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Employing structural topic modelling to explore perceived service quality attributes in Airbnb accommodation
Institution:1. CEFE, Univ Paul Valéry Montpellier 3, CNRS, Univ Montpellier, EPHE, IRD, Montpellier, France;2. PRAXILING UMR 5267, Univ Paul Valéry Montpellier 3, CNRS, F34000, Montpellier, France;3. French Institute of Pondicherry, UMIFRE21 CNRS/MAEE, Puducherry, India
Abstract:This study employs the structural topic model to extract service quality attributes from 242,020 Airbnb reviews in Malaysia. 22 service related topics were extracted from the corpus and four topics have not appeared in previous Airbnb studies. A widely used modified SERVQUAL questionnaire (MSQ) is cross-validated in this study by comparing its service quality attributes with the results of the topic modelling, which indicates that this MSQ can cover general Airbnb service quality attributes. This study also examines the different preferences of Malaysian and international Airbnb users and the changing patterns of the top six service quality attributes during a five-year period. The findings reveal that Malaysian Airbnb users care more about the appearance and location of the property, and international Airbnb users pay more attention to whether the property can accommodate a group of people. In addition, communication with the host is found to play an increasingly important role in Airbnb users’ lodging experiences.
Keywords:Airbnb  Service quality  Online reviews  Structural topic model  Text mining
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