TY - JOUR
T1 - Finding environmentally important industry clusters
T2 - Multiway cut approach using nonnegative matrix factorization
AU - Kagawa, Shigemi
AU - Okamoto, Shunsuke
AU - Suh, Sangwon
AU - Kondo, Yasushi
AU - Nansai, Keisuke
N1 - Funding Information:
An early version of this paper was prepared for the International Conference on Input–Output Techniques, Seville, 9–11 July, 2008 and for the 19th Conference of the Pan Pacific Association of Input–Output Studies, Yamaguchi, 15–16 November, 2008. This research was supported by a Grant-in-Aid for research (No. 21710044 ) and (No. 23510046 ) from the Ministry of Education, Culture, Sports, Science and Technology in Japan , and partially supported by the Environment Research and Technology Development Fund ( K122024 ) from the Japanese Ministry of Environment . We thank Patrick Doreian, Chris H.Q. Ding and three anonymous referees for their helpful comments on this manuscript.
PY - 2013/7
Y1 - 2013/7
N2 - This paper proposes an optimal combinatorial method for finding groups of industries with relatively large CO2 emissions through industrial relations. Using an economic input-output table, we estimated a non-symmetric matrix describing how much CO2 is emitted in producing the commodity of industry i, which was purchased to produce commodity of industry j, to meet the final demand for a specific commodity. A symmetric strength of relations matrix describing the CO2 emissions associated with the industrial relations was further estimated using the non-symmetric matrix. The strength of relations matrix can be viewed as a representation of the supply-chain network of the final commodity. In this study, we estimated the strength of relations matrix associated with the final demand for automobiles and applied the multiway cut approach using nonnegative matrix factorization to the matrix in order to find environmentally important industry clusters in the Japanese automobile supply chain. According to our empirical results, the optimal number of industry clusters is 19, and 4 industry clusters are playing a key role in CO2 emission reduction.
AB - This paper proposes an optimal combinatorial method for finding groups of industries with relatively large CO2 emissions through industrial relations. Using an economic input-output table, we estimated a non-symmetric matrix describing how much CO2 is emitted in producing the commodity of industry i, which was purchased to produce commodity of industry j, to meet the final demand for a specific commodity. A symmetric strength of relations matrix describing the CO2 emissions associated with the industrial relations was further estimated using the non-symmetric matrix. The strength of relations matrix can be viewed as a representation of the supply-chain network of the final commodity. In this study, we estimated the strength of relations matrix associated with the final demand for automobiles and applied the multiway cut approach using nonnegative matrix factorization to the matrix in order to find environmentally important industry clusters in the Japanese automobile supply chain. According to our empirical results, the optimal number of industry clusters is 19, and 4 industry clusters are playing a key role in CO2 emission reduction.
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U2 - 10.1016/j.socnet.2013.04.009
DO - 10.1016/j.socnet.2013.04.009
M3 - Article
AN - SCOPUS:84880620292
VL - 35
SP - 423
EP - 438
JO - Social Networks
JF - Social Networks
SN - 0378-8733
IS - 3
ER -