Exploring the networks of knowledge retrieval in the farm biogas sector in Tuscany, Italy

Feed-in tariffs for electricity production from biomass (2008) have boosted biogas diffusion in livestock intensive areas of northern Italy (Carrosio, 2013) and promoted its adoption in regions (NUTS2) where arable farming is the major agricultural system. Among those latter regions, Tuscany has experienced the most impressive increase in the number of biogas plants. The diffusion of agroenergy systems in arable areas is likely to drive land and water use change from food and feed to energy production, thus raising sustainability concerns. To date, agricultural economists have mainly approached the understanding of the process of agroenergy adoption on farm through econometric or mathematical programming models. Beside rational behaviour, both methodologies assume that farmers can access perfect information, thus missing to investigate knowledge transfer and the role of research and extension services in technology adoption and diffusion. Another strand of literature builds on Granovetter (1985) and Uzzi (1996), thereby acknowledging the embeddedness of economic activities and recognising that stakeholder positions within the network influence adopter ability to access information, knowledge, resources and technology (Inkpen and Tsang, 2005). This study draws on network literature and focuses on the communication network behind biogas adoption across farms in Tuscany, for identifying the interest groups involved in knowledge flow, i.e. the Agricultural Knowledge and Innovation System, as well as highlighting their functions and mutual relationships (World Bank, 2006; Edquist, 2005). The methodology lies on social network analysis of primary data and considers cohesion, centrality, and structural hole indexes. Data collection (spring-summer 2015) encompasses exploratory interviews with experts and survey to adopters. Respondents either own and manage the plant (farmers), or are in charge of plant operations management, working for Energy Service Companies (ESCos). Farmers and ESCos have different knowledge-seeking attitudes. The former holding a gating position for more sources, channels, and recipients of knowledge than the latter. Farmers, in turn, are likely to acquire knowledge from nodes with high betweenness centrality, such as public-funded projects, which improves its gating potential. This could provide farmers with grater resilience compared to ESCos. Structural hole metrics approximate for nodes’ brokerage abilities and highlight that the brokerage potentialities of ESCos are higher.