This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.
This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.
Innovations generally arise out of a network of actors and relationships and network structure determines how effective networks are at fostering innovation. This paper (Part II) presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia. The prototype method used is based on social network analysis methodology. This paper concludes with a final section to identify lessons learnt and makes recommendations for future research.
As global populations continue to increase, agricultural productivity will be challenged to keep pace without overtaxing important environmental resources. A dynamic and integrated approach will be required to solve global food insecurity and position agriculture on a trajectory toward sustainability. Genetically modified (GM) crops enhanced through modern biotechnology represent an important set of tools that can promote sustainable agriculture and improve food security.
Empirical studies on agricultural technology adoption generally divide a population into adopters and nonadopters, and analyse the reasons for adoption or nonadoption at a point in time. In reality, technology adoption is not a one-off static decision, rather it involves a dynamic process in which information gathering, learning and experience play pivotal roles, particularly in the early stage of adoption. A conceptual framework for an adoption pathway is suggested in which farmers move from learning to adoption, to continuous or discontinuous use over time.
Sustainable agricultural intensification requires the use of multiple agricultural technologies in an integrated manner to enhance productivity while conserving the natural resource base. This study analyses the adoption and impacts of sustainable intensification practices (SIPs) using a dataset from Ghana. A multivariate probit (MVP) model was estimated to assess the adoption of multiple SIPs. Moreover, we used a multivalued semi-parametric treatment effect (MVTE) model to estimate the effects of adopting multiple SIPs on maize productivity.
Inadequate feed and nutrition are major constraints to livestock production in sub-Saharan Africa. National and international research agencies, including the International Livestock Research Institute (ILRI), have developed several feed production and utilisation technologies. However, adoption of these technologies has so far been low. Identification of the major socio-economic and policy factors influencing the adoption of improved feed technologies is required to help design policy and institutional interventions to improve adoption.
Numerous innovation platforms have been implemented to encourage the adoption of agricultural innovations and stakeholder interactions within a value chain. Yet little research has been undertaken on the design and implementation of innovation platforms focussing on issues other than market access and aiming to encourage agro-ecological intensification.
The article examines the effect of membership in farmer groups (MFG) on adoption lag of agricultural technologies and farm performance in Burundi, the Democratic Republic of Congo and Rwanda. We use duration and stochastic production frontier models on farm household data. We find that the longer the duration of MFG, the shorter the adoption lag and much more so if combined with extension service delivery. Farmer groups function as an important mechanism for improving farm productivity through reduced technical inefficiency in input use.
The promotion of land, soil and water conservation measures has been a widespread development in sub-Saharan Africa in a bid to tackle degradation and improve productivity. As a result, several governments have launched various campaigns on soil, land and water conservation measures. The aim of this study is to determine some of the factors that influence farmers’ awareness (knowledge) and adoption of land, soil and water conservation practices. Data for this study was collected from 312 households using a questionnaire survey in the Chinyanja Triangle of Southern Africa.