A stochastic dominance-based approach for hotel selection under probabilistic linguistic environment

Abstract

Online reviews of hotels reflect tourist perception and evaluation, which are becoming an important perspective of studying hotel selection. In this paper, we prefer to use a probabilistic linguistic term set (PLTS) to fully reveal evaluation grades and the corresponding probability distribution in the online reviews of hotels. In this way, we propose a novel stochastic dominance-based approach based on stochastic dominance degrees of PLTSs and a stochastic multi-criteria acceptability analysis (SMAA) method that tolerates missing information. Among them, first-, second-, and third-order stochastic dominance degrees of PLTSs are calculated on the premise that the dominance relationships between PLTSs can be defined based on first-, second-, and third-order stochastic dominance rules of PLTSs. Based on these basic researches, five hotels are selected as alternatives in our case study to verify the validity and feasibility of the proposed approach. In the end, data analysis illustrates the influence of parameter and linguistic scale functions and how to choose appropriate parameter values. Furthermore, comparative analysis with other methods shows the stability of the proposed approach.