Correlation Analysis of Urban Agglomeration Travel and Business Connections Based on Big Data

Urban agglomerations are becoming the main engines for the development of the national economy. As the cooperation and interaction between cities are continuously strengthened, transportation planning and development in urban agglomeration are becoming increasingly important. Studying the passenger flow network structure and business relationship of urban agglomeration is helpful for analyzing and predicting the intercity travel demand. In this paper, one-month mobile phone data and industrial and commercial data of more than 120,000 enterprises are used to study the intercity travel and enterprise connection in the Yangtze River Delta Agglomeration of China. Through the Quadratic Assignment Procedure (QAP) method, it is found that there is a significant correlation between passenger flow and the enterprise connection network. The results of this study are useful for the transportation planning of urban agglomeration.

• Record URL:
  • https://doi.org/10.1061/9780784484869.226
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784484869
• Supplemental Notes:
  • © 2023 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Hu, Jun-Tao
  • Duan, Zheng-Yu
  • Luo, Song-Wen
• Conference:
  • 23rd COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2023-7-14 to 2023-7-17
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 2391-2399
• Monograph Title: CICTP 2023: Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation

Subject/Index Terms

• TRT Terms: Business trips; Correlation analysis; Intercity transportation; Passenger traffic; Transportation planning; Urban areas
• Geographic Terms: Yangtze River Delta
• Subject Areas: Data and Information Technology; Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01908128
• Record Type: Publication
• ISBN: 9780784484869
• Files: TRIS, ASCE
• Created Date: Feb 14 2024 2:33PM