Travellers Segmentation and Choice Prediction through Online Reviews: The Case of Wellington’s Hotels in New Zealand

Ali Ahani, Mehrbakhsh Nilashi, Othman Ibrahim

Abstract


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.


Keywords


Market Segmentation, Online Reviews, MCDM, TOPSIS, Choice Prediction, Wellington’s 5-star hotels, New Zealand

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References


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