Biodistricts (BDs) leverage the “significant presence” at the local level of organic farming and its supply chain to reach greater economic and environmental viability for farmers. Despite their increasing recognition by policymakers and inclusion in European strategies, empirical evidence of their effectiveness on farms’ competitiveness remains limited. Using Italian FADN data and a post-Keynesian econometric model with dynamic panel data and GMM estimators, this paper explores how BDs impact farm labour productivity growth, which captures both innovation processes and competitiveness. Results suggest being in a BD significantly enhances labour productivity growth compared to outside, highlighting the role of territorial specialisation and collaborative networks. These benefits extend beyond organic farms, suggesting that the district's “industrial atmosphere” facilitates broader knowledge spillovers. Findings call for policies to strengthen social capital and promote farming’s sustainable practices, leveraging the BD as a win-win strategy in enhancing both farms’ labour productivity and sustainability through agglomeration externalities.
This study examines how the share of grassland shapes the relationship between energy productivity and greenhouse gas (GHG) emission intensity in Polish milk-specialised farms operating under mixed-forage systems. The analysis uses a balanced panel of dairy farms observed from 2014 to 2022 in the Polish FADN database. In the first stage, farm-level GHG estimates are used together with FADN input and output data to construct Hicks-Moorsteen indices of energy productivity change and GHG emission-intensity change. In the second stage, the causal effect of grassland share is identified using the Generalised Propensity Score combined with Generalised Additive Models. The results indicate that energy productivity generally increases with the grassland share, although the effect is non-linear and strongest at very low and very high levels. GHG emission intensity follows a U-shaped pattern: it declines as grassland share rises to around 50%, then increases at higher shares. The findings suggest a synergy zone at moderate grassland shares and a trade-off when pasture-based production becomes too dominant.
In recent decades, global value chains (GVCs) have reshaped international trade, cross-border production, and specialization. Yet agriculture and food manufacturing remain underrepresented in comparative regional GVC research. This paper examines how countries in the European Union (EU) and the Regional Comprehensive Economic Partnership (RCEP) integrate into GVCs in these sectors. Distinguishing between forward and backward participation, it identifies structural and institutional drivers of different integration modes. Using inter-country input-output data for 2001–2022 and sector-level decomposition, participation rates are calculated for 42 countries. The results reveal clear sectoral asymmetries: backward participation is much higher in food manufacturing, especially in the EU, whereas forward participation is stronger in agriculture and driven by raw material exports. Regression results show backward participation is mainly explained by income levels, with tariffs mattering only in agriculture. Forward participation is more complex, with significant effects from development-status shifts only in agriculture, not in food manufacturing.
This study analyses an innovative multi-sensor remote sensing technology for the early and accurate detection of crop diseases, viewing technological integration into agriculture as a socio-technical process. The key objective is to identify the multiple economic, environmental and social costs and benefits incurred by the technology, using a novel methodology (process modelling + ACBA). This research highlights the technological contribution to reducing chemical use, lowering input costs, and improving both environmental and human health. Moreover, the integration facilitates the transition toward bio-based economies by decreasing pesticide reliance, conserving biodiversity, and aligning agricultural practices with long-term sustainability objectives. Conversely, it poses several challenges, including high investments, technical complexity, system interoperability issues, and privacy concerns. It should be noted, however, that the study was conducted in an experimental context, and thus the results are limited. Further research is encouraged to conduct the multi-dimensional impact analysis in diverse contexts to enable sustainable technological integration.
Operational Groups (OGs) are a key element of the European Innovation Partnership for Agricultural Productivity and Sustainability (EIP-AGRI), promoting innovative and sustainable agricultural practices. Although communication is crucial to their success, little research has examined its impact on project performance. This study addresses this gap by analysing how three communication actions, namely information, interaction, and participation, affect OG performance. Using partial least squares structural equation modelling and data from an online survey of Italian OG partners, the analysis reveals that participation has the strongest positive effect on project outcomes, surpassing both interaction and information. The findings highlight the need to prioritise member participation to maximise OG effectiveness. However, the limited use of innovation brokers may have constrained engagement. Future project proposals should therefore include dedicated intermediaries and detailed partner engagement plans to strengthen collaboration and enhance the overall impact of OGs within the EIP-AGRI framework.
