TY - JOUR
T1 - Industrial clusters with substantial carbon-reduction potential
AU - Kanemoto, Keiichiro
AU - Hanaka, Tesshu
AU - Kagawa, Shigemi
AU - Nansai, Keisuke
N1 - Funding Information:
This work was supported by the Japan Society for the Promotion of Science through its Grant-in-Aid for Young Scientists (A) 15H05341, (Start-up) 26881005, and Grant-in-Aid for Scientific Research (A) 26241031 and 16H01797.
Publisher Copyright:
© 2018, © 2018 The International Input–Output Association.
PY - 2019/4/3
Y1 - 2019/4/3
N2 - To successfully reduce environmental emissions, companies need to expand the scope of their emissions accounting to include entire supply chains. A clustering approach has been used to find emission-intensive industry clusters. However, this approach did not include entire direct and indirect supply chains when forming high emission industry clusters. We propose a new method based on a modified normalized cut function with Leontief’s input–output model and basic clustering algorithms to find industry clusters with high levels of embodied within-cluster emissions that are well separated in the supply chain network. We use this method to identify 58 carbon-intensive clusters of Japanese industries and visualize the within-cluster supply chains in terms of embodied carbon flows. We recommend that companies collaborate within clusters to reduce environmental emissions. Our results provide new insights on where to target emissions reduction actions and technology development within industrial supply chains.
AB - To successfully reduce environmental emissions, companies need to expand the scope of their emissions accounting to include entire supply chains. A clustering approach has been used to find emission-intensive industry clusters. However, this approach did not include entire direct and indirect supply chains when forming high emission industry clusters. We propose a new method based on a modified normalized cut function with Leontief’s input–output model and basic clustering algorithms to find industry clusters with high levels of embodied within-cluster emissions that are well separated in the supply chain network. We use this method to identify 58 carbon-intensive clusters of Japanese industries and visualize the within-cluster supply chains in terms of embodied carbon flows. We recommend that companies collaborate within clusters to reduce environmental emissions. Our results provide new insights on where to target emissions reduction actions and technology development within industrial supply chains.
KW - Cluster analysis
KW - embodied emissions
KW - input–output analysis
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U2 - 10.1080/09535314.2018.1492369
DO - 10.1080/09535314.2018.1492369
M3 - Article
AN - SCOPUS:85050518054
SN - 0953-5314
VL - 31
SP - 248
EP - 266
JO - Economic Systems Research
JF - Economic Systems Research
IS - 2
ER -