AFINET is one of the seventeen thematic networks that the European Union has financed under the H2020 framework and it is supervised by the EIP-Agri in order to foster innovation in Europe. The main topic of AFINET is agroforestry a practice of deliberately integrating woody vegetation with crops and/or animal systems and the promotion of this practice to foster climate changes. AFINET follows a multi-actor approach linked to the nine Regional Innovations Networks created to identify main challenges and develop main innovations about agroforestry.

This study aims at contributing to a better understanding of the linkage between supply chain performance and possible performance improvement with respect to food quality and safety. Therefore, the paper addresses the question whether the level of collaborative planning and close supply chain relationships could help improve quality and safety of organic supply chains. The study was conducted as a part of the multi-disciplinary EU-wide survey of organic supply chains, carried out in 8 European countries.

The paper is structured as follows. First, definitions and conceptualisations of trust are considered, before moving on review the literature on trust in rural network models of business support. Next, the empirical study design is described, which consisted of case studies of business advice programmes offered to artisanal food enterprises in Northern Ireland and displaying varying degrees of trust. The results of the empirical study are reported and then discussed, with reflections on how trust evolved in each case, and the ways in which trust was lost

This paper estimates the farm level impact of producer organizations’ (PO) membership in Slovakia and the effectiveness of support provided to POs under the EU Rural Development Programme (RDP). The study employ the  Propensity Score Matching and Difference in Differences econometric approach on a database of large Slovak commercial farms for 2006 and 2015. First, our results show that belonging to a PO improves the economic performance of farms in Slovakia.

Communities of Practice (CoPs) are a promising concept for transdisciplinary knowledge co-creation in sustainable agricultural development, but empirical evidence from the farmers’ viewpoint is scarce. This paper contributes to empirical insights on the knowledge creation in CoPs as valued by farmers. Using concepts from CoP theory (domain, community, and practice) and the value creation framework (VCF) developed by Wenger et al. (Promoting and assessing value creation in communities and networks: a conceptual framework.

In this paper the authors used a network perspective to study the micro level of agricultural innovation systems and investigate the different roles and functions that collaborating actors have to perform to spread their innovation both horizontally and vertically. Based on a literature review, we distinguish between three separate network functions: (1) learning and knowledge co-creation, (2) upscaling and institutional entrepreneurship and (3) outscaling and innovation brokerage.

Grassroots initiatives for sustainable development are blossoming, offering localised alternatives for a range of societal functions including food and energy. Research into grassroots organisations often recognises the difficulties grassroots groups face to continue operations. However, there is a need for better understanding dynamics that enable or constrain grassroots organisational survival. Here, we specifically shed light on how such survival is dependent on the organisation’s ability to construct legitimacy.

Proven that the adoption rate of a new product is influenced by the network characteristics of the early adopters, the aim of this paper is to find the network features of the early adopters associated with high adoption rates of a specific new practice: the use of biodegradable mulching films containing soluble bio-based substances derived from municipal solid wastes. The study simulated the diffusion process by means of an agent-based model calibrated on real-world data.