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This study examines service quality dimensions and attributes of the hotel industry in a famous beach resort destination of Phuket based on 25,267 online reviews from the TripAdvisor website collected for 56 hotels. Machine learning analysis using the KNIME analytics platform was employed to analyze four datasets, namely the total dataset, the couple dataset, the family dataset, and the friend dataset. The results reveal six dimensions of guest service quality in the hotel industry: leisure activities, tangibles and surroundings, reliability, responsiveness, service process, and food, with specific attributes identified in each dimension. The study was able to verify the robustness of HOLSERV Plus model as the dimensions developed by topic modelling of online reviews are found to correspond to the dimensions of HOLSERV framework, with some adaptation required. It is also confirmed by the current study that the same set of service quality dimensions and attributes is not applicable to all groups of customers, instead each group has its own unique requirements and expectations. In addition, service process is revealed in this study as the most sensitive dimension that determines customer dissatisfaction.
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Stored only when both papers are in the corpus — 44 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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