Document Type : Original Article
Extended Abstract
1. Introduction
The expansion of shopping centers in urban areas plays a significant role in meeting the economic and welfare needs of a growing population. However, empirical studies in Iran indicate an uneven and spatially concentrated distribution of these centers. In the city of Yazd—a historic and cultural fabric of the country—the distribution of shopping centers is imbalanced. Alongside its heritage attractions, numerous modern shopping centers have been constructed, contributing substantially to the urban structure and regional economy. Investigating the spatial patterns and influential factors behind this distribution is especially important, as the location of shopping centers directly affects the movement of residents and tourists. Spatial analyses such as spatial regression and clustering models reveal that various factors—including population density, transportation accessibility, infrastructural facilities, and economic support—contribute to the concentration of shopping centers. International research also emphasizes urban planning as well as socio-economic issues as key determinants in the location and spatial distribution of these centers. The aim of this study is to identify spatial patterns and explore the relationships among variables affecting the distribution of shopping centers in Yazd, in order to provide strategies for promoting a more equitable spatial arrangement.
2. Materials and Methods
The study is applied in nature and is based on spatial data analysis. Data collected include the location of shopping centers, land use types, road density, access to public transportation, population distribution, and tourism attractions. To identify the impact of local factors on the spatial distribution of shopping centers, exploratory analyses and spatial modeling methods were employed, including Geographically Weighted Poisson Regression (GWPR) and Global Poisson Regression (GPR). The city of Yazd, located at 31°53′50″ N latitude and 54°22′3″ E longitude, is renowned as a symbol of traditional architecture and a UNESCO World Heritage site, encompassing both historic bazaars and modern shopping centers. The statistical population consists of urban blocks containing polygonal, point, and linear data. To analyze the data, a grid with dimensions of 500×500 meters was designed to ensure that all data were gathered within a consistent and defined spatial unit, minimizing issues related to the modifiable areal unit problem (MAUP).
3. Results and Discussion
The results indicate that the spatial distribution of shopping centers in Yazd exhibits clustering and spatial correlation. The Geographically Weighted Panel Regression (GWPR) model demonstrates superior performance compared to the Global Poisson Regression (GPR), which suggests that the influence of key factors varies across different regions. Factors such as commercial and residential land uses exert the most significant effects, particularly in Areas 2, 3, and the historical zone, where they largely determine the distribution of retail centers. Conversely, green spaces have a negative impact, consistently showing a negative coefficient across all regions. Population density and the road network also negatively influence the distribution; however, their effects are most pronounced in Areas 1, 4, and the historical zone. Tourism attractions and access to public transportation stations positively affect the dispersion of shopping centers, especially in the historic and central districts of Yazd.
4. Conclusions
This research demonstrates that the relationships between spatial determinants and the distribution of retail centers in Yazd exhibit complex and multidimensional patterns. The application of spatial modeling techniques, particularly the Geographically Weighted Panel Regression (GWPR) model, proves critical in analyzing these spatial patterns, given its capacity to simultaneously assess the localized and heterogeneous effects of various influencing factors. A comprehensive understanding of spatial drivers—such as active land uses, accessibility levels, tourism attractions, and transportation infrastructure—serves as a strategic guide for land use planning and infrastructural development. Findings indicate that the development of retail centers should be concentrated in active zones with optimal access, while indiscriminate expansion in areas constrained by inadequate infrastructure should be avoided. In this context, spatial analysis and modeling play a pivotal role in policy formulation and the management of retail facility siting, with the mapping of location-allocation and overlay analyses providing practical and strategic insights for urban planners, policymakers, and investors aiming to promote sustainable and balanced urban growth. Furthermore, future research should explore factors such as consumer behavior, digital transformation, and economic and social impacts, while comparative studies across different urban contexts may enhance the generalizability of findings and deepen understanding of spatial and cultural variations influencing retail location patterns.
5. Aknowledgmant & Funding
The manuscript did not receive a grant from any organization.
6. Conflict of Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
