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Research on Safety Production Risk Identification and Assessment Model for Power Grid Mergers and Acquisitions Enterprises Based on Due Diligence

Author

Listed:
  • Chao Liu

    (China Southern Power Grid Co., Ltd., Guangzhou 510623, China)

  • Qinying Liu

    (Electric Power Research Institute, China Southern Power Grid, Guangzhou 510700, China)

  • Dongming Peng

    (China Southern Power Grid Co., Ltd., Guangzhou 510623, China)

  • Pingping Que

    (Electric Power Research Institute, Guangxi Power Grid Co., Ltd., Nanning 530013, China)

  • Yiqi Li

    (China Academy of Safety Science & Technology, Beijing 100012, China)

  • Bingkang Li

    (Department of Economic Management, North China Electric Power University, Baoding 071003, China)

Abstract

Safety production constitutes a core pillar of operational management for power grid enterprises. Assessing the safety production risks of target entities in mergers and acquisitions (M&A) is a prerequisite for strengthening safety governance, and it holds significant value for elevating the safety levels of power grids, equipment, and personnel. To address the issues of inconsistent assessment dimensions and over-reliance on empirical judgment in safety production risk evaluation during power grid M&A activities, this paper proposes an assessment model that integrates due diligence information with hybrid multi-attribute decision-making (MADM). By systematically identifying safety production risk factors throughout the M&A process, an indicator system encompassing four dimensions—physical constraints, management systems, historical performance, and dynamic adaptability—is established. A game-theoretic approach is adopted to combine the Level-Based Weight Assessment (LBWA) method and the Criteria Importance Through Inter-criteria Correlation (CRITIC) method for subjective–objective integrated weighting. Additionally, grey relational analysis (GRA) is introduced to refine the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) algorithm, enabling quantitative evaluation of risk levels. Case analysis results demonstrate that the proposed model can effectively distinguish risk discrepancies across different M&A scenarios with rational weight allocation for key indicators. Compared with traditional methods, it maintains ranking consistency while exhibiting higher discrimination efficiency, thus providing a scientific and effective risk assessment tool for power grid enterprises’ M&A decision-making.

Suggested Citation

  • Chao Liu & Qinying Liu & Dongming Peng & Pingping Que & Yiqi Li & Bingkang Li, 2026. "Research on Safety Production Risk Identification and Assessment Model for Power Grid Mergers and Acquisitions Enterprises Based on Due Diligence," Sustainability, MDPI, vol. 18(5), pages 1-25, March.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:5:p:2410-:d:1876150
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