Adapting through innovation is one way for rural communities to sustain and improve their livelihoods and environments. Since the 1980s research and development organizations have developed participatory approaches to foster rural innovation. This paper develops a model, called the Learning-to-Innovate (LTI) model, of four basic processes linked to decision making and learning which regulate rate and quality of innovation. The processes are: creating awareness of new opportunities; deciding to adopt; adapting and changing practice; and learning and selecting.
Recently, Agricultural Knowledge and Innovation Systems (AKISs) have gained considerable attention in scientific and political forums in the European Union (EU). AKIS is considered a key concept in identifying, analysing and assessing the various actors in the agricultural sector as well as their communication and interaction for innovation processes. Using qualitative expert interviews and organizational mapping, the features of national AKISs were investigated in selected EU member states (Belgium, France, Ireland, Germany, Portugal and the UK).
In this paper the authors provide climate smart agriculture (CSA) planners and implementers at all levels with a generic framework for evaluating and prioritising potential interventions. This entails an iterative process of mapping out recommendation domains, assessing adoption potential and estimating impacts. Through examples, related to livestock production in sub-Saharan Africa, they demonstrate each of the steps and how they are interlinked. The framework is applicable in many different forms, scales and settings.
This article starts by describing the evolution of innovation in agricultural research and cooperation for development, including an historical overview of agricultural research for development from green revolution to the re-discover of traditional knowledge. Then the authors analyze participation in innovation processes and make a comparison of innovation systems and platforms targeting the agri-food sector in developing countries. A particular focus is reserved to the European regional networks and to the experience of the USAID Middle East Water and Livelihoods Initiative.
This study aims to assess if AKIS are effectively disseminating integrated soil fertility management (ISFM) knowledge by comparing results from two sites in Kenya and Ghana, which differ in the uptake of ISFM. Social network measures and statistical methods were employed using data from key formal actors and farmers. Their results suggest that the presence of weak knowledge ties is important for the awareness of ISFM at both research sites.
In order for agricultural development to fulfill its potential role as a source of growth and reducer of poverty, it must be constantly renewed through knowledge and innovation. Getting resources into the hands of innovators and providing incentives for producers, agricultural service providers, and entrepreneurs to collaborate in developing and applying new methods and technologies is a priority among institutions concerned with agricultural knowledge.
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.
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.
In developing regions with high levels of poverty and a dependence on climate sensitive agriculture, studies focusing on climate change adaptation, planning, and policy processes, have gained relative importance over the years. This study assesses the impact of farmer perceptions regarding climate change on the use of sustainable agricultural practices as an adaptation strategy in the Chinyanja Triangle, Southern Africa.