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We study the identification and estimation of key parameters in a basic model of technology adoption when specifically collected information on subjective beliefs and expectations about the technology’s impact is available. We discuss identification with both non-parametrically and parametrically specified utility as well as parametric and semi-parametric specifications for observed heterogeneity. We propose parametric and semi-parametric estimation methods to recover underlying preferences and use the model to study the adoption of bednets among poor households in rural Orissa (India). We carry out counterfactual exercises to examine the effects of price and belief changes on net ownership decisions. The results suggest that net purchase decisions are relatively insensitive to changes from current prices and beliefs. The methods proposes here should have applicability to other discrete choice settings with non-linear indices.