Version 1
: Received: 27 March 2024 / Approved: 28 March 2024 / Online: 28 March 2024 (07:10:21 CET)
How to cite:
Wang, Y.; Xu, F.; Li, G. Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19 in China. Preprints2024, 2024031739. https://doi.org/10.20944/preprints202403.1739.v1
Wang, Y.; Xu, F.; Li, G. Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19 in China. Preprints 2024, 2024031739. https://doi.org/10.20944/preprints202403.1739.v1
Wang, Y.; Xu, F.; Li, G. Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19 in China. Preprints2024, 2024031739. https://doi.org/10.20944/preprints202403.1739.v1
APA Style
Wang, Y., Xu, F., & Li, G. (2024). Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19 in China. Preprints. https://doi.org/10.20944/preprints202403.1739.v1
Chicago/Turabian Style
Wang, Y., Feng Xu and Gang Li. 2024 "Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19 in China" Preprints. https://doi.org/10.20944/preprints202403.1739.v1
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 uses text analysis, spatial analysis, model analysis, and other methods to analyze the operation mode, spatial distribution, and influencing factors of CGPCDPs. The conclusions are as follows: CGPCDPs initiators are mainly shopkeepers. They depend mainly on wholesale and retail shops. Service targets are mainly urban and rural communities, followed by industrial areas. 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 meso-micro scale, different built environments in developed areas of cities, villages in the city (ChengZhongCun) and rural areas show distinct distribution patterns. The MGWR regression model has a better fitting effect than OLS and GWR. The main influencing factors are population density, construction land, house price, supporting place, residence density, urban community, and road proximity.
Keywords
Community group purchasing collection and delivery points; Location selection; Mixed geographically weighted regression; Influence mechanism; Nansha District
Subject
Social Sciences, Geography, Planning and Development
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
