Based on the Computing with Words (CW), double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) can be used to express complex linguistic information accurately with two simple linguistic hierarchies. This paper proposes a group decision making (GDM) model based on multiplicative consistency and consensus with double hierarchy hesitant fuzzy linguistic preference relations (DHHFLPRs). Firstly, a correlation coefficient of DHHFLTSs is defined based on the distance measures of double hierarchy hesitant fuzzy linguistic elements (DHHFLEs). Then, a multiplicative consistency property of DHHFLPRs is investigated, and a consistency checking method and a feedback mechanism-based repairing algorithm are developed to ensure all DHHFLPRs with acceptable multiplicative consistency. Furthermore, a correlation measure for DHHFLPRs based on the correlation coefficient of DHHFLTSs is proposed, and a new consensus reaching method on the basis of the correlation measure is developed, which can be used to fully obtain the consensus degree from both positive and negative angles. Finally, we make some comparative analyses with other existing consistency checking and repairing method as well as the consensus reaching approach to illustrate the effectiveness of the proposed method by a case study concerning the assessment of the venture capital project about real estate market in some cities of China. First published online 8 October 2019


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    Titel :

    Consensus based on multiplicative consistent double hierarchy linguistic preferences: venture capital in real estate market


    Beteiligte:
    Gou, Xunjie (Autor:in) / Liao, Huchang (Autor:in) / Wang, Xinxin (Autor:in) / Xu, Zeshui (Autor:in) / Herrera, Francisco (Autor:in)

    Erscheinungsdatum :

    2020-01-01


    Anmerkungen:

    doi:10.3846/ijspm.2019.10431
    International Journal of Strategic Property Management; Vol 24 No 1 (2020); 1-23 ; 1648-9179 ; 1648-715X



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629





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