A multi-criteria decision-making model for hotel selection by online reviews: Considering the traveller types and the interdependencies among criteria

Many efforts have been dedicated to the research on online reviews-based hotel selection. However, the existing methods often fail to take into account the types of potential travellers and, moreover, they rarely consider the impact of the interdependencies among hotel criteria when modelling the ho...

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Bibliographic Details
Published inApplied intelligence (Dordrecht, Netherlands) Vol. 52; no. 11; pp. 12436 - 12456
Main Authors Tao, Ling-Ling, You, Tian-Hui
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2022
Springer Nature B.V
Subjects
Artificial Intelligence
Case studies
Computer Science
Decision making
Hotels & motels
Machines
Manufacturing
Mechanical Engineering
Multiple criteria decision making
Multiple criterion
Processes
Traveller types
2-order additive fuzzy measures
Aggregation function
Choquet average integral
Hotel selection
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Summary:Many efforts have been dedicated to the research on online reviews-based hotel selection. However, the existing methods often fail to take into account the types of potential travellers and, moreover, they rarely consider the impact of the interdependencies among hotel criteria when modelling the hotel selection process. To counter these defects, this paper proposes a multi-criteria decision-making model for hotel selection that considers the types of potential travellers and the interdependencies among criteria. To achieve this, the proposed model first converts online reviews into picture fuzzy numbers, and introduces 2-order additive fuzzy measures to capture the interdependencies among criteria by proposing a novel aggregation function based on Choquet average integral. Furthermore, it uses the similarity between each traveller type and the potential traveller type to calculate the weights of different traveller types so as to account the impact of traveller type. To validate the effectiveness of the proposed model, a case study is conducted on the reviews collected from TripAdvisor. The study shows that the proposed decision support model can effectively help potential travellers of different traveller types to make their desirable hotel choices.
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-021-03151-2