軌道交通站的普及對中國城市居民的居住環境產生了巨大的改變，但軌道交通站點對條件不同住宅的價格影響差異在過往鮮有被關注。因此本研究選取中國福州市的住宅樣本作爲研究對象，通過綫性回歸模型，以及計量經濟學中的交互作用概念，對過往的研究空白進行補充。並以空間回歸模型對軌道交通站點的房價影響差異進行空間異質性的分析。研究發現，軌道交通站點對於不同屬性住宅價格的影響，具有普遍性的差異，並且該房價影響差異還存在著顯著的地理空間分宜。
本研究使用了中國福州市2021年三月份住宅交易信息的斷面數據作爲研究資料。這些交易信息數據包含了因變數：住宅的成交價格；自變數：住宅的自身屬性變數，住宅的區位屬性變數以及住宅的鄰里屬性變數。而後研究通過空間句法模型，核密度估算模型等研究方法來補充獲取研究所需的其他自變數。然後研究再通過特徵價格模型（Hedonic Model），交互回歸模型（Interactive Regression），空間自相關回歸模型（Spatial Autocorrelation Models）和地理加權回歸模型（Geographically Weighted Regression）等方法，來分析研究所關注研究變數、交互變數的顯著性及其空間分宜規律。
通過分析，本研究發現軌道交通站點便利性對不同自身屬性住宅、不同區位屬性住宅以及不同鄰里屬性住宅的房價影響程度並不相同。在以住宅性質類別和營建商類別為代表的自身屬性差異中，軌道交通站點對含公租房的住宅社區以及福建省營建商開發的住宅社區，有著房價影響的差異性。在以住宅所處路網形態特徵為代表的區位屬性差異中，軌道交通站點對路網鏈接能較好路段的住宅，具有較小的房價擡升作用。在以住宅周邊最近三甲醫院的空間直綫距離爲代表的鄰里屬性差異中，軌道交通站點對醫院服務便利住宅的房價擡升能力較小。
除了首次嘗試探索的房價影響因素外，本研究在房價醫療鄰里因素中的發現結論與過往相同主題研究的結論存在部分相同，但本研究更深入地揭示了軌道交通站點對於不同屬性條件住宅的房價影響差異及其空間分異。本研究在空間維度上的研究發現結論可以為城市購房者在思考捷運需求時提供更準確的效益參考；也可以為政府相關規劃負責人員，在規劃城市捷運站點或制定政策時提供更多公平性的建議；同時還可以為科研學者提供方法論的啓示。

In past studies, scholars often used hedonic model to explore the impact of rail station factors on real estate prices. However, these studies have rarely focused on the differential impacts of rail stations on real estate prices with different attributes. Therefore, this study introduces the concept of "interaction" from econometrics to discuss this differential impact on real estate prices, and uses spatial autocorrelation models (SAR, SEM) or geographically weighted regression (GWR) to examine the spatial heterogeneity of differential impact.
This study selects Fuzhou City in mainland China as the research area. In addition to rail station factors, this study also selects three factors influencing housing prices: property attributes, location attributes, and neighborhood attributes, as additional research factors. The study analyzes how rail station factors affect real estate prices with different attributes. The results indicate that rail stations have a significant differential impact on the real estate prices with different attributes. Furthermore, the differences can be confirmed by various spatial regression models.
The conclusions of this study can provide more accurate benefit references for homebuyers considering transit demand, offer more equitable insights for government planners in planning transit stations or formulating policies, and provide methodological inspiration for researchers and scholars.

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