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Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Research on Risk Evaluation of Human Resource Management Outsourcing Based on Data Driven

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  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322783,
        author={Tao  Liu},
        title={Research on Risk Evaluation of Human Resource Management Outsourcing Based on Data Driven},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={human resource management; information systems; digital transformation; outsourcing risk; analytic hierarchy process; cloud model},
        doi={10.4108/eai.17-6-2022.2322783}
    }
    
  • Tao Liu
    Year: 2022
    Research on Risk Evaluation of Human Resource Management Outsourcing Based on Data Driven
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322783
Tao Liu1,*
  • 1: Wuhan Business University
*Contact email: 7891950@qq.com

Abstract

This paper proposes a set of data-driven human resources information system architecture, and specifically clarifies the technical implementation method of each layer in the architecture, the program flow of the system and the management of employee basic data, employee information management, reward and punishment management, salary management, service The setting, function and key technologies in development of five subsystems including management have been deeply analyzed and studied. The weight coefficient of each index is determined by the Analytic Hierarchy Process (AHP), the cloud model is introduced, and the quantitative and qualitative concepts are converted to each other using the forward and reverse cloud generator.

Keywords
human resource management; information systems; digital transformation; outsourcing risk; analytic hierarchy process; cloud model
Published
2022-10-13
Publisher
EAI
http://dx.doi.org/10.4108/eai.17-6-2022.2322783
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