Optimal Interventions for Increasing Healthy Food Consumption Among Low-Income Populations

More than $60 billion per year in the United States is spent on policies aimed to increase fruit and vegetable (FV) consumption among low-income households. Many of these policy interventions are either monetary (e.g., financial incentives) or education related. The goal of this paper is to improve the performance of these interventions through a more strategic and personalized allocation of funds. This paper introduces a consumer behavioral model for grocery shopping decisions, which is nested into the policymaker’s upper-level optimization problem. The policymaker’s goal is to ensure that the FV spending of all consumers in a given population exceeds a specified threshold by utilizing a small strategic set of different intervention bundles—combinations of monetary and education-related interventions. Although an exact solution to the upper-level problem is intractable, we provide an analytical upper bound on the number of intervention bundles needed to achieve the policymaker’s goal, as well as a method for constructing these intervention bundles and assigning them to individuals based on their characteristics. We demonstrate the practicality of the model and approach using the low-income households in the U.S. Department of Agriculture’s FoodAPS data set.

This paper was accepted by Jayashankar Swaminathan, operations management.

Funding: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under [Grant 1745302].

Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02324.