Travellers segmentation and choice prediction through online reviews: the case of Wellingtons Hotels in New Zealand
Customer choice and segmentation through online reviews can help hotels to improve their marketing strategy development. Nevertheless, old-style approaches are unproductive in analysing online data generated by customers because of size, dissimilar proportions and structures of online review data. T...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Journal of Soft Computing and Decision Support Systems
2019
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/88348/1/OthmanIbrahim2019_TravellersSegmentationandChoicePrediction.pdf http://eprints.utm.my/id/eprint/88348/ https://jscdss.com/index.php/files/article/download/209/pdf_249 |
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| Summary: | Customer choice and segmentation through online reviews can help hotels to improve their marketing strategy development. Nevertheless, old-style approaches are unproductive in analysing online data generated by customers because of size, dissimilar proportions and structures of online review data. Therefore, this research aims to develop a method for 5-star hotels segmentation and travellers’ choice forecast through online reviews analysis using machine learning methods. Assessment of method was directed through the gathering of data from travellers’ ratings of Wellington’s 5-star hotels on different features in TripAdvisor. Results confirm that the projected hybrid machine learning approaches can be applied as a progressive recommender mediator for 5-star hotel segmentation by applying ‘big data’ obtained from online social media settings. |
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