The diversified innovative strategies adopted by the new retail format in urban spaces have significantly driven retail transformation and innovation. The combination of online platforms and physical stores provides a substantial advantage in market competition. This paper takes “Freshippo”, a typical representative of China’s new retail, as an example. Based on multi-source data and using tools such as GIS spatial analysis, statistical analysis, and geographical detectors, this study comprehensively examines the spatial clustering characteristics and influencing factors of Freshippo physical stores in Shanghai. The findings show that Freshippo has significantly expanded in the Shanghai fresh food market by innovatively opening various types of stores. However, there are substantial differences in the proportions of different types of stores, with 94% of the stores having online retail capabilities. Each offline store in the new retail format presents a multi-level “complementary” spatial distribution feature across the urban space, with distinctive clusters in the urban central districts, urban periphery areas, and outer suburban districts. The radiation range of logistics and distribution services exhibits characteristics of “central agglomeration and multi-point distribution”, providing residents with diverse and accurate services. Additionally, the comparison of multiple model results shows that the location selection of various types of new retail stores is significantly influenced by multiple factors, especially the nonlinear amplification effect of factor interactions on store agglomeration. These findings provide an important scientific reference for understanding the development of new retail formats and offer new ideas that promote the transformation and innovation of the retail industry, thereby achieving sustainable development.

Governmental attention towards the high-quality development of the Yellow River basin has brought new development opportunities for the hotel industry. This study aims to reveal the spatial-temporal evolution patterns and influencing factors of hotels in the Yellow River Basin from 2012 to 2022, based on economic, social, and physical geographic data of 190,000 hotels in the Yellow River flowing. With the help of a GIS technology system, the spatial-temporal evolution patterns of all hotels, star hotels, and ordinary hotels were explored, respectively. Then, the significant influencing factors of these patterns were revealed by using geographic detector and Person correlation analysis. The following conclusions were drawn: (1) the overall scale of the hotel industry in the Yellow River Basin expanded year by year, achieving rapid growth from 2016, and fluctuating around 2020 due to the impact of the novel coronavirus epidemic; the overall spatial distribution had significant regional differences, showing the structural characteristics of “southeast more, northwest less”; (2) there was a great difference in the degree of spatial autocorrelation agglomeration among prefecture-level cities, and the degree of agglomeration of both the hotel industry as a whole and general hotels decreased year by year, showing a random distribution in 2022; star hotels were always distributed randomly. Additionally, a strong synergistic correlation was shown between the number of ordinary hotels and the number of star hotels in local space; (3) overall, the development of the hotel industry was significantly affected by seven factors: structural force, macro force, ecological force, internal power, consumption power, intermediary power, and external power. There were differences in the forces acting on different types of hotels, which gives a pattern recognition in-depth.