The digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.
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.
More than 25 years after the first implementation of Farmer Field Schools (FFS), there is a rich corpus of evidence that participation in FFS improves farmers’ knowledge, skills, and competencies. On the other hand, several studies converge to show that FFS, by strengthening group action, have the potential to build-up social capital among participants and, thereafter, within local communities.
We present a model for research and development (R&D) investment in food innovations based on new plant engineering techniques (NPETs) and traditional hybridization methods. The framework combines uncertain and costly food innovation with consumers' willingness to pay (WTP) for the new food. The framework is applied with elicited WTP of French and US consumers for new improved apples. NPETs may be socially beneficial under full information and when the probability of success under NPETs is relatively high. Otherwise, the traditional hybridization is socially optimal.
There are divergent views on what capacity development might mean in relation to agricultural biotechnology. The core of this debate is whether this should involve the development of human capital and research infrastructure, or whether it should encompass a wider range of activities which also include developing the capacity to use knowledge productively. This paper uses the innovation systems concept to shed light on this discussion, arguing that it is innovation capacity rather than science and technology capacity that has to be developed.
Les leçons et les recommandations mises en avant dans cette publication sont issues d’un atelier de capitalisation de PAEPARD qui a réuni tous les partenaires à Cotonou, au Bénin, du 2 au 6 octobre 2017. Cet atelier a joué un rôle essentiel dans l’évaluation globale de PAEPARD, car il a encouragé les participants à analyser leurs expériences relatives aux PMA afro-européens pour les processus de RAD facilités par PAEPARD durant ces sept dernières années. Lors des discussions, les partenaires ont réfléchi à l’avenir des activités de PAEPARD et à la pérennité de ses réalisations.
The lessons and recommendations outlined in this paper were captured at a PAEPARD Capitalization Workshop with all partners, held in Cotonou, Benin, on 2-6 October 2017. The workshop was key to the overall evaluation of PAEPARD II, as it encouraged participants to analyse and reflect on their experiences of the AfricanEuropean MSP for ARD processes facilitated by PAEPARD over the last 7 years.
LenCD has prepared a joint statement on results and capacity development (presented in this publication), which stresses that meaningful, sustainable results are premised on proper investments in capacity development and that these results materialize at different levels and at different times, along countries’ development trajectory. To provide evidence in support of this statement, LenCD launched a call for submission of stories.
The present case study investigated a policy-induced agricultural innovation network in Brandenburg.
Looking at local learning capacity and systems of relations can help to understand the potential to develop innovation within a specific context. This work contributes to the definition of new actors who are developing innovation for sustainability in rural areas. The study focuses on the knowledge systems of farmers who are applying alternative breeding strategies: it uses a network approach to explore the knowledge system in which individual farmers are embedded in order to understand their specific relational features.