Machine Learning Techniques in Tourism and Hospitality Research: A Critical Assessment
Year: 2025
Type: article
Study design: Systematic Review
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.
Source: Journal of Travel Research
Authors: Ningqiao Li, Xiaoyi Liu, Fang Meng
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,900
OpenAlex ID: W7117676513