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Research Title: Trip Distribution Post-Pandemic and Disparate Impacts of Work from Home on Demands for Transit Services in Chicago: Evaluating Mobility Network Patterns from Mobile Phone Tracing Data
Projected Timeline
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Start Date: Mon, 01/01/2024 - 00:00
End Date: Tue, 12/31/2024 - 00:00

Research Abstract:
Across the United States, transit ridership has recovered to about 71 percent
of pre-COVID-19 pandemic levels. The slow ridership recovery translates into
less farebox revenue and large budget gaps for the nation’s largest transit
agencies when revenue support from the federal government ceased in October
2024. Ridership recovery is slower in Chicago than national averages, below
70 percent for bus and below 60 percent for rail. Our paper illuminates
disparate impacts from possible service reductions in eliminating an
estimated $700 million deficit in the budget for Chicago’s Regional
Transportation Authority. We construct monthly mobility pattern networks from
mobile phone tracing data (Dantsuji et al. 2023) and characterize the
patterns before and after the pandemic across 4.4 million residential
blockgroup-to-workplace blockgroup networks. We then test an empirical trip
distribution model to assess importance of the share of workforce in Skilled
Scalable Services occupations (Althoff et al. 2022) as a determinant of
commuting flows. Our focus on the mobility networks allows us to pinpoint
transit services throughout the city where continued investment might be
justified for employer demand at the destination (vis-à-vis the share of
jobs that cannot work from home) or suggested by limited alternatives for
mobility at the origin (vis-à-vis low household incomes and house values
among other factors).



Project Type: Faculty, Student
Lead Researcher(s):
- Name: Richard Funderburg
  Email: rfund2@uis.edu
  Phone: 2172994149
  Link: /directory/richard-funderburg

Assistant Researcher(s):
- Name: Tong Ye
  Email: tye23@uic.edu
- Name: Chen Xie
  Email: cxie25@uic.edu

Department(s):
School of Public Management and Policy (149811193)

Keywords:
- Machine Ñî¹óåú´«Ã½ (ML) (2600003350)
- Artificial Intelligence (AI) (2600003349)

Associated File(s):
- /system/files/webform/submit_your_research_project/8489/Funderburg_Ye_Xie_Abstract_NARSC2024.docx

Has this research project received IRB approval?: Not required
Links:
- Using Artificial Intelligence and Cell Phone Tracing Data to Reevaluate Travel Demand and Investments in Public Transit (/news/using-artificial-intelligence-and-cell-phone-tracing-data-reevaluate-travel-demand-and)

Comments:
This project does not involve human subjects and does not require IRB approval.