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Visitor Mobility and Spatial Structure in a Local Urban Tourism Destination: GPS Tracking and Network analysis

Author

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  • Koun Sugimoto

    (Department of Tourism Science, Graduate School of Urban Environment Sciences, Tokyo Metropolitan University; 1-1 Minamiohsawa, Hachioji, Tokyo 192-0397, Japan)

  • Kei Ota

    (Department of Tourism Science, Graduate School of Urban Environment Sciences, Tokyo Metropolitan University; 1-1 Minamiohsawa, Hachioji, Tokyo 192-0397, Japan)

  • Shohei Suzuki

    (Department of Tourism Science, Graduate School of Urban Environment Sciences, Tokyo Metropolitan University; 1-1 Minamiohsawa, Hachioji, Tokyo 192-0397, Japan)

Abstract

Visitor mobility is an important element for facilitating sustainable local economics and management in urban tourism destinations. Research on visitor mobility often focuses on the patterns and structures of spatial visitor behavior and the factors that influence them. This study examines the relationship between visitor mobility and urban spatial structures through an exploratory analysis of visitors’ movements and characteristics, which were collected from surveys with global positional system (GPS) tracking technologies and questionnaires. The Ueno district, one of the most popular tourism destinations in Tokyo, Japan, was selected as the study area. For local stakeholders, the low accessibility levels between this district’s park zone and downtown zone have become a major destination management issue. We compared visitor movements and flow networks in various places from different major trip origins (railway stations) by using several analysis techniques (GPS log distribution, spatial movement sequences, and network analysis), and examined physical and human factors that caused the different mobility patterns. The results demonstrated that physical factors, including major transport hubs (railway stations), topography, commercial accumulation, and POI distribution, affected intra-destination visitor behavior, and segmented visitor markets into different main zones. Such findings could inform future destination management policies and planning in local urban tourism destinations.

Suggested Citation

  • Koun Sugimoto & Kei Ota & Shohei Suzuki, 2019. "Visitor Mobility and Spatial Structure in a Local Urban Tourism Destination: GPS Tracking and Network analysis," Sustainability, MDPI, vol. 11(3), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:3:p:919-:d:204981
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    References listed on IDEAS

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    3. Yang Yang & Xiang Chen & Song Gao & Zhenlong Li & Zhe Zhang & Bo Zhao, 2023. "Embracing geospatial analytical technologies in tourism studies," Information Technology & Tourism, Springer, vol. 25(2), pages 137-150, June.
    4. Qian Yao & Yong Shi & Hai Li & Jiahong Wen & Jianchao Xi & Qingwei Wang, 2020. "Understanding the Tourists’ Spatio-Temporal Behavior Using Open GPS Trajectory Data: A Case Study of Yuanmingyuan Park (Beijing, China)," Sustainability, MDPI, vol. 13(1), pages 1-13, December.
    5. Ahmed Derdouri & Toshihiro Osaragi, 2021. "A machine learning-based approach for classifying tourists and locals using geotagged photos: the case of Tokyo," Information Technology & Tourism, Springer, vol. 23(4), pages 575-609, December.
    6. Tiantian Zhang & Weicheng Hua & Yannan Xu, 2019. "“Seeing” or “Being Seen”: Research on the Sight Line Design in the Lion Grove Based on Visitor Temporal–Spatial Distribution and Space Syntax," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    7. Tosporn Arreeras & Mikiharu Arimura & Takumi Asada & Saharat Arreeras, 2019. "Association Rule Mining Tourist-Attractive Destinations for the Sustainable Development of a Large Tourism Area in Hokkaido Using Wi-Fi Tracking Data," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    8. Eunbee Gil & Yongjin Ahn & Youngsang Kwon, 2020. "Tourist Attraction and Points of Interest (POIs) Using Search Engine Data: Case of Seoul," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    9. Yuzhen Li & Guofang Gong & Fengtai Zhang & Lei Gao & Yuedong Xiao & Xingyu Yang & Pengzhen Yu, 2022. "Network Structure Features and Influencing Factors of Tourism Flow in Rural Areas: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    10. Jieping Chen & Chao Ma & Shijun Chen, 2024. "Determinant of the tourism economy in Chinese cities: from an urban centrality perspective," Tourism Economics, , vol. 30(1), pages 44-66, February.
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