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<p>Commercial districts are centers of a city’s economic activity. Quantitative assessment of their attractiveness can reflect the economic vitality and development level of each district. However, existing studies rarely investigate the fine-grained spatial patterns of commercial district attractiveness and are limited in extracting the catchment area of each district, which hinders operations management of commercial districts at a micro scale. To address the gap, we propose three attractiveness metrics to quantify the intensity and spatial attractiveness of each commercial district, i.e., Total Attractiveness (TA), Attractiveness Per Unit Area (APUA), and Attractiveness on each external Grid Cell (AGC), based on grid-level mobile positioning flow data. A case study on eight Shanghai commercial districts, e.g., Xujiahui, Lujiazui, and East Nanjing Road, was conducted using a three-month flow dataset comprising 20&#xa0;million Origin-Destination (OD) pairs. The correlation analysis reveals strong associations with ancillary data: TA with nighttime light (Spearman’s ρ = 0.976), APUA with commercial POIs (ρ = 0.762), and AGC with WorldPop (ρ = 0.606). Moreover, a power-law distribution of AGC caused by the distance-decay effect was observed. Based on the distance-decay model, we graded the catchment area into four tiers and conducted an anisotropy analysis to reveal a heterogeneous spatial distribution of attractiveness. Spatial competitiveness analysis further indicated that spatial proximity and transportation accessibility are two critical factors associated with the attractiveness advantages of commercial districts. These findings provide valuable insights for urban planners and policymakers in commercial district planning and operations.</p>

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Quantitative Assessment of Attractiveness and Catchment Area for Urban Commercial Districts Via Mobile Positioning Flow Data

  • 期刊论文

  • 发表日期：

    2026年5月7日

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  • Cho-Ho Lo,
  • Sunkangning Fang,
  • Zhipeng Gui,
  • Mei Li,
  • Dehua Peng,
  • Huan Chen,
  • Yuhang Liu,
  • Kai Li,
  • Kun Guan,
  • Huayi Wu,
  • Chuang Tao

摘要

Commercial districts are centers of a city’s economic activity. Quantitative assessment of their attractiveness can reflect the economic vitality and development level of each district. However, existing studies rarely investigate the fine-grained spatial patterns of commercial district attractiveness and are limited in extracting the catchment area of each district, which hinders operations management of commercial districts at a micro scale. To address the gap, we propose three attractiveness metrics to quantify the intensity and spatial attractiveness of each commercial district, i.e., Total Attractiveness (TA), Attractiveness Per Unit Area (APUA), and Attractiveness on each external Grid Cell (AGC), based on grid-level mobile positioning flow data. A case study on eight Shanghai commercial districts, e.g., Xujiahui, Lujiazui, and East Nanjing Road, was conducted using a three-month flow dataset comprising 20 million Origin-Destination (OD) pairs. The correlation analysis reveals strong associations with ancillary data: TA with nighttime light (Spearman’s ρ = 0.976), APUA with commercial POIs (ρ = 0.762), and AGC with WorldPop (ρ = 0.606). Moreover, a power-law distribution of AGC caused by the distance-decay effect was observed. Based on the distance-decay model, we graded the catchment area into four tiers and conducted an anisotropy analysis to reveal a heterogeneous spatial distribution of attractiveness. Spatial competitiveness analysis further indicated that spatial proximity and transportation accessibility are two critical factors associated with the attractiveness advantages of commercial districts. These findings provide valuable insights for urban planners and policymakers in commercial district planning and operations.