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.
Digital agriculture is likely to transform productive processes both on- and off- farm, as well as the broader social and institutional context using digital technologies. It is largely unknown how agricultural knowledge providing organisations, such as advisors and science organisations, understand and respond to digital agriculture. The concept of ‘organisational identity’ is used to describe both initial understandings of, and emerging responses, to digital agriculture, which together show how organisations ‘digi-grasp’, i.e.
Growing empirical evidence suggests that innovation platforms can be effective in enhancing agricultural research impact by creating an enabling environment for scaling of innovations such as novel technologies, practices and busines models . However, efforts to understand how these innovation platforms operate to scale innovations are insufficient. Such knowledge is critical for improving the design of agricultural innovation systems, specifically within the context of a rising interest in the innovation platform approach to support the transformation of agriculture across Africa.
Latin America has historically been a vanguard of agroecology. In Nicaragua, an agroecological transition is occurring, with three decades of building a groundswell based on the farmer-to-farmer movement and the recent institutionalization of agroecology in national law. Yet, problems remain with agroecology’s diffusion. We introduce the Technological Innovation Systems approach to examine systemic barriers to the agroecological transition and cycles of blockages caused by barriers’ interactions.
While there is a lot of literature from a natural or technical sciences perspective on different forms of digitalization in agriculture (big data, internet of things, augmented reality, robotics, sensors, 3D printing, system integration, ubiquitous connectivity, artificial intelligence, digital twins, and blockchain among others), social science researchers have recently started investigating different aspects of digital agriculture in relation to farm production systems, value chains and food systems. This has led to a burgeoning but scattered social science body of literature.
This editorial paper brings together different streams of research providing novel perspectives on co-design and co-innovation in agriculture, including methods, tools and organizations.
The transition to a market for agricultural research and knowledge-intensive services presents various challenges for actors in the agricultural knowledge infrastructure, on both the demand side (end users of innovations such as farmers, and the government) and the supply side (providers of research and knowledge-intensive services). New organizational arrangements try to bring together supply and demand in the agricultural knowledge infrastructure. This thesis is about such new organizational arrangements
How do systemic intermediaries obtain legitimate roles for themselves in innovation systems and transition processes? This is still an understudied question in the study of systemic intermediaries. This study started from the observation that roles, or positions, are not given, but emerge in interactions as a negotiated set of rights and obligations.
This study identifies systemic problems in the New Zealand Agricultural Innovation System (AIS) in relation to the AIS capacity to enact a co-innovation approach, in which all relevant actors in the agricultural sector contribute to combined technological, social and institutional change. Systemic problems are factors that negatively influence the direction and speed of co-innovation and impede the development and functioning of innovation systems. The contribution in the paper is twofold.
Esta revisión de la literatura muestra la diversidad de puntos de vista en la caracterización del AIS (visión estructural, visión funcional, visión ba-sada en procesos, visión basada en capacidades). Estas diferentes visiones del AIS se basan en diferentes hipótesis y abarcan diferentes métodos de análisis del AIS. Los académicos consideran que estos puntos de vista son complementarios y útiles para una evaluación operativa del AIS. Debido a esta multiplicidad de puntos de vista analíticos, se ha desarrollado un gran número de métodos.