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

Elaheh Yadegaridehkordi, Mehrbakhsh Nilashi, Mohd Hairul Nizam Bin Md Nasir, Saeedeh Momtazi, Sarminah Samad, Eko Supriyanto and Fahad Ghabban

Technology in Society, 2021, vol. 65, issue C

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.

Keywords: Green hotels; Decision making; Segmentation; Online travel reviews; Choice behaviour; Multi-criteria decision making (MCDM) (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0160791X21000038
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:65:y:2021:i:c:s0160791x21000038

DOI: 10.1016/j.techsoc.2021.101528

Access Statistics for this article

Technology in Society is currently edited by Charla Griffy-Brown

More articles in Technology in Society from Elsevier
Bibliographic data for series maintained by Catherine Liu ().