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Travellers segmentation and choice prediction through online reviews: the case of Wellingtons Hotels in New Zealand

Ahani, Ali and Nilashi, Mehrbakhsh and Ibrahim, Othman (2019) Travellers segmentation and choice prediction through online reviews: the case of Wellingtons Hotels in New Zealand. Journal of Soft Computing and Decision Support Systems, 6 (5). pp. 25-30. ISSN 2289-8603

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Official URL: https://jscdss.com/index.php/files/article/downloa...

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.

Item Type:Article
Uncontrolled Keywords:Market Segmentation, Online Reviews, MCDM, TOPSIS, Choice Prediction, Wellington’s 5-star hotels, New Zealand
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:88348
Deposited By: Fazli Masari
Deposited On:15 Dec 2020 00:19
Last Modified:15 Dec 2020 00:19

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