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One in 10 U.S. households experience food insecurity, with millions of low-income families lacking access to fresh food. In response, federal and state governments recently launched the Supplemental Nutrition Assistance Program (SNAP) Online Purchasing Pilot (SNAP Online), enabling SNAP benefits to cover online food purchases. Although prior research suggests that the SNAP Online program may increase overall food consumption, its impact on fresh food consumption remains unclear. This research leverages NielsenIQ consumer panel data and employs a Difference-in-Differences approach to address this question. Our findings reveal that the SNAP Online program increases fresh food consumption among low-income households by 7.1%. However, the effect is minimal in areas with limited access to online grocery delivery and among households with poor prior fresh food consumption habits. These results underscore the potential of supply-side policies, such as expanding online purchasing options, to improve fresh food consumption. They also highlight the importance of addressing demand-side barriers and enhancing digital accessibility to maximize the effectiveness of nutrition assistance programs. This paper was accepted by D. J. Wu, information systems. Funding: Z. Li received financial support from the National Science Foundation Division of Social and Economic Sciences [CAREER Award 2243736]. Supplemental Material: The web appendix and data files are available at https://doi.org/10.1287/mnsc.2025.00012 .
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Improving community resilience to disrupted food access: Empirical spatio-temporal analysis of volunteer-based crowdsourced food delivery
Unplanned disaster events can greatly disrupt access to essential resources, with calamitous outcomes for already vulnerable households. This is particularly challenging when concurrent extreme events affect both the ability of households to travel and the functioning of traditional transportation networks that supply resources. This paper examines the use of volunteer-based crowdsourced food delivery as a community resilience tactic to improve food accessibility during overlapping disruptions with lasting effects, such as the COVID-19 pandemic and climate disasters. The study uses large-scale spatio-temporal data (n = 28,512) on crowdsourced food deliveries in Houston, TX, spanning from 2020 through 2022, merged with data on community demographics and significant disruptive events occurring in the two-year timespan. Three research lenses are applied to understand the effectiveness of crowdsourced food delivery programs for food access recovery: 1) geographic analysis illustrates hot spots of demand and impacts of disasters on requests for food assistance within the study area; 2) linear spatio-temporal modeling identifies a distinction between shelter-in-place emergencies and evacuation emergencies regarding demand for food assistance; 3) structural equation modeling identifies socially vulnerable identity clusters that impact requests for food assistance. The findings from the study suggest that volunteerbased crowdsourced food delivery adds to the resilience of food insecure communities, supporting its effectiveness in serving its intended populations. The paper contributes to the literature by illustrating how resilience is a function of time and space, and that similarly, there is value in a dynamic representation of community vulnerability. The results point to a new approach to resource recovery following disaster events by shifting the burden of transportation from resource-seekers and traditional transportation systems to home delivery by a crowdsourced volunteer network.
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- Award ID(s):
- 1847537
- PAR ID:
- 10617026
- Publisher / Repository:
- Journal of Transport Geography
- Date Published:
- Journal Name:
- Journal of Transport Geography
- Volume:
- 121
- Issue:
- C
- ISSN:
- 0966-6923
- Page Range / eLocation ID:
- 104018
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript
- Journal Article:
- https://doi.org/10.1016/j.jtrangeo.2024.104018
