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Identifying environmentally important supply chain clusters in the automobile industry

Author

Listed:
  • Shigemi Kagawa
  • Sangwon Suh
  • Yasushi Kondo
  • Keisuke Nansai

Abstract

In this paper, we develop a new approach that combines the spectral clustering method and input-output analysis to detect environmentally important supply chain clusters. The newly developed method was applied to automobile manufacturing in Japan, and major clusters with high energy intensities in the automobile supply chain were identified. This paper proposes that the car manufacturers will be able to regularly publish their life-cycle assessment reports with a focus on the indirect energy consumptions within the critical supply chains and request key auto-part manufacturers in the cluster to reduce the indirect consumptions through the relevant supply chain engagement.

Suggested Citation

  • Shigemi Kagawa & Sangwon Suh & Yasushi Kondo & Keisuke Nansai, 2013. "Identifying environmentally important supply chain clusters in the automobile industry," Economic Systems Research, Taylor & Francis Journals, vol. 25(3), pages 265-286, September.
    • Handle: RePEc:taf:ecsysr:v:25:y:2013:i:3:p:265-286
    DOI: 10.1080/09535314.2012.730992
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    Citations

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    Cited by:

    1. Maeno, Keitaro, 2023. "Identifying critical sectors in the restructuring of low-carbon global supply chains," Energy Economics, Elsevier, vol. 127(PA).
    2. Hanaka, Tesshu & Kagawa, Shigemi & Ono, Hirotaka & Kanemoto, Keiichiro, 2017. "Finding environmentally critical transmission sectors, transactions, and paths in global supply chain networks," Energy Economics, Elsevier, vol. 68(C), pages 44-52.
    3. Zhen, Wei & Zhong, Zhangqi & Wang, Yichen & Miao, Lu & Qin, Quande & Wei, Yi-Ming, 2019. "Evolution of urban household indirect carbon emission responsibility from an inter-sectoral perspective: A case study of Guangdong, China," Energy Economics, Elsevier, vol. 83(C), pages 197-207.
    4. Yicheol Han & Stephan J. Goetz & Claudia Schmidt, 2021. "Visualizing Spatial Economic Supply Chains to Enhance Sustainability and Resilience," Sustainability, MDPI, vol. 13(3), pages 1-15, February.
    5. Manojit Chattopadhyay & Sourav Sengupta & B.S. Sahay, 2016. "Visual hierarchical clustering of supply chain using growing hierarchical self-organising map algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(9), pages 2552-2571, May.
    6. Tokito, Shohei, 2018. "Environmentally-Targeted Sectors and Linkages in the Global Supply-Chain Complexity of Transport Equipment," Ecological Economics, Elsevier, vol. 150(C), pages 177-183.
    7. Keisuke Nansai & Kenichi Nakajima & Sangwon Suh & Shigemi Kagawa & Yasushi Kondo & Wataru Takayanagi & Yosuke Shigetomi, 2017. "The role of primary processing in the supply risks of critical metals," Economic Systems Research, Taylor & Francis Journals, vol. 29(3), pages 335-356, July.
    8. Tian, Xu & Chen, Bin & Geng, Yong & Zhong, Shaozhuo & Gao, Cuixia & Wilson, Jeffrey & Cui, Xiaowei & Dou, Yi, 2019. "Energy footprint pathways of China," Energy, Elsevier, vol. 180(C), pages 330-340.
    9. Maeno, Keitaro & Tokito, Shohei & Kagawa, Shigemi, 2022. "CO2 mitigation through global supply chain restructuring," Energy Economics, Elsevier, vol. 105(C).
    10. Tokito, Shohei & Kagawa, Shigemi & Nansai, Keisuke, 2016. "Understanding international trade network complexity of platinum: The case of Japan," Resources Policy, Elsevier, vol. 49(C), pages 415-421.

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