Market segmentation and travel choice prediction in Spa hotels through TripAdvisor's online reviews
Author(s)
Ahani, Ali
Nilashi, Mehrbakhsh
Ibrahim, Othman
Sanzogni, Louis
Weaven, Scott
Year published
2019
Metadata
Show full item recordAbstract
Customer segmentation via online reviews and ratings can assist different hotels, including spa hotels, to better inform marketing strategy development and ensure optimal marketing expenditures. However, traditional market segmentation approaches are ineffective in analysing social data on account of size, different dimensions and features of online review data. Machine learning approaches can assist in developing effective hybrid algorithms to overcome data-related complications associated with online reviews. Hence, the objective of this study is to develop a method for spa hotel segmentation and travel choice prediction ...
View more >Customer segmentation via online reviews and ratings can assist different hotels, including spa hotels, to better inform marketing strategy development and ensure optimal marketing expenditures. However, traditional market segmentation approaches are ineffective in analysing social data on account of size, different dimensions and features of online review data. Machine learning approaches can assist in developing effective hybrid algorithms to overcome data-related complications associated with online reviews. Hence, the objective of this study is to develop a method for spa hotel segmentation and travel choice prediction by applying machine learning approaches. Method evaluation is conducted through a collection of datasets from travelers’ ratings and textual reviews of spa hotels on several features in TripAdvisor. Findings confirm that the proposed hybrid machine learning methods can be implemented as an incremental recommendation agent for spa hotel/resort segmentation through effectively utilizing ‘big data’ procured from online social media contexts.
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View more >Customer segmentation via online reviews and ratings can assist different hotels, including spa hotels, to better inform marketing strategy development and ensure optimal marketing expenditures. However, traditional market segmentation approaches are ineffective in analysing social data on account of size, different dimensions and features of online review data. Machine learning approaches can assist in developing effective hybrid algorithms to overcome data-related complications associated with online reviews. Hence, the objective of this study is to develop a method for spa hotel segmentation and travel choice prediction by applying machine learning approaches. Method evaluation is conducted through a collection of datasets from travelers’ ratings and textual reviews of spa hotels on several features in TripAdvisor. Findings confirm that the proposed hybrid machine learning methods can be implemented as an incremental recommendation agent for spa hotel/resort segmentation through effectively utilizing ‘big data’ procured from online social media contexts.
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Journal Title
International Journal of Hospitality Management
Volume
80
Subject
Commercial Services
Marketing
Tourism