The effect of dairy farming on water quality in New Zealand streams has been identified as an important environmental issue. Stream fencing, to keep cattle out of streams, is seen as a way to improve water quality. Fencing ensures that cattle cannot defecate in the stream, prevents bank erosion, and protects the aquatic habitat. Stream fencing targets have been set by the dairy industry. In this paper the results of a study to identify the factors influencing dairy farmers' decisions to adopt stream fencing are outlined. Qualitative methods were used to gather data from 30 dairy farmers in four New Zealand catchments. Results suggest that farm contextual factors influenced farmers' decision making when considering stream fencing. Farmers were classified into four segments based on their reasons for investing in stream fencing. These reasons were fencing boundaries, fencing for stock control, fencing to protect animal health, and fencing because of pressure to conform to local government guidelines or industry codes of practice. This suggests that adoption may be slow in the absence of on-farm benefits, that promotion of stream fencing needs to be strongly linked to on-farm benefits, and that regulation could play a role in ensuring greater adoption of stream fencing.
Abstract. In this article, the relationship between individual productivity in research, as measured by an index of publications produced, and their preferences and perceptions about research-related issues is explored. A sample of t34 Australian university economists were classified as low, average and high in respect of their publication performance using cluster analysis. Discriminant analysis was then used to see whether membership of these groups was associated with items representing individuals' preferred research approach, their involvement in a range of research-related activities, the things which they felt constrained their research and their perceptions of the benefits of their position which might be conducive to research.Our results show that there was a relationship between these items and group membership, and therefore productivity. Highly productive researchers made deliberate choices about the type of research they undertook in order to enhance their career advancement; they were heavily involved in a number of areas of research activity; they felt relatively few constraints on their research by comparison with low producers; and they enjoyed the freedom and challenge of their positions. These results imply that research performance is more a function of individual motivation than resource support.
Climate change is likely to increase the variability in environmental conditions that Australian farmers will have to contend with, potentially threatening farm viability. In this research we use general systems theory to describe how farmers use the three types of system regulators (aggregation, error control and anticipation) to manage variability in the environment. We present codling moth management as an example of system regulation in agriculture. We found that adaptation to climate change is likely to require that farmers modify the structure of their farm systems by changing their combination of system regulators. Decisions regarding changes in structure may favour certain types or system regulators over others. This has implications for policy development to support farm adaptation.
Governments around the world are seeking to slow the spread of Covid-19 by implementing measures that encourage, or mandate, changes in people’s behaviour. These changes include the wearing of face masks, social distancing, and testing and self-isolating when unwell. The success of these measures depends on the commitment of individuals to change their behaviour accordingly. Understanding and predicting the motivation of individuals to change their behaviour is therefore critical in assessing the likely effectiveness of these measures in slowing the spread of the virus. In this paper we draw on a novel framework, the I3 Compliance Response Framework, to understand and predict the motivation of residents in Auckland, New Zealand, to comply with measures to prevent the spread of Covid-19. The Framework is based on two concepts. The first uses the involvement construct to predict the motivation of individuals to comply. The second separates the influence of the policy measure from the influence of the policy outcome on the motivation of individuals to comply. In short, the Framework differentiates between the strength of individuals’ motivation and their beliefs about the advantages and disadvantages of policy outcomes and policy measures. We found this differentiation was useful in predicting an individual’s possible behavioural responses to a measure and discuss how it could assist government agencies to develop strategies to enhance compliance.
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