Zonal variation in commercial function–human activity relationships around North Ring Road Station, Changchun: Evidence from sampled weekday and weekend conditions

Commercial concentration does not necessarily correspond to observed human activity in metro station areas, and temporal differences may occur through localized changes even when the overall activity structure remains stable. Identifying such internal restructuring is important because aggregate station-wide measures may overlook how specific commercial functions relate differently to human activity across spatial zones. North Ring Road Station in Changchun is examined within 800 m of its two operational entrances. A total of 951 commercial and service points of interest in seven categories are combined with Baidu-derived human activity intensity from one sampled weekday and one sampled weekend day. Data are integrated into 30 m analytical grids and divided into Core (0–300 m), Transitional (300–500 m), and Peripheral (500–800 m) zones. A standardized relative positional change indicator (ΔZ) tracks changes in each grid’s relative position, and functional associations are assessed using Spearman correlations and spatial block bootstrap. The overall commercial function–activity relationship remains broadly similar across the two sampled days, whereas clearer internal differences emerge. Mean ΔZ is −0.085 in the Core Zone and +0.048 in the Peripheral Zone, with a small overall zonal effect (ε2 = 0.015). Shopping, food and beverage, daily life services, sports and recreation, and healthcare show clearer core-to-peripheral shifts in their associations with ΔZ. Because the observations are limited to one sampled weekday and one sampled weekend day, the identified differences reflect the two sampled conditions and should not be generalized to broader weekday–weekend patterns. These findings provide sampled-day evidence of localized functional restructuring within a broadly stable activity pattern and demonstrate the value of zonal and function-specific analysis beyond aggregate station-wide measures.