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Forecast Tourist Arrivals Using Map Search Data

  • Yunhao Liu
  • , Gengzhong Feng
  • , Shaolong Sun
  • , Kwai Sang Chin
  • , Shouyang Wang
  • Xi’an Jiaotong University
  • City University of Hong Kong
  • Key Lab of the Ministry of Education for Process Control and Efficiency Egineering
  • State Key Laboratory of AI Safety
  • CAS - Academy of Mathematics and System Sciences
  • ShanghaiTech University

科研成果: 期刊稿件文章同行评审

摘要

The map search data, which reflect the willingness to travel, have the potential in forecasting tourist arrivals. This study introduces the map search data as a new indicator in tourist arrivals forecasting. The authors use Mount Tai and Macao, China’s daily tourist arrival data as experimental data and the map search volume index. By employing four widely-used methods, the authors use the map search data and search engine data as indicators in tourist arrivals forecasting. The experimental results show that the map search data can effectively improve forecasting performance, which is better than using search engine data. These findings are still valid during the COVID-19 pandemic by examining them in Macao, China’s data.

源语言英语
页(从-至)1642-1659
页数18
期刊Journal of Systems Science and Complexity
39
4
DOI
出版状态已出版 - 8月 2026
已对外发布

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