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• W2756109718 startingPage "1078" @default.
• W2756109718 abstract "Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice." @default.
• W2756109718 created "2017-09-25" @default.
• W2756109718 creator A5004836300 @default.
• W2756109718 creator A5069928262 @default.
• W2756109718 date "2017-09-17" @default.
• W2756109718 modified "2023-09-23" @default.
• W2756109718 title "Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection" @default.
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• W2756109718 doi "https://doi.org/10.3390/ijerph14091078" @default.
• W2756109718 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5615615" @default.
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• W2756109718 hasPublicationYear "2017" @default.
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