IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v96y2021ics0966692321002313.html
   My bibliography  Save this article

Using cellular data to analyze the tourists' trajectories for tourism destination attributes: A case study in Hualien, Taiwan

Author

Listed:
  • Chu, Chih-Peng
  • Chou, Yu-Hsin

Abstract

This study adopts social network analysis (SNA) to identity the spatial role of nodes in a tourism region. The trajectory of multi-destination tourists will provide great information for tourism management, but tracking tourists' movements is a big challenge. Thanks to the popularity of mobile communication devices (mobile phones) nowadays, these can passively or actively provide information on owners' movement. This study uses call detail records (CDR), which are mobile phone positioning data, to construct a trajectory network of tourists in Hualien, Taiwan. Three types of centralities, as well as brokerage analysis and role analysis, are used to measure the relations in a complicated network. Degree centrality (DC) reveals popular nodes that have good relationships with others directly. Reach closeness centrality (RCC) shows indirect relationships with others. Betweenness centrality (BC) indicates the most important mediator nodes that help others to connect. BC and brokerage analysis are used to classify destinations into five brokers: the coordinator, consultant, gatekeeper, representative, and liaison. We also identify social positions of each destination by role analysis. This study identifies a total of 78 nodes (origins and destinations) and their functions in the tourism network. We find some nodes have more than one mission, while some only have one. The functions of nodes can be different on weekdays and weekends. We distinguish the tourism region into different size of districts. The results of this study can help managers consolidate strategies for tourism marketing.

Suggested Citation

  • Chu, Chih-Peng & Chou, Yu-Hsin, 2021. "Using cellular data to analyze the tourists' trajectories for tourism destination attributes: A case study in Hualien, Taiwan," Journal of Transport Geography, Elsevier, vol. 96(C).
    • Handle: RePEc:eee:jotrge:v:96:y:2021:i:c:s0966692321002313
    DOI: 10.1016/j.jtrangeo.2021.103178
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692321002313
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2021.103178?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Crawford, F. & Watling, D.P. & Connors, R.D., 2018. "Identifying road user classes based on repeated trip behaviour using Bluetooth data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 55-74.
    3. Egbert Van der Zee & Dario Bertocchi, 2018. "Finding patterns in urban tourist behaviour: a social network analysis approach based on TripAdvisor reviews," Information Technology & Tourism, Springer, vol. 20(1), pages 153-180, December.
    4. Hee Chung Chung & Namho Chung & Yoonjae Nam, 2017. "A Social Network Analysis of Tourist Movement Patterns in Blogs: Korean Backpackers in Europe," Sustainability, MDPI, vol. 9(12), pages 1-19, December.
    5. Rosario D’Agata & Simona Gozzo & Venera Tomaselli, 2013. "Network analysis approach to map tourism mobility," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3167-3184, October.
    6. Patrick Bonnel & Mariem Fekih & Smoreda Zbigniew, 2018. "Origin-Destination estimation using mobile network probe data," Post-Print halshs-02114628, HAL.
    7. Milne, Dave & Watling, David, 2019. "Big data and understanding change in the context of planning transport systems," Journal of Transport Geography, Elsevier, vol. 76(C), pages 235-244.
    8. Jones, Peter & Lucas, Karen, 2012. "The social consequences of transport decision-making: clarifying concepts, synthesising knowledge and assessing implications," Journal of Transport Geography, Elsevier, vol. 21(C), pages 4-16.
    9. Pike, Susan & Lubell, Mark, 2016. "Geography and social networks in transportation mode choice," Journal of Transport Geography, Elsevier, vol. 57(C), pages 184-193.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guangming Yang & Yunrui Yang & Guofang Gong & Qingqing Gui, 2022. "The Spatial Network Structure of Tourism Efficiency and Its Influencing Factors in China: A Social Network Analysis," Sustainability, MDPI, vol. 14(16), pages 1-22, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hwayoon Seok & George A. Barnett & Yoonjae Nam, 2021. "A social network analysis of international tourism flow," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 419-439, April.
    2. 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.
    3. Angela Chantre-Astaiza & Laura Fuentes-Moraleda & Ana Muñoz-Mazón & Gustavo Ramirez-Gonzalez, 2019. "Science Mapping of Tourist Mobility 1980–2019. Technological Advancements in the Collection of the Data for Tourist Traceability," Sustainability, MDPI, vol. 11(17), pages 1-32, August.
    4. F. Crawford & D. P. Watling & R. D. Connors, 2023. "Analysing Spatial Intrapersonal Variability of Road Users Using Point-to-Point Sensor Data," Networks and Spatial Economics, Springer, vol. 23(2), pages 373-406, June.
    5. Rawad Choubassi & Lamia Abdelfattah, 2020. "How Big Data is Transforming the Way We Plan Our Cities," Briefs, Fondazione Eni Enrico Mattei, December.
    6. Juan Brida & Marta Disegna & Raffaele Scuderi, 2014. "The behaviour of repeat visitors to museums: review and empirical findings," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2817-2840, September.
    7. Cavoli, Clemence, 2021. "Accelerating sustainable mobility and land-use transitions in rapidly growing cities: Identifying common patterns and enabling factors," Journal of Transport Geography, Elsevier, vol. 94(C).
    8. Kevin Credit & Zander Arnao, 2023. "A method to derive small area estimates of linked commuting trips by mode from open source LODES and ACS data," Environment and Planning B, , vol. 50(3), pages 709-722, March.
    9. Duvarci, Yavuz & Yigitcanlar, Tan & Mizokami, Shoshi, 2015. "Transportation disadvantage impedance indexing: A methodological approach to reduce policy shortcomings," Journal of Transport Geography, Elsevier, vol. 48(C), pages 61-75.
    10. Lin, Joanne Yuh-Jye & Jenelius, Erik & Cebecauer, Matej & Rubensson, Isak & Chen, Cynthia, 2023. "The equity of public transport crowding exposure," Journal of Transport Geography, Elsevier, vol. 110(C).
    11. Collins, Timothy W. & Nadybal, Shawna & Grineski, Sara E., 2020. "Sonic injustice: Disparate residential exposures to transport noise from road and aviation sources in the continental United States," Journal of Transport Geography, Elsevier, vol. 82(C).
    12. Carmela Iorio & Giuseppe Pandolfo & Antonio D’Ambrosio & Roberta Siciliano, 2020. "Mining big data in tourism," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(5), pages 1655-1669, December.
    13. Guzman, Luis A. & Cantillo-Garcia, Victor A. & Oviedo, Daniel & Arellana, Julian, 2023. "How much is accessibility worth? Utility-based accessibility to evaluate transport policies," Journal of Transport Geography, Elsevier, vol. 112(C).
    14. Selima Sultana & Hyojin Kim & Nastaran Pourebrahim & Firoozeh Karimi, 2018. "Geographical Assessment of Low-Carbon Transportation Modes: A Case Study from a Commuter University," Sustainability, MDPI, vol. 10(8), pages 1-23, August.
    15. Kaplan, Sigal & Popoks, Dmitrijs & Prato, Carlo Giacomo & Ceder, Avishai (Avi), 2014. "Using connectivity for measuring equity in transit provision," Journal of Transport Geography, Elsevier, vol. 37(C), pages 82-92.
    16. 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.
    17. Massingue, Suzanna Allen & Oviedo, Daniel, 2021. "Walkability and the Right to the city: A snapshot critique of pedestrian space in Maputo, Mozambique," Research in Transportation Economics, Elsevier, vol. 86(C).
    18. Yuanyuan Mao & Xiyuan Ren & Ling Yin & Qingying Sun & Ke Song & De Wang, 2021. "Investigating Tourists’ Willingness to Walk (WTW) to Attractions within Scenic Areas: A Case Study of Tongli Ancient Town, China," Sustainability, MDPI, vol. 13(23), pages 1-15, November.
    19. Vallejo-Borda, Jose Agustin & Barchelot-Aceros, Laura Juliana & Barrero, German A. & Ortiz-Ramirez, Hernan Alberto & Pabón-Poches, Daysy Katherine & Silva-Fernández, Claudia Susana, 2023. "Addressing pedestrian perceived externalities influenced by motor vehicles: A perspective from curb space typologies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    20. Monther M. Jamhawi & Roa’a J. Zidan & Mohammed Fareed Sherzad, 2023. "Tourist Movement Patterns and the Effects of Spatial Configuration in a Cultural Heritage and Urban Destination: The Case of Madaba, Jordan," Sustainability, MDPI, vol. 15(2), pages 1-25, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:96:y:2021:i:c:s0966692321002313. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.