Abstract

Medical tourism has developed rapidly worldwide, especially in Asia, and one of the most important problems facing the patient-tourists is the selection of the optimum destination. In this paper, we present a novel multiple criteria group decision making (MCGDM) methodology to evaluate and rank the medical tourism destinations vague based on vague information. A systematic assessment and selection model was constructed by investigating MCGDM problems with neutrosophic fuzzy preference relations (NFPRs). We began by defining NFPRs which allow the patient-tourists lacking information, time or patience, to express their uncertainty and hesitancy about the given preference values. The additive consistency and acceptable consistency for NFPRs were then proposed. Furthermore, the approach to improve the consistency for NFPRs was also validated and a series of aggregation operators were developed. In addition, we presented a systematic MCGDM method using NFPRs (MCGDM-NFPRs) in this paper to rank the medical tourism destinations. Then our proposed approach was applied to two cases considering different kinds of original data to prioritize medical tourism places. Finally, the applicability and feasibility of proposed approach were verified by the comparison with other previous methods, along with some analyses and a comprehensive discussion

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