Leveraging Analytics to Understand Food Consumption and Waste in Achieving Personalized Nudging
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Date
2025-01-07
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926
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Managing food waste is pivotal in advancing sustainable consumption practices. This study investigates how various factors such as food type, consumer spending, socio-economic characteristics, and demographics correlate with food waste patterns, utilizing data analytics and statistical analysis. Drawing on studies in green information systems (IS) and digital nudging, we propose three strategic nudging designs: pre-existing nudges based on food type characteristics, configurable nudges tailored to demographic and socio-economic profiles, and dynamic nudges responsive to evolving consumer behaviors. These interventions are designed to utilize behavioral insights to promote more sustainable consumer habits and present a novel methodology for substantially reducing food waste.
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Analytics and Intelligent Decision Support for Green IS and Sustainability Applications, consumer behavior, data analytics, digital nudging, food waste reduction, green is
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10
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Proceedings of the 58th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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