Understanding tourism consumer behavior using biometric technologies: bibliographic review and research agenda

Abstract

Recent technological advances, particularly in biometrics, have significantly impacted the tourism industry. Amidst the COVID-19 pandemic, these technologies have grown rapidly, posing challenges and opportunities in utilizing the resulting data. This study aims to develop a research agenda concerning biometrics in tourism consumer behavior, detailing what biometric data entails and outlining its diverse applications. Through a bibliographic review of 422 recent papers, employing machine learning and artificial intelligence techniques, we extracted keywords, topics, and frequencies using the methodological approach of corpus linguistics and latent Dirichlet allocation algorithm. The results identified 26 topics, including “KPIs”,” Techniques”, “Personalization”, “Health”, and “Travel and transport”. Furthermore, we observed that the COVID-19 pandemic has dramatically impacted the tourism sector, with “Health” present in four categories. The practical implications of our study suggest that companies can find the issues that most concern the tourism consumer in the lines of research presented in the research agenda, paying particular attention to the lines developed in the research agenda involving “personalization”, "travel and transport" and "health".