Dual Knowledge Structures in Circular Economy Research: A Multi-Database Bibliometric Framework to Support Sustainable and Life Cycle-Based Circular Solutions

The circular economy (CE) has emerged as a central paradigm for advancing sustainable development; however, most bibliometric studies rely on single-database approaches, potentially generating partial and structurally biased representations of the field. This study addresses this limitation by developing a multi-database bibliometric framework integrating Web of Science (WoS) and Scopus to support more robust, evidence-based circular economy solutions. A total of 17,836 records from Scopus and 13,552 from WoS (2015–2024) were analyzed using the Bibliometrix R-package, combining performance analysis, science mapping, and conceptual structure techniques. The results reveal the existence of dual and complementary knowledge structures: WoS predominantly captures theory-driven, policy-oriented, and strategic research, whereas Scopus expands techno-industrial, application-oriented, and innovation-driven domains. This study demonstrates that database selection functions as an epistemic mechanism shaping knowledge structures, introducing systematic biases when single-source approaches are used. By bridging conceptual and technological knowledge domains, the proposed framework enhances the design, evaluation, and scalability of circular strategies, particularly when aligned with life cycle-based approaches (LCA, S-LCA, and LCSA) and cleaner production systems. These findings contribute to sustainability science by reframing bibliometric structures as operational enablers of solution development, providing a robust decision-support perspective for sustainability transitions, climate change mitigation, and circular economy implementation across diverse sectors.