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Open AccessArticle

A Hybrid Method with TOPSIS and Machine Learning Techniques for Sustainable Development of Green Hotels Considering Online Reviews

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Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City 758307, Vietnam
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Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City 758307, Vietnam
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Department of Marketing, College of Business Administration, University of South Florida, Tampa, FL 33813, USA
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Business School, Sichuan University, Chengdu 610064, China
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Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, 18071 Granada, Spain
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Department of Information Technology, University of Human Development, Sulaymaniyah 00964, Iraq
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Department of Cybersecurity, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia
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Department of Software Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia
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Author to whom correspondence should be addressed.
Sustainability 2019, 11(21), 6013; https://doi.org/10.3390/su11216013
Received: 28 August 2019 / Revised: 15 October 2019 / Accepted: 25 October 2019 / Published: 29 October 2019
This paper proposes a hybrid method for online reviews analysis through multi-criteria decision-making, text mining and predictive learning techniques to find the relative importance of factors affecting travelers’ decision-making in selecting green hotels with spa services. The proposed method is developed for the first time in the context of tourism and hospitality by this research, especially for customer segmentation in green hotels through customers’ online reviews. We use Self-Organizing Map (SOM) for cluster analysis, Latent Dirichlet Analysis (LDA) technique for analyzing textual reviews, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for ranking hotel features, and Neuro-Fuzzy technique to reveal the customer satisfaction levels. The impact of green hotels with spa and non-spa services on travelers’ satisfaction is investigated for four travelling groups: Travelled solo, Travelled with family, Travelled as a couple and Travelled with friends. The proposed method is evaluated on the travelers’ reviews on 152 hotels in Malaysia. The findings of this study provide an important method for travelers’ decision-making for hotel selection through User-Generated Content (UGC) and help hotel managers to improve their service quality and marketing strategies. View Full-Text
Keywords: sustainable development; green hotels; multi-criteria decision-making; TOPSIS; machine learning techniques; neuro-fuzzy; big data; satisfaction sustainable development; green hotels; multi-criteria decision-making; TOPSIS; machine learning techniques; neuro-fuzzy; big data; satisfaction
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Nilashi, M.; Mardani, A.; Liao, H.; Ahmadi, H.; Manaf, A.A.; Almukadi, W. A Hybrid Method with TOPSIS and Machine Learning Techniques for Sustainable Development of Green Hotels Considering Online Reviews. Sustainability 2019, 11, 6013.

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