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The behavioural intentions of a sample of livestock farmers in the south-west of England towards new technologies were analysed within a Theory of Reasoned Action (TORA) framework, in order to explore reasons for the apparently low rate at which research-based knowledge is being transferred to the livestock industry. Correlations between components of attitudes (outcome beliefs and evaluations), subjective norms (normative beliefs and motivation to comply) and behavioural intentions were integrated with Positivistic Mathematical Programming (PosMP) to create a set of farm type models, which can predict the potential rate and equilibrium level of uptake of different kinds of technologies. Data relating to techniques for oestrus detection in dairy cows are used to illustrate the analysis and to show how this approach can help improve the targeting of knowledge and technology transfer strategies. Linking the Theory of Reasoned Action findings with the Positivistic Mathematical Programming approach identified where there is a realistic prospect for increasing or accelerating the uptake of a technology, thus helping an agency charged with knowledge and technology transfer to decide where investment in communication is likely to pay off. In the case of MDC observation times, even a 20% change in attitude score among hill and upland dairy farmers would have minimal impact on the numbers adopting; while a similar change among mixed farms would lead to a greater increase. Targeting mixed farms with this particular technology would make more sense than promoting it among upland farmers. The overall findings reinforce the importance of understanding and addressing the prevailing beliefs and values within the objective population.


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