摘要
住宅租金及其影响因素研究可为城市基础设施规划和住宅租赁市场管理提供科学参考。本文基于网络数据,构建混合地理加权回归模型探索南京市住宅租金及其影响因素的空间分异特征。结果表明:①MGWR模型相较传统计量模型对住宅租金的解释效果更优;②研究区住宅租金空间分布呈"一主三副"多中心组团模式;③商业中心、重点中小学、大学校园、城市快速路、地铁站以及铁路线分布是住宅租金的主要影响因素,且在不同区域对住宅租金的影响存在显著差异。
Residential rents and their influencing factors can provide a scientific reference for urban infrastructure planning and residential leasing market management.Based on network data,this paper constructs a hybrid geographic weighted regression model to explore the spatial differentiation characteristics of residential rents and their influencing factors in Nanjing.The results show that:①MGWR model has better interpretation effect on residential rent than traditional measurement model;②the spatial distribution of residential rent in the study area is "one main and three pairs" multi-center group mode;③The distribution of expressways,subway stations and railway lines is the main influencing factor of residential rents,and there are significant differences in the impact of residential rents in different regions.
作者
张世伟
王琳
鲁凤
ZHANG Shiwei;WANG Lin;LU Feng
出处
《现代城市研究》
CSSCI
2019年第11期97-103,共7页
Modern Urban Research
基金
国家自然科学基金项目“江苏沿海地区生态足迹空间模拟及其与社会经济耦合关系研究”(41301646)
关键词
住宅租金
混合地理加权回归
分异特征
影响因素
南京
housing rent
mixed geographically weighted regression
differential characteristics
influencing factors
spatial differentiation
Nanjing
