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Connecting intercity mobility with urban welfare.

Sayat Mimar1, David Soriano-Paños2,3, Alec Kirkley4,5,6

  • 1Department of Physics & Astronomy, University of Rochester, Rochester, NY 14607, USA.

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|January 30, 2023
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Summary

Global city networks reveal how population flows impact urban welfare. Mobility data predicts prosperity in developed cities, but developing cities need neighborhood insights for accurate welfare assessment.

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Area of Science:

  • Urban Studies
  • Network Science
  • Socioeconomics

Background:

  • Limited understanding of interurban interactions on urban welfare.
  • Focus on intraurban characteristics for sustainability and growth.
  • Need to explore how cities influence each other's development.

Purpose of the Study:

  • Analyze global population mobility networks as a proxy for interurban communication.
  • Correlate mobility patterns with socioeconomic indicators.
  • Investigate the role of city development stage in welfare prediction.

Main Methods:

  • Utilized global population flow data to construct a mobility network.
  • Applied centrality measures (e.g., PageRank) to rank city importance.
  • Developed a generative model for population flow allocation.

Main Results:

  • PageRank centrality effectively reflects urban prosperity indicators.
  • Mobility-based welfare predictions correlate with economic indicators in mature cities.
  • Developing cities require additional neighborhood mobility data for accurate welfare assessment.
  • Generative model accurately fits observed flows and highlights developed/developing city differences.

Conclusions:

  • Interurban connections are crucial for urban development and welfare.
  • Mobility network analysis offers insights into city prosperity.
  • Development stage significantly influences the interpretation of mobility data for urban welfare.