Research on the risk evaluation of enterprises' carbon compliance failure
In order to mitigate global warming and help the country achieve its carbon peaking and carbon neutrality targets at the earliest possible time, the emission-control companies should accomplish the carbon compliance in accordance with relevant national policies and regulations. However, these compan...
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2023-04-01
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Series: | Frontiers in Ecology and Evolution |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fevo.2023.1152804/full |
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author | Xu Wang Ye Xu Wei Li |
author_facet | Xu Wang Ye Xu Wei Li |
author_sort | Xu Wang |
collection | DOAJ |
description | In order to mitigate global warming and help the country achieve its carbon peaking and carbon neutrality targets at the earliest possible time, the emission-control companies should accomplish the carbon compliance in accordance with relevant national policies and regulations. However, these companies frequently face the failure risk of carbon compliance subjected to various factors, including the national carbon quota policy, local carbon market situation, the verification of carbon offset projects, as well as the effectiveness of carbon reduction technologies. To help the enterprises avoid the risk of carbon-compliance failure and design rational carbon asset management strategy, in this research, the innovative combination of interpretive structural modeling (ISM), Bayesian network model, risk calculation and sensitivity analysis method was formulated. Firstly, the ISM method was used to establish a hierarchical relationship of risk factors that contribute to the failure of carbon compliance. Secondly, the probability prediction model of carbon-compliance failure risk based on the Bayesian network model was established by aid of the Netica software. Thirdly, the risk value of enterprise's carbon compliance failure was quantitatively calculated based on its production operation and carbon asset management. Finally, the sensitivity analysis method was used to identify critical risk factors and design risk control measures for six well-known domestic enterprises, laying good foundation for improving the success rate of carbon compliance and facilitating low-carbon green transformation. Compared to traditional qualitative risk assessment method, this combined approach is capable of realizing the quantitative evaluation of failure risk based on comprehensive investigation and analysis of the production and operational situation, which provides effective technical support to enhance enterprise's compliance awareness and improve low carbon competitiveness. |
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institution | Directory Open Access Journal |
issn | 2296-701X |
language | English |
last_indexed | 2024-04-09T16:06:39Z |
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publisher | Frontiers Media S.A. |
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series | Frontiers in Ecology and Evolution |
spelling | doaj.art-b26cdfe809b641108d93c301c752c2f82023-04-25T05:48:42ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2023-04-011110.3389/fevo.2023.11528041152804Research on the risk evaluation of enterprises' carbon compliance failureXu WangYe XuWei LiIn order to mitigate global warming and help the country achieve its carbon peaking and carbon neutrality targets at the earliest possible time, the emission-control companies should accomplish the carbon compliance in accordance with relevant national policies and regulations. However, these companies frequently face the failure risk of carbon compliance subjected to various factors, including the national carbon quota policy, local carbon market situation, the verification of carbon offset projects, as well as the effectiveness of carbon reduction technologies. To help the enterprises avoid the risk of carbon-compliance failure and design rational carbon asset management strategy, in this research, the innovative combination of interpretive structural modeling (ISM), Bayesian network model, risk calculation and sensitivity analysis method was formulated. Firstly, the ISM method was used to establish a hierarchical relationship of risk factors that contribute to the failure of carbon compliance. Secondly, the probability prediction model of carbon-compliance failure risk based on the Bayesian network model was established by aid of the Netica software. Thirdly, the risk value of enterprise's carbon compliance failure was quantitatively calculated based on its production operation and carbon asset management. Finally, the sensitivity analysis method was used to identify critical risk factors and design risk control measures for six well-known domestic enterprises, laying good foundation for improving the success rate of carbon compliance and facilitating low-carbon green transformation. Compared to traditional qualitative risk assessment method, this combined approach is capable of realizing the quantitative evaluation of failure risk based on comprehensive investigation and analysis of the production and operational situation, which provides effective technical support to enhance enterprise's compliance awareness and improve low carbon competitiveness.https://www.frontiersin.org/articles/10.3389/fevo.2023.1152804/fullcarbon compliancerisk evaluationISM methodBayesian networksensitivity analysis method |
spellingShingle | Xu Wang Ye Xu Wei Li Research on the risk evaluation of enterprises' carbon compliance failure Frontiers in Ecology and Evolution carbon compliance risk evaluation ISM method Bayesian network sensitivity analysis method |
title | Research on the risk evaluation of enterprises' carbon compliance failure |
title_full | Research on the risk evaluation of enterprises' carbon compliance failure |
title_fullStr | Research on the risk evaluation of enterprises' carbon compliance failure |
title_full_unstemmed | Research on the risk evaluation of enterprises' carbon compliance failure |
title_short | Research on the risk evaluation of enterprises' carbon compliance failure |
title_sort | research on the risk evaluation of enterprises carbon compliance failure |
topic | carbon compliance risk evaluation ISM method Bayesian network sensitivity analysis method |
url | https://www.frontiersin.org/articles/10.3389/fevo.2023.1152804/full |
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