Outsourcing resource selection : A rough set approach

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings of the Annual Hawaii International Conference on System Sciences
StatePublished - 2007
Externally publishedYes

Publication series

Name
ISSN (Print)1530-1605

Conference

Title40th Annual Hawaii International Conference on System Sciences 2007, HICSS'07
PlaceUnited States
CityBig Island, HI
Period3 - 6 January 2007

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. © 2007 IEEE.

Citation Format(s)

Outsourcing resource selection : A rough set approach. / Zhu, Dan; Meng, Qiang; Zhao, J. Leon.

Proceedings of the Annual Hawaii International Conference on System Sciences. 2007. 4076480.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review