Yuanxin Liu, Xu Luo, Shuo He, Jiahai Yuan, Yao Tao
{"title":"Risk identification, analysis, and solution to carbon finance development in China: An improved DEMATEL-ISM approach under fuzzy environment","authors":"Yuanxin Liu, Xu Luo, Shuo He, Jiahai Yuan, Yao Tao","doi":"10.1177/0958305x231205513","DOIUrl":null,"url":null,"abstract":"Developing carbon finance is significant to a green-oriented transition of energy but suffering risks in China. This article aims to construct a framework for the risk identification, analysis, and solution of carbon finance development. It could help trading parties, third-party intermediaries, and government to understand the main obstacles to carbon finance and then take effective control measures. Firstly, 12 risk factors in policy, economy, environment, technology, and society five aspects are identified. Secondly, the risk analysis data is obtained through a comparison of the mutual influence degree of factors, where hesitant fuzzy linguistic term set is used to collect the initial information and triangular intuitionistic fuzzy number is employed to quantify the qualitative linguistics. Expanding the analysis into fuzzy environment can avoid the loss of decision information caused by traditional single real number evaluation. Thirdly, the improved decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling methods are combined to gain the risk analysis results. K-means is used to refine the influence relationship between factors in traditional DEMATEL to three categories: high effect, low effect, and no effect, which enhances applicability of the model in reality. Finally, corresponding improvement schemes and policy suggestions are proposed for each risk factor. The findings of research show that among the risks hindering carbon finance development: low carbon price, immature carbon abatement technology, lack of carbon financial products, and operational risk are the direct factors; adjustments in international climate policy is the fundamental factor.","PeriodicalId":505265,"journal":{"name":"Energy & Environment","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy & Environment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/0958305x231205513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Developing carbon finance is significant to a green-oriented transition of energy but suffering risks in China. This article aims to construct a framework for the risk identification, analysis, and solution of carbon finance development. It could help trading parties, third-party intermediaries, and government to understand the main obstacles to carbon finance and then take effective control measures. Firstly, 12 risk factors in policy, economy, environment, technology, and society five aspects are identified. Secondly, the risk analysis data is obtained through a comparison of the mutual influence degree of factors, where hesitant fuzzy linguistic term set is used to collect the initial information and triangular intuitionistic fuzzy number is employed to quantify the qualitative linguistics. Expanding the analysis into fuzzy environment can avoid the loss of decision information caused by traditional single real number evaluation. Thirdly, the improved decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling methods are combined to gain the risk analysis results. K-means is used to refine the influence relationship between factors in traditional DEMATEL to three categories: high effect, low effect, and no effect, which enhances applicability of the model in reality. Finally, corresponding improvement schemes and policy suggestions are proposed for each risk factor. The findings of research show that among the risks hindering carbon finance development: low carbon price, immature carbon abatement technology, lack of carbon financial products, and operational risk are the direct factors; adjustments in international climate policy is the fundamental factor.