A Cross-Scale Representation of Tourist Activity Space

Bibliographic Data

ID3775205
AuthorsXinyue Chen (0000-0003-2181-5172, Hong Kong Polytechnic University), Yang Xu (0000-0003-3898-022X, Hong Kong Polytechnic University), Sangwon Park (0000-0003-3021-1987, Kyung Hee University), Yimin Chen (0000-0003-1976-6041, Sun Yat-sen University), Xintao Liu (0000-0002-7323-9878, Hong Kong Polytechnic University), Chengxiang Zhuge (0000-0002-9942-3462, Hong Kong Polytechnic University)
Year2023
Volume113
Issue10
Pages2333-2358
Publication date2023-11-26
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAnnals of the American Association of Geographers (JOURNAL)
Journal identifiersISSN: 2469-4452 • E-ISSN: 2469-4460
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2023.2231533
OpenAlexW4386160661
LanguageEN
Citations received4
References cited72

Destination, as a key concept in tourism geography, has largely determined the scale at which tourist activity space was modeled and studied. Existing studies usually focused on investigating tourists’ activities and movements either at the intradestination (e.g., within a city) or interdestination scale. Although useful in numerous research contexts, these models based on fixed spatial scales are incapable of portraying the complex spatial structure of tourist activity spaces, which sometimes exhibit hierarchical structures, and could span across different spatial scales. In this study, we propose a new representation of tourist activity space to bridge these gaps. The representation takes tourists’ accommodation locations as key reference points. At the macroscale, the sequence of accommodation locations forms the backbone of tourist activity space, denoted as itinerary type. At the microscale, we introduce the concept of territory to describe how individuals organize activities around these overnight “base camps” (i.e., accommodation locations). We apply this representation over a large-scale mobile phone data set of international travelers visiting South Korea to demonstrate its capability. Results show that four generic itinerary types capture the activity space structure of 89 percent of the tourists. The interrelationships of territories and their topological structures further categorize activity spaces into subtypes, leading to a new method of tourist classification based on their spatiotemporal activity patterns. We believe the proposed representation could enrich new perspectives and debates on how tourist activities can be studied. The representation can also be extended as a generic framework to delineate complex forms of human activity space

Accommodation · Cartography · Categorization · Economic geography · Geography · Political science · Representation (politics · Scale (ratio · Tourism · Computer Science · Diverse Aspects of Tourism Research · Human Mobility and Location-Based Analysis · Psychology · Urban Transport and Accessibility · Artificial Intelligence

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