This research focuses on real estate values in central Hanoi, with the objective of analyzing factors influencing real estate prices, with particular emphasis on locational characteristics, for the case of Hanoi’s central districts. A geographically weighted regression (GW)R model is employed to address the limitations of traditional Hedonic Pricing Models (HPM), based on data from 1,545 properties across 12 central districts of Hanoi during the period from November 2024 to March 2025. The study evaluates the impact of 7 accessibility variables: distance to hospitals, parks, schools, universities, shopping centers, administrative offices at various levels, and the city center. Results show that the relationship between distance to public amenities and property prices varies significantly according to geographic location - a characteristic not reflected in traditional HPM models. Notably, many variables that lack statistical significance in the HPM model show differentiated impacts at specific locations in the GWR model, with higher coefficients of determination, demonstrating better explanatory power for real estate price variations. The research has demonstrated spatial heterogeneity in the relationships between valuation variables, indicating that location characteristics and spatial variation have not been adequately considered in current valuation methods in Vietnam. These findings not only address the limitations of HPM models but also provide important reference perspectives for policymakers regarding the significance of spatial factors.
Son et al. (Tue,) studied this question.