Machine Learning Techniques in Tourism and Hospitality Research: A Critical Assessment

Machine learning techniques have gained increasing prominence in tourism and hospitality research for data analysis and business strategy formulation. This study systematically reviews 406 peer-reviewed articles published between 2007 and 2023, highlighting the growth of machine learning studies, the expansion of academic journal coverage, and the adoption of diverse data modalities employed in this field. More importantly, it discusses emerging research topics and associated machine learning approaches across different data modalities (i.e., numerical, textual, and image data). This study further addresses key issues and challenges in current applications and outlines future research directions in this domain. Overall, it offers an in-depth understanding and assessment of the current machine learning techniques within the tourism and hospitality literature.

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Publication Details

Journal
Journal of Travel Research
Published
2025-12-31
DOI
https://doi.org/10.1177/00472875251401912
Primary Topic
Digital Marketing and Social Media
Type
article
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article

Machine Learning Techniques in Tourism and Hospitality Research: A Critical Assessment

Ningqiao Li, Xiaoyi Liu, Fang Meng
Journal of Travel Research
Digital Marketing and Social Media
article

Machine Learning Techniques in Tourism and Hospitality Research: A Critical Assessment

Ningqiao Li, Xiaoyi Liu, Fang Meng
article en

Abstract

Machine learning techniques have gained increasing prominence in tourism and hospitality research for data analysis and business strategy formulation. This study systematically reviews 406 peer-reviewed articles published between 2007 and 2023, highlighting the growth of machine learning studies, the expansion of academic journal coverage, and the adoption of diverse data modalities employed in this field. More importantly, it discusses emerging research topics and associated machine learning approaches across different data modalities (i.e., numerical, textual, and image data). This study further addresses key issues and challenges in current applications and outlines future research directions in this domain. Overall, it offers an in-depth understanding and assessment of the current machine learning techniques within the tourism and hospitality literature.

Journal of Travel Research
Beijing University of Chinese Medicine (CN), Vistula School of Hospitality (PL), University of Houston (US)
Decent work and economic growth
Openalex Percentile: Top 22%
Digital Marketing and Social Media
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Machine Learning Techniques in Tourism and Hospitality Research: A Critical Assessment — Ningqiao Li, Xiaoyi Liu, et al. · Journal of Travel Research (2025) | TGRS Research Map | TGRS