Promoting Methane Reductions Through Behavioural Nudges and Informational Boosts: A Field Choice Experiment in Japanese Rice Farming

Shengyi Du et al.

Journal of Agricultural Economics2026https://doi.org/10.1111/1477-9552.70038article
AJG 3ABDC A
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0.50

Abstract

Agricultural methane emissions represent a significant contributor to global climate change, with irrigated rice cultivation being one of the primary sources. Despite the availability of effective mitigation technologies, their adoption often remains limited due to behavioural and institutional constraints. Water management practice that extends drainage periods during cultivation can curb methane emissions from irrigated rice at low cost, yet uptake among Japanese farmers remains modest. We surveyed 2219 rice producers in Shiga Prefecture using a labelled choice experiment that embedded two behavioural nudges (social norm and loss aversion) and one informational boost (knowledge enhancement), presented with or without a reminder. Farmers most favoured a 7‐day drainage extension. Social‐norm messages did not robustly shift adoption intentions, but loss‐aversion and knowledge enhancement paired with reminders increased the probability of choosing water management practice by 5–10 percentage points, particularly when financial incentives were modest. The added value of nudges and boosts faded once subsidies approached prevailing ceiling levels, suggesting diminishing marginal returns to stacking instruments. These findings suggest that timely, low‐cost behavioural interventions can effectively complement agri‐environmental payments in resource‐constrained settings, providing a scalable and context‐sensitive strategy to accelerate the adoption of climate‐smart rice practices.

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https://doi.org/https://doi.org/10.1111/1477-9552.70038

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@article{shengyi2026,
  title        = {{Promoting Methane Reductions Through Behavioural Nudges and Informational Boosts: A Field Choice Experiment in Japanese Rice Farming}},
  author       = {Shengyi Du et al.},
  journal      = {Journal of Agricultural Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/1477-9552.70038},
}

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R · text relevance †0.50 × 0.4 = 0.20

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