A behavioural agent-based modelling approach for the ex-ante assessment of policies supporting precision agriculture
Open access
Date
2023-10Type
- Journal Article
Abstract
Precision agriculture technologies can help reduce nitrogen losses and the associated negative environmental impacts. As the adoption rate of such technologies in small-scale farming systems is still low, additional policy measures are required to support their broader application. We provide an ex-ante assessment of policy measures (payments for reduced nitrogen, subsidy for the technology or area subsidies) to incentivize the adoption of sensing technologies for site-specific nitrogen fertilization with a specific focus on farmers' behavioural characteristics such as reluctance to change and their individual perception of the policy measures. We combine a bio-economic optimization model with data from a choice experiment, survey, and census data in an agent-based modelling framework. We simulate the impact of the policy measures on farmers' adoption decisions in Swiss wheat production. Simulations suggest that for the same level of nitrogen reduction a results-based payment (paying farmers for reduced nitrogen) is 1.5 times more cost-efficient than area-based subsidies and subsidies for technology use. Our results also suggest that considering how farmers perceive costs and benefits decreases the potential to reduce nitrogen input by ∼20%. We conclude that disregarding behavioural factors such as the perception of the instrument may result in a significant overestimation of the policy effect. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000621732Publication status
publishedExternal links
Journal / series
Ecological EconomicsVolume
Pages / Article No.
Publisher
ElsevierSubject
Precision agriculture; Behavioural factors; Ex-ante policy assessment; Agent-based modelling; Nitrogen efficiencyOrganisational unit
09564 - Finger, Robert / Finger, Robert
Funding
172433 - Reconciling innovative farming practices and networks to enable sustainable development of smart Swiss farming systems (SNF)
Related publications and datasets
Is supplemented by: https://doi.org/10.3929/ethz-b-000619462
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