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With the increasing popularity of big data analytics, significant research has been conducted in the field of tourism and hospitality studies, particularly in the form of reviews that examine current works. Even though tourism is closely intertwined with the movements of tourists, a comprehensive review that investigates how big data analytics is utilised to track tourist mobility is still lacking. Hence, the primary objective of this study is to delve into the understanding of tracking tourists' mobility through the utilisation of big data analytics, considering data sources, methodologies, theoretical contributions, limitations, and future research directions. To accomplish this, an extensive literature review was conducted, encompassing publications from tourism and hospitality journals spanning a decade, from 2013 to 2023. This paper thoroughly examines five distinct types of data sources and explains how they enable researchers to monitor and track tourists' mobility for various research objectives. Moreover, the paper contributes to the academic discourse by identifying the gap in the literature where the application of theoretical frameworks has not kept pace with the advancements in data collection and analysis technologies. To bridge this gap, we introduce an innovative conceptual model that aligns the theoretical aspects of tourist studies with the practical application of big data, thereby offering a richer understanding of tourist mobility patterns. In addition, the research identifies and discusses the limitations of current studies, such as concerns regarding data privacy, representativeness, and the dichotomy between qualitative and quantitative data analysis in the field. By establishing a foundational framework and advocating for theoretical development, this paper sets a new standard for the integration of big data into tourism research, paving the way for future scholarly exploration.
Chen et al. (Fri,) studied this question.