The primary aim of this research was to examine the factors influencing behavioral intention of farmers to use ICTs for agricultural risk management. The past research reveals that many researchers had tried to determine factors affecting behavioural intentions of the respondents and TPB has been applied as technology acceptance model in various contexts. However, predicting behavioral intentions to use ICTs for agricultural risk management has not been evaluated from the actual field. Therefore, the data were collected from 360 farmers through multistage cluster sampling technique.
This study aims at exploring scaling up factors that determine the successful up scaling or otherwise of agriculture innovations in Ghana. This is done through a case study approach by analysing selected agricultural innovations to determine the strategies used to scale up as well as factors that account for successes or failures of the scaling up.
This study analyzed the determinants of ICT usage in agricultural value chains among rural youth in Busia County, Kenya. A total of 213 young farmers were randomly selected and interviewed using semi-structured questionnaires. Descriptive statistics and Poisson regression model were applied in data analysis. Findings showed youth participation using ICTs was concentrated at the marketing level of the agricultural chain activities.
This study presents a quasi-experimental analysis of the impact of FairTrade certification on the commercial performance of coffee farmers in Tanzania. In doing so the study emphasises the importance of a well-contextualised theory of change as a basis for evaluation design. It also stresses the value of qualitative methods to control for selection bias. Based on a longitudinal (pseudo-panel) dataset comprising both certified and conventional farmers, it shows that FairTrade certification introduced a disincentive to farmers’ commercialisation.
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This Module is the third in a series of four that address capacity development competencies in FAO. It is intended to enhance FAO’s practices in designing, developing, delivering and evaluating its activities in support of learning in Member Countries, while ensuring that learning leads to sustainable capacity development.
The profound changes in European policy for farms advisory services (FAS) require a period of experimentation and results observation before the new CAP 2021-2027. This paper focuses on Measure 2 of Rural Development Programme (RDP) 2014-2020. The paper is focused on the description of case studies in three Italian regions: Campania, Emilia-Romagna and Veneto. Different Measure 2 – sub-measure 2.1 models are analyzed through a qualitative approach, using a conceptual framework adapted by Birner et al. (2009).
Recent research has analyzed whether higher levels of farm production diversity contribute to improved diets in smallholder farm households. We add to this literature by using and comparing different indicators, thus helping to better understand some of the underlying linkages. The analysis builds on data from Indonesia, Kenya, and Uganda. On the consumption side, we used 7-day food recall data to calculate various dietary indicators, such as dietary diversity scores, consumed quantities of fruits and vegetables, calories and micronutrients, and measures of nutritional adequacy.
This paper reviews the empirical literature on the determinants of farmer adoption of sustainable intensification technologies in maize agri-food systems of the Global South. The attributes of the technology and the dissemination institutions interact with farm/farmer-specific variables, leading to heterogeneous impacts, making the prediction of technology adoption challenging.
Farmer innovation diffusion (FID) in the developing world is not simply the adoption of an innovation made by farmers, but a process of communication and cooperation between farmers, governments, and other stakeholders. While increasing attention has been paid to farmer innovation, little is known about how farmers’ innovations are successfully diffused. To fill this gap, this paper aims to address the following questions: What conditions are necessary for farmers to participate in FID? How is a collaborative network built up between farmers and stakeholders for this purpose?