This paper addresses the question how public-private partnerships (PPPs) function as systemic innovation policy instruments within agricultural innovation systems. Public-private partnerships are a popular government tool to promote innovations. However, the wide ranging nature of PPPs make it difficult to assess their effects beyond the direct impacts they generate for the partners.
Although agricultural innovation systems (AIS) have recently received considerable attention in academic and development circles, links between an AIS's regional specifications and structural-functional analysis have been neglected. This paper aims to understand how regional and structural dimensions determine systemic problems and blocking mechanisms that, in turn, hinder a regional AIS's function.
This paper evaluated the implementation of an initiative for promoting risk-based approaches to improve food safety management in Vietnam. A Taskforce of Risk Assessment for Food Safety (Taskforce) was formed and consisted of researchers working on risk assessment and food safety, and representatives of the related ministries of Health and of Agriculture. We used the OECD Development Assistance Committee Evaluation Criteria as a framework for assessing the impact of the Taskforce with five evaluation areas – relevance, effectiveness, efficiency, impact and sustainability.
This paper assesses the role of economic, social, political and organizational processes on technology adoption in smallholder livestock production systems based on innovation systems perspective. Functions of the innovation systems framework was used to assess the missing links in the dairy sector value chains
This paper makes a contribution to understanding the impact of relational trust, as embodied within bonding, bridging and linking social capital, on rural innovation. Using cases of multi-stakeholder groups who work together on shared problems it explores how social capital and different forms of trust (companion, competence and commitment) influence rural innovation processes. Looking at both the ‘bright’ and ‘dark’ side of social capital, our focus is on how social capital and trust constrain and enable the process of innovation.
This paper makes a contribution to understanding the impact of relational trust, as embodied within bonding, bridging and linking social capital, on rural innovation. Using cases of multi-stakeholder groups who work together on shared problems it explores how social capital and different forms of trust (companion, competence and commitment) influence rural innovation processes. Looking at both the ‘bright’ and ‘dark’ side of social capital, our focus is on how social capital and trust constrain and enable the process of innovation.
On-farm agricultural innovation through incorporation of new technologies and practices requires access to resources such as knowledge, financial resources, training, and even emotional support, all of which require the support of different actors such as peers, advisors, and researchers. The literature has explored the support networks that farmers use and the overall importance ranking of different support actors, but it has not looked in detail at how these networks may differ for different farmers.
This paper comparatively analyzes the structure of agricultural policy development networks that connect organizations working on agricultural development, climate change and food security in fourteen smallholder farming communities across East Africa, West Africa and South Asia.
This study proposes a modelling digital marketplace with FinTech enabled especially crowdfunding and payment system in order to support agriculture’s sustainability. The model connects all actors (farmers, landowners, investors, and consumers) into a platform that can promote transparency, empowerment, resourcefulness, and public engagement in agriculture
This paper examines the determinants of participation in an outsourced extension programs and its impact of smallholder farmers' net farm income in Msinga, KwaZulu-Natal, South Africa. A multi-stage sampling technique was used to obtain cross-sectional farm-level data from a sample of 300 farm households, using a structured questionnaire for the interview. The determinants and impacts of participation were estimated using the propensity score matching (PSM) to account for sample selection bias.