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Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19

Author

Listed:
  • Yingying Wang

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
    Collaborative Research Center for Archaeology of Silk Roads, Northwest University, Xi’an 710127, China)

  • Feng Xu

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Zhe Lin

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

  • Jianying Guo

    (College of Tourism and Geographical Science, Leshan Normal University, Leshan 614000, China)

  • Gang Li

    (College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China)

Abstract

The rapid development of new retail and the impact of COVID-19 have catalyzed the blowout growth of community group purchasing. The emergence of community group purchasing collection and delivery points (CGPCDPs) has become a new way to solve the “last mile” problem of new retail delivery. Based on the point of interest (POI) data of CGPCDPs of Nansha District, Guangzhou City, this study advances our understanding by identifying unique operational models, service targets, and spatial distribution patterns of CGPCDPs, which differ significantly from traditional pick-up points (PPs). The conclusions are as follows: (1) Most CGPCDPs depend on wholesale and retail shops, and their main service targets are urban and rural communities, followed by industrial areas. (2) The distribution of CGPCDPs has apparent spatial differentiation. At the macro scale, it shows the characteristics of “central agglomeration and peripheral dispersion”. It is distributed along the “northwest-southeast” direction and presents a “dual-core multi-center” pattern. At the meso–micro scale, different built environments in developed areas of cities, villages in the city (ChengZhongCun), and rural areas show distinct distribution patterns. (3) The main influencing factors of their spatial distribution are population density, construction land, house price, supporting place, residence density, urban community, and road proximity.

Suggested Citation

  • Yingying Wang & Feng Xu & Zhe Lin & Jianying Guo & Gang Li, 2024. "Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19," Sustainability, MDPI, vol. 16(16), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:7233-:d:1461853
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    References listed on IDEAS

    as
    1. Baldi, Mauro Maria & Manerba, Daniele & Perboli, Guido & Tadei, Roberto, 2019. "A Generalized Bin Packing Problem for parcel delivery in last-mile logistics," European Journal of Operational Research, Elsevier, vol. 274(3), pages 990-999.
    2. Maren Schnieder & Chris Hinde & Andrew West, 2022. "Land Efficient Mobility: Evaluation of Autonomous Last Mile Delivery Concepts in London," IJERPH, MDPI, vol. 19(16), pages 1-21, August.
    3. Gue, Kevin R. & Ivanović, Goran & Meller, Russell D., 2012. "A unit-load warehouse with multiple pickup and deposit points and non-traditional aisles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 795-806.
    4. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
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