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

Abstract It is now widely accepted that a significant portion of emissions reductions required to meet net zero targets must come from individual behaviour change. Shifting consumers towards more sustainable food consumption and avoiding food waste and loss (FWL) have been identified as two key levers to tackle climate change at the individual and household level. While the IPCC estimates substantial “technical potential” to reduce emissions via changes in diets and reductions in FWL, there is a lack of learning on which climate solutions can best harness this potential. The purpose of this systematic review and meta-analysis is to synthesise the empirical literature reporting on demand-side interventions targeting sustainble food consumption and food waste behaviours of individuals and households. The review encompasses empirical research evaluating a wide range of policy interventions targeted at changing actual food consumption and waste behaviours, which have the potential to contribute towards climate change mitigation. 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. The reviews within the ecosystem utilise state-of-the-art AI-assisted screening procedures and follow a set of harmonised inclusion criteria.