Operationalising S-LCA impact pathways through behavioural modelling: evidence from sustainable coffee production

Coffee is a major source of value creation in many developing countries, yet it is associated with significant sustainability challenges. In this context, Social Life Cycle Assessment (S-LCA) has highlighted the need for a deeper understanding of cause-and-effect relationships, particularly regarding social sustainability outcomes. Against this background, this study investigates the social impact pathway linking the adoption of sustainable agricultural practices (SAP) to farmers’ well-being in coffee production systems. The research builds upon the S-LCA framework and integrates the Theory of Planned Behaviour to identify factors influencing farmers’ adoption of SAP. Structural Equation Modelling (SEM) is then employed to analyse the relationships between behavioural determinants, SAP adoption and perceived well-being. Expert consultations further support the contextual interpretation of the results. The findings indicate that both attitude and perceived behavioural control are positively associated with the adoption of SAP and with improvements in farmers’ well-being. Also, socio-demographic factors significantly influence both behavioural patterns and well-being outcomes. Expert consultations reveal that socio-cultural dynamics help explain several context-specific correlations identified by the SEM analysis. By integrating behavioural theory and statistical modelling into S-LCA, the study advances the operationalisation of Type II social impact pathways. The findings also provide valuable insights for decision-making and capacity building initiatives aimed at promoting SAP adoption in coffee production. More broadly, the study sheds light on socio-ecological trade-offs inherent in agricultural sustainability and offers practical implications for coffee cooperatives and policymakers seeking to maximise positive impacts on farmers’ well-being.