Finding environmentally important industry clusters: Multiway cut approach using nonnegative matrix factorization

Shigemi Kagawa, Shunsuke Okamoto, Sangwon Suh, Yasushi Kondo, Keisuke Nansai

    Research output: Contribution to journalArticle

    29 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)423-438
    Number of pages16
    JournalSocial Networks
    Volume35
    Issue number3
    DOIs
    Publication statusPublished - 2013 Jul

    Fingerprint

    Industry
    commodity
    industry
    Automobiles
    industrial relations
    motor vehicle
    supply
    demand
    Economics
    economics
    Group

    Keywords

    • CO
    • Industry cluster
    • Multiway cut approach
    • Nonnegative matrix factorization
    • Supply chain

    ASJC Scopus subject areas

    • Sociology and Political Science
    • Social Sciences(all)
    • Anthropology
    • Psychology(all)

    Cite this

    Finding environmentally important industry clusters : Multiway cut approach using nonnegative matrix factorization. / Kagawa, Shigemi; Okamoto, Shunsuke; Suh, Sangwon; Kondo, Yasushi; Nansai, Keisuke.

    In: Social Networks, Vol. 35, No. 3, 07.2013, p. 423-438.

    Research output: Contribution to journalArticle

    Kagawa, Shigemi ; Okamoto, Shunsuke ; Suh, Sangwon ; Kondo, Yasushi ; Nansai, Keisuke. / Finding environmentally important industry clusters : Multiway cut approach using nonnegative matrix factorization. In: Social Networks. 2013 ; Vol. 35, No. 3. pp. 423-438.
    @article{cbe9e176a16a429db0b33bc96c03a036,
    title = "Finding environmentally important industry clusters: Multiway cut approach using nonnegative matrix factorization",
    abstract = "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.",
    keywords = "CO, Industry cluster, Multiway cut approach, Nonnegative matrix factorization, Supply chain",
    author = "Shigemi Kagawa and Shunsuke Okamoto and Sangwon Suh and Yasushi Kondo and Keisuke Nansai",
    year = "2013",
    month = "7",
    doi = "10.1016/j.socnet.2013.04.009",
    language = "English",
    volume = "35",
    pages = "423--438",
    journal = "Social Networks",
    issn = "0378-8733",
    publisher = "Elsevier BV",
    number = "3",

    }

    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

    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.

    KW - CO

    KW - Industry cluster

    KW - Multiway cut approach

    KW - Nonnegative matrix factorization

    KW - Supply chain

    UR - http://www.scopus.com/inward/record.url?scp=84880620292&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84880620292&partnerID=8YFLogxK

    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 -