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

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...

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Main Authors: Yadegaridehkordi, Elaheh, Nilashi, Mehrbakhsh, Md Nasir, Mohd Hairul Nizam, Momtazi, Saeedeh, Samad, Sarminah, Supriyanto, Eko, Ghabban, Fahad
Format: Article
Published: Elsevier 2021
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.um.edu.my/25916/
https://doi.org/10.1016/j.techsoc.2021.101528
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spelling my.um.eprints.259162021-04-30T03:22:32Z http://eprints.um.edu.my/25916/ Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques Yadegaridehkordi, Elaheh Nilashi, Mehrbakhsh Md Nasir, Mohd Hairul Nizam Momtazi, Saeedeh Samad, Sarminah Supriyanto, Eko Ghabban, Fahad QA75 Electronic computers. Computer science 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. © 2021 Elsevier Ltd Elsevier 2021 Article PeerReviewed Yadegaridehkordi, Elaheh and Nilashi, Mehrbakhsh and Md Nasir, Mohd Hairul Nizam and Momtazi, Saeedeh and Samad, Sarminah and Supriyanto, Eko and Ghabban, Fahad (2021) Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques. Technology in Society, 65. p. 101528. ISSN 0160-791X https://doi.org/10.1016/j.techsoc.2021.101528 doi:10.1016/j.techsoc.2021.101528
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Yadegaridehkordi, Elaheh
Nilashi, Mehrbakhsh
Md Nasir, Mohd Hairul Nizam
Momtazi, Saeedeh
Samad, Sarminah
Supriyanto, Eko
Ghabban, Fahad
Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
description 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. © 2021 Elsevier Ltd
format Article
author Yadegaridehkordi, Elaheh
Nilashi, Mehrbakhsh
Md Nasir, Mohd Hairul Nizam
Momtazi, Saeedeh
Samad, Sarminah
Supriyanto, Eko
Ghabban, Fahad
author_facet Yadegaridehkordi, Elaheh
Nilashi, Mehrbakhsh
Md Nasir, Mohd Hairul Nizam
Momtazi, Saeedeh
Samad, Sarminah
Supriyanto, Eko
Ghabban, Fahad
author_sort Yadegaridehkordi, Elaheh
title Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
title_short Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
title_full Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
title_fullStr Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
title_full_unstemmed Customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
title_sort customers segmentation in eco-friendly hotels using multi-criteria and machine learning techniques
publisher Elsevier
publishDate 2021
url http://eprints.um.edu.my/25916/
https://doi.org/10.1016/j.techsoc.2021.101528
_version_ 1698697324425904128
score 13.209306

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