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.

This study aims to explore how the Positive Deviance approach can be adapted to identify and prioritize rural development interventions for diverse farming households that pursue multiple objectives. We describe the adapted approach, consisting of three research steps, and a case study implementation in Tanzania. Based on this experience,  the potential of the Positive Deviance approach for household-specific prioritization of multi-objective development opportunities is discussed

Sustainable intensification (SI) is promoted as a rural development paradigm for sub-Saharan Africa. Achieving SI requires smallholder farmers to have access toinformation that is context-specific, increases their decision-making capacities, andadapts to changing environments. Current extension services often struggle toaddress these needs. New mobile phone-based services can help.

Rapid climatic and socio-economic changes challenge current agricultural R&D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance.