Application of Machine Learning in the Hotel Industry: A Critical Review | ||
| Journal of Association of Arab Universities for Tourism and Hospitality | ||
| Article 6, Volume 18, Issue 3 - Serial Number 42, June 2020, Pages 78-96 PDF (873.98 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/jaauth.2020.38784.1060 | ||
| Author | ||
| EID ALOTAIBI* | ||
| Department of Tourism and Archaeology٫ College of Arts٫ University of Hail٫ Hail City٫ Saudi Arabia | ||
| Abstract | ||
| Study purpose – The hotel industry like any other industry is witnessing a change due to information and communication technology. However, this change is quite slow. Many researchers in recent time have garnered interest in exploring and implementing the new technologies of artificial intelligence and machine learning in the hotel industry. Therefore, the purpose of this study is to give insights on the role of ML and its integrated technologies in the hotel industry. Design/Methodology/Approach – The study has critically reviewed articles published from 2010 to 2020. To achieve the research objective, the study seeks to answer three main research questions related to the existing literature; RQ1: Where does the hotel industry implement machine learning? RQ2: What are the machine learning techniques used in the hotel industry? RQ3: Which countries are using machine learning in the hotel industry? Findings – The study found that machine learning is helpful in demand forecasting, price forecasting, booking cancellation prediction, financial efficiency, and work efficiency. The machine learning algorithms outperform in the forecast accuracy against the statistical models. The countries at the forefront in machine learning technologies are China and USA. The other countries should take the cue from them and implement machine learning in their hotels Originality of the research – This research conducts exploratory analysis to identify the extent of scientific community knowledge and awareness on machine learning in the hotel industry. To the best of the authors’ knowledge, no prior researcher has conducted a similar study specifically in the hotel industry. | ||
| Keywords | ||
| hotel industry; machine learning; artificial intelligence; deep learning; hotel management | ||
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