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Analyzing Night Shift Workers’ Commute Burden and Nighttime Mobility Patterns: A Case Study in Baltimore

Xiaomeng Dong, Tianyu Shen, Qi Zhang, Di Yang, Xianfeng Yang, Mansoureh Jeihani
July 9, 2026
Published Date

Research Abstract & Technology Focus

Despite occupying essential roles in healthcare, warehouses, and manufacturing, night shift workers remain underserved by transportation systems designed around standard daytime schedules. Using the Baltimore Metropolitan Area as a case study, this study provides an in-depth examination of night shift workers’ travel behavior and commute wellbeing. Survey data on commute choices, commute durations, travel costs, and perceived perspectives were collected from workers employed in night shift-based occupations. Structural equation modeling was then used to examine the relationships between travel behavior and perceived inconvenience by constructing a latent variable of commute burden. The results show that longer commute times and reliance on public transit are significant indicators of commute burden among this population. To further investigate why commute burden is associated with public transit, we conducted spatial visualizations and K-means clustering based on origin-destination nighttime trips derived from anonymized mobile phone data. Land use maps and nighttime public transit networks were referenced to identify travel flows and mobility patterns between high-flow zones, revealing the need to expand nighttime transit services in those areas. These findings reflect limited transit accessibility affecting night shift workers and offer actionable insights for nighttime transit planning and public service improvements in similar metropolitan contexts.
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What is the core focus of the research titled 'Analyzing Night Shift Workers’ Commute Burden and Nighttime Mobility Patterns: A Case Study in Baltimore'?

This literature focuses on: Despite occupying essential roles in healthcare, warehouses, and manufacturing, night shift workers remain underserved by transportation systems designed around standard daytime schedules. Using the Baltimore Metropolitan Area as a case study, thi...

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Yes, highly correlated activity was mapped. An entry titled 'The Most Sleep-Deprived U.S. Cities, Mapped' discusses this: Factors like lack of exercise, high alcohol consumption, and stress contribute to sleep deprivation. See where your closest city ranks.

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