| 新零售背景下连锁店区位选择及其空间关联特征 |
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| 引用本文： | 张英浩,汪明峰.新零售背景下连锁店区位选择及其空间关联特征[J].热带地理,2021,41(3):573-583. |
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| 作者姓名： | 张英浩 汪明峰 |
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| 作者单位： | 1.华东师范大学 中国现代城市研究中心，上海 200062;2.华东师范大学 城市与区域科学学院，上海 200241 |
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| 基金项目： | 国家社会科学基金重点项目(19AZD007);上海市教育委员会科研创新计划重大项目(2021-01-07-00-08-E00130) |
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| 摘 要： | 零售活动的空间关系研究是城市地理学研究的一个热点问题。以上海市内环地区的星巴克、COSTA和瑞幸咖啡三家咖啡连锁公司的门店为研究对象，综合运用多种空间统计方法和实地调研分析三者之间的空间关联特征。结果表明：1）无论是传统零售还是新零售模式下的咖啡门店，其空间分布均大致表现出靠近消费市场的空间导向特征；2）星巴克门店的空间集聚程度最强，瑞幸咖啡门店空间集聚程度最弱；3）利用一种新的多元空间统计方法计算后发现，无论是传统咖啡零售星巴克和COSTA的门店，还是星巴克与新零售瑞幸咖啡的门店，均呈现显著相互吸引的空间关联特征，但其形成机制存在差异；4）星巴克与COSTA常常成对出现在商圈或商务区中心位置，而后进入市场的瑞幸咖啡门店常常位于“非中心”位置。新零售模式可以通过互联网平台、大数据分析等技术重构交易基础逻辑，改变传统零售依赖门店的成本结构模型；同时，新零售模式高度重视用户线上体验，在一定程度上弱化了实体区位的重要性。因此，在进行城市规划，特别是商业区规划时，应重视新零售模式对区位选择的影响，重视互联网与大数据在区位决策中的作用，挖掘传统弱区位地区或地段的发展可能性，提高城市土地利用效率。
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| 关 键 词： | 零售业态 空间关系 新零售 多元空间分析法 连锁店 |
| 收稿时间： | 2020-11-23 |
Location Selection and Correlation Characteristics of Chain Stores against the Background of New Retail |
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| Yinghao Zhang,Mingfeng Wang.Location Selection and Correlation Characteristics of Chain Stores against the Background of New Retail[J].Tropical Geography,2021,41(3):573-583. |
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| Authors: | Yinghao Zhang Mingfeng Wang |
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| Institution: | 1.Center for Modern Chinese City Studies, East China Normal University, Shanghai 200062, China;2.School of Urban and Regional Science, East China Normal University, Shanghai 200241, China |
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| Abstract: | Research on the spatial relationship of retail activities is a hot topic in urban geography. With the continuous upgrade of Internet technology, the development mode of business has evolved from the traditional retail model into the e-commerce model, and now the new retail model. While the new retail model influences the locational decision-making behavior of enterprises, it also affects the intrinsic mechanism of attraction and avoidance among retail stores, which in turn affects the spatial association relationship of commercial retail. In such a context, we take the Starbucks, COSTA, and Luckin Coffee stores in Shanghai's inner ring as our research objects, and use a variety of spatial statistical methods and field research to analyze the spatial correlation characteristics among the three. The results show that, first, the spatial distribution of coffee stores under both traditional and new retail models generally exhibit the spatially oriented characteristics of being close to the consumer market. Therefore, it can be indirectly inferred that although Luckin Coffee, which is characterized by new retail, can create "infinite space" to meet consumers' consumption needs in different spaces by virtue of its own Internet development advantage, it remains difficult to completely break away from the spatial orientation of the offline consumption market. Second, in terms of spatial agglomeration, Starbucks' high sensitivity to specific consumer groups and its sales strategy of providing a comfortable environment have led the business to open stores in dense proximity in locations with high consumption potential, thus contributing to its strongest spatial agglomeration. Luckin Coffee, by contrast, has a certain degree of flexibility in choosing store locations due to its independent instant delivery service, and in order to occupy a wider market as soon as possible, it chooses store locations in favor of uniform coverage, resulting in the weakest degree of spatial agglomeration. Third, based on multivariate spatial statistics, it can be seen that Starbucks, COSTA, and Luckin coffee stores all exhibit positive spatial relationship characteristics in the two corresponding spatial relationships. Among them, traditional coffee retailers Starbucks and COSTA show a more obvious spatial relationship of mutual attraction, indicating that both can increase their market shares by converting the fierce price competition between them into an attraction drive to increase their total profits. At the same time, the stores of traditional retailer Starbucks and new retailer Luckin Coffee also show a significant spatial relationship of mutual attraction in space, indicating that the market share effect dominates. Finally, micro-location analysis reveals that Starbucks and COSTA stores have a stronger mutual attraction relationship and often appear in pairs in the center of shopping districts or business areas, while Luckin Coffee stores are often located in "non-central" areas. As a representative of new retail, Luckin Coffee can make up for its location disadvantage to a certain extent by virtue of its mobile application online service and instant delivery service. The store can also utilize its Internet platform, big data analysis, and other technical advantages, so that it can combine its own product positioning characteristics when choosing store locations, and accurately find potential store locations and opening models. Therefore, when carrying out urban planning, especially the planning of commercial areas, attention should be paid to the impact of the new retail model on location selection, the role of the Internet, and big data in location decision making. The development possibilities of traditionally weaker locations should be explored, and the efficiency of urban land use should be improved. |
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| Keywords: | retail format spatial relationship new retail multiple spatial analysis chain stores |
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