The rural production in Brazil has experienced a significant competitive impact with the stabilization of the economy promoted by the Real Plan in 1994. Indeed, the Brazilian agriculture has achieved efficiency gains in terms of technology, economies of scale and general modernization of the activity in the field. In this context, the professional management of rural production evolved. However, the governance process does not evolve in the same dimension, and the “governance risk” is still poorly addressed in the rural environment, which often limits the potential of operations.

The question of how social enterprises foster social innovation in rural regions remains largely unexplored. In this paper, was developed the assumption that the embeddedness of social enterprises in rural communities and their ability to connect rural communities with supra-regional networks and decision makers are crucial preconditions for generating and fostering social innovation in the countryside.

This paper discusses ICT for Open Innovation (OI) from a capabilities perspective. The study distinguish two types of capabilities for OI: strategic, which need to be developed so that the organization can take advantage of an OI strategy proactively, and operational for the efficient implementation of OI processes.

The European Union (EU) promotes collaboration across functions and borders in its funded innovation projects, which are seen as complex collaboration to co-create knowledge. This requires the engagement of multiple stakeholders throughout the duration of the project. To probe complexity in EU-funded innovation projects the research question is: How does complexity affect the co-creation of knowledge in innovation projects, according to project participants?

This article conceptualizes the diffusion of user innovations from a service ecosystem perspective. With the focus on sustainable innovations, the service ecosystem is evaluated, along with other systemic innovation concepts, as a possible theoretical basis for explaining the first adoption and diffusion of user innovations.

Rather than merely supporting R&D and strengthening innovation systems, the focus of innovation policy is currently shifting towards addressing societal challenges by transforming socio-economic systems. A particular trend within the emerging era of transformative innovation policy is the pursuit of challenge-based innovation missions, such as achieving a 50 % circular economy by 2030. By formulating clear and ambitious societal goals, policy makers are aiming to steer the directionality and adoption of innovation.

So far, numerous studies have exhibited Silicon Valley and other thriving innovation ecosystems by distinguishing special characteristics in which their survival rely on sustaining activities that convert them to specific regions. These regions provide ready-made grounds for networking to be innovative. Meantime, it is struggling for innovations to be transformed into measurable economic results if players encounter a weak network of collaborative relationships in the ecosystem.

Brazil’s influence in agricultural development in Africa has become noticeable in recent years. South–South cooperation is one of the instruments for engagement, and affinities between Brazil and African countries are invoked to justify the transfer of technology and public policies. In this article, examines the case of one of Brazil’s development cooperation programs, More Food International (MFI), to illustrate why policy concepts and ideas that emerge in particular settings, such as family farming in Brazil, do not travel easily across space and socio-political realities.

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.

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions.