Social Network Analysis and Connection Strength Evaluation of Urban Tourist Attractions Using Car-Hailing Data: A Case Study of Beijing

For large cities with huge tourism market, tourism travels can have significant impact on the urban traffic, which, cannot be ignored in both urban transportation and tourism planning. This paper first proposes a simple and effective spatial matching method to identify tourist travel patterns based on massive online car-hailing data. Then we construct the tourist attractions network based on the tourist movement by car. From the perspective of social network analysis, the development status of the holistic tourist attractions network and the influence of the attractions are evaluated. Finally, connection strength based Jenks natural breaks classification method is employed to divide the attractions into four levels: unconnected, weak, moderate and strong connection. Taking Beijing as case study, the main factors that affect the connection strength among attractions are the popularity of the attraction and the spatial proximity of the attraction. These findings in tourist movement can facilitate authorities and planners to develop tourism destinations and manage tourism traffic better.

• Record URL:
  https://doi.org/10.1007/978-981-15-0644-4
• Record URL:
  https://link.springer.com/chapter/10.1007/978-981-15-0644-4_90
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9789811506437
• Supplemental Notes:
  • © Springer Nature Singapore Pte Ltd. 2020.
• Corporate Authors:

  Springer Singapore

  152 Beach Road
  Singapore,     189721
• Authors:
  • Ma, Shixia
  • Yan, Xuedong
  • Liu, Xiaobing
  • Chen, Deqi
• Conference:
  • 9th International Conference on Green Intelligent Transportation Systems and Safety
  • Location: Guilin , China
  • Date: 2018-7-1 to 2018-7-3
• Publication Date: 2020-3

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1171-1184
• Monograph Title: Green, Smart and Connected Transportation Systems: Proceedings of the 9th International Conference on Green Intelligent Transportation Systems and Safety
• Serial:
  • Lecture Notes in Electrical Engineering
  • Volume: 617
  • Publisher: Springer
  • ISSN: 1876-1100

Subject/Index Terms

• TRT Terms: Ridesourcing; Social factors; Tourists; Travel behavior; Urban transportation
• Geographic Terms: Beijing (China)
• Subject Areas: Highways; Safety and Human Factors; Society;

Filing Info

• Accession Number: 01898996
• Record Type: Publication
• ISBN: 9789811506437
• Files: TRIS
• Created Date: Nov 13 2023 4:57PM