ArticleFrontiers in big data2026
From crisis to new routine: shifts in urban shopping mobility and socioeconomic inequality during and after the COVID-19 shock.
Article in Frontiers in big data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: This study examines the impact of the COVID-19 pandemic on revealed shopping-location patterns and their persistence during the early recovery period. It focuses on urban shopping mobility in New York City and investigates whether observed store-selection patterns returned to, or remained different from, their pre-pandemic baseline by 2021 across different socioeconomic communities. Methods: We use large-scale mobility and place datasets together with census information to analyze visits to general merchandise and department stores in New York City. A modified Huff gravity model and a metaheuristic calibration method are used to quantify temporal shifts in store-selection patterns. We also use unsupervised learning techniques and statistical inference models to examine heterogeneity across socioeconomic communities and evaluate changes before, during, and after the COVID-19 shock. Results: The proposed model captures the dynamics of shopping-location decisions and temporal visit patterns under changing pandemic-era constraints. The results suggest that New Yorkers' revealed store-selection patterns changed substantially during the COVID-19 shock, with increased emphasis on store area, chain loyalty, and nearby points of interest, and reduced sensitivity to customer-store distance. These patterns did not fully revert to their 2019 baseline by 2021, although 2021 is interpreted as an early recovery and reopening period rather than a fully post-pandemic equilibrium. Discussion: The findings highlight the societal dimension of urban shopping mobility disruptions during crises and show that mobility-based store-selection patterns vary across socioeconomic communities. The results can help urban planners, managers, and marketers better understand heterogeneous shifts in shopping mobility and adapt strategies under crisis and recovery conditions.
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