Internal structural attributes and external locational factors are commonly used as predictive variables in housing price models, enabling the identification of key determinants for assessing whether a property is fairly priced or represents a good investment. However, prior research has largely overlooked alternative applications of such models that could further enhance the identification of advantageous purchase opportunities. This study addresses this gap by applying lateral thinking to identify a “green zone”, thereby supporting more informed housing purchase decisions. This study investigates the impact of geographic features on housing prices, based on 229 transactions recorded between September 2023 and September 2024 in the North District of Taichung City, Taiwan, using data from the Ministry of the Interior’s real estate platform. Building upon an existing regression model that includes structural variables, such as the lot size, number of rooms, age, number of floors, availability of an elevator, and the presence of a garage, we introduced six additional geographic variables that reflect the proximity to a metro station, hospital, museum, CBD, funeral home, and clothing outlets. The revised model demonstrates improved explanatory power, with the R2 increasing from 0.756 to 0.791. Among the newly included variables, proximity to the CBD and the museum exhibit the strongest positive effects on housing prices, contributing increases of TWD 9.8834 million and TWD 6.1644 million, respectively. These effects are both statistically significant. In contrast, proximity to a metro station has a significant negative impact of – TWD 7.2272 million , a finding attributed to a boundary constraint, since only sales south of the station fall within the district, creating a data bias. Using the escape technique of lateral thinking, these results also provide practical guidance for buyers by identifying cost-effective areas located just outside the 500 m proximity zones of high-value amenities. One such example is located near the intersection of Zhongming Road and Section 1, Zhongqing Road, with price savings of at least TWD 7.36 million. A residual analysis reveals clustering in the Yizhong Business District, suggesting that other unobserved value factors may warrant future investigation.
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