Shifting consumers towards sustainable food consumption and avoiding food waste: 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 behavior. 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 level. While the IPCC estimates that there is a significant “technical potential” to reduce emissions through changes in diets and reductions in FWL, there is a lack of knowledge about which climate solutions are best suited to achieve this potential.
This systematic review and meta-analysis aims to synthesize the existing research on demand-side interventions targeting sustainable food consumption and food waste behaviors of individuals and households. It includes studies that evaluate a wide range of policy interventions aimed at changing actual food consumption and waste behaviors, which have the potential to contribute to climate change mitigation.
The review will include studies that observe food consumption or food waste and loss (FWL) behaviors of individuals or households in any relevant food choice setting, including real-world settings (supermarkets, restaurants, cafeterias) or online experimental settings. It will include studies that examine at least one of the following interventions targeted at changing behavior: Monetary interventions, informational and/or educational interventions, behavioral interventions, command-and-control regulation. The review will include studies that have a valid comparison group as a benchmark, and measures actual behavior or incentive-compatible choices that entail potential emissions reductions that can be categorized as “shifting” consumers towards sustainable food consumption or “avoiding” food waste and loss. The review will include studies that make use of an experimental design, quasi-experimental methods, or pre-post intervention designs and exclude descriptive, conceptual, theoretical and qualitative studies, as well as stated preference studies and simulation and other modelling studies.
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 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. The reviews within the ecosystem utilise state-of-the-art AI-assisted screening procedures and follow a set of harmonised inclusion criteria.