| 基于网络大数据的城市轨道交通时空溢价效应研究 |
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| 引用本文： | 崔娜娜,夏海山,张纯,古恒宇.基于网络大数据的城市轨道交通时空溢价效应研究[J].地理与地理信息科学,2022,38(1):133-137. |
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| 作者姓名： | 崔娜娜 夏海山 张纯 古恒宇 |
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| 作者单位： | 北京交通大学建筑与艺术学院,北京 100044;香港中文大学地理与资源管理学系,香港999077 |
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| 基金项目： | 国家自然科学基金项目“基于复杂适应系统的轨道交通站城协同机理与预测方法研究”(52078027)。 |
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| 摘 要： | 城市轨道交通是大城市缓解交通拥堵的重要公共交通方式,其对周边住宅的时空溢价效应一直是城市研究热点,但传统研究存在样本量少、数据时间跨度短、忽视预期效应等问题。该文利用网络爬虫获取住宅交易大数据,以天津市地铁6号线为例,采用直接比较法、特征价格模型测度城市轨道交通对沿线住宅价格的时空溢价效应,结果表明:1)空间尺度上,轨道交通对沿线住宅价格具有显著溢价效应,但溢价程度并非随着距轨道交通站点距离的增加而下降,而是呈现先上升后下降的“倒U形”趋势。其中,500~1000 m的影响区溢价幅度最大,溢价率高达17.2%。2)时间尺度上,轨道交通对住宅价格的影响具有超前效应,在施工期溢价就已显现,且在首个开通运营年达到峰值,说明住宅价格对开通运营这一“标志性”事件反应强烈。3)受心理预期效应的影响,轨道交通全线开通运营的溢价效应明显低于首个开通运营年的溢价效应。研究结论可为公共交通导向模式下城市综合开发和轨道交通的“溢价回收”策略提供决策支持。
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| 关 键 词： | 大数据 轨道交通 时空溢价 特征价格模型 |
Research on the Spatio-temporal Premium Effect of Urban Rail Transit Based on Big Data |
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| CUI Na-na,XIA Hai-shan,ZHANG Chun,GU Heng-yu.Research on the Spatio-temporal Premium Effect of Urban Rail Transit Based on Big Data[J].Geography and Geo-Information Science,2022,38(1):133-137. |
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| Authors: | CUI Na-na XIA Hai-shan ZHANG Chun GU Heng-yu |
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| Institution: | (School of Architecture and Design,Beijing Jiaotong University,Beijing 100044;Department of Geography and Resource Management,The Chinese University of Hong Kong,Hong Kong 999077,China) |
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| Abstract: | The premium effect of urban rail transit on surrounding residential buildings has always been a hotspot in the urban research.Traditional research on spatio-temporal premium effect of urban rail transit has some problems,such as small sample size,short time span of data,and neglect of expected effects.Taking Tianjin Metro Line 6 as an example,using web crawler housing transaction big data and employing direct comparison and hedonic price model,this paper measures the spatio-temporal premium effect of urban rail transit on the housing prices.It is found as follows.1)Rail transit has a significant positive effect on housing prices in terms of spatial effects,but the premium does not decrease as the distance to the rail transit station increases,but shows an"inverted U-shaped"trend that first rises and then falls.The 500~1000 m influence area has the largest premium,with a premium rate of 17.2%.2)The premium of rail transit on housing prices has a leading effect in terms of temporal effects,which has already appeared during the construction period of rail transit,and reached its peak in the first year of operation,indicating that housing prices have responded strongly to the"landmark"event of opening operation.3)Due to the effect of psychological expectations,the premium effect of the opening operation of the entire rail transit is significantly lower than that in the first year of operation.The research conclusions provide decision support for the urban comprehensive development under the TOD(transit-oriented development)mode and the"premium recovery"strategy of urban rail transit. |
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| Keywords: | big data rail transit spatio-temporal premium hedonic price model |
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