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

Mehrbakhsh Nilashi, Abbas Mardani, Huchang Liao, Hossein Ahmadi, Azizah Abdul Manaf and Wafa Almukadi
Additional contact information
Mehrbakhsh Nilashi: Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City 758307, Vietnam
Huchang Liao: Business School, Sichuan University, Chengdu 610064, China
Hossein Ahmadi: Department of Information Technology, University of Human Development, Sulaymaniyah 00964, Iraq
Azizah Abdul Manaf: Department of Cybersecurity, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia
Wafa Almukadi: Department of Software Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia

Sustainability, 2019, vol. 11, issue 21, 1-21

Abstract: 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.

Keywords: sustainable development; green hotels; multi-criteria decision-making; TOPSIS; machine learning techniques; neuro-fuzzy; big data; satisfaction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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