Angela Guerrero
Dr Angela Guerrero is an environmental social scientist at the Queensland University of Technology. She investigates human behaviour, social-ecological interactions, and collaboration in the planning and management of complex environmental problems, like adapting to climate change, mitigating the impact of agricultural systems on ecosystems, or responding to climate-related disasters.
Session
Social networks are increasingly used to explain variation in agricultural decision-making, including the adoption of innovations, responses to environmental change, and collective action. Recognition of the importance of networks is increasingly shaping intervention programs and extension strategies that seek to accelerate desirable outcomes, particularly by targeting highly connected individuals. However, despite growing interest in both the explanatory and practical applications of social network analysis, the strength of the empirical evidence linking network characteristics to land management and environmental outcomes has not been systematically assessed.
This study provides a systematic review of social network literature in the domain of agriculture to evaluate the empirical evidence supporting claims that social network structure influences environmental outcomes. Agriculture provides an important context for this assessment because it contains one of the longest and most extensive traditions of research examining relationships between social networks and behavioural change. Using a systematic review protocol, we identified and analysed 327 empirical studies examining social networks in agricultural settings.
We first provide a broad assessment of the evidence base, examining the characteristics of studies, analytical approaches, network metrics and outcomes investigated. The review reveals a rapidly expanding field dominated by cross-sectional, survey-based studies. Degree centrality was by far the most frequently measured network metric, appearing in 242 studies and substantially exceeding all other metrics. However, fewer than half of studies measuring centrality reported a relationship between centrality and the outcomes examined. Moreover, among those reporting a relationship, less than half provided strong empirical evidence supporting the claim, suggesting that confidence in effects attributed to centrality may exceed the strength of the available evidence.
We then synthesise findings from the subset of studies providing the strongest evidence to examine when and how centrality appears to influence adoption-related outcomes, the mechanisms proposed to explain these relationships, and the contexts in which they are most consistently observed. We conclude by identifying methodological priorities for strengthening causal inference and advancing the evidence-based use of social network analysis in agricultural and environmental management.