Research on the spatial divergence characteristics and multi-scale influence of innovative industries and housing prices–the case of knowledge-intensive service industries in Guangzhou

The impact of industries on housing prices has been a hot topic in urban geography research. The influence of knowledge-intensive business services (KIBS), as a representative of innovative industries, on surrounding housing prices has been understudied. This paper employs Spearman’s correlation analysis, Hedonic Price Model (HPM), Geographically Weighted Regression (GWR) and Optimal Parameters-based Geographical Detector (OPGD) to analyze the impact of Guangzhou’s knowledge-intensive industries on surrounding housing prices and spatial differentiation effects from multiple scales. The results indicate a significant spatial agglomeration and correlation between the two. From a meso-perspective, there is a critical value between industrial agglomeration and housing prices; beyond this threshold, central and peripheral areas begin to show negative correlation coefficients. Microscopically, there is a displacement effect between industrial agglomeration and housing prices, with the peak distance between the two exceeding 500–1000 m in the core urban area (Zhujiang New City) and even in the most industrially dense areas of the peripheral region (Nansha District), which also appear in the core urban area (Nansha District). In the core urban area (Zhujiang New City), the peak distance exceeds 500–1000 m, and in the peripheral urban area (Nansha District), the most concentrated industrial area’s lowest housing prices phenomenon has emerged.