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Understanding customer experience with Vietnamese hotels by analyzing online reviews

Author

Listed:
  • Ha Thi Thu Nguyen

    (FPT University)

  • Trung Xuan Nguyen

    (Vietnam Graduate Academy of Social Sciences)

Abstract

On the post-pandemic recovery green economy track, especially in the hospitality and tourism industry, businesses must accelerate digital transformation and enter the race to increase customer experience. Improving customer experience is critical, and understanding customers’ emotions and needs after using hotel services is crucial. This is why businesses increasingly rely on online customer reviews on booking sites to gain insight into what their customers seek. By understanding their needs and experiences, hotel managers can provide services that meet customer expectations and improve overall service quality. Although online review analysis is meaningful for hotel managers because of its practicality in business operations, a specific model, method, or tool is needed to explore customer emotions. This study proposes a method to analyze customers’ online reviews of Vietnamese hotel services. With a Data set of 20,551 reviews collected from TripAdvisor, the study examines customers’ perceptions of Vietnamese hotel services overall and aspects of hotel services by combining language rules of natural language and inferential statistics. The key findings indicate that customers are most satisfied with the “place” aspect of hotels, with a satisfaction rate of 78%, while the “room” service aspect has the lowest satisfaction rate at 61.3%. These results have recommended that hotel managers in Vietnam prioritize understanding customers’ sentiments and opinions to improve service quality in aspects where satisfaction rates are lower.

Suggested Citation

  • Ha Thi Thu Nguyen & Trung Xuan Nguyen, 2023. "Understanding customer experience with Vietnamese hotels by analyzing online reviews," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-02098-8
    DOI: 10.1057/s41599-023-02098-8
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    References listed on IDEAS

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    1. Liu, Yong & Teichert, Thorsten & Rossi, Matti & Li, Hongxiu & Hu, Feng, 2017. "Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews," Tourism Management, Elsevier, vol. 59(C), pages 554-563.
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