This assessment has been conducted over December 2015 to May 2016 under the Powering Agriculture Support Task Order (PASTO). PASTO is funded by USAID and implemented by Tetra Tech ES, Inc. PASTO provides support services to the Powering Agriculture: An Energy Grand Challenge for Development (PAEGC) and its Founding Partners to enable their effective management, monitoring and evaluation of the program.
Innovation policies are considered the long-term strategy to overcome the present systemic crisis. But this crisis is questioning such policies, their presuppositions and institutional arrangements. This questioning includes the Triple Helix theory and its impact on research and innovation policies. The goal is to examine how this theory can respond to theoretical and practical challenges, how the theory needs to evolve in order to fit the present context.
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.
This chapter documents the learning process within the framework of innovation of soil fertility management practices that emerged from the implementation of Participatory Extension Approach (PEA) as part of service delivery reorientation within the Limpopo Department of Agriculture in South Africa.The chapter gives a narrative description of what transpired during the interaction between researchers, extension officers and farmers, the processes involved, the lessons and the conclusion.
We are facing complex societal problems such as climate change, human conflict, poverty and inequality, and need innovative solutions. Multi-stakeholder processes (MSPs) are more and more seen as a critical way of coming to such innovative solutions. It is thought that when multiple stakeholders are able to meet, share experiences, learn together and contribute to decisions, new and innovative ways of dealing with problems are found and turned into action. Still, much remains to be understood about the role and effectiveness of social learning in multi-stakeholder settings.
This research project aims to build ACP capacity to better understand the strengths and weaknesses of the local science, technology and innovation system in the agricultural sector.
This paper introduces a new research framework for social learning, to be able to derive ways to facilitate social learning. The authors report on an explorative interview study to substantiate the framework. One interesting conclusion was that hidden agenda’s were shown to undermine trust, which in turn undermined the social learning process. This explains the importance of openness for social learning. Research results show substantiate the research framework, and show that it can be used to derive methods to facilitate social learning.
Multi-stakeholder (MS) platforms, such as innovation platforms (IP), public-private partnerships (PPP) are becoming more common but what they can achieve in innovation and scaling is limited and depends on different factors. This poster and the broader research paper provide evidence what MS platforms can and cannot achieve in their early phases and give insights about effectiveness and efficiency of Agricultural Research for Development (AR4D) interventions such as CGIAR research programs (CRPs) in low and middle income countries.
The capacity of existing monitoring and decision making tools in generating evidence about the performance of R4D with multi-stakeholder processes, such as innovation platforms (IPs), public private partnerships (PPP), participatory value chain management (PVCM) is very limited. Results of these tools are either contextual and qualitative such as case studies that can not be used by other R4D interventions or quantitative i.e. impact assessments that do not inform what works in R4D.
This booklet grew out of a study on what makes for responsible scaling in the context of agrifood systems, thinking along the same lines as ideas that gave rise to the concept of responsible research and innovation. In our initial exploration, we brought together a number of angles on the topic area (Wigboldus and Leeuwis, 2013; Wigboldus et al. 2016).