In this chapter, it is applied the CGPE model to analyzing the performance of policy processes with respect to the production of efficient policy choices. Within the CGPE approach participation of stakeholder organizations is modeled in two ways. First, as classical lobbying influence and second as informational influence within a model of political belief formation.

This chapter proposes a network-based framework to analyze and evaluate participatory and evidence-based policy processes. Four network based performance indicators are derived by incorporating a network model of political belief formation into a political bargaining model of the Baron–Grossmann–Helpman type. The application of our approach to the CAADP reform in Malawi delivers the following results: (i) beyond incentive problems, i.e.

Agroforestry (AF) systems have been the focus of numerous research and development projects in southern Africa, yet their adoption rate generally remains low. Employing on-farm, participatory research techniques in southern Malawi, was compared the suitability of three AF-based systems that relay crop the dominant staple, maize (Zea mays), with the perennial legumes Sesbania sesban, Tephrosia vogelii, and Cajanus cajan (pigeonpea).

In agricultural-dependent economies, extension programmes have been the main conduit for disseminating information on farm technologies, support rural adult learning and assist farmers in developing their farm technical and managerial skills. It is expected that extension programmes will help increase farm productivity, farm revenue, reduce poverty and minimize food insecurity.

In this paper, it is reported the results of a case study of the Community Engagement (CE) strategies employed by the Africa Harvest Biotech Foundation International (AH) to introduce tissue culture banana (TCB) agricultural practices to small-hold farmers in Kenya, and their impact on the uptake of the TCB, and on the nature of the relationship between AH and the relevant community of farmers and other stakeholders.

Diffusion of innovations has gained a lot of attention and concerns different scientific fields. Many studies, which examine the determining factors of technological innovations in the agricultural and agrifood sector, have been conducted using the widely used Technology Accepted Model, for a random sample of farmers or firms engaged in agricultural sector. In the present study, a holistic examination of the determining factors that affect the propensity of firms to innovate or imitate, is conducted

The generation of innovations has traditionally been attributed to research organizations and the farmer’s own potential for the development of innovative solutions has largely been neglected. In this chapter, we explore the innovativeness of farmers in Upper East Ghana. To this end, we employ farmer innovation contests for the identification of local innovations. Awards such as motorcycles function as an incentive for farmers to share innovations and develop new practices.

This article explores how conflict-induced displacement influences agricultural innovation processes and systems, and its implications after the return home or permanent resettlement of smallholder farmers. Results show that high rates of agricultural innovation occurred during displacement in the Sudanese Civil War (1983-2005), many of which were maintained afterwards.

The development and scaling of orange-fleshed sweetpotato (OFSP) during the past 25 years is a case study of a disruptive innovation to address a pressing need – the high levels of vitamin A deficiency among children under five years of age in sub-Saharan Africa. When the innovation was introduced consumers strongly preferred white or yellow-fleshed sweetpotato, so it was necessary to create a demand to respond to that need. This was at odds with the breeding strategy of responding to consumers’ demands.

Smartphone technology is promising for the future development of agriculture, as it can facilitate and improve many operational procedures and can also be combined with precision agriculture technologies. Yet, existing research on smartphone adoption in agriculture is scarce. Therefore, this paper empirically explores the factors influencing smartphone adoption by German farmers. The relationship between farmers, farm characteristics and smartphone adoption was analysed using a binomial logit model.