Review: Do Green Defaults Reduce Meat Consumption?

Johanna Meier*, Mark Andor, Friederike C. Döbbe, Neal R. Haddaway, Lucia A. Reisch

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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Meat consumption and production cause a significant share of greenhouse gas (GHG) emissions in the food sector. Behavioural food policy suggests using defaults – i.e., pre-setting a specific choice option – as an effective demand-side instrument to reduce meat consumption. This systematic review compiles, critically appraises, and synthesises existing empirical evidence on defaults that aim to reduce meat consumption. Beyond that, the underlying mechanisms and potential effect moderators in this context are explored. Our synthesis includes twelve individual studies comprising sixteen different default interventions. Although the extent of evidence is limited, we assess the quality to be relatively good. We find that defaults are effective in nudging consumers to eat less meat; despite heterogeneity in the design and implementation of interventions, virtually all studies find the default to reduce meat consumption. Moreover, our explorative analysis provides insights into how the default works in this context. First, we suppose the default primarily operates through the underlying mechanisms of endorsement and effort. Second, we identify four contextual moderators – namely the default’s invasiveness, the recognisability and presentation of the alternative, and the objective of the study setting – that appear to influence the impact. We conclude that defaults are a promising tool for climate-sensitive food policy. Future research could verify and quantify the causal impact of mechanisms and moderators, and assess defaults’ long-term and large-scale effectiveness.
Original languageEnglish
Article number102298
JournalFood Policy
Number of pages17
Publication statusPublished - Jul 2022


  • Defaults
  • Meat consumption
  • Food policy
  • Behavioural intervention
  • Climate change
  • Evidence synthesis

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