刘伯初 周楷宸 雷安妮 王玉霞 王兰

LIU Bochu, ZHOU Kaichen, LEI An’ni, WANG Yuxia, WANG Lan

外卖餐食配送服务的过度使用可能对公众健康和城市活力造成负面影响，明确外卖餐食消费的环境和人口影响因素对于制定减轻外卖餐食过度依赖的空间政策至关重要。本文以上海市虹口区为例，结合网络食品零售、建成环境和人口属性等多源数据，探究空间和人口特征对外卖餐食消费的影响。通过拓展两步移动搜索法，推导出格网单元的外卖餐食消费频次，并揭示其空间分布特征。在此基础上，运用空间计量模型探究食品零售环境、建成环境、人口构成等因素对外卖餐食消费的影响。研究发现，餐馆数量、道路密度、居民和就业者人数对外卖餐食消费总频次具有正向影响；人均外卖餐食消费频次随着1 200 m范围内生鲜食品零售店数量、500 m范围内餐馆数量、高龄和中高收入人群比例的增加显著下降，但随着15 分钟生活圈范围内餐馆数量和就业者占比的增加而显著升高。本文最后探讨了案例实证对城市规划干预食品消费行为的启示和未来研究方向。

The excessive use of online meal delivery services may negatively impact population health and urban vitality. Before developing urban policies to reduce undue dependence on meal delivery services, it is crucial to identify the environmental and demographic factors affecting their usage. This paper selects Hongkou District, Shanghai, for a case study. It integrates data from multiple sources, such as online food consumption, built environment, and demographic characteristics, to explore the determinants of online meal delivery service usage. By expanding the two-step floating catchment area (2SFCA) method, we estimate the frequency of online meal delivery use and demonstrated the spatial distribution of online meal delivery usage. Subsequently, spatial econometric models are employed to examine how food retail environment, built environment, and socio-demographics influence online meal consumption. It is found that the number of restaurants, road density, and the number of usual residents and employees positively impact the total frequency of online meal consumption. The per capita frequency of online meal consumption significantly decreases with an increase in the number of grocery retailers within 1 200 m, restaurants within the neighborhood, and the proportion of older and middle-to-high income residents but increases significantly with a rising number of restaurants within the 15-minute life circle and the proportion of employees. Ultimately, this paper discusses the implications of this case study for urban planning interventions on food consumption and directions for future research.

刘伯初，同济大学建筑与城市规划学院，高密度人居环境生态与节能教育部重点实验室（同济大学），助理教授，硕士生导师。liubochu@tongji.edu.cn
周楷宸，同济大学建筑与城市规划学院，博士研究生。1730042@tongji.edu.cn
雷安妮，同济大学建筑与城市规划学院，博士研究生。2310322@tongji.edu.cn
王玉霞，华东师范大学地理科学学院，地理信息科学教育部重点实验室，副教授，硕士生导师。yxwang@geo.ecnu.edu.cn
王兰（通信作者），同济大学建筑与城市规划学院，自然资源部国土空间智能规划技术重点实验室，长聘教授，博士生导师。wanglan@tongji.edu.cn

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