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Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques

Yadegaridehkordi, Elaheh and Nilashi, Mehrbakhsh and Md. Nasir, Mohd. Hairul Nizam and Momtazi, Saeedeh (2021) Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques. Technology in Society, 65 . ISSN 0160-791X

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Official URL: http://dx.doi.org/10.1016/j.techsoc.2021.101528

Abstract

This study aims to investigate the travellers' choice behaviour towards green hotels through existing online travel reviews on TripAdvisor. Accordingly, a method combining segmentation and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) techniques was developed to segment travellers based on their provided reviews and to prioritize green hotel attributes based on their level of importance in each segment. The data were taken from travellers' online reviews of Malaysian eco-friendly hotels on TripAdvisor. The results showed that the sleep quality was one of the most imporant factors for eco-hotel selection in the majority of segments. The developed method in this study was able to analyse travellers’ reviews and ratings on eco-friendly hotels to identify the future choice behaviour and aid travellers in their decision-making process. The study provides new insights for hotel managers and green policy makers on developing environmental-friendly practices.

Item Type:Article
Uncontrolled Keywords:choice behaviour, decision making, green hotels
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General) > T58.5-58.64 Information technology
Divisions:Biosciences and Medical Engineering
ID Code:94222
Deposited By: Yanti Mohd Shah
Deposited On:31 Mar 2022 15:24
Last Modified:31 Mar 2022 15:24

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