The Spatial Dynamics of Amazon Lockers in Los Angeles County

The rise of e-commerce has imposed increasing pressures on urban freight distribution systems with a significant demand for dedicated delivery services to the end consumers. Last-mile delivery, which usually happens in residential areas conducted by small vans or trucks with low speeds, raises concerns for environmental and safety issues. One of the strategies to address these problems is to set up Pick-up Point (PPs) networks or Automated Parcel (APs) systems. This research will focus on the spatial dynamics and the associated potential GHG emission reductions of Amazon Lockers, one of the most popular APs, in Los Angeles County. The location data of Amazon Lockers will be obtained by Google Map API and Python. Specifically, the questions to be answered include: (1) Describing the spatial distribution of lockers using spatial pattern analysis tool (Kernel density and Moran’s I statistics); (2) Analyzing the socio-economic and built environmental factors that might affect the spatial distribution of Amazon Lockers using spatial regression models (Geographically Weight Regression); and (3) Predict and estimate the potential GHG emission reduction based on the spatial regression models. The results indicate that (1) There is a “three-tier-clustering” pattern based on the level of density; (2) There is a significant positive spatial autocorrelation at 99% confidence level; (3) Geographic Weighted Regression with independent variables population/internet use, income, education, walkability, transit and parking can explain 41% of the variations in dependent variables; (4) Business cooperation and spillover effects also greatly affect the locker distribution.

• Dataset URL:
  https://doi.org/10.7910/DVN/QTUW3J
• Record URL:
  https://www.metrans.org/research/the-spatial-dynamics-of-amazon-lockers-in-los-angeles-county
• Record URL:
  https://merritt.cdlib.org/api/presign-file/ark%253A%252F13030%252Fm5ns66db/1/producer%252FMF-5.4c.pdf
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/68178
• Supplemental Notes:
  • Supporting datasets available at: https://doi.org/10.7910/DVN/QTUW3J This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  University of Southern California

  Los Angeles, California  United States 

  METRANS Transportation Center

  University of Southern California
  Los Angeles, CA  United States  90089-0626

  MetroFreight

  Volvo Center of Excellence
  ,    

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Authors:
  • Fang, Jiawen
  • 0000-0002-6339-134X
  • Giuliano, Genevieve
  • 0000-0002-9257-8269
  • Wu, An-Min
• Publication Date: 2019-10-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; References; Tables;
• Pagination: 30p

Subject/Index Terms

• TRT Terms: Cluster analysis; Electronic commerce; Freight transportation; Greenhouse gases; Regression analysis; Spatial analysis; Urban goods movement
• Identifier Terms: Amazon.com
• Geographic Terms: Los Angeles County (California)
• Subject Areas: Freight Transportation; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01749275
• Record Type: Publication
• Report/Paper Numbers: MF-5.4c, MF-5.4c
• Contract Numbers: USDOT Grant 69A3551747109
• Files: BTRIS, UTC, NTL, TRIS, ATRI, USDOT
• Created Date: Aug 27 2020 10:21AM