Database-assisted Social Life Cycle Assessment for innovations: Lessons learnt from application

The imperative to integrate social impact metrics into early-stage innovation assessments reflects a broader shift toward holistic value creation. This study introduces a novel, database-assisted Social Life Cycle Assessment (S-LCA) framework specifically tailored for emerging, low Technology Readiness Level (TRL) innovations. By adapting conventional S-LCA methodologies to the uncertain and dynamic context of novel technologies, exemplified through a case study on silver nanowire production within the EU-funded DIAGONAL project (GA 953152), our approach offers a pioneering strategy to quantify latent social risks and supply chain ethical dilemmas. In contrast to traditional S-LCA applications aimed at fully scaled products, our innovative method bridges theoretical constructs with practical imperatives by synthesizing generalized datasets with dynamic, context-sensitive variables. Our findings underscore that, while S-LCA can illuminate previously overlooked social risks, static assumptions and overly generic data may inadvertently constrain engagement with vulnerable regions. Consequently, we propose a reimagined role for S-LCA emphasizing methodological adaptability and nuanced stakeholder consideration. This redefined framework not only advances scholarly debate on the operationalization of S-LCA for emerging technologies but also provides practitioners with actionable insights to inform decision-making within innovation ecosystems. • S-LCA reveals challenges in low-TRL technologies due to data gaps and dynamic systems. • An approximation to the eco-design paradox is performed for social assessments. • S-LCA applied to silver nanowire production reveals key risks in the supply chain. • Critical assessments are proved relevant for context-specific S-LCA. • Database-assisted assessments as a screening S-LCA tool can suffer from biases.