Large Food Bank Research Articles

Equitable distribution of perishable items in a food bank supply chain

In the United States, food banks play an important role in helping to reduce the rate of food insecurity by distributing donated food among the population in need. One of the challenges that food banks face is to equitably distribute food donations among their clients such that, ideally, each recipient receives the same amount of food. They aim to do so while minimizing waste that occurs due to spoilage and capacity limitations. Perishable food items present specific challenges since they are susceptible to spoilage and need to be distributed before their expiry dates. Based on our longstanding partnership with a large food bank located in the southeastern United States, we present a capacitated, multiperiod, multiproduct network flow model to help them equitably and effectively distribute perishable food donations among the food‐insecure population in their service region. The model is applied within the context of a case study and reveals managerial insights that would be useful to practitioners. Our findings show that although equity is one of the food bank's highest priorities, inequities cannot be eliminated completely. Given the inevitability of inequitable food allocations in practice, this paper provides food banks guidance on how to strategically control inequities using two approaches: ( i) by increasing the number of periods for which equity should be satisfied or ([Formula: see text]) by allowing deviations from a perfectly equitable distribution. The results show that modest deviations from perfect equity using either approach can lead to significant improvements in both the quality and quantity of food distributed and can also reduce food waste. While approach ([Formula: see text]) is preferable, the most desirable outcomes occur when both are applied simultaneously. We also find that county capacities inhibit a food bank's ability to achieve balance between equity and effectiveness when distributing perishables. Our framework provides food banks the flexibility to balance the trade‐off between effectiveness and equity based on their preferences.

Resiliency within the Socio-Ecological System of a Large Food Bank Network: Preparing, mitigating, responding, and recovering from Hurricane Florence

The network of a food bank consists of a complex web of entities. The entities may include the warehouses and charitable agencies. A food bank relies on the smooth interactions among these entities in distributing the donated food to the food-insecure population. In this study, we theorize that these entities and their complex interactions form a Socio-ecological System (SES). However, such an SES is vulnerable to disruptions, i.e., Hurricanes. We explore the behavior of the SES of our partner food bank, the Food Bank of Central and Eastern North Carolina (FBCENC), during Hurricane Florence, one of the deadliest hurricanes in the Carolinas. Specifically, we adopt a mixed-method research design to study the preparedness, mitigation, response, and recovery of the FBCENC SES over the lifecycle of Hurricane Florence. The design consists of quantitative methods (descriptive and statistical analyses), and qualitative methods (focus groups and semi-structured interviews). Our analysis reveals the preparation of the entities in terms of food flow within the SES, the impact of Hurricane Florence in terms of facility closure and inaccessibility, and the mitigation and response (studied together as “incidence”) of the entities through elevated activities, i.e, increase in received donations and distributions of relief items. Moreover, our analysis also reveals how the SES recovered through cooperation among the entities empowered by social capital. We also observe that new entities and connections were formed to recover from Hurricane Florence, providing a glimpse of how the FBCENC SES has been ”Built-Back-Better” after the hurricane.

How partnerships shaped the Dane CARES Farm-to-Food Bank program

The COVID-19 pandemic forced Wisconsin’s food systems institutions into rapid innovation as they responded to rising community food insecurity. With support from the Dane County Executive’s office, federal relief funding eased previously onerous barriers to allow Dane County’s largest food bank to implement a unique local purchasing program: Dane CARES. The program sought to support Dane County producers experiencing reductions in market opportunities, while feeding the rising number of Dane County families experiencing food hardship. Drawing on existing food and agriculture partner­ships, Extension Dane County staff connected partners to assist with project expedition and docu­mented partners’ efforts through a series of semistructured interviews. The program achieved its two primary goals of replacing lost markets for local farmers and facilitating increased food distribution to communities in need. To elevate this multisector collaboration and inspire more great work like Dane CARES, we outline the evidence of program value to farmers’ livelihoods, demonstrate the growth of partner networks to support institutional purchasing of local food, and offer recommendations to improve future program iterations.

A Dynamic Model for Managing Volunteer Engagement

Non-profit organizations that provide food, shelter, and other services to people in need, rely on volunteers to deliver their services. Unlike paid labor, non-profit organizations have less control over unpaid volunteers’ schedules, efforts, and reliability. However, these organizations can invest in volunteer engagement activities to ensure a steady and adequate supply of volunteer labor. We study a key operational question of how a non-profit organization can manage its volunteer workforce capacity to ensure consistent provision of services. In particular, we formulate a multiclass closed queueing network model to characterize the optimal engagement activities for the non-profit organization to minimize the costs of enhancing volunteer engagement and reducing abandonments, while maximizing productive work done by volunteers. Because this problem appears intractable, we formulate an approximating Browning control problem in the heavy traffic limit and study the dynamic control of that system. Our solution is a nested threshold policy with explicit congestion thresholds that indicate when the non-profit should optimally pursue various types of volunteer engagement activities. A numerical example calibrated using data from a large food bank shows that our dynamic policy for deploying engagement activities can reduce the food bank's total annual cost of its volunteer operations by 31%, while lowering its throughput by only 0.01%. This improvement in performance does not require any additional resources -- it only requires that the food bank strategically deploy its engagement activities based on the number of volunteers signed up to work volunteer shifts.

Accountability and Relationship-Definition Among Food Banks Partnerships

Food pantries typically operate in a partnership structure where they are primarily supported by a larger food bank. However, the ability to execute that mission through cooperative arrangements greatly depends upon accountability, a key dynamic that ensures partners are fulfilling expectations and key roles. This exploratory study utilizes qualitative interview data (n = 61) from a large food bank network to understand the extent to which a lead agency (i.e., a large food bank) meets expectations of accountability among partners. The interview results demonstrate that the extent to which expectations are met relate to different types of relationships between the lead agency and partner members. Furthermore, the ways in which partners assess the strengths or weaknesses of the food bank’s accountability reveal different types of relationships within the network, namely that of supplier–customer, supporter–customer, and supporter–collaborator.

Examining Patterns of Food Bank Use Over Twenty-Five Years in Vancouver, Canada

Food banks have grown substantially in Canada since the 1980s but little is known about patterns or predictors of engagement including frequency or duration of service use. This study examined food bank program data from a large food bank organization in Vancouver, Canada, finding that between January 1992 and June 2017, at least 116,963 individuals made over 2 million food bank visits. The majority of members were engaged for a short time and came for relatively few visits, but 9% of members engaged in longer-term episodic or ongoing usage over several years, accounting for 65% of all visits. Results from cluster and regression analyses found that documented health and mobility challenges, larger household size, primary income source, and older age were predictors of higher frequency and duration of service usage. Findings add to growing critical examinations of the “emergency food system” highlighting the need for better understanding of the broader social policies influencing food bank use.

Location, Location, Location: Teaching About Neighborhoods in Pediatrics

Location, Location, Location: Teaching About Neighborhoods in Pediatrics

Sensing Abnormal Resource Flow Using Adaptive Limit Process Charts in a Complex Supply Network*

ABSTRACTSupply networks are becoming increasingly complex with multiple overlapping relationships between firms that may span across industries. Consequently, inventory management is becoming more difficult as managers have to cope with variability in the supply flows that originate from different parts of the network. Managers that quickly sense abnormal flows may intervene and adapt their inventory policies in response to system changes. In this article, we present a framework for sensing abnormal flows originating within the upstream supply network of a focal organization. Our framework combines time series modeling with process charts to identify abnormal flow patterns in the incoming supply streams. It is a flexible framework that uses off‐the‐shelf technology to provide managers with a process that can be employed for monitoring multiple individual or aggregated data streams originating within any complex system such as complex adaptive supply networks. We illustrate our framework on four years of longitudinal supply data from the second largest food bank in the United States. We identify multiple instances of abnormal supply flows and validate our results through rigorous inventory analysis as well as field‐based expert interviews. We discuss the implications of our findings for inventory management in complex supply networks, both from academic and practitioner points of view.

First SEG Volunteer Day a big success

On Saturday, 21 September, before the SEG convention began in earnest, the first SEG Volunteer Day was held at the Houston Food Bank. About 32 volunteers ( Figure 1 ) participated in sorting and packing donated food for distribution across southeast Texas. Many of the volunteers were from the University of Houston GeoSociety. The Houston Food Bank is the largest food bank in the United States (by pounds) distributing more than 80 million pounds in the past year to more than 600 partner agencies (soup kitchens, food pantries, senior centers, and other agencies) in 18 southeast Texas counties. The Houston Food Bank generates food for more than 137,000 people per week. Most of the food goes to the working poor—those persons who have jobs but still struggle to put enough food on the table for their families. Only 6% of the people served are homeless; the other 94% are working people who struggle to pay bills and provide adequate food on the table.

Understanding the Sustainability of Retail Food Recovery

In this paper we study the simultaneous problems of food waste and hunger in the context of food (waste) rescue and redistribution as a means for mitigating hunger. To this end, we develop an empirical model that can be used in Monte Carlo simulations to study the dynamics of the underlying problem. Our model's parameters are derived from a data set provided by a large food bank and food rescue organization in north central Colorado. We find that food supply is a non-parametric heavy-tailed process that is well modeled with an extreme value peaks over threshold model. Although the underlying process is stochastic, the basic approach of food rescue and redistribution to meet hunger demand appears to be feasible. The ultimate sustainability of this model is intimately tied to the rate at which food expires and hence the ability to preserve and quickly transport and redistribute food. The cost of the redistribution is related to the number and density of participating suppliers. The results show that costs can be reduced (and supply increased) simply by recruiting additional donors to participate. With sufficient funding and manpower, a significant amount of food can be rescued from the waste stream and used to feed the hungry.