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March 4, 2026Sustainability0 citationsOpen Access

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

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CLChao LiuQLQinying LiuDPDongming Peng

Key Points

  • The aim is to develop a model for assessing safety production risks during mergers and acquisitions in power grid enterprises.
  • Integrate due diligence information with multi-attribute decision-making (MADM) techniques.
  • Establish an indicator system based on four dimensions: physical constraints, management systems, historical performance, and dynamic adaptability.
  • Utilize game-theoretic approaches combined with Level-Based Weight Assessment (LBWA) and Criteria Importance Through Inter-criteria Correlation (CRITIC) for weighting.
  • Employ grey relational analysis to enhance the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) algorithm.
  • The proposed model effectively distinguishes risk differences across various M&A scenarios.
  • Achieves rational weight allocation for key indicators leading to improved assessment accuracy.
  • Maintains ranking consistency and higher discrimination efficiency compared to traditional methods.

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.

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Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/69a7cce8d48f933b5eed8cebhttps://doi.org/10.3390/su18052410
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