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GIS Monitoring of Traveler Flows Based on Big Data

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Analytics in Smart Tourism Design

Part of the book series: Tourism on the Verge ((TV))

Abstract

This chapter reports on a study that employs geo-tagged data from Sina Weibo to investigate the spatial pattern of Chinese domestic tourist flows during the National Day Golden Week in 2014. Based on a dyadic matrix of inter-province tourist flows, the results show that the Weibo data is highly correlated with the official tourism statistics. Factor analysis unveils several spatially independent fields of tourist flows in China, such as the area around Beijing as well as the regions in the East, Southwest, Northwest, Northeast, and Central South. Furthermore, the estimation results from the negative binomial spatial interaction model highlight several determinants of tourist flows, including the distance between the origin and destination, the size of economies in the origin and destination, the hotel infrastructure in the destination, and the number of world heritage sites and AAAA scenic spots in the destination areas.

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Author information

Authors and Affiliations

  1. Beijing Tsinghua Tongheng Urban Planning & Design Institute (THUPDI), Beijing, People’s Republic of China

    Dong Li

  2. Temple University, Philadelphia, PA, USA

    Yang Yang

Authors
  1. Dong Li
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  2. Yang Yang
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Correspondence to Yang Yang .

Editor information

Editors and Affiliations

  1. Department of Hospitality and Tourism Management, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA

    Zheng Xiang

  2. National Laboratory for Tourism & eCommerce Department of Tourism, Recreation and Sport Management, University of Florida, Gainesville, Florida, USA

    Daniel R. Fesenmaier

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Li, D., Yang, Y. (2017). GIS Monitoring of Traveler Flows Based on Big Data. In: Xiang, Z., Fesenmaier, D. (eds) Analytics in Smart Tourism Design. Tourism on the Verge. Springer, Cham. https://doi.org/10.1007/978-3-319-44263-1_7

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