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Risk management of project information system operation and maintenance based on Cloud Computing

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  • Qunying Mao

    (Xinxiang University)

Abstract

In this experiment, according to the actual situation and content of the project information system operation and maintenance project, combined with the systematic research of relevant literature, the paper proposes to combine the coupling matrix method with the expert survey method to identify the risk factors in the operation and maintenance of engineering project information system. According to the results of risk factors identification, the risk evaluation system is established, and the corresponding risk matrix is constructed, and the risk organization structure is established to complete the risk control. The results show that the top three factors of occupation risk occurrence probability are spare parts arrival and damage (95%), cloud platform data backup and archiving (91%), change control process (90%); the top three factors of occupation risk value are cloud platform data backup and archiving (86.45%), spare parts and arrival (84.55%), change control process (83.70%); the above results show that the operation and maintenance risk of project information system Management should focus on spare parts arrival and damage, cloud platform data backup and archiving, change control process, and other risk factors in high-risk areas. At the same time, the risk management and control measures should be targeted, and the measures taken are different according to the degree of risk; the establishment of the project information system operation and maintenance risk management organization based on the management team structure is conducive to the operation and maintenance risk management.

Suggested Citation

  • Qunying Mao, 2023. "Risk management of project information system operation and maintenance based on Cloud Computing," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 176-187, February.
  • Handle: RePEc:spr:ijsaem:v:14:y:2023:i:1:d:10.1007_s13198-021-01461-9
    DOI: 10.1007/s13198-021-01461-9
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    References listed on IDEAS

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    1. Shikha Gupta & Anil K. Saini, 2017. "Modeling Trust Based Risk Management in Cloud Adoption using Fuzzy Inference System," International Journal of Technology Diffusion (IJTD), IGI Global, vol. 8(1), pages 52-60, January.
    2. Masky Mackita & Soo-Young Shin & Tae-Young Choe, 2019. "ERMOCTAVE: A Risk Management Framework for IT Systems Which Adopt Cloud Computing," Future Internet, MDPI, vol. 11(9), pages 1-21, September.
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