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基于手机APP的居民线上行为空间分布特征研究——以南京中心城区为例
引用本文:管若尘,甄峰,席广亮,李智轩.基于手机APP的居民线上行为空间分布特征研究——以南京中心城区为例[J].人文地理,2022,37(5):89-96.
作者姓名:管若尘  甄峰  席广亮  李智轩
作者单位:1. 南京大学 建筑与城市规划学院, 南京 210093;
2. 江苏省智慧城市设计仿真与可视化技术工程实验室, 南京 210093
基金项目:国家社会科学重点基金项目(20AZD040)
摘    要:智慧社会时代,线上服务逐渐成为大众日常生活的重要组成,深刻影响城市居民的生活、工作及出行方式。论文基于手机信令数据等多源数据,分析了不同年龄段居民在居住区空间基础上的手机 APP使用特征,进而总结了休闲娱乐、网络购物及日常服务三类 APP的使用强度分布特征。结果表明:①休闲娱乐、网络购物与生活服务等成为居民高频使用 APP类型,不同年龄段对 APP类型存在偏好差异;②三类APP 高使用强度集聚区与城市中心分布基本吻合,主要分布在商业集聚区、大型居住中心以及大学、景点等周边小区,遵循技术扩散假说,不符合效率假说;③不同年龄段使用强度城市分布热点存在差异,另保障房类型居住区其使用三类APP使用强度偏低。

关 键 词:手机  APP  线上行为  使用率  使用强度  南京市  
收稿时间:2021-05-14

RESEARCH ON THE SPATIAL DISTRIBUTION CHARACTERISTICS OF RESIDENTS' ONLINE BEHAVIOR BASED ON MOBILE APP: A CASE STUDY OF NANJING CENTRAL BLOCK
GUAN Ruo-chen,ZHEN Feng,XI Guang-liang,LI Zhi-xuan.RESEARCH ON THE SPATIAL DISTRIBUTION CHARACTERISTICS OF RESIDENTS' ONLINE BEHAVIOR BASED ON MOBILE APP: A CASE STUDY OF NANJING CENTRAL BLOCK[J].Human Geography,2022,37(5):89-96.
Authors:GUAN Ruo-chen  ZHEN Feng  XI Guang-liang  LI Zhi-xuan
Institution:1. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China;
2. Provincial Engineering Laboratory of Smart City Design Simulation & Visualization, Nanjing 210093, China
Abstract:In the era of smart society, online services have gradually become an important part of the daily life of the general public, which profoundly affects the life, work and travel methods of urban residents. Mobile Internet applications (APPs) have gradually become an important part of residents' daily life due to their convenience, ease of use and ultra-high coverage, providing residents with rich and diverse functional experiences for their work, life and travel modes. Based on mobile phone signaling data and other multi-source data, the paper analyzes the characteristics of mobile phone APP use by residents of different age groups, and then summarizes the use intensity distribution characteristics of the three types of APP for leisure and entertainment, online shopping and daily services. The results show that: 1) Recreation and entertainment, online shopping and life services have become the types of residents who frequently use APPs, and different age groups have different preferences for the types of APPs. 2) The high-use intensity clusters of the three types of APPs are basically consistent with the distribution of the city center, mainly distributed in Commercial agglomeration areas, large residential centers, universities, scenic spots and other surrounding communities follow the innovation diffusion hypothesis, but do not conform to the efficiency hypothesis; 3) There are differences in the urban distribution hotspots of different age groups, and they are reflected in the types of special residential areas such as affordable housing.
Keywords:mobile app  online behavior  usage rate  intensity of use  Nanjing  
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