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Directional Bias between Communities of a Production Network in Japan

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Intelligent Decision Technologies

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 16))

Abstract

We investigate a production network constructed by about 800 thousand firms in Japan with focus on its transaction flow between communities. Communities detected by maximizing modularity often contain nodes with common properties such as characterized by regions or industry sectors. Communities may thus upstream-downstream relationship according to their characteristics. Such directional bias of the connections between communities is evaluated through a polarization matrix of the network direction. We also devise a visualization method for directed network based on physical model. We attempt to draw a map of Japanese transaction flow in viewpoint of community structure.

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Author information

Authors and Affiliations

  1. Faculty of Science, Niigata University, Ikarashi, Niigata, 950-2181, Japan

    Takashi Iino & Hiroshi Iyetomi

Authors
  1. Takashi Iino
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  2. Hiroshi Iyetomi
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Corresponding author

Correspondence to Takashi Iino .

Editor information

Editors and Affiliations

  1. Graduate School of Information,, Production & Systems (IPS), Waseda University, Hibikino 2-7, Kitakyushu, 808-0135, Japan

    Junzo Watada

  2. Graduate School of Information Science, Nagoya University, Furo-cho, Nagoya, 464-8601, Japan

    Toyohide Watanabe

  3. Sellinger School of Business and, Management, Loyola University Maryland, Charles Street 4501 N, Baltimore, 21210, USA

    Gloria Phillips-Wren

  4. KES International, PO Box 2115, Shoreham-by-Sea, BN43 9AF, United Kingdom

    Robert J. Howlett

  5. , School of Electrical and Information, University of South Australia, 5095, Adelaide, Australia

    Lakhmi C. Jain

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© 2012 Springer-Verlag Berlin Heidelberg

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Iino, T., Iyetomi, H. (2012). Directional Bias between Communities of a Production Network in Japan. In: Watada, J., Watanabe, T., Phillips-Wren, G., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29920-9_28

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  • DOI: https://doi.org/10.1007/978-3-642-29920-9_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29919-3

  • Online ISBN: 978-3-642-29920-9

  • eBook Packages: EngineeringEngineering (R0)

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