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.
The study relies on the activities performed within EU funded Horizon 2020 project, AgriSpin (www.agrispin.eu), specifically for the case of Cilento Bio-district in Campania region, Italy. The methodology is centred on the “cross-visit method” developed within the AgriSpin Project, based on direct observation, interviews with relevant actors and analysis of grey literature.
This paper explores the potential of Actor Network Theory (ANT) in understanding how the process of interaction and translation between human and non-human actors contribute to the development, adoption and diffusion of science-based innovations linked to the transition to organic farming. The study relies on two case studies, the French Camargue case covering a range of technical and social innovations, and the case from Bulgaria focusing on the development of a technical and product innovation, i.e. a veterinary product for organic beekeeping.
This paper is an inquiry into the process of setting up a national, multi-stakeholder project collaboration aimed at stimulating the role of the private sector in the Australian agricultural extension and innovation systems.
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.
In the AgriSpin project (2015-2017) fifteen organisations involved in innovation support tried to understand better how each of them made a difference in helping farmers to innovate. In principle, each partner organisation hosted a Cross Visits of 3 – 4 days, to present a number of interesting innovation cases in which it was involved. The visiting team, composed of colleagues from other partner organisations, interviewed key actors in each case, and gave feedback about pearls, puzzlings and proposals in these innovation processes.
This paper is part of the H2020 project AgriLink “Agricultural Knowledge: Linking farmers, advisors and researchers to boost innovation”. It presents and develops the concept of ‘microAKIS’, i.e. the micro knowledge- and innovation-system that farmers personally assemble to manage their agricultural practices and ensure sustainability.
This research is dedicated to illuminating the relationship between knowledge and innovation within agrifood supply chains (ASCs) – although insightful and informative – is marked by conceptual and methodological issues that restrict our ability to understand the ways knowledge affects innovation and vice versa. In this work, adopting a systems approach to ASCs and synthesizing literature from different fields of study, we discuss the metaphors that guide research in this area, and we propose an alternative conceptualization of ASCs
The policy implications of cumulative innovation are essential to consider in order to mitigate risk and capitalise on opportunities as digitalisation transforms agriculture. One project that involves imagining the future of the sector and aims to develop the necessary tools and infrastructure is the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Digiscape Future Science Platform (FSP). This paper explores the policy framework encompassing these tools and elucidates considerations for future governance in Australia.
It is adressed in this paper opportunities of Q Methodology for empirical agricultural innovation studies. In the systems perspective on innovation, multi-actor innovation networks are seen as a key strategy to successful innovation. Given the several types of actors involved, the scientific and policy literature points at the need for ‘innovation brokers’ to build capacity for collective innovation and prevent innovation network failures.