Abstract
In the fight against hunger, Food Banks must routinely make strategic distribution decisions under uncertain supply (donations) and demand. One of the challenges facing the decision makers is that they tend to rely heavily on their prior experiences to make decisions, a phenomenon called cognitive bias. This preliminary study seeks to address cognitive bias through a visual analytics approach in the decision-making process. Using certain food bank data, interactive dashboards were prepared as an alternative to the customary spreadsheet format. A preliminary study was conducted to evaluate the effectiveness of the dashboard and results indicated dashboards reduced the amount of confirmation bias.
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Acknowledgments
The study is supported in part by a National Science Foundation grant - PFI: Flexible Equitable Efficient Effective Distribution (FEEED) (Award number: 1718672).
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Delpish, R., Jiang, S., Davis, L., Odubela, K. (2019). A Visual Analytics Approach to Combat Confirmation Bias for a Local Food Bank. In: Boring, R. (eds) Advances in Human Error, Reliability, Resilience, and Performance. AHFE 2018. Advances in Intelligent Systems and Computing, vol 778. Springer, Cham. https://doi.org/10.1007/978-3-319-94391-6_2
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DOI: https://doi.org/10.1007/978-3-319-94391-6_2
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