AbstractRetail clusters lead to the establishment of cluster hierarchies and significantly influence the neighborhood economy and job market, mobility patterns, land-use change, and residents’ quality of life. The prosperity or decline of retail clusters depends on the volume of retail sales. Few studies have investigated how commercial environments and agglomeration change retail sales while considering cluster hierarchies. This study compared the effects of commercial environments and agglomeration of retail stores on sales across retail cluster hierarchies at the district-level, neighborhood-level, and traditional market-level retail clusters in Seoul in 2019. Multilevel regression models were utilized to identify the effects of retail type-level and retail cluster-level factors on retail sales with diverse geographical data. The empirical models confirmed that commercial environments and agglomeration had an uneven effect on the variations in retail sales across different hierarchies. Specifically, dense and mixed land use, a higher proportion of the floating population, and higher land prices were significantly correlated with higher retail sales. The positive or negative effect of the proximity of small retail stores to large-scale retail stores and the density and mixture of retail stores on retail sales varied with the local context of the retail cluster hierarchies. The findings of this study show that considering the local contexts and features of retail cluster hierarchies is crucial for designing effective policies to ensure that retail sectors prosper across their cluster hierarchies.Practical ApplicationsThis study focuses on the effect of commercial environments and agglomeration on local retail sales, considering cluster hierarchies in Korea in the year 2019. The key findings from empirical models suggest a few insightful implications for the practical community. First, dense land development positively affected the local retail sales. Thus, strategies for land-use development should be harmonious with spatial patterns of retail sales. Second, a higher floating population has been beneficial for retail prosperity. Therefore, the pedestrian-friendly urban design would effectively support retail stores. Third, the presence of public transit is not directly linked with the better economic performance of retailers. Enhancing the accessibility of public transit improves higher retail sales. Fourth, large retailers were not always competitors of small- and medium-sized retail stores. The shopping behavior of large retailers and small, local retail stores within specific local contexts would determine the variation of neighborhood retail sales. Finally, cooperation among relevant policy authorities needs the prosperity of retail sectors because diverse commercial environments and contexts of retail agglomeration determine retail sales.