The dynamics of food shopping behavior: Exploring travel patterns in low-income Detroit neighborhoods experiencing extreme disinvestment using agent-based modeling

Abstract

Only a handful of studies have leveraged agent-based models (ABMs) to examine public health outcomes and policy interventions associated with uneven urban food environments. While providing keen insights about the role of ABMs in studying urban food environments, these studies underutilize real-world data on individual behavior in their models. This study provides a unique contribution to the ABM and food access literature by utilizing survey data to develop an empirically-rich spatially-explicit ABM of food access. This model is used to simulate and scrutinize individual travel behavior associated with accessing food in low-income neighborhoods experiencing disinvestment in Detroit (Michigan), U.S. In particular, the relationship between trip frequencies, mode of travel, store choice, and distances traveled among individuals grouped into strata based on selected sociodemographic characteristics, including household income and age, is examined. Results reveal a diversified picture of not only how income and age shape food shopping travel but also the different thresholds of tolerance for non-motorized travel to stores. Younger and poorer population subgroups have a higher propensity to utilize non-motorized travel for shopping than older and wealthier subgroups. While all groups tend to travel considerable distances outside their immediate local food environment, different sociodemographic groups maintain unique spatial patterns of grocery-shopping behavior throughout the city and the suburbs. Overall, these results challenge foundational tenets in urban planning and design, regarding the specific characteristics necessary in the built environment to facilitate accessibility to urban amenities, such as grocery stores. In neighborhoods experiencing disinvestment, sociodemographic conditions play a more important role than the built environment in shaping food accessibility and ultimately travel behavior.

Designing a food supply chain strategy during COVID-19 pandemic using an integrated Agent-Based Modelling and Robust Optimization

“…Through the simulation, they are able to point out several key entrepreneurial capabilities to enhance the firm performance. Whereas, Vojnovic et al (2020) studied the food shopping behaviour via ABM simulation. They observed factors affecting the food shopping behaviour by constructing the agents' behaviour based on survey data of food access.…”

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“…Several studies (e.g., Smith 1992;Föbker and Grotz 2006;Vojnovic et al 2020) address the issue of the supply provision for the elderly urban dwellers. This is a significant issue, especially considering the income and mobility constraints this growing population faces.…”

Examining changes to food and beverage availability and marketing in a low-income community after the opening of a new supermarket

“…Only food stores located within one mile of the new supermarket were included in this assessment. Existing literature suggest that low-income individuals often shop at food stores outside of their community area for reasons such as schedule, safety and pricing (40,41) . If this is the case in Chicago, those other stores were not captured in this assessment.…”