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Investigate Tourist Behavior through Mobile Signal: Tourist Flow Pattern Exploration in Tibet

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  • Lina Zhong

    (Institute for Big Data Research in Tourism, School of Tourism Sciences, Beijing International Studies University, Beijing 100020, China)

  • Sunny Sun

    (College of Asia Pacific Studies, Ritsumeikan Asia Pacific University, Beppu, Oita 874–8577, Japan)

  • Rob Law

    (School of Hotel & Tourism Management, The Hong Kong Polytechnic University, Hong Kong, China)

  • Liyu Yang

    (School of Tourism Sciences, Beijing International Studies University, Beijing 100020, China)

Abstract

Identifying the tourist flow of a destination can promote the development of travel-related products and effective destination marketing. Nevertheless, tourist inflows and outflows have only received limited attention from previous studies. Hence, this study visualizes the tourist flow of Tibet through social network analysis to bridge the aforementioned gap. Findings show that the Lhasa prefecture is the transportation hub of Tibet. Tourist flow in the eastern part of Tibet is generally stronger than that in the western part. Moreover, the tourist flow pattern identified mainly includes “(diverse or balanced) diffusion from the main center”, “clustering to the main center”, and “diffusion from a clustered circle”.

Suggested Citation

  • Lina Zhong & Sunny Sun & Rob Law & Liyu Yang, 2020. "Investigate Tourist Behavior through Mobile Signal: Tourist Flow Pattern Exploration in Tibet," Sustainability, MDPI, vol. 12(21), pages 1-13, November.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:21:p:9125-:d:439166
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    References listed on IDEAS

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    1. Roberto Patuelli & Maurizio Mussoni & Guido Candela, 2016. "The Effects of World Heritage Sites on Domestic Tourism: A Spatial Interaction Model for Italy," Advances in Spatial Science, in: Roberto Patuelli & Giuseppe Arbia (ed.), Spatial Econometric Interaction Modelling, chapter 0, pages 281-315, Springer.
    2. N. Kulendran, 1996. "Modelling Quarterly Tourist Flows to Australia Using Cointegration Analysis," Tourism Economics, , vol. 2(3), pages 203-222, September.
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    Cited by:

    1. 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.

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