Shifting consumers towards sustainable food consumption and avoiding food waste: Protocol for a machine-learning assisted systematic review and meta-analysis of demand-side interventions
It is widely acknowledged that a significant portion of the emissions reductions necessary to meet net-zero targets must come from changes in individual behaviour. Encouraging more sustainable food consumption and reducing food waste and loss (FWL) have been identified as key ways to address climate change at the individual and household levels. While the IPCC estimates that there is a significant “technical potential” to reduce emissions through diet changes and FWL reductions, this project aims to fill the knowledge gap and identify the best climate solutions to achieve this potential.
This systematic review and meta-analysis aim to synthesise the existing research on demand-side interventions targeting sustainable food consumption and food waste behaviours of individuals and households. It includes studies that evaluate a wide range of policy interventions aimed at changing actual food consumption and waste behaviours, which have the potential to contribute to climate change mitigation. The review will include various studies, including real-world settings (supermarkets, restaurants, cafeterias) and online experimental settings.
The review forms part of an ‘ecosystem of reviews’, a large-scale evidence synthesis initiative seeking to provide a comprehensive analysis of household-scale interventions and their emissions reduction potential across multiple behavioural domains. The reviews within the ecosystem utilise state-of-the-art AI-assisted screening procedures and follow a set of harmonised inclusion criteria. The initiative, led by the Mercator Research Institute on Global Commons and Climate Change (MCC) in Berlin, will strengthen our understanding of the emissions-mitigation potential of demand-side climate change policies and contribute towards broader evidence synthesis efforts for upcoming IPCC Assessment reports.