Jakku, Emma (author), Taylor, Bruce (author), Fleming, Aysha (author), Mason, Claire (author), Fielke, Simon (author), Sounness, Chris (author), and Thorburn, Peter (author)
Format:
Journal article
Publication Date:
2019-12
Published:
Netherlands: Elsevier
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 203 Document Number: D12272
13 pages, Advances in Smart Farming and Big Data applications have the potential to help agricultural industries meet productivity and sustainability challenges. However, these benefits are unlikely to be realised if the social implications of these technological innovations are not adequately considered by those who promote them. Big Data applications are intrinsically socio-technical; their development and deployment are a product of social interactions between people, institutional and regulatory settings, as well as the technology itself. This paper explores the socio-technical factors and conditions that influence the development of Smart Farming and Big Data applications, using a multi-level perspective on transitions combined with social practice theory. We conducted semi-structured interviews with 26 Australian grain farmers and industry stakeholders to elicit their perspectives on benefits and risks of these changes. The analysis shows that issues related to trust are central concerns for many participants. These include procedural concerns about transparency and distributional concerns about who will benefit from access to and use of "farmers' data". These concerns create scepticism about the value of `smart' technologies amongst some industry stakeholders, especially farmers. It also points to a divergence of expectations and norms between actors and institutions at the regime and niche levels in the emerging transition towards Smart Farming. Bridging this divide will require niche level interventions to enhance the agency of farmers and their local networks in these transactions, and, the cooperative design of new institutions at regime level to facilitate the fair and transparent allocation of risk and benefit in farming data information chains.
10 pages, Enormous quantities of data are generated through social and online media in the era of Web 2.0. Understanding consumer perceptions or demand efficiently and cost effectively remains a focus for economists, retailer/consumer sciences, and production industries. Most of the efforts to understand demand for food products rely on reports of past market performance along with survey data. Given the movement of content-generation online to lay users via social media, the potential to capture market-influencing shifts in sentiment exists in online data. This analysis presents a novel approach to studying consumer perceptions of production system attributes using eggs and laying hen housing, which have received significant attention in recent years. The housing systems cage-free and free-range had the greatest number of online hits in the searches conducted, compared with the other laying hen housing types. Less online discussion surrounded enriched cages, which were found by other methods/researchers to meet many key consumer preferences. These results, in conjunction with insights into net sentiment and words associated with different laying hen housing in online and social media, exemplify how social media listening may complement traditional methods to inform decision-makers regarding agribusiness marketing, food systems, management, and regulation. Employing web-derived data for decision-making within agrifood firms offers the opportunity for actionable insights tailored to individual businesses or products.
Online from publisher website. 5 pages., Describes a new Food Trust Consortium , run by IBM, using blockchain technologies to improve food traceability.
Force, J.E. (author / Department of Forest Resources College of Forestry, Wildlife and Range Sciences, University of Idaho, Moscow, ID) and Department of Forest Resources College of Forestry, Wildlife and Range Sciences, University of Idaho, Moscow, ID
Format:
Conference paper
Publication Date:
1984
Published:
UK
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 54 Document Number: C01051
Notes:
Phase 2, In: Moeller, G.H. and Seal, D.T., eds., Technology transfer in forestry : proceedings of a meeting of the International Union of Forestry Research Organizations, subject group s608; 1983 25 July - 1 August. London : Great Britain Forestry Commission, 1984. (Forestry Commission Bulletin No. 61) p. 74-80.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 30 Document Number: D10562
Notes:
3 pages., via blog from Janzen Ag Law - online via AgriMarketing Weekly., Since big data arrived in agriculture a few years ago, I have watched companies struggle with how to address farmers' concerns with ag data privacy, security, and control. Some companies have started with a clean sheet of paper and drafted agreements that reflect what they actually do. Others have taken a short cut by cutting and pasting agreements from other industries. The result is that contracts for ag data collection, use and sharing are inconsistent and often miss the point-to communicate the company's intentions with users.
