During the decision-making process, especially in multi-disciplinary complex cases, assessment technique is needed to assist policy-makers in making the right decision. Many of such assessment techniques have been dev...During the decision-making process, especially in multi-disciplinary complex cases, assessment technique is needed to assist policy-makers in making the right decision. Many of such assessment techniques have been developed for policy-makers, but the inevitable subjectivity of policy-makers often becomes the main obstacle in making the right or proper policy. Interlink decision-making index （IDMI） is a newly proposed assessment method with the advantages of being simple to use and having less human interference over other methods, as it does not require a weighting process of each selection criterion. This paper implements IDMI to assist with decision-making in national or regional low-carbon development, using China as a case study. The Chinese government has annotmced its carbon emission reduction target along with other development targets by 2020. Many policy settings can be chosen in order to achieve those targets. The problem is how to determine the best setting and the means by which decision-makers can avoid subjectivity and extremes. A number of policy setting options are generated carefully by a system dynamic model under different policy scenarios. The IDMI demonstrates a perfect way to assist in selecting the ＂best＂ among all the options that can achieve the goals within the acceptable range.展开更多
基金Supported by National Natural Science Foundation of China(No.71273185)
文摘During the decision-making process, especially in multi-disciplinary complex cases, assessment technique is needed to assist policy-makers in making the right decision. Many of such assessment techniques have been developed for policy-makers, but the inevitable subjectivity of policy-makers often becomes the main obstacle in making the right or proper policy. Interlink decision-making index （IDMI） is a newly proposed assessment method with the advantages of being simple to use and having less human interference over other methods, as it does not require a weighting process of each selection criterion. This paper implements IDMI to assist with decision-making in national or regional low-carbon development, using China as a case study. The Chinese government has annotmced its carbon emission reduction target along with other development targets by 2020. Many policy settings can be chosen in order to achieve those targets. The problem is how to determine the best setting and the means by which decision-makers can avoid subjectivity and extremes. A number of policy setting options are generated carefully by a system dynamic model under different policy scenarios. The IDMI demonstrates a perfect way to assist in selecting the ＂best＂ among all the options that can achieve the goals within the acceptable range.
