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The spatial coupling effect between urban street network's centrality and collection & delivery points: A spatial
Muhammad Sajid Mehmood1,2, Gang Li1,2, Annan Jin1,2
1College of Urban and Environmental Sciences, Northwest University, Xi'an, PR China.
Plos One
|May 6, 2021
Summary
Urban street network centrality significantly influences the location of logistics collection and delivery points. Understanding these spatial relationships aids in optimizing delivery networks for businesses and urban planners.
Area of Science:
- Urban planning
- Logistics management
- Spatial analysis
Background:
- Sustainable development of collection and delivery points is crucial for logistics.
- Urban street networks significantly impact the location of these points.
- The spatial relationship between street network centrality and delivery points lacks in-depth study.
Purpose of the Study:
- To analyze the spatial relationship between urban street network centrality and the location of collection and delivery points.
- To evaluate the influence of different centrality measures on delivery point placement.
- To provide insights for optimizing logistics networks.
Main Methods:
- Utilized a multiple centrality assessment model with point of interest and street network data.
- Assessed street centrality using closeness, betweenness, severance, and efficiency indicators in Nanjing.
- Employed kernel density estimation and spatial autocorrelation to analyze spatial patterns and coupling effects.
Main Results:
- Nanjing street centrality strongly influences delivery point locations, with varying centrality directions.
- Cainiao Station locations correlate most with closeness, then betweenness, severance, and efficiency.
- China Post Station locations show weak correlation with efficiency and severance, and no correlation with closeness and betweenness.
Conclusions:
- Street network centrality is a key factor in locating logistics collection and delivery points.
- Different centrality measures have distinct impacts on various types of delivery points.
- Findings support logistics enterprises and urban planners in developing efficient delivery networks.
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