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A Group Decision-Making Model of Risk Evasion in Software Project Bidding Based on VPRS

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Book cover Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3642))

Abstract

This study develops a group decision-making model based on Variable Precision Rough Set, which can be used to adjust classification error in decision tables consisting of risk-evading level (REL) of software project bidding. In order to reflect experts’ ability, impartiality and carefulness roundly during the course of group decision-making, a weight is endowed with each expert. Integrated risk-evading level (IREL) of projects and risk indices are computed. Then, risk-evading measures, the rank of risk-evading strength and risk-evading methodology are discussed.

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Author information

Authors and Affiliations

  1. School of Management, Huazhong University of Science and Technology, 430074, Wuhan, China

    Gang Xie & Jinlong Zhang

  2. Department of Management Sciences, City University of Hong Kong, Hong Kong and College of Business Administration, Hunan University, China

    K. K. Lai

Authors
  1. Gang Xie
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  2. Jinlong Zhang
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  3. K. K. Lai
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2 Canada, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, P.O. Box, Poland

    Dominik Ślęzak

  2. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    JingTao Yao  & Wojciech Ziarko  & 

  3. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

  4. College of Computer and Information Engineering, Hehan University, Henan, China

    Xiaohua Hu

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© 2005 Springer-Verlag Berlin Heidelberg

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Xie, G., Zhang, J., Lai, K.K. (2005). A Group Decision-Making Model of Risk Evasion in Software Project Bidding Based on VPRS. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_56

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  • DOI: https://doi.org/10.1007/11548706_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28660-8

  • Online ISBN: 978-3-540-31824-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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