Which farmer(s) should we target? How do extension approaches influence social learning and spread of agricultural innovations?

Theme: 'Agriculture'.

In this research we investigate if and how extension services can influence levels of spread of a new agricultural technology through the selection of different lead farmers, i.e. farmers who implement and maintain demonstration plots of a new technology. These farmers learn about the most effective way to implement the new technology and spread this information to family and friends. Different methods to select lead farmers may have profound effects on subsequent learning on and spread of a new technology. This we propose to investigate in a rural African setting, and analyse if one selection method works better than others (in some locations), in terms of subsequent spread and adoption levels.

We randomly select sixty different villages in our region of study, around lake Kivu in the Democratic Republic of Congo. Here, our local partner implements a regular extension program. In each selected village they promote the use of nitrogen-fixing legumes. However, for the purpose of this approach, the method by which lead and satellite farmers are selected will differs from one village to the other. We thereby built upon approaches to select lead farmers as are commonly used by extension services and compare two different approaches, each in 30 villages. The methods included selection, or election, based on a participatory group meeting, versus a selection in consultation with village heads. To ensure that our research is well connected to actual practice, a final decision on treatments is taken at the start of the project in close consultation with various local stakeholders.

In order to better understand if, and why some selection methods work better than others, for example, in reaching specific farmer groups such as female farmers, or work better in selected areas only, we collect additional data on village and household characteristics before and after the implementation of the extension program. A baseline survey documents village and household characteristics. In addition, we map social networks by documenting which farmers are linked, and the nature of such links, and we measure social characteristics of the villages experimentally that could explain, or could be explained from, characteristics of the households and social networks surveyed. Such measures include trust or the willingness to invest in a public good.

At two points in time after the initial extension activity -one and two years after the initial training- we document levels of awareness, experimentation and adoption levels of the new technologies in an end-line survey. For each village we determine the total number of adopters and number of fields on which the technology is practiced. We use statistical analyses to determine if one of the treatments, i.e. the methods for selecting lead farmers, has led to a significantly higher level of awareness on, or adoption of the technologies.

Subsequent statistical analyses, combining data from the baseline and end-line surveys, is deployed to better understand how information on technologies diffuses, and why diffusion processes may have been different across the treatments. We thereby analyse if variation in the treatment response can be related to specific village characteristics and we determine if the structure of some social networks, and or decisions by others in social networks, has played an important role in facilitating adoption or information spread.

These analyses provide important information on the processes of technology diffusion and serve to identify best approaches of agricultural technology promotion and diffusion. This in turns helps agricultural development programs to increase their reach amongst rural African smallholders.

The central aim of this research project is to learn how extension services can more effectively disseminate agricultural technologies amongst smallholder farmers in Africa. Thus, the eventual impact of this project will be for agricultural development organisations in Africa to achieve a greater impact.

The end-users of this research are the various organisations, either public or private, that promote and diffuse new agricultural technologies to rural smallholders in Sub-Saharan Africa. This research provides information about best methods, depending on local conditions, to select lead farmers when extending new agricultural technologies. Organisations that promote rural development will benefit through improved knowledge on the effectiveness of their operations, can increase the effectiveness of their operations, and potentially reach more farmers with the same level of resources. Moreover, identifying selection methods that enhance learning on new technologies may also prevent costly mistakes, since farmers more quickly identify technologies that are not suited to local conditions or inferior to alternative methods, thereby preventing organisations from further propagating such technologies. We reiterate that this research benefits academics conducting research in the domain of technology diffusion (see "academic beneficiaries"), assisting researchers to improve and refine current extension appraoches.

The beneficiaries of more effective extension operations are the end-users of new agricultural technologies (i.e. smallholder farmers in Sub-Saharan Africa). First, more effective extension approaches imply that more farmers can benefit from limited funds of extension services, either through direct contact with such organisations, or indirectly through an increased chance of a friend or family member being targeted. Next to such benefits across space, benefits to farmers may arise through a reduced time between initial experimentation and adoption (with the full associated benefits). This occurs because methods that facilitate higher levels of social learning could reduce the time needed to identify best local adaptations of a new agricultural technology.

As researchers we are primarily in control of the research process, but through the careful choice of research partners, we increase the chances that our research outcomes translate into true impact (i.e. changes in the way end users of this research - NGOs, international agencies and national extension services- go about their business). This research is implemented in collaboration with researchers from the N2Africa-project, a project disseminating improved legume-technologies to smallholder farmers in eight African countries. We conduct this research project in close collaboration with CIAT-TSBF, the organisation implementing N2Africa in East and Central Africa, but we benefit from the wider network of local extension organisations involved in N2Africa.

We put this network to use through two workshops organised in the course of this project. The first workshop, organised at the start of the research project, is aimed towards identifying research input, and specifically to ensure that the treatments used in our project, i.e. the methods of selecting lead and satellite farmers, are similar and/or comparable to actual practices of local stakeholders. This ensures that we get the research questions right and that we build ownership of the project amongst local stakeholders. A second workshop is organised towards the end of the project whereby we share our own research outputs with involved and other stakeholders. In this way our research output is directly shared with the most important end-users, enabling them to more effectively bring new technologies to smallholder farmers across Africa.