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A Two-Level Principal-Agent Model for Schedule Risk Control of IT Outsourcing Project Based on Genetic Algorithm

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Proceedings of the 23rd International Conference on Industrial Engineering and Engineering Management 2016

Abstract

IT service outsourcing is an effective way to enhance the core competitiveness for many enterprises. But the schedule risk of IT outsourcing project may cause enormous economic loss to enterprise. In this paper, the principal-agent theory is used to build the model for schedule risk control of IT outsourcing project. According to the feature of problem, Genetic Algorithm (GA) is designed to solve the proposed model and the optimal plan of controlling schedule risk is given based on the simulation analysis. The simulation results demonstrate that this paper can provide the scientific quantitative proposal for the decision maker who needs to control the schedule risk of IT outsourcing project.

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Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Fuquan Sun, Shupeng Duan, Fuqian Lu & Hualing Bi

Authors
  1. Fuquan Sun
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  2. Shupeng Duan
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  3. Fuqian Lu
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  4. Hualing Bi
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Corresponding author

Correspondence to Fuqian Lu .

Editor information

Editors and Affiliations

  1. College of Management and Economics, Tianjin University College of Management and Economics, Tianjin, China

    Ershi Qi

  2. College of Management and Economics, Tianjin University College of Management and Economics, Tianjin, China

    Jiang Shen

  3. College of Mgmt & Economics, Tianjin University College of Mgmt & Economics, Tianjin, China

    Runliang Dou

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Sun, F., Duan, S., Lu, F., Bi, H. (2017). A Two-Level Principal-Agent Model for Schedule Risk Control of IT Outsourcing Project Based on Genetic Algorithm. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of the 23rd International Conference on Industrial Engineering and Engineering Management 2016. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-255-7_37

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  • DOI: https://doi.org/10.2991/978-94-6239-255-7_37

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  • Publisher Name: Atlantis Press, Paris

  • Print ISBN: 978-94-6239-254-0

  • Online ISBN: 978-94-6239-255-7

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