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Applying Big Data Analytics to Monitor Tourist Flow for the Scenic Area Operation Management

Author

Listed:
  • Siyang Qin
  • Jie Man
  • Xuzhao Wang
  • Can Li
  • Honghui Dong
  • Xinquan Ge

Abstract

Considering the rapid development of the tourist leisure industry and the surge of tourist quantity, insufficient information regarding tourists has placed tremendous pressure on traffic in scenic areas. In this paper, the author uses the Big Data technology and Call Detail Record (CDR) data with the mobile phone real-time location information to monitor the tourist flow and analyse the travel behaviour of tourists in scenic areas. By collecting CDR data and implementing a modelling analysis of the data to simultaneously reflect the distribution of tourist hot spots in Beijing, tourist locations, tourist origins, tourist movements, resident information, and other data, the results provide big data support for alleviating traffic pressure at tourist attractions and tourist routes in the city and rationally allocating traffic resources. The analysis shows that the big data analysis method based on the CDR data of mobile phones can provide real-time information about tourist behaviours in a timely and effective manner. This information can be applied for the operation management of scenic areas and can provide real-time big data support for “smart tourism”.

Suggested Citation

  • Siyang Qin & Jie Man & Xuzhao Wang & Can Li & Honghui Dong & Xinquan Ge, 2019. "Applying Big Data Analytics to Monitor Tourist Flow for the Scenic Area Operation Management," Discrete Dynamics in Nature and Society, Hindawi, vol. 2019, pages 1-11, January.
    • Handle: RePEc:hin:jnddns:8239047
    DOI: 10.1155/2019/8239047
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    Cited by:

    1. Zhenshan Yang & Shuying Zhang & Jiaming Liu & Huijuan Sun, 2022. "Network of Tourism–Industrial Complex in Cities: Typologies and Implications through a Critical Literature Review," IJERPH, MDPI, vol. 19(9), pages 1-16, April.

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