Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China

Research Article

Research on the Evaluation Model of Physical Asset Management Maturity of China's Inter-provincial Grid Enterprises

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  • @INPROCEEDINGS{10.4108/eai.18-11-2022.2327155,
        author={Xiaoman  Zhang and Xia  Qi and Xu  Cheng and Pinjie  Xie},
        title={Research on the Evaluation Model of Physical Asset Management Maturity of China's Inter-provincial Grid Enterprises},
        proceedings={Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China},
        publisher={EAI},
        proceedings_a={ICEMME},
        year={2023},
        month={2},
        keywords={physical assets of power grid; comprehensive evaluation; indicator system; maturity model},
        doi={10.4108/eai.18-11-2022.2327155}
    }
    
  • Xiaoman Zhang
    Xia Qi
    Xu Cheng
    Pinjie Xie
    Year: 2023
    Research on the Evaluation Model of Physical Asset Management Maturity of China's Inter-provincial Grid Enterprises
    ICEMME
    EAI
    DOI: 10.4108/eai.18-11-2022.2327155
Xiaoman Zhang1, Xia Qi1, Xu Cheng1, Pinjie Xie2,*
  • 1: State Grid Jibei Electric Power Co., Ltd. Economic and Technical Research Institute
  • 2: College of Economics and Management Shanghai University of Electric Power
*Contact email: yjzxpj@shiep.edu.cn

Abstract

A comprehensive evaluation of the physical assets of power grid enterprises is conducive to promoting the management of assets of enterprises and avoiding the loss and waste of state-owned assets. This paper collects the objective statistics of the enterprise and the subjective scoring data of the experts in the index system for the past 5 years, and determines the comprehensive weight of each index through the combination of subjective and objective weights. Grey correlation and topsis method is used to establish a dynamic evaluation model for objective data to capture the trend of the comprehensive value of physical assets, and subjective data is used to establish a maturity model to calculate the maturity level of physical assets. In this way, the results of dynamic assessment and maturity assessment are combined to obtain the results of grid enterprise asset evaluation under multi-dimensional dynamic perspective. Finally, an empirical analysis using a grid data shows that the company should learn from the scientific management experience of 2016, maintain a high level of asset structure and utilization efficiency, and focus on improving the optimal management of asset decommissioning and health.