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The Spatially Heterogeneous Influence of Multiple Factors on Housing Prices Around Subway Stations: An MGWR-Based Empirical Analysis in Chaoyang District, Beijing
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Shiwei HU1, Chang FU1, Tianfu YU2, Kechao CAI1, Ziyi LI2
Urban Rapid Rail Transit | 2026, 39(3) : 47 - 53
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Urban Rapid Rail Transit | 2026, 39(3): 47-53
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The Spatially Heterogeneous Influence of Multiple Factors on Housing Prices Around Subway Stations: An MGWR-Based Empirical Analysis in Chaoyang District, Beijing
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Shiwei HU1, Chang FU1, Tianfu YU2, Kechao CAI1, Ziyi LI2
Affiliations
  • 1.Henan Railway Construction Investment Comprehensive Development Group Co., Ltd., Zhengzhou 454002
  • 2.School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044
doi: 10.3969/j.issn.1672-6073.2026.03.006
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Based on a case study of Beijing's Chaoyang District, this research employs a multiscale geographically weighted regression (MGWR) model to systematically examine the spatial heterogeneity of housing prices around subway stations and the mechanisms through which multiple factors affect them. Using second-hand housing listing data from Lianjia in 2023, the study incorporates both internal estate characteristics (e.g., average housing age, property fees, greening rate, and plot ratio) and external location-based attributes (e.g., proximity to subway stations, bus stops, commercial centers, schools, hospitals, and parks) to construct the MGWR model, which is compared against ordinary least squares (OLS) model and the geographically weighted regression (GWR) model. The results show that the MGWR model achieves the highest goodness-of-fit (R2=0.691) and effectively captures the scale-varying effects of different factors. Distance to subway stations exhibits a significant negative correlation with housing prices, with a stronger effect in peripheral areas than in the urban core. Proximity to top-tier schools shows a heterogeneous pattern, positive in clustered areas but negative in peripheral zones, reflecting a localized saturation effect of educational resources. The influences of commercial, park, and hospital accessibility also demonstrate notable spatial variations, highlighting the complex interplay and contextual dominance of transportation, education, commerce, ecology, and medical services in the capitalization of housing prices. This study provides a multiscale analytical framework for understanding the formation mechanisms of housing prices in the context of urban rail transit, offering valuable insights for spatial governance and public service allocation.

subway station  /  housing prices  /  multiscale geographically weighted regression (MGWR)  /  ordinary least squares (OLS) model  /  spatial heterogeneity
胡世伟, 付昌, 于天夫, 蔡科潮, 李梓祎. 多因素对地铁站周边住宅价格的空间异质性影响——基于MGWR的北京市朝阳区实证分析. 都市快轨交通, 2026 , 39 (3) : 47 -53 . DOI: 10.3969/j.issn.1672-6073.2026.03.006
Shiwei HU, Chang FU, Tianfu YU, Kechao CAI, Ziyi LI. The Spatially Heterogeneous Influence of Multiple Factors on Housing Prices Around Subway Stations: An MGWR-Based Empirical Analysis in Chaoyang District, Beijing[J]. Urban Rapid Rail Transit, 2026 , 39 (3) : 47 -53 . DOI: 10.3969/j.issn.1672-6073.2026.03.006
Year 2026 volume 39 Issue 3
144
36
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doi: 10.3969/j.issn.1672-6073.2026.03.006
  • Receive Date:2025-07-09
  • Online Date:2026-09-20
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  • Received:2025-07-09
  • Revised:2025-11-21
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    1.Henan Railway Construction Investment Comprehensive Development Group Co., Ltd., Zhengzhou 454002
    2.School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044
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表12种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
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红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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