Urban tourists’ spatial distribution and subgroup identification in a metropolis --the examination applying mobile signaling data and latent profile analysis

Cheng Shi (), Yujia Zhai () and Dongying Li ()
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Cheng Shi: Tongji University
Yujia Zhai: Tongji University
Dongying Li: Texas A&M University

Information Technology & Tourism, 2023, vol. 25, issue 3, No 9, 453-476

Abstract: Abstract Understanding tourists’ spatial distribution and subgroups is important for urban tourism planning and management. This study utilized mobile signaling data from 21 million equipments to examine the tourist spots travelers visited and their movements in the city of Shanghai. In addition, we used latent profile analysis (LPA) to identify potential tourist groups according to their duration of stay and the tourist spots they visited. The results indicated that historical tourist spots drew a lot of travelers and nearly half of all tourists visited at least one historical site/district. Areas within the inner ring and around the ancient towns beyond the outer ring were frequently visited by tourists. Tourists preferred to visit famous tourist spots sequentially, rather than stopping by nearby less famous spots. Moreover, the connections between these famous spots were more frequent than between other spots. Three groups of tourists were identified, including long-stay multi-interest traveler, short-stay history-lover, and short-stay culture-lover. This study contributes to the application of mobile signaling data in exploring urban tourists’ spatial distribution, as well as can shed light on urban tourism planning and strategy development.

Keywords: Mobile signaling data; Urban tourists; Spatial distribution; Subgroups (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s40558-023-00255-y

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