Journal of Smart Tourism

Smart Tourism Research Center, Kyung Hee University (경희대학교 스마트관광연구소)
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From Machine Learning Algorithms to Superior Customer Experience: Business Implications of Machine Learning-Driven Data Analytics in the Hospitality Industry

  • Egor Cherenkov (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston) ;
  • Vlad Benga (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston) ;
  • Minwoo Lee (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston) ;
  • Neil Nandwani (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston) ;
  • Kenan Raguin (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston) ;
  • Marie Clementine Sueur (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston) ;
  • Guohao Sun (Conrad N. Hilton College of Global Hospitality Leadership, University of Houston)
  • Received : 2024.01.17
  • Accepted : 2024.07.01
  • Published : 2024.06.30
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Abstract

This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

Keywords

Acknowledgement

The leading author mainly reviewed, revised, and finalized the manuscript. The rest of the authors have made equal contributions and their order of authorship is alphabetical based on their last name.

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