Spatial Heterogeneity of A-Level Logistics Enterprises Influencing Sustainability Research

Strategic Insights -

Researchers at Central South University of Forestry and Technology have conducted a study to explore the spatial heterogeneity of factors influencing A-level logistics enterprises in China over time. The study used a multi-scale geographically weighted regression model, analyzing the spatial evolution characteristics of A-level logistics enterprises through spatial visualization and density estimation methods. The results show that the spatial evolutionary pattern of A-level logistics enterprises in Chinese cities demonstrates simultaneous agglomeration-diffusion dynamics, and the MGWR model provides an innovative scientific approach to the study of spatial heterogeneity in logistics.

Key Takeaways:

  • The study found that the spatial evolutionary pattern of A-level logistics enterprises in Chinese cities demonstrates simultaneous agglomeration-diffusion dynamics.
  • The study concluded that the factors influencing the spatial heterogeneity of A-level logistics enterprises have different scales and intensities of action with cities over time and in different years.
  • The research analyzed the spatial evolution characteristics of A-level logistics enterprises through spatial visualization and density estimation methods.
  • The MGWR model provided an innovative scientific approach to the study of spatial heterogeneity in logistics.
  • The study identified key influencing factors and supported the planning of sustainable logistics enterprises.
  • The research was conducted by Yin Huang, with additional authors Xiaojia Yang, Gufeng Xue, Sijin Li, and Xiangni Huang.
  • The study was supported by the Central South University of Forestry and Technology.

Statistics:

  • The intensity and range of the influence of the 2021 significance indicators expanded compared to 2019, with a fluctuating upward trend in the intensity of impact.
  • The variability in the intensity of the impact was more pronounced across cities.
  • The study analyzed data from the 2019-2021 list of China's A-level logistics enterprises.
  • The MGWR model provided a more reliable regression results compared to traditional methods.

Sources:

  • Yin Huang et al. Evolution Characteristics and the Spatial Heterogeneity of the Factors Influencing A-level Logistics Enterprises In China. Environment, Development and Sustainability, 2025.
  • Springer (www.springer.com)
  • Environment, Development and Sustainability (www.springerlink.com/content/1387-585x/)
  • Central South University of Forestry and Technology (Sch Logist, Changsha 410004, People's Republic of China)
  • NewsRx (www.newsrx.com)

(NewsRx. Findings on Sustainable Development Detailed by Investigators at Central South University of Forestry and Technology (Evolution Characteristics and the Spatial Heterogeneity of the Factors Influencing A-level Logistics Enterprises In China). China Weekly News. October 21, 2025; p 185)