Spatiotemporal associations between e-shopping in Transport-SuperApps and daily time use across urban contexts

The rise of e-shopping and the continuous advancement of its platforms have coincided with changes in travel demand and the broader transportation landscape. With the predicted increase in e-shopping usage in the future, there is an urgent need to further understand how this service associates with individual activity participation. This study investigates how e-shopping, delivered through Transport-SuperApps (app-based platforms that integrate ride-hailing, e-shopping, and other on-demand services), is associated with a reorganisation of daily time use across spatial and temporal dimensions and diverse urban contexts. Using one-week time-use and app-use diaries collected in Indonesian cities (Jakarta, Bandung, Denpasar, Cianjur), combined with a Mixed Multiple Discrete-Continuous Extreme Value model with inverse probability weights, the analysis compares users and non-users, weekdays and weekends, and in-home and out-of-home activities. The findings reveal patterns consistent with both substitution and rebound effects. E-shopping usage is associated with lower engagement in out-of-home activities, particularly physical shopping. The corresponding time appears to shift toward in-home leisure rather than toward mandatory pursuits. This shift is most pronounced on weekdays and carries over into the following weekend, where out-of-home activity remains lower. Weekend usage shows a related but distinct pattern. In-home leisure duration is higher on the weekend itself and on the following weekday, alongside lower out-of-home mandatory and leisure activity. Across cities, the association between e-shopping and physical maintenance activity is negative in nearly all cities and scenarios, with the largest metropolitan areas generally showing the largest declines in out-of-home activity. Virtual maintenance duration shows a small positive association instead, consistent with a generation-type pattern. This pattern appears within the digital channel itself rather than following a clear gradient between larger and smaller cities. These findings highlight the need to extend travel demand management beyond weekdays and to align urban planning with the changing rhythms of e-shopping.