Collaborative project: Digital decision support for sustainable nutrition (DINER) - Subproject B

Basic data for this project

Description

The project aims to develop an automated and personalized food recommendation system that is easy to use for all consumers and that promotes a sustainable, i.e. healthy, environmentally and socially acceptable diet and at the same time expands users' knowledge of sustainable foods. The application to be developed is intended to initiate implicit learning processes using nudges, triggers and priming effects and thus contribute to a more sustainable diet for consumers in a simple and natural way. Strengthening consumers' nutritional competence is therefore not done through instruction, but through the sustainability-oriented design of food environments. In order to support consumers in implementing a more sustainable diet, this project creates the basis for designing a fair food environment. Consumers should be supported in identifying sustainable foods and substituting less sustainable foods when deciding what to buy. The possibility of substitution (e.g. oat milk instead of cow's milk) enables a low-threshold adjustment of shopping behavior without wanting to change the nutritional preferences of consumers. In order to change shopping planning in the direction of a sustainable diet, it is necessary to improve the nutritional competence of consumers. Consumers learn how to use more sustainable product alternatives when preparing food in order to create preferred taste experiences. The application to be developed will be developed from scratch over the course of the project and will go through the TRL stages from the technology concept to the proof of concept and the laboratory sample to use in living labs.