9 pages, In agricultural research for development adoption of new technology tends to be cast in categories: adoption, partial adoption, dis-adoption or non-adoption. While these may serve for pragmatic classification and measures for project success or impact they fail to properly acknowledge the ongoing and independent efforts of farmers (and others) in experimentation and integration of knowledge across a range of sources. This paper explores responses to practices for cattle management introduced during a research project, at project close, and five years after the project has finished. We consider the perceptions and application of new knowledge by farmers, extension staff, and policy makers. By taking a longer-term view, we demonstrate how farming households adapt and integrate knowledge from different sources into their daily practice, influenced by local institutions and changing cultural expectations, as well as external researchers. We also consider the influence of changing government priorities and incentives in steering farm-management decisions. Results suggest that a focus on measures to build capacity and empower farmers with information to adapt and respond to change, regardless of project activities, is a much more important goal and indicator of impact than measuring adoption.
Online from publisher. 3 pages., In 2019 cover crop report, SHP dives into cover crop adoption practices. Summary of findings from a survey among 80 farmers in 11 states in the Soil Health Partnership network.
16pgs, Joint venture (JV) farm structures have the potential to increase the productivity and profitability of traditional family farms. However, such structures are not widely adopted within the farm business community. Furthermore, knowledge on the relative attractiveness of different JV models to farmers is limited. We use a choice experiment to explore what JV structures are preferred by Australian farmers, and how farmers’ socio-demographic and attitudinal characteristics influence the type of JV structure preferred. A latent class analysis revealed significant unobserved preference heterogeneity amongst the population. We identify four latent classes that differ in their preferences regarding the number of JV partners, access to new machinery, and/or the opportunity for additional annual leave. All classes of farmers displayed positive preferences for operational decision-making with other JV partners, although they varied in their preferences towards final operational responsibility. The diversity in preferences shows that there is no ‘one size fits all’ JV design, leaving opportunities for a range of JV decision models. Such flexibility in JV design is likely to have advantages when seeking JV partners, with a significant proportion of the sampled population open to collaborative decision-making models.
