This study aims to achieve a better understanding of the agricultural risk and risk management situation in Tanzania with a view to identifying key solutions to reduce current gross domestic product (GDP) growth volatility. For the purpose of this assessment, risk is defined as the probability that an uncertain event will occur that can potentially produce losses to participants along the supply chain.
Despite myriad challenges, Kenya has emerged in recent years as one of Africa’s frontier economies, with headline growth in the most recent decade propelling the country toward middle-income status. Less well understood is how risk dynamics associated with production, markets, and policy adversely impact sector performance, in terms of both influencing ex ante decision making among farmers, traders, and other sector stakeholders and causing ex post losses to crops, livestock, and incomes - destabilizing livelihoods and jeopardizing the country’s food security.
This report is comprised of two volumes: (i) volume one: risk assessment; and (ii) volume two: risk management strategy. Volume one continues with chapter one, which characterizes the recent performance of the agriculture sector, including agro-climatic and market conditions. It also identifies the productive systems used for this analysis. Chapter two describes the main risks in the agricultural sector, capturing market, production, and enabling environment risks along the value chains involved in the selected productive system typologies.
The present study is part of an effort by the World Bank and the State of Bahia to assess agriculture sector risks as a contribution to the strategic economic development and poverty reduction agenda of the state government. It is composed of two phases: an agricultural sector risk identification and prioritization (volume one) and a risk management strategy and action plan (volume two).
In this paper its argued that when flexibly applied and adapted to capture dynamics typical in systems innovation projects, the Log Frame Approach (LFA) ( and logical frameworks have considerable utility to support evaluation for both learning and accountability, and for identifying and addressing institutional logics, which leads to system innovation.
Primary Innovation is a five year collaborative initiative demonstrating and evaluating co-innovation, a systemic approach to innovation addressing complex problems, in five ‘innovation projects’ (active case studies) in different agricultural industries. In defining the elements of co-innovation, Primary Innovation has emphasised nine principles which guide activity in the innovation projects.
This paper describes a process for stimulating this engagement to develop a shared understanding of systemic problems, challenge prevalent institutional logics, and identify individual and collective actions that change agents might undertake to stimulate system innovation. To achieve this the process included (i) multiple actors from the agricultural innovation systems, (ii) steps to prompt reflexivity to challenge underlying institutional logics, (iii) an iterative process of practical experimentation to challenge current practices, and (iv) actions to encourage generative collaboration.
This study identifies systemic problems in the New Zealand Agricultural Innovation System (AIS) that affect the ability of participants in the agricultural sectors to co-develop technologies. We integrate structural and functional streams of innovation system enquiry, gathering data through 30 semi-structured interviews with individuals in Government, industry and research. Interviews explored perceptions of the influence of actors, interactions, institutions, infrastructure, and market structure on the effectiveness of AIS functions.
In this article it is analysed the results of applying a co-innovation approach to five research projects in the New Zealand primary sector. The projects varied in depth and breadth of stakeholder engagement, availability of ready-made solutions, and prevalence of interests and conflicts. The projects show how and why co-innovation approaches in some cases contributed to a shared understanding of complex problems. Our results confirm the context-specificity of co-innovation practices
This paper details the analytical framework used for developing a nested understanding of systemic innovation capacity in an AIS. The paper then introduces the two case studies, along with the data and methods of analysis, followed by a presentation of the results as timelines of configurations of capabilities at different levels of the AIS.