El objetivo del presente trabajo fue evaluar la aplicación de la metodología de redes como una herramienta para el análisis socioeconómico y la transferencia de tecnologías de un sistema producto, como es el caso del sistema de bovinos productores de carne y doble propósito en el Estado de Michoacán
El objetivo de la presente investigación fue analizar a través del tiempo el impacto de la intervención de la agencia de gestión de la innovación (AGI) en pequeños ovinocultores en el Estado de México. Se mapeó la red de 78 productores de ovinos en las delegaciones Atlacomulco y Jilotepec del Estado de México, durante tres momentos de observación: momento I, antes de la intervención (año 2007); Momento II, con la intervención (año 2009) y momento III, posterior a la intervención (año 2011)
Este trabajo presenta una fase teórica orientada a la argumentación que sustenta la naturaleza y el alcance de las redes como estructuras interorganizacionales para apoyar el desarrollo integral con base en las capacidades de investigación, innovación y desarrollo tecnológico localizado. En una segunda fase se formulan las hipótesis de contrastación empírica.
This paper presents results from an action research intervention aimed at strengthening the role of private sector advisers in the Australian agricultural extension system. Private sector advisers participating in the research identified a number of barriers to their effective inclusion in this system.
On-farm agricultural innovation through incorporation of new technologies and practices requires access to resources such as knowledge, financial resources, training, and even emotional support, all of which require the support of different actors such as peers, advisors, and researchers. The literature has explored the support networks that farmers use and the overall importance ranking of different support actors, but it has not looked in detail at how these networks may differ for different farmers.
This paper examines the determinants of participation in an outsourced extension programs and its impact of smallholder farmers' net farm income in Msinga, KwaZulu-Natal, South Africa. A multi-stage sampling technique was used to obtain cross-sectional farm-level data from a sample of 300 farm households, using a structured questionnaire for the interview. The determinants and impacts of participation were estimated using the propensity score matching (PSM) to account for sample selection bias.
The paper is structured as follows. First, definitions and conceptualisations of trust are considered, before moving on review the literature on trust in rural network models of business support. Next, the empirical study design is described, which consisted of case studies of business advice programmes offered to artisanal food enterprises in Northern Ireland and displaying varying degrees of trust. The results of the empirical study are reported and then discussed, with reflections on how trust evolved in each case, and the ways in which trust was lost
The objective of the study was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania independently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, was identified socio-economic household variables that improved model-based predictions of individual farmers’ information preferences.
Digitalisation is widely regarded as having the potential to provide productivity and sustainability gains for the agricultural sector. However, there are likely to be broader implications arising from the digitalisation of agricultural innovation systems. Agricultural knowledge and advice networks are important components of agricultural innovation systems that have the potential to be digitally disrupted.
The paper explores the strength of social networks in the agricultural innovation systems (AISs) in Ghana and the effect of AISs on adoption of improved farm technology. The paper uses social network analysis (SNA) tools to identify, map and analyze the AISs and the two-stage Heckman selection model. Combining qualitative and quantitative methods allows testing the differential effects of social networks on technology adoption in the Ghananian Plantain Sector