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地铁增值作用相关研究通常假设不同地铁站周围具有相同的增值作用规律,但实际不然。本文以深圳地铁为试验对象,提出利用地理加权回归构建局部特征价格模型,揭示了地铁增值作用的空间异质性,实现了地铁增值作用空间变化的定量分析,提高了地铁增值作用的量化评估质量。这为地铁沿线房地产价格评估、地铁联合建设方案编制乃至地铁增值收益分享机制构建等提供了新的工作思路和技术方法。未来在城市大数据的支撑下,基于地理加权回归的局部特征价格模型可辅助人们深入开展地铁增值作用空间异质性的内在机理研究,对于城市地铁的智慧管理和科学决策具有重要的启示意义。
Substantial research on the role of metro value added usually assumes the same value-added law around different metro stations, but it is not. This paper takes Shenzhen Subway as the test object, proposes the use of geographical weighted regression to build local feature price model, reveals the spatial heterogeneity of metro value added, realizes the quantitative analysis of the spatial change of metro added value and improves the quality of quantitative evaluation of metro added value . This provides a new work train of thought and technical method for the assessment of real estate prices along the MTRC, the joint construction plan of the MTRC and the construction of the sharing mechanism of metro value added revenue. In the future, under the support of urban big data, the local feature price model based on geo-weighted regression can help people study the intrinsic mechanism of the spatial heterogeneity of metro value-added deeply and has important implications for the wisdom management and scientific decision-making of urban metro.