A partitioned random network agent model for organizational sectionalism studies

  • Authors:

  • Kikuo Yuta;Yoshi Fujiwara;Wataru Souma;Keiki Takadama;Katsunori Shimohara;Osamu Katai

  • Affiliations:

  • ATR Network Informatics Laboratories, Kyoto, Japan and Kyoto University, Graduate School of Informatics, Kyoto, Japan;ATR Network Informatics Laboratories, Kyoto, Japan;ATR Network Informatics Laboratories, Kyoto, Japan;ATR Network Informatics Laboratories, Kyoto, Japan and Tokyo Institute of Technology, Interdisciplinary Graduate School of Science and Engineering, Yokohama, Kanagawa, Japan;ATR Network Informatics Laboratories, Kyoto, Japan and Kyoto University, Graduate School of Informatics, Kyoto, Japan;Kyoto University, Graduate School of Informatics, Kyoto, Japan

  • Venue:
  • JSAI'03/JSAI04 Proceedings of the 2003 and 2004 international conference on New frontiers in artificial intelligence
  • Year:
  • 2003

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Abstract

This paper presents a new organization model that addresses the effects of networks on the sectionalism phenomenon, defined as excessive concern that members of a section have for the interests of their own section. No studies tackled the relationship between human communication networks and sectionalism. The points of our model design are: network distributed agents with a sense of values, extended random network structures, and a new index to monitor sectionalism. A homogeneous effect of communication networks and a heterogeneous effect of sectional specialization were also introduced into the model. Empirical results showed that sectionalism behavior and the performance of the proposed index were superior to conventional indices when capturing sectional structures. Finally, we showed one example of the availability of such a multi-agent network approach. Simulation results clearly illustrated the effect of cross-sectional links on sectionalism reduction by following a so-called "power law."