The roles of attitudes, social influence and human behaviour in the adoption of strategies to improve lamb survival by sheep producers

Joanne Elliott

    Research output: ThesisDoctoral Thesis

    219 Downloads (Pure)

    Abstract

    [Truncated abstract] Current lamb mortality rates on Australian farms range between 15 and 35 percent, and pose financial risks for individual farmers and for the industry. Research institutions and industry research and development corporations have prioritised lamb survival and, as such, have invested heavily in research to improve lamb survival rates. The resulting management strategies, including pregnancy scanning, the provision of shelter and focussed-feeding, have been shown to reduce lamb mortality by up to 50 percent. However, the adoption of these strategies by farmers has been low, with no appreciable increase in lamb survival rates over the last century. This thesis investigates the factors influencing farmers’ adoption of strategies to improve lamb survival, with the aim of increasing lamb survival rates. A mixed-method study was undertaken, incorporating both qualitative and quantitative research methods in order to strengthen the foundations of the research. The first, qualitative, phase of the study involved a series of focus groups designed to elicit sheep producers' beliefs about lamb mortality and strategies to improve lamb survival rates. The findings from this phase of the research were used to develop a quantitative survey, used in the second phase of the research. Behavioural models from the marketing and social psychology disciplines, such as the Theory of Planned Behaviour and the Model of Goal-directed Behaviour, were used as the basis of the survey and examined for their applicability to the adoption of lamb survival strategies, in particular the use of pregnancy scanning. Structural equation modelling was used in the data analysis to quantify the ability of the behavioural models to explain variation in farmers' intentions to adopt lamb survival strategies, and latent class regression was used to identify sources of variation between farmers.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Publication statusUnpublished - 2012

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