• DocumentCode
    2770242
  • Title

    Cooperation-based Clustering for Profit-maximizing Organizational Design

  • Author

    Tran, Nghia ; Giraud-Carrier, Christophe ; Seppi, Kevin ; Warnick, Sean

  • Author_Institution
    Brigham Young Univ., Provo
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1813
  • Lastpage
    1817
  • Abstract
    This paper shows how the notion of value of cooperation, a measure of the percentage of a Arm´s profits due strictly to the cooperative effects among the goods it sells, can be used to analyze the relative economic advantage afforded by various organizational structures. The value of cooperation is computed from transactions data by solving a regression problem to fit the parameters of the consumer demand function, and then simulating the resulting profit-maximizing dynamic system under various organizational structures. A hierarchical agglomerative clustering algorithm can be applied to reveal the optimal organizational substructure.
  • Keywords
    organisational aspects; pattern clustering; profitability; regression analysis; consumer demand function; cooperation-based clustering; economic advantage; hierarchical agglomerative clustering algorithm; profit-maximizing dynamic system; profit-maximizing organizational design; regression problem; Clustering algorithms; Computational modeling; Computer science; Corporate acquisitions; Game theory; Mutual coupling; Organizational aspects; Performance analysis; Profitability; Virtual colonoscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246899
  • Filename
    1716329