EXECUTIVE SUMMARY
SLP LINK Project LK0647
Improving the targeting of knowledge and technology transfer in the
livestock sector by understanding farmer attitudes and behaviour
Start date: 01/08/2001
Partners:
Sponsors:
End date: 31/07/2003
Meat & Livestock Commission
Milk Development Council
The University of Reading
Defra
Environment Agency
The project aimed to develop models which can be used to identify strategies for
promoting specific types of technology among livestock farmers. It integrated insights
and methods from social psychology and economic modelling. The Theory of
Reasoned Action (TORA) suggests that behavioural intention is a reasonable
predictor of behaviour and is influenced by the individual’s attitudes and subjective
norm – the degree to which decisions are affected by others’ views. Identifying the
components of these factors suggests possible strategies to encourage uptake.
Positivistic Mathematical Programming (PosMP) models farm decisions under
various sets of resource constraints. Twenty farm type models were constructed
using June census data, Farm Business Survey and Farm Management Handbooks.
Testing these with historical data showed they were able to predict enterprise activity
levels accurately.
Three areas of innovation were selected: oestrus detection in dairy cows,
encouraging white clover in pastures, and optimising the use of N available in slurry
and farmyard manure. Qualitative data from focus groups and telephone interviews
with dairy, sheep and beef farmers were used to design three questionnaires to elicit
variables within the TORA framework. Each questionnaire was administered through
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postal survey to a separate random sample of 500 farmers in the South West of
England with a response rate of 29.3 per cent. Values for the components of
attitudes and subjective norms were calculated for different farm and farmer types.
These were correlated with respondents’ reported behavioural intention to identify the
main cognitive barriers and drivers towards using each of the technologies.
Measures of attitude and subjective norms from the TORA analysis were
incorporated into the farm type models, to generate predictions of future levels of
adoption. These suggest that equilibrium levels of adoption are reached well below
100 per cent within the relevant farm type. However, there is scope for influencing
rates and equilibrium levels of uptake through strategies that address specific
cognitive barriers and drivers. These findings can be used to select specific
audiences, content and appeals for technology transfer, and appropriate sources to
present as championing new technologies or to use as communication channels.
The findings confirm that attitudes towards a technology influence whether farmers
intend to adopt it. Carefully planned communication can help to reinforce attitudes
which support adoption and counteract those which act as barriers. Attitudes vary
between farm and farmer types. Strategies for knowledge transfer should therefore
be tailored to the specific technology and audience. The farming press and local
colleges are suitable channels for promoting white clover among sheep farmers,
while content should highlight that other farmers have been able to adjust timing of
silage cuts to maximise the benefit and have developed successful strategies for
weed control. For methods of improving heat detection, the vet is regarded as a
highly credible source of advice: any promotion, however, should highlight how the
technology enhances rather than displaces the farmer’s own herd management
expertise. With optimising N from slurry/FYM, promotion will need to convince large
scale beef farmers that inconsistent nutrient quality can be managed through
adjusting application rates in response to testing. Local and personal contacts have
more influence on farmers’ intentions than more distant and impersonal sources. In
particular, many farmers are not disposed to follow advice from institutions that they
feel do not fully understand their situation: this is the case for MDC regarding heat
detection and for Defra regarding white clover.
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CONTACT
Professor Chris Garforth
International & Rural Development Department
The University of Reading
Agriculture Building
PO Box 237
Reading
RG6 6AR
Tel: 01189 318134
Fax: 01189 261244
[email protected]
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