Behavior-based dependency networks between places shape urban economic resilience

TL;DR

This paper introduces behavior-based dependency networks derived from human mobility data to better understand and predict urban economic resilience during shocks like pandemics, revealing significant long-distance dependencies and improving resilience predictions.

Contribution

It develops a novel approach to quantify dependencies between urban points-of-interest using mobility data, enhancing the understanding of economic shock propagation beyond physical proximity.

Findings

Behavior-based dependency networks show higher long-distance connections than physical proximity.

Using these networks improves resilience prediction accuracy by around 40%.

Neglecting behavioral dependencies underestimates disruption cascades.

Abstract

Urban economic resilience is intricately linked to how disruptions caused by pandemics, disasters, and technological shifts ripple through businesses and urban amenities. Disruptions, such as closures of non-essential businesses during the COVID-19 pandemic, not only affect those places directly but also influence how people live and move, spreading the impact on other businesses and increasing the overall economic shock. However, it is unclear how much businesses depend on each other in these situations. Leveraging large-scale human mobility data and millions of same-day visits in New York, Boston, Los Angeles, Seattle, and Dallas, we quantify dependencies between points-of-interest (POIs) encompassing businesses, stores, and amenities. Compared to places' physical proximity, dependency networks computed from human mobility exhibit significantly higher rates of long-distance connections and biases towards specific pairs of POI categories. We show that using behavior-based dependency relationships improves the predictability of business resilience during shocks, such as the COVID-19 pandemic, by around 40% compared to distance-based models. Simulating hypothetical urban shocks reveals that neglecting behavior-based dependencies can lead to a substantial underestimation of the spatial cascades of disruptions on businesses and urban amenities. Our findings underscore the importance of measuring the complex relationships woven through behavioral patterns in human mobility to foster urban economic resilience to shocks.