This study combines automated and manual text mining techniques on guest reviews data to understand the most recurring themes reported by guests staying at luxury hotels. Data cover ten years of online reviews for 15 luxury hotel brands belonging to nine global hotel chains located in London. Reviews are firstly cluster analyzed by Leximancer software to isolate the most recurring luxury themes; then a qualitative content analysis is performed to further investigate into the semantics. The findings reveal that luxury hotel guests primarily refer to the physical attributes of the establishment and afterwards to a set of intangibles concepts. Practical implications are also provided.
Exploring guests’ associations with luxury: an analysis of online reviews
D'Acunto D;
2020-01-01
Abstract
This study combines automated and manual text mining techniques on guest reviews data to understand the most recurring themes reported by guests staying at luxury hotels. Data cover ten years of online reviews for 15 luxury hotel brands belonging to nine global hotel chains located in London. Reviews are firstly cluster analyzed by Leximancer software to isolate the most recurring luxury themes; then a qualitative content analysis is performed to further investigate into the semantics. The findings reveal that luxury hotel guests primarily refer to the physical attributes of the establishment and afterwards to a set of intangibles concepts. Practical implications are also provided.
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