A Network Driven Data Collection Approach For Agri Food Value Chains

A key challenge in systematically collecting data on intermediary agri-food value chain actors is that value chains take the form of a network, with actors linked by a series of transactions. Moreover, we have limited ex ante knowledge about the structure or scale of these networks, which complicates the construction of valid sampling frames and limits traditional random sampling approaches to collect data. To address these challenges, we adapt the respondent-driven sampling approach to collect data on intermediary agri-food value chain actors within their transaction-linked network and implement this approach in the arabica coffee and soybean value chains in Uganda and the rice and potato value chains in Bangladesh. We observe meaningful heterogeneity in the structure and scale of agri-food value chains across commodities and countries. Focusing on traders, we show that the respondent-driven sampling approach generates a larger sample of traders who differ in observable characteristics (i.e., value added, enterprise scale, and financial access) compared to a sub-sample of traders generated in a way that mimics traditional random sampling approaches used to study traders. We conclude by discussing how this respondent-driven sampling approach, applied within transaction-linked networks, can provide a useful data collection method for studying intermediary agri-food value chain actors.

This book is the first volume in a collection of contributions arising from a multidisciplinary project developed in the field of agri-food value chain analysis. The respective papers combine a range of disciplines to analyse major agri-food challenges in Europe and South America, offering readers a practical understanding of how risk and uncertainties can be managed by means of validated data and results from agri-food systems analysis. Experts from agronomy, information communication and technology, operations and supply chain management share their findings and propose novel approaches. Given its scope, the book will be of interest to a broad readership who want to learn about current agri-food challenges and requirements, and to professionals whose work involves real-life industry requirements, food and/or farming.

This book addresses major challenges faced by farmers and the technological solutions based on Internet of Things (IoT). A major challenge in agriculture is cultivating and supplying high-quality produce at the best. Currently, around 50% of global farm produce never reaches the end consumer due to wastage and suboptimal prices. The book presents solutions that reduce the transport costs, improve the predictability of prices based on data analytics and the current market conditions, and reduce the number of middle steps and agents between the farmer and the end consumer. It discusses the design of an IoT-based monitoring system to analyze crop environments and a method to improve the efficiency of decision-making by analyzing harvest statistics. Further, it explores climate-smart methods, known as smart agriculture, that have been adopted by a number of Indian farmers.

This book aims to strengthen the skills of professionals who use, manage data for the benefit of farmers and farmers organizations by exposing them to the topics of importance of data in the agriculture value chain and how new and existing technologies, products and services can leverage farm level and global data to improve yield, reduce loss, add value and increase profitability and resilience.

This paper goes beyond the “business” case for agricultural value chain development and presents an economy-wide framework to make the “development” case. We show that there are several key transmission channels that determine the economy-wide impacts of promoting various value chains, including forward and backward economic linkages, price responses, and net employment effects. These impacts all matter for household incomes, poverty, and dietary diversity. Results for Egypt show that agricultural value chain development generates economy-wide growth as well as growth in the agri-food system, but the impacts on employment suggest that agricultural growth can create new (and better) jobs in and beyond the agri-food system, but not necessarily more jobs. The results also show that productivity-driven agricultural growth in all crops is pro-poor and improves nutrition. However, potential adverse effects of livestock-led growth show that growth acceleration in single sectors can be negative, highlighting the importance of a systems analysis or, in our case, an economy-wide analysis. It is clear that no single sub-sector is best at achieving all the development outcomes examined. Moreover, the ranking of value chains by their development outcomes differs across sub-national regions. As such, results from this paper may provide useful decision support for the government and its development partners to select value chains depending on their priority development outcomes.

Using sustainable food value chain development (SFVCD) approaches to reduce poverty presents both great opportunities and daunting challenges. SFVCD requires a systems approach to identifying root problems, innovative thinking to find effective solutions and broad-based partnerships to implement programmes that have an impact at scale. In practice, however, a misunderstanding of its fundamental nature can easily result in value-chain projects having limited or non-sustainable impact. Furthermore, development practitioners around the world are learning valuable lessons from both failures and successes, but many of these are not well disseminated. This new set of handbooks aims to address these gaps by providing practical guidance on SFVCD to a target audience of policy-makers, project designers and field practitioners. This first handbook provides a solid conceptual foundation on which to build the subsequent handbooks. It (1) clearly defines the concept of a sustainable food value chain; (2) presents and discusses a development paradigm that integrates the multidimensional concepts of sustainability and value added; (3) presents, discusses and illustrates ten principles that underlie SFVCD; and (4) discusses the potential and limitations of using the value-chain concept in food-systems development. By doing so, the handbook makes a strong case for placing SFVCD at the heart of any strategy aimed at reducing poverty and hunger in the long run.

The digital agriculture revolution holds a promise to build an agriculture and food system that is efficient, environmentally sustainable, and equitable, one that can help deliver the Sustainable Development Goals. Unlike past technological revolutions in agriculture, which began on farms, the current revolution is being sparked at multiple points along the agrifood value chain. The change is driven by the ability to collect, use, and analyze massive amounts of machine-readable data about practically every aspect of the value chain, and by the emergence of digital platforms disrupting existing business models. All this allows for drastically reduced transaction costs and pervasive information asymmetries that plague the agrifood system. The success of the digital transformation, however, is not guaranteed as the risks it brings are numerous, including those related to data governance and inadequate competition within and between digital platforms. What’s Cooking: Digital Transformation of the Agrifood System investigates how digital technologies can accelerate the transformation of the agrifood system by increasing efficiency on the farm; improving farmers’ access to output, input, and financial markets; strengthening quality control and traceability; and improving the design and delivery of agriculture policies. It also identifies a key role for the public sector in maximizing the benefits of this process while minimizing its risks, through enabling an innovation ecosystem featuring open datasets, digital platforms, digital entrepreneurship, digital payment systems, and digital skills and encouraging equitable technology adoption.