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Analysis of systemic factors affecting carbon reduction in Chinese energy-intensive industries: A dual-driven DEMATEL model

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  • Sun, Yonghe
  • Huang, Zihang
  • Chi, Fudong

Abstract

To achieve China’s carbon reduction targets, energy-intensive industries (EIIs) must reduce emissions. This study aimed to investigate the driving forces affecting the carbon reduction of EIIs, presenting a novel dual-driven decision-making trial and evaluation laboratory (DU-DEMATEL) model to analyze the interactions between the driving factors. The proposed model overcomes the shortcomings of the traditional DEMATEL, which can only utilize the subjective experience of experts, and introduces objective data to form a DU-DEMATEL model that integrates both knowledge-driven and data-driven factors. The initial direct-relation matrix was organized as four modules by classifying the driving factors into knowledge-driven and data-driven, and four types of influence mechanisms are obtained. Low-quality data are corrected through expert reliability and quantifying the strength of influence between driving factors using Kullback–Leibler divergence. To verify the practicability of the novel model, this study investigated the smelting and pressing of ferrous metals industry in China using the DU-DEMATEL model, and demonstrated the superiority of the method through comparative analyses. The results revealed seven cause-driving and three effect-driving factors, and the most influence-driving factor was innovation, followed by economic scale. This study promotes the low-carbon development of China’s EIIs, and assists policymakers in formulating a scientific strategy for carbon reduction.

Suggested Citation

  • Sun, Yonghe & Huang, Zihang & Chi, Fudong, 2023. "Analysis of systemic factors affecting carbon reduction in Chinese energy-intensive industries: A dual-driven DEMATEL model," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223027135
    DOI: 10.1016/j.energy.2023.129319
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    References listed on IDEAS

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