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• W2896643528 abstract "Abstract: Selecting the supplier is a very critical part to the comprehensive performance of modern enterprises. With the large-scale development of straw biomass industry, green supplier selection has become a key decision-making task which needs to collect and process mass of information, it is necessary to make the supplier to go green. Nevertheless, it is safe to say, in fact, that so far there are a few researches on supplier selection in straw biomass industry. At the same time, some crucial problems urgently needed to be solved exist in present research, as shown below:①decision-making methods are frequently used, even though they have some serious problems, e.g. information loss.②some key index factors are ignored, green supplier selection hasn't got attracted sufficient attention.③little work has been performed on the fuzziness or the uncertainty of index weight. To solve the problems mentioned above, this paper tries to find out some ways to make improvements:①Cloud model is proposed to handle the fuzziness and randomness of evaluation information.②Index system is more comprehensive. Important issues, such as on-time delivery, pollutant emissions per unit fuel(t) and green certification, are paid more attention to.③Fuzzy AHP is applied to determine the index weight, the uncertainty of criteria and sub-criteria are considered, the vagueness of human thought is dealt with.④A decision framework based on Cloud model and possibility degree is put forward to guide the optimal selection of green supplier selection.⑤A Chinese case is carried out and related sensitivity analysis is performed. The results show that the proposed novel model not only can find the more suitable green supplier, but also reveal the big gap between alternatives clearly. The strength of the proposed new decision framework is proved." @default.
• W2896643528 created "2018-10-26" @default.
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• W2896643528 date "2019-02-01" @default.
• W2896643528 modified "2023-10-12" @default.
• W2896643528 title "Green supplier selection in straw biomass industry based on cloud model and possibility degree" @default.
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• W2896643528 doi "https://doi.org/10.1016/j.jclepro.2018.10.130" @default.
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