Foreign city users and in-store versus online retail channel choice: urban logistics and planning implications

This study examines the in-store and online purchasing behaviour of foreign city users (FCUs) in Bratislava, using a mixed-method quantitative approach that combines binary logit models with machine-learning classifiers, including support vector machines (SVM), random forests, and artificial neural networks. FCUs, defined as non-native residents such as international students, migrant workers, and refugees, display distinctive shopping patterns compared to locals, influenced by factors such as age, mobility resources, and product type. The analysis shows that FCUs are significantly less likely to shop online, particularly for essential goods, while younger FCUs are more inclined to purchase discretionary items online. The increased reliance of FCUs on physical retail for essentials tends to concentrate passenger trips in accessible districts (often walkable and transit-served, but in some contexts also around car-oriented shopping centres) whereas local higher uptake of online shopping generates more dispersed last-mile delivery flows. Beyond freight implications, this pattern helps policymakers calibrate the local retail mix and ensure its multi-modal accessibility (not only passenger trips). Policy recommendations include maintaining accessible retail in FCU-dense areas, improving multilingual e-commerce access, and strategically locating parcel collection infrastructure. The study underscores the need for demographic-sensitive retail and freight planning to support inclusive, sustainable, and resilient cities.