Understanding tourist behavior using large-scale mobile sensing approach: A case study of mobile phone users in Japan

• Main Authors: Santi Phithakkitnukoon, Teerayut Horanont, Apichon Witayangkurn, Raktida Siri, Yoshihide Sekimoto, Ryosuke Shibasaki
• Format: Journal
• Published: 2018
• Subjects: Computer Science; Mathematics
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85027925252&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/54345
• Institution: Chiang Mai University

© 2014 Elsevier B.V. All rights reserved. This article describes a framework that capitalizes on the large-scale opportunistic mobile sensing approach for tourist behavior analysis. The article describes the use of massive mobile phone GPS location records to study tourist travel behavior, in particular, number of trips made, time spent at destinations, and mode of transportation used. Moreover, this study examined the relationship between personal mobility and tourist travel behavior and offered a number of interesting insights that are useful for tourism, such as tourist flows, top tourist destinations or origins, top destination types, top modes of transportation in terms of time spent and distance traveled, and how personal mobility information can be used to estimate the likelihood in tourist travel behavior, i.e., number of trips, time spent at destinations, and trip distance. Furthermore, the article describes an application developed based on the analysis in this study that allows the user to observe touristic, non-touristic, and commuting trips along with home and workplace locations as well as tourist flows, which can be useful for urban planners, transportation management, and tourism authorities.