More online deliveries, fewer work commutes? joint evidence on behavioral shifts relative to pre-pandemic conditions

The COVID-19 pandemic accelerated remote work, online shopping, and home-based activity, raising questions about how passenger travel and residential goods movement are evolving together. This study examines whether changes in physical workplace travel and online home delivery reflect interconnected and asymmetric adjustments in household activity organization. Using 6,186 employed respondents from the 2022 NextGen National Household Travel Survey, we analyze reported changes in both activities relative to pre-pandemic conditions and distinguish the direction of change from respondents’ perceived durability. Although “about the same as before” is the most common response for both activities, respondents reporting change predominantly indicate increased online home delivery and reduced physical workplace travel. A bivariate ordered probit model, supplemented by average discrete changes in predicted probabilities, reveals substantial socioeconomic asymmetry. Higher-income and advanced-degree respondents show greater movement toward online home delivery and reduced workplace travel, whereas lower-income respondents exhibit the opposite pattern. Advanced-degree and higher-income respondents have approximately 10–11 percentage-point higher probabilities of reporting reduced physical workplace travel than their respective comparison groups. Mobility resources, lifecycle, and geographic context introduce additional differences across the two activities. A significant negative cross-equation error correlation further indicates that delivery and workplace-travel adjustments remain related through unobserved factors after accounting for observed differences. Rather than supporting direct trip-for-trip substitution, the combined evidence points to interconnected but uneven reorganization of work and consumption activities. These findings support jointly considering passenger travel and residential goods movement while accounting for socioeconomic and spatial heterogeneity in transportation forecasting and scenario analysis.