Spatial analysis and optimization of self-pickup points of a new retail model in the Post-Epidemic Era: the case of Community-Group-Buying in Xi'an City.

IF 3.2 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computational urban science Pub Date : 2023-01-01 DOI:10.1007/s43762-023-00089-8
Zhe Lin, Gang Li, Muhammad Sajid Mehmood, Qifan Nie, Ziwan Zheng
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引用次数: 2

Abstract

The Community-Group-Buying Points (CGBPs) flourished during COVID-19, safeguarding the daily lives of community residents in community lockdowns, and continuing to serve as a popular daily shopping channel in the Post-Epidemic Era with its advantages of low price, convenience and neighborhood trust. These CGBPs are allocated on location preferences however spatial distribution is not equal. Therefore, in this study, we used point of interest (POI) data of 2,433 CGBPs to analyze spatial distribution, operation mode and accessibility of CGBPs in Xi'an city, China as well as proposed the location optimization model. The results showed that the CGBPs were spatially distributed as clusters at α = 0.01 (Moran's I = 0.44). The CGBPs operation mode was divided into preparation, marketing, transportation, and self-pickup. Further CGBPs were mainly operating in the form of joint ventures, and the relying targets presented the characteristic of 'convenience store-based and multi-type coexistence'. Influenced by urban planning, land use, and cultural relics protection regulations, they showed an elliptic distribution pattern with a small oblateness, and the density showed a low-high-low circular distribution pattern from the Palace of Tang Dynasty outwards. Furthermore, the number of communities, population density, GDP, and housing type were important driving factors of the spatial pattern of CGBPs. Finally, to maximize attendance, it was suggested to add 248 new CGBPs, retain 394 existing CGBPs, and replace the remaining CGBPs with farmers' markets, mobile vendors, and supermarkets. The findings of this study would be beneficial to CGB companies in increasing the efficiency of self-pick-up facilities, to city planners in improving urban community-life cycle planning, and to policymakers in formulating relevant policies to balance the interests of stakeholders: CGB enterprises, residents, and vendors.

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后疫情时代新零售模式自提点空间分析与优化——以西安市社区团购为例
新冠肺炎疫情期间,社区团购点蓬勃发展,保障了社区封锁期间社区居民的日常生活,并以价格低廉、便捷、邻里信任等优势,继续成为后疫情时代流行的日常购物渠道。这些CGBPs是按地点偏好分配的,但空间分布并不相等。因此,本研究利用西安市2433个CGBPs的兴趣点(POI)数据,分析了西安市CGBPs的空间分布、运营模式和可达性,并提出了CGBPs的区位优化模型。结果表明:CGBPs在空间上呈簇状分布,α = 0.01 (Moran’s I = 0.44);CGBPs运营模式分为筹备、营销、运输、自提。CGBPs以合资经营为主,依托对象呈现“便利店为主、多类型并存”的特点。受城市规划、土地利用、文物保护规定等因素影响,其分布呈椭圆形,扁度偏小,密度由唐宫向外呈低-高-低圆形分布。此外,社区数量、人口密度、GDP和住房类型是CGBPs空间格局的重要驱动因素。最后,为了最大化上座率,建议新增248个CGBPs,保留现有的394个CGBPs,并将剩余的CGBPs替换为农贸市场、流动摊贩和超市。本研究结果可为CGB企业提高自助提货设施效率、城市规划者改善城市社区生命周期规划、政策制定者制定相关政策以平衡CGB企业、居民和供应商三方利益提供参考。
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