Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach
The crucial role of customers' positive experience and their subsequent word-of-mouth have been highlighted by both scholars and practitioners for all industry sectors. In response to an increasing concern of environmental sustainability and sensitivity of consumers for deteriorating environm...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/81801/ http://psasir.upm.edu.my/id/eprint/81801/1/Preference%20learning%20for%20eco-friendly%20hotels.pdf |
| _version_ | 1848859178604429312 |
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| author | Nilashi, Mehrbakhsh Ahani, Ali Esfahani, Mohammad Dalvi Yadegaridehkordi, Elaheh Samad, Sarminah Ibrahim, Othman Mohd Sharef, Nurfadhlina Akbari, Elnaz |
| author_facet | Nilashi, Mehrbakhsh Ahani, Ali Esfahani, Mohammad Dalvi Yadegaridehkordi, Elaheh Samad, Sarminah Ibrahim, Othman Mohd Sharef, Nurfadhlina Akbari, Elnaz |
| author_sort | Nilashi, Mehrbakhsh |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The crucial role of customers' positive experience and their subsequent word-of-mouth have been
highlighted by both scholars and practitioners for all industry sectors. In response to an increasing
concern of environmental sustainability and sensitivity of consumers for deteriorating environment, eco-
friendly (green) products and services gained tremendous attention. TripAdvisor is increasingly known
as one of the most popular e-tourism platforms. Understanding and predicting the traveler’ preferences
by advanced big data analytics technology is an important task that the recommendation engine of this
platform does. In this paper, we aim to develop a new soft computing method with the aid of machine
learning techniques in order to find the best matching eco-friendly hotels based on the several quality
factors in TripAdvisor. We develop the method using dimensionality reduction and prediction machine
learning techniques to improve the scalability of prediction from the large number of users' ratings. The
proposed soft computing method is evaluated on a large dataset discovered from the TripAdvisor
platform. The results show that the combination of dimensionality reduction and prediction machine
learning techniques is robust in processing the large number of the ratings provided by users on the
features of eco-friendly hotels and predicting travelers’ choice preferences of eco-friendly hotels in
TripAdvisor. |
| first_indexed | 2025-11-15T12:25:13Z |
| format | Article |
| id | upm-81801 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:25:13Z |
| publishDate | 2019 |
| publisher | Elsevier Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-818012022-12-07T01:59:00Z http://psasir.upm.edu.my/id/eprint/81801/ Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach Nilashi, Mehrbakhsh Ahani, Ali Esfahani, Mohammad Dalvi Yadegaridehkordi, Elaheh Samad, Sarminah Ibrahim, Othman Mohd Sharef, Nurfadhlina Akbari, Elnaz The crucial role of customers' positive experience and their subsequent word-of-mouth have been highlighted by both scholars and practitioners for all industry sectors. In response to an increasing concern of environmental sustainability and sensitivity of consumers for deteriorating environment, eco- friendly (green) products and services gained tremendous attention. TripAdvisor is increasingly known as one of the most popular e-tourism platforms. Understanding and predicting the traveler’ preferences by advanced big data analytics technology is an important task that the recommendation engine of this platform does. In this paper, we aim to develop a new soft computing method with the aid of machine learning techniques in order to find the best matching eco-friendly hotels based on the several quality factors in TripAdvisor. We develop the method using dimensionality reduction and prediction machine learning techniques to improve the scalability of prediction from the large number of users' ratings. The proposed soft computing method is evaluated on a large dataset discovered from the TripAdvisor platform. The results show that the combination of dimensionality reduction and prediction machine learning techniques is robust in processing the large number of the ratings provided by users on the features of eco-friendly hotels and predicting travelers’ choice preferences of eco-friendly hotels in TripAdvisor. Elsevier Ltd 2019-04-04 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81801/1/Preference%20learning%20for%20eco-friendly%20hotels.pdf Nilashi, Mehrbakhsh and Ahani, Ali and Esfahani, Mohammad Dalvi and Yadegaridehkordi, Elaheh and Samad, Sarminah and Ibrahim, Othman and Mohd Sharef, Nurfadhlina and Akbari, Elnaz (2019) Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach. Journal of Cleaner Production, 215. pp. 767-783. ISSN 0959-6526 https://reader.elsevier.com/reader/sd/pii/S0959652619300125?token=0A4DE1A46E89F3A770B1A2036ACEE6F9B5267DC58818A8FCA246BCDD14BB1EC8C07F1EAFC6608A713F536A603352DA97&originRegion=eu-west-1&originCreation=20220919085018 10.1016/j.jclepro.2019.01.012 |
| spellingShingle | Nilashi, Mehrbakhsh Ahani, Ali Esfahani, Mohammad Dalvi Yadegaridehkordi, Elaheh Samad, Sarminah Ibrahim, Othman Mohd Sharef, Nurfadhlina Akbari, Elnaz Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| title | Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| title_full | Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| title_fullStr | Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| title_full_unstemmed | Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| title_short | Preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| title_sort | preference learning for eco-friendly hotels recommendation: a multi-criteria collaborative filtering approach |
| url | http://psasir.upm.edu.my/id/eprint/81801/ http://psasir.upm.edu.my/id/eprint/81801/ http://psasir.upm.edu.my/id/eprint/81801/ http://psasir.upm.edu.my/id/eprint/81801/1/Preference%20learning%20for%20eco-friendly%20hotels.pdf |