2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07) (2007)
Big Island, Hawaii
Jan. 3, 2007 to Jan. 6, 2007
Dan Zhu , Iowa State University, Ames, IA
Qiang Meng , Iowa State University, Ames, IA
J. Leon Zhao , University of Arizona, Tucson, AZ
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.
Q. Meng, J. L. Zhao and D. Zhu, "Outsourcing Resource Selection: A Rough Set Approach," 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)(HICSS), Big Island, Hawaii, 2007, pp. 54a.