Advancing primary data-based social life cycle assessment: Methodological challenges and potential solutions
Year: 2026
Type: article
Study design: Systematic Review
Abstract: Social life cycle assessment (S-LCA) is increasingly applied to evaluate the social impacts of products and organizations. Primary data is preferred for S-LCA as it is specific to the social impacts of the product system under study which can vary greatly depending on the actors involved. However, primary data-based S-LCAs still face many methodological challenges. A systematic literature review was conducted to review the methodological challenges and potential solutions described in primary data-based S-LCA case studies. 68 case studies were identified and included for an in-depth analysis. 65 challenges and 54 solutions were grouped to the four phases: goal and scope, social life cycle inventory, impact/performance assessment, and interpretation. Challenges include relating the defined functional unit to the results and including social impact data for the background system to fully cover the life cycle perspective. Data collection also poses challenges with potential bias and varying perspectives expressed during interviews. There is a lack of standardized reference scales, leading to differences in data collection and results. Further, S-LCA practitioners employ various scoring systems and weighting factors, making it challenging to achieve consistency across assessments. There is also significant variation in how transparent case studies were regarding methodological choices. The identified challenges impact the consistency and comprehensiveness of S-LCA results, thereby emphasizing the need for methodological developments and consistent application. Recognizing and addressing these challenges is essential for enhancing the practical relevance of S-LCA in industry. This study provides recommendations for good practices to ensure the quality of S-LCA moving forwards.
Institution: Technische Universität Berlin
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,770
OpenAlex ID: W7123531810