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Evaluation index system for carbon information disclosure quality in China's electric power sector based on a mutual information and back propagation neural network model

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  • Liu, Zhibin
  • Wu, Jiayin

Abstract

This paper employs the Mutual Information (MI) and Back Propagation (BP) neural network model to screen the preliminarily constructed evaluation index system for carbon information disclosure (CID) quality of public companies in China's electric power sector (EPS), which is subsequently incorporated into the fuzzy comprehensive evaluation (FCE) method for evaluation application. The results show that (1) after screening, 19 out of the 31 preliminarily constructed indicators constitute an optimal index set, and (2) the evaluation application of the screened index system validates the feasibility and applicability of the index system. Simultaneously, the evaluation results reveal a generally low CID quality in the EPS.

Suggested Citation

  • Liu, Zhibin & Wu, Jiayin, 2024. "Evaluation index system for carbon information disclosure quality in China's electric power sector based on a mutual information and back propagation neural network model," Utilities Policy, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:juipol:v:89:y:2024:i:c:s0957178724000742
    DOI: 10.1016/j.jup.2024.101781
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    References listed on IDEAS

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    1. Tian Li & Shihong Zeng & Shaomin Wu & Qiao Peng, 2024. "Construction of a Corporate Carbon Disclosure Indicator System and Quality Evaluation: Evidence from Resource-Based Listed Companies," Sustainability, MDPI, vol. 17(1), pages 1-26, December.
    2. Peng Chen & Li Lan & Yanyuan Qian & Mingxing Guo & Wenhui Zhao, 2025. "Multi-Faceted Collaborative Investment Models and Investment Benefit Assessment Under the New Type Power System," Energies, MDPI, vol. 18(15), pages 1-26, July.

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