Digital footprint for tourism research

Abstract

Tourists leave a digital footprint across a variety of repositories when planning and carrying out their activities. This information can be pro- cessed to extract valuable insights about tourist behavior. The objective of this paper is to conduct a comprehensive analysis of the digital foot- print sources employed in understanding and predicting the main variables associated with tourist behavior. A model of the purchase consumption system specific to leisure travel behavior is utilized for source classification, as it identifies potential predictors of travelers’ choices and classifies them into three stages: pre-trip, during-trip, and post-trip. Our work presents a comprehensive map of the utilization of digital footprint resources in tourism research, which provides insights into the potential predictors of tourists’ choices.

رصد البصمة الرقمية السياحية ومراكز الأنشطة السياحية من خلال بيانات التوسيم الجغرافي والبيانات المحددة للموقع: مدينة الإسكندرية كدراسة حالة

“…Furthermore, social media has emerged as a major source of highly accurate and instantly updated geographic data (Gao, 2024) that is referred to as "digital footprints" (Girardin et al 2008). In fact, tourists leave a digital "footprint" in most of their activities in the cities they visit (Wu, 2022).They use bank cards to make payments, snap vast numbers of photographs and post them to photo-sharing websites, communicate on social media and mobile devices (Cebrián & Domenech, 2023). According to Jianheng and Yanling (2021), a significant amount of these data is geolocated, so these electronic traces may reflect the temporal and geographical movement trajectory of tourists.…”

“…According to Salas-Olmedo et al (2018), innovation has also been achieved in the usage of LBSNs, especially Twitter, Foursquare, and Panoramio, to determine tourism activities from usergenerated content in the context of Barcelona, Spain. In spite of the developed benefits of LBSNs for locating points of interest (POIs) in urban areas, this study conveys a methodology for identifying and pinpointing tourist activity centers (TACs) by incorporating data from five distinct LBSNs: Twitter (Salas-Olmedo et al, 2018;Cebrián & Domenech, 2023), Instagram (Mondo et al, 2020), Instasights heatmaps (Avuxi Ldt 2024), Foursquare (Foursquare Inc. 2019), and TripAdvisor (TripAdvisor LLC 2022.…”

“…Nevertheless, several research additionally take into account tweet geo-tagged data (Bhatt and Pickering, 2021;Kim et al, 2021). Furthermore, other researches consider the number of likes, retweets, comments, and tweets as well as the time at which they are posted as significant sources of information (Kwok et al, 2022;Cebrián & Domenech, 2023). Secondly, Cebrián and Domenech (2023) state that Instagram is a free online multimedia platform that allows people and businesses to publish images, videos, reels, and stories (Yubero et al,2021).…”

“…Furthermore, other researches consider the number of likes, retweets, comments, and tweets as well as the time at which they are posted as significant sources of information (Kwok et al, 2022;Cebrián & Domenech, 2023). Secondly, Cebrián and Domenech (2023) state that Instagram is a free online multimedia platform that allows people and businesses to publish images, videos, reels, and stories (Yubero et al,2021). A variety of researchers concentrate on the content of the photos uploaded to the platform, including the colors (Yu & Egger, 2021;Yu et al, 2023) or the topic of the photograph (Aramendia-Muneta et al,2021).…”

“…In recent years, Big Data have shown significant potential in the field of tourism research, owing to their ability to offer spatiotemporal data derived from a large number of tourists (Salas Olmedo et al, 2018). The progression of technology has facilitated the capture and examination of each user interaction and click on electronic devices, forming a digital foot print (Bondarenko et al, 2021), which plays a crucial role in comprehending the spatiotemporal trends in tourist decision-making processes, thus enabling the identification of tourist preferences and formulation of tourism strategies (Cebrián & Domenech, 2023). Notably, the emergence of social media has had a significant impact on the field of tourism, being extensively utilized in various research studies.…”