• DocumentCode
    3322460
  • Title

    Outsourcing Resource Selection: A Rough Set Approach

  • Author

    Zhu, Dan ; Meng, Qiang ; Zhao, J. Leon

  • Author_Institution
    Dept. of Logistics, Operations & MIS, Iowa State Univ., Ames, IA
  • fYear
    2007
  • fDate
    Jan. 2007
  • Firstpage
    54
  • Lastpage
    54
  • Abstract
    Today´s economic reality is forcing firms to become increasingly more efficient in managing their resource functions. Outsourcing has moved to the mainstream of business development and promised to be one of the many enterprise strategies for cost-effective service delivery. Proper screening and automatic selection of outsource partners are critical to the business. Resource selection is one of the most important steps in outsourcing decision-making processes. This paper considers a data intensive selection problem in outsourcing software development projects. We analyze the properties of the resource selection problem and propose some criteria for an automatic resource selection model. A naive model, a traditional rough set model, and a generalized rough set (GRS) model are introduced and the advantages and disadvantages of each model are compared. Experimental results indicate that the GRS model is superior to other models
  • Keywords
    decision making; outsourcing; project management; rough set theory; software development management; business development; cost-effective service delivery; data intensive resource selection; decision-making process; enterprise strategy; generalized rough set; naive model; outsourcing; software development project; Conference management; Contracts; Humans; Java; Manufacturing; Outsourcing; Programming; Proposals; Resource management; Rough sets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences, 2007. HICSS 2007. 40th Annual Hawaii International Conference on
  • Conference_Location
    Waikoloa, HI
  • ISSN
    1530-1605
  • Electronic_ISBN
    1530-1605
  • Type

    conf

  • DOI
    10.1109/HICSS.2007.422
  • Filename
    4076480