Purpose: The impact of agricultural knowledge transfer (KT) is related to the access to and the quality of services available. Within this context, the allocation of resources in terms of KT offices and the number of advisers are important considerations for understanding KT impact. This quantitative study evaluates the impact of KT resources on farm profitability for clients in Ireland during the recessionary period 2008–2014.
Design/Methodology: Teagasc, the public KT service provider in Ireland, experienced significant office closures (43%) and a reduction in advisers (38%) during the economic crisis, yet client numbers declined only slightly (4.5%). Administrative data are merged with a panel data set on farm-level performance to evaluate the impact through Random Effects estimation.
Findings: The results show that clients gained a 12.3% benefit to their margin per hectare over the period. However, there was a negative effect of 0.2% for each additional client assigned to the adviser which averaged at 9.6%.
Practical Implications: The quantitative findings provide a measure of impact that represents the value for money for the KT service. The key implication is that the client ratio for advisers should be considered when allocating resources and lower ratios would positively impact client margins.
Theoretical Implications: This article outlines the value of quantitative studies to estimate impact in a clear translatable manner which can aid the policy discussion around resource deployment.
Originality/Value: This study evaluates the impact of KT during a recessionary period when resources were constrained, and uses client ratios to examine the spatial effects.
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.
