Aim: This study aims to identify the spatial pattern and examine the spatially varying relationships between the distribution of shopping centers and their determining factors in the city of Yazd.
Materials & Methods: The research is based on spatial data analysis methods. Data related to the location of shopping centers, land use type, road network density, access to public transportation, population density, and tourist attractions were collected. To identify the local effects of factors affecting the spatial distribution of shopping centers, exploratory spatial analyses and spatial modeling (GWPR) and (GPR models) were used.
Finding: The results show that the spatial distribution of shopping centers is clustered. The GWPR model performed better than the GPR, which shows that the effect of factors affecting different distributions varies in different regions. Factors such as commercial, administrative, residential uses, density of bus stops, and tourist attractions have a positive effect. In contrast, green space and population density at different levels of regions have a negative effect.
Conclusion: This study highlights the complex spatial relationships between determining factors and the distribution of shopping. The findings underscore the importance of employing spatial modeling approaches to analyze distribution patterns. Understanding the spatial determinants and their localized effects on site selection for shopping centers can significantly inform strategic decision-making in land use planning, zoning regulations, and infrastructure development.
Innovation: This study advances the analysis by employing more sophisticated spatial modeling methods, which provide greater accuracy and detail in revealing the local effects of influential factors. The innovation in applying these models enhances regional sensitivity in analysis and can guide effective policymaking. The findings can assist city managers in formulating development policies based on actual spatial and regional realities, ultimately supporting more effective urban management that responds to demographic and economic needs.