Problem
Research questions and friction points this paper is trying to address.
workplace dependence
urban economy
remote work inequality
spatial distribution
socio-economic disparity
Workplace dependence in urban economies
🤖 AI Summary
The widespread adoption of remote work has exacerbated intra-urban inequalities in health risks, social interaction, and economic opportunity. Leveraging high-resolution hourly human mobility data and firm registration records, this study exploits variations in pandemic-related mobility restrictions as a quasi-natural experiment to investigate the drivers of workplace dependence through multidimensional regression and spatial heterogeneity models. The analysis reveals that industry type and firm productivity are key determinants. Moreover, income and gender effects are significantly moderated by distance from the city center, giving rise to a “service trap” in core urban areas: neighborhoods characterized by female-dominated employment and diverse income sources exhibit heightened reliance on in-person attendance, thereby extending remote-work disparities from the individual level to the broader urban ecosystem.
📝 Abstract
Remote work has fundamentally reshaped urban economic life, and the spatial organisation of activity across cities. However, access to flexible work is distributed unevenly across industries, income groups, and genders, creating disparities in health risks, social mixing, and economic opportunity. Understanding where workplace dependence (WPD) is concentrated is therefore important, yet its distribution across urban areas remains poorly understood. Here we pair fine-grained hourly population data with detailed company records in a large European city to examine how location, industry composition, and socio-economic characteristics shape physical workplace attendance. By comparing workplace activity during periods of low versus high COVID-19 restrictions, we identify the determinants of WPD. We find that while industry and firm productivity are key drivers, the relationship between WPD, income, and gender is highly contingent on distance from the city center. Near the centre, female-majority and income-diverse locations show the highest WPD, consistent with a residual, place-bound service workforce. These findings reveal a spatially contingent 'service trap' at the urban core, extending remote-work inequalities beyond individuals to the urban ecosystem as a whole.
Innovation
Methods, ideas, or system contributions that make the work stand out.
workplace dependence
remote work inequality
urban spatial analysis
high-resolution mobility data
service trap
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