Choice experiments and agent-based modeling demonstrate additive individual adoption but divergent system-level diffusion across four countries, highlighting benefits of policy coupling.
Policy mixes are key to accelerating low-carbon transitions. Yet, how combined policies impact electric vehicle (EV) adoption decisions and scale up to system-level diffusion remains unclear. Here we combine individual-level and system-level analyses to investigate how a carbon tax and information intervention, implemented individually and in combination, impact individual decision-making and system-wide EV diffusion. Across four countries (Mexico, South Africa, the USA and the UK; N = 1,589), we assessed attention towards EV information in EV choice experiments and integrated decision outcome data into a behavioural agent-based diffusion model (ABM). The policies competed for attention but had additive effects on individual EV adoption choices. When scaled through ABM, these behavioural effects produced sub- or superadditive diffusion outcomes depending on the diffusion stage and national context. Moreover, we endogenously coupled the ABM with policy support data. Our findings illustrate that combining policies can boost policy support relative to a tax alone, translating into sustained diffusion trajectories under different policy review scenarios.
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Günther et al. (2026) studied this question.
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