Low-income residents of American cities tend to live far from the districts where job creation is concentrated, and therefore incur high transportation costs (in terms of time and money) when seeking employment outside their neighborhoods. These high transportation costs depress income, limit employment, and lower socioeconomic mobility. This is known as the spatial mismatch problem, and it is likely to pose even bigger challenges for low-income mothers with young children, given their parental responsibilities. While this problem has existed for decades, the recent and widespread diffusion of smartphones has enabled a proliferation of new transportation options that offer some of the flexibility of personal vehicles without the high fixed cost of vehicle ownership. Could these new transportation options significantly expand the geographic and socioeconomic mobility of low-income mothers? If so, how? To explore these possibilities, this project proposes a set of field experiments which provide low-cost access to these transportation options for a treatment group and compare the mobility and socioeconomic outcomes to a control group. The experiments can use the GPS capabilities embedded in modern smartphones to measure the quantity and nature of increased geographic mobility thereby conferred on low-income mothers in the treatment groups. Through innovative partnerships with local government agencies, this project will measure the impact of increased geographic mobility on socioeconomic mobility in the short-run and the long-run. Through partnerships with a diverse set of regional nonprofits, this project will directly involve low-income mothers in our research design. The results of the research will provide immediate guidance for policymakers seeking to fund practical policy and engineering solutions to the spatial mismatch problem.

Given the rapid diffusion of these transportation options across the country and around the world, policy lessons derived from our study could be implemented in hundreds of cities, potentially impacting the lives of millions. The research will also support fundamental breakthroughs in the modeling of regional transportation systems. Transportation researchers currently have limited visibility into how new transportation options are impacting multi-modal transit choices within regional transportation systems. By leveraging the detailed data collected through our proposed research, this project will create new methods for modeling these regional transportation systems. The new models will reflect the growing interaction between conventional mass transit and a range of complementary new (and old) transit technologies. The knowledge gained from these models could further expand mass transit ridership and resident mobility, while also promoting environmental sustainability. This project is supported by the CIVIC Innovation Challenge program Track A. Communities and Mobility: Offering Better Mobility Options to Solve the Spatial Mismatch Between Housing Affordability and Jobs through a collaboration between NSF and the Department of Energy Vehicle Transportation Office.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Type
Standard Grant (Standard)
Application #
2043634
Program Officer
David Corman
Project Start
Project End
Budget Start
2021-02-15
Budget End
2021-09-30
Support Year
Fiscal Year
2020
Total Cost
$49,899
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
DUNS #
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213