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Revealing travellers’ satisfaction during COVID-19 outbreak: Moderating role of service quality

Author

Listed:
  • Nilashi, Mehrbakhsh
  • Abumalloh, Rabab Ali
  • Minaei-Bidgoli, Behrouz
  • Abdu Zogaan, Waleed
  • Alhargan, Ashwaq
  • Mohd, Saidatulakmal
  • Syed Azhar, Sharifah Nurlaili Farhana
  • Asadi, Shahla
  • Samad, Sarminah

Abstract

User-Generated-Content (UGC) has gained increasing attention as an important indicator of business success in the tourism and hospitality sectors. Previous literature has analyzed travelers' satisfaction through quantitative approaches using questionnaire surveys. Another direction of research has explored the dimensions of satisfaction based on online customers' reviews using the machine learning approach. This study aims to present a new method that combines machine learning and survey-based approaches for customers' satisfaction analysis during the COVID-19 outbreak. In addition, we investigate the moderating role of service quality on the relationship between hotels' performance criteria and customers' satisfaction. To achieve this, the Latent Dirichlet Allocation (LDA) was used for textual data analysis, k-means was used for data segmentation, dimensionality reduction approach was used for the imputation of the missing values, and fuzzy rule-based was used for the prediction of satisfaction level. Following that, a survey-based approach was used to validate the research model by distributing the questionnaire and analyzing the collected data using the Structural Equation Modeling technique. The result of this research presents important contributions from the methodological and practical perspectives in the context of customers' satisfaction in tourism and hospitality during the COVID-19 outbreak. The outcomes of this research confirm the significant influence of the quality of services during the COVID-19 crisis on the relationship between hotel services and travellers’ satisfaction.

Suggested Citation

  • Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Minaei-Bidgoli, Behrouz & Abdu Zogaan, Waleed & Alhargan, Ashwaq & Mohd, Saidatulakmal & Syed Azhar, Sharifah Nurlaili Farhana & Asadi, Shahla & Samad, Sar, 2022. "Revealing travellers’ satisfaction during COVID-19 outbreak: Moderating role of service quality," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:joreco:v:64:y:2022:i:c:s0969698921003490
    DOI: 10.1016/j.jretconser.2021.102783
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    7. Muñoz-Villamizar, Andrés & Piatti, Matias & Mejía-Argueta, Christopher & Pirabe, Luis Felipe & Namdar, Jafar & Gomez, Juan Felipe, 2024. "Navigating retail inflation in Brazil: A machine learning and web scraping approach to the basic food basket," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
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    9. Kumar, Anand & Bala, Pradip Kumar & Chakraborty, Shibashish & Behera, Rajat Kumar, 2024. "Exploring antecedents impacting user satisfaction with voice assistant app: A text mining-based analysis on Alexa services," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    10. Tiwari, Veenus & Mishra, Abhishek, 2023. "The effect of a hotel's star-rating-based expectations of safety from the pandemic on during-stay experiences," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).

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