). Assessing the performance of energy innovation systems: Towards an established set of indicators. Energy Research and Social Science, 40, 159–176. https://doi.org/10.1016/j.erss.2018.01.002

    Article  Google Scholar 

  • OECD & IPEEC. (2016). Energy Efficiency Networks –An effective policy to stimulate energy efficiency. Paris: OECD publishing.

  • OECD & IPEEC. (2017). Energy Efficiency Networks: Towards good practices and guidelines for effective policies to stimulate energy efficiency. Paris: OECD publishing.

  • Price, L., & Worrell, E. (2000). International industrial sector energy efficiency policies. Lawrence Berkeley National Lab (LBNL).

    Book  Google Scholar 

  • Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill.

    MATH  Google Scholar 

  • Sen, S., & Ganguly, S. (2017). Opportunities, barriers and issues with renewable energy development – A discussion. Renewable and Sustainable Energy Reviews, 69, 1170–1181. https://doi.org/10.1016/j.rser.2016.09.137

    Article  Google Scholar 

  • Shen, M., Huang, W., Chen, M., Song, B., Zeng, G., & Zhang, Y. (2020). (Micro) plastic crisis: Un-ignorable contribution to global greenhouse gas emissions and climate change. Journal of Cleaner Production, 254, 120138. https://doi.org/10.1016/j.jclepro.2020.120138

    Article  Google Scholar 

  • Tørstad, V., Sælen, H., & Bøyum, L. S. (2020). The domestic politics of international climate commitments: Which factors explain cross-country variation in NDC ambition? Environmental Research Letters, 15(2), 24021. https://doi.org/10.1088/1748-9326/ab63e0

    Article  Google Scholar 

  • Trianni, A., Cagno, E., & Farné, S. (2016). Barriers, drivers and decision-making process for industrial energy efficiency: A broad study among manufacturing small and medium-sized enterprises. Applied Energy, 162, 1537–1551. https://doi.org/10.1016/j.apenergy.2015.02.078

    Article  Google Scholar 

  • Trianni, A., Cagno, E., Marchesani, F., & Spallina, G. (2017). Classification of drivers for industrial energy efficiency and their effect on the barriers affecting the investment decision-making process. Energy Efficiency, 10(1), 199–215. https://doi.org/10.1007/s12053-016-9455-6

    Article  Google Scholar 

  • Van Vuuren, D. P., Hoogwijk, M., Barker, T., Riahi, K., Boeters, S., Chateau, J., Scrieciu, S., van Vliet, J., Masui, T., Blok, K., Blomen, E., & Kram, T. (2009). Comparison of top-down and bottom-up estimates of sectoral and regional greenhouse gas emission reduction potentials. Energy Policy, 37(12), 5125–5139. https://doi.org/10.1016/j.enpol.2009.07.024

    Article  Google Scholar 

  • Verbruggen, A., Fischedick, M., Moomaw, W., Weir, T., Nadaï, A., Nilsson, L. J., Nyboer, J., & Sathaye, J. (2010). Renewable energy costs, potentials, barriers: Conceptual issues. Energy Policy, 38(2), 850–861. https://doi.org/10.1016/j.enpol.2009.10.036

    Article  Google Scholar 

  • Wu, Y.-H., Liu, C.-H., Hung, M.-L., Liu, T.-Y., & Masui, T. (2019). Sectoral energy efficiency improvements in Taiwan: Evaluations using a hybrid of top-down and bottom-up models. Energy Policy, 132, 1241–1255. https://doi.org/10.1016/j.enpol.2019.06.043

    Article  Google Scholar 

  • Zarazua de Rubens, G. (2019). Who will buy electric vehicles after early adopters? Using machine learning to identify the electric vehicle mainstream market. Energy, 172, 243–254. https://doi.org/10.1016/j.energy.2019.01.114

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the support of the KU-KIST School Project (Korea University).

Author information

Authors and Affiliations

Authors

Contributions

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

Corresponding author

Correspondence to JongRoul Woo.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12053-023-10110-y

Keywords

Navigation