Abstract Risk and risk preferences belong to the key determinants of investment-based technology adoption in agriculture. We develop and apply a novel approach in which an inverse second order stochastic dominance approach is integrated into a stochastic dynamic farm-level model to quantify the effect of both risk and risk aversion on the timing and scale of agricultural technology adoption. Our illustrative example on short rotation coppice adoption shows that risk aversion leads to technology adoption that takes place earlier, but to a smaller extent. In contrast, higher levels of risk exposure lead to postponed but overall larger adoption. These effects would be obscured if technology adoption is not analyzed in a farm-scale context or considered as a now-or-never decision, the still dominant approach in the literature.