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In the quest for equitable resource distribution within food banks and their partner agencies, understanding the dependencies of these agencies on food banks emerges as a critical factor. This study investigates the intricate dynamics influencing agency dependency ratios, exploring the complex factors that shape the demand for food resources. Leveraging historical self-reported dependency ratio data, this preliminary study employs predictive modeling using Multiple Linear Regression to forecast agency dependencies on food banks. The primary objective is to discern the underlying factors that significantly impact agency dependency ratios. Employing Least Absolute Shrinkage and Selection Operator (LASSO) as a feature selection technique, the study identifies the key variables that capture the essence of the dataset. Identifying the variables that contribute the most to the model paves the way for robust predictive modeling. This study offers a comprehensive approach to understanding and predicting agency dependencies on food banks. The findings hold significant implications for non-profit hunger relief organizations, aiding in strategic decision- making for equitable resource distribution. 

Food banks provide services and food assistance to those facing food insecurity, a challenge that can affect families and individuals from various backgrounds and communities. Diversity, equity, and inclusion (DEI) are principal factors in food bank operations. This study focuses on diversity as measured by client ethnicities and the rurality of the counties served by the food banks. Over 44 food banks were interviewed to understand their operations. Key performance indicator (KPI) metrics in each organization were identified and classified as Community Focused (CF), involving tailored services based on community needs, and Organizational Efficiency Focused (OE), involving processes and strategies to increase output and minimize resources. A clustering analysis was conducted to group these organizations depending on the percentage of rural counties served by the food banks and their respective zscore based on diversity index, so four clusters (tiers) were created (Tier 1 are the least diverse and the most rural, while those in the fourth tier are the most diverse and the least rural). The KPIs in each tier organization were examined and results suggest that organizations in Tier 1 use more OE KPI metrics whereas those in Tier 4 use a more balanced combination of CF and OE metrics. This research provides hunger-relief organizations insights to adopt practices that acknowledge, accommodate, and celebrate the diverse needs and characteristics of the neighborhood they serve. 

Food banks are key players in the fight against hunger. The complexity of the food bank operations data makes decision-making very challenging. Data visualization can allow food bank operations managers to quickly and easily understand the data and make evidence-based decisions. However, poorly designed visualizations could be confusing and/or misleading. This study uses eye-tracking technology to understand how users interact with various food bank data visualizations and use eye-tracking data to better design those visualizations. The findings of this study will have an impact on improving the effectiveness and efficiency of the food bank operations. 

Food banks are at the forefront of the battle against food insecurity which is a condition where households do not have adequate access to food. Traditionally speaking, food banks focus on distributing food to meet the needs. Recently, more food banks are shifting to supply adequate healthy food based on the populations they serve. However, the question remains whether a local food bank can find racial communities in need with dietary considerations. This study's purpose is to use data collected by a local food bank and create visualizations to aid strategic decision-making for the food bank to recognize racial communities with those who have dietary considerations. Results revealed nine out of sixteen counties in the service area of the local food bank have the highest number of African Americans allergic to shellfish compared to a few counties having the highest number of Whites, American Indians, and Hispanic/Latinos. Additionally, 53.7% of African Americans, 11.2% of Hispanics and Latinos, and 34.3% of Whites face lactose intolerance. Data shows that African Americans have the highest number of dietary considerations in most categories that are in several counties. The significance of this study supports a local food bank in finding dietary considerations within the areas they serve. Finding racial communities that face dietary considerations will aid the local food bank in making better strategic decisions on what types of food they should serve and where. Ultimately, the importance of this study is to combat food insecurity and hunger, so that members of the local food bank community can have dignity in knowing the food that will be given is valuable and not wasted.