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A Choquet integral-based hesitant fuzzy gained and lost dominance score method for multi-criteria group decision making considering the risk preferences of experts: Case study of higher business education evaluation

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A Choquet integral-based hesitant fuzzy gained and lost dominance score method for multi-criteria group decision making considering the risk preferences of experts: Case study of higher business education evaluation

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Liao, Z.; Liao, H.; Tang, M.; Al-Barakati, A.; Llopis-Albert, C. (2020). A Choquet integral-based hesitant fuzzy gained and lost dominance score method for multi-criteria group decision making considering the risk preferences of experts: Case study of higher business education evaluation. Information Fusion. 62:121-133. https://doi.org/10.1016/j.inffus.2020.05.003

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/169417

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Título: A Choquet integral-based hesitant fuzzy gained and lost dominance score method for multi-criteria group decision making considering the risk preferences of experts: Case study of higher business education evaluation
Autor: Liao, Zhiqiang Liao, Huchang Tang, Ming Al-Barakati, Abdullah Llopis-Albert, Carlos
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Mecánica y de Materiales - Departament d'Enginyeria Mecànica i de Materials
Fecha difusión:
Resumen:
[EN] With the rapid development of higher business education, higher business education evaluation has attracted considerable attention of researchers and practitioners. The higher business education evaluation is an ...[+]
Palabras clave: Multiple criteria group decision making , Hesitant fuzzy set , Gained and lost dominance score method , Choquet integral , Prospect theory
Derechos de uso: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Fuente:
Information Fusion. (issn: 1566-2535 )
DOI: 10.1016/j.inffus.2020.05.003
Editorial:
Elsevier
Versión del editor: https://doi.org/10.1016/j.inffus.2020.05.003
Código del Proyecto:
info:eu-repo/grantAgreement/SPDST//2019JDR0141/
info:eu-repo/grantAgreement/NSFC//71771156/
Agradecimientos:
The work was supported by the National Natural Science Foundation of China (71771156) and the 2019 Soft Science Project of Sichuan Science and Technology Department (No. 2019JDR0141).
Tipo: Artículo

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