@article{hasnain_walton_odubela_mcconnell_davis_ivy_jiang_coan_islam_mpere_2023, title={Resiliency within the Socio-Ecological System of a Large Food Bank Network: Preparing, mitigating, responding, and recovering from Hurricane Florence}, volume={88}, ISSN={["2212-4209"]}, DOI={10.1016/j.ijdrr.2023.103580}, abstractNote={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.}, journal={INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION}, author={Hasnain, Tanzid and Walton, Tobin N. and Odubela, Kehinde and McConnell, Sarah and Davis, Lauren and Ivy, Julie and Jiang, Steven and Coan, Danielle and Islam, Md Hafizul and Mpere, Elsie}, year={2023}, month={Apr} }
 @article{hasnain_sengul orgut_ivy_2021, title={Elicitation of Preference among Multiple Criteria in Food Distribution by Food Banks}, ISSN={["1937-5956"]}, DOI={10.1111/poms.13551}, abstractNote={The United Nations Sustainable Development Goals provide a road map for countries to achieve peace and prosperity. In this study, we address two of these sustainable development goals: achieving food security and reducing inequalities. Food banks are nonprofit organizations that collect and distribute food donations to food‐insecure populations in their service regions. Food banks consider three criteria while distributing the donated food: equity, effectiveness, and efficiency. The equity criterion aims to distribute food in proportion to the food‐insecure households in a food bank's service area. The effectiveness criterion aims to minimize undistributed food, whereas the efficiency criterion minimizes the total cost of transportation. Models that assume predetermined weights on these criteria may produce inaccurate results as the preference of food banks over these criteria may vary over time, and as a function of supply and demand. In collaboration with our food bank partner in North Carolina, we develop a single‐period, weighted multi‐criteria optimization model that provides the decision‐maker the flexibility to capture their preferences over the three criteria of equity, effectiveness, and efficiency, and explore the resulting trade‐offs. We then introduce a novel algorithm that elicits the inherent preference of a food bank by analyzing its actions within a single‐period. The algorithm does not require direct interaction with the decision‐maker. The non‐interactive nature of this algorithm is especially significant for humanitarian organizations such as food banks which lack the resources to interact with modelers on a regular basis. We perform extensive numerical experiments to validate the efficiency of our algorithm. We illustrate results using historical data from our food bank partner and discuss managerial insights. We explore the implications of different decision‐maker preferences for the criteria on distribution policies.}, journal={PRODUCTION AND OPERATIONS MANAGEMENT}, author={Hasnain, Tanzid and Sengul Orgut, Irem and Ivy, Julie Simmons}, year={2021}, month={Oct} }