Bridging circular economy business models and rebound effects: Mapping systemic associations with semantic network analysis.

UNLABELLED: While the circular economy (CE) holds significant promise, its potential sustainability gains are often undermined by rebound effects (RE). The field has documented numerous instances of RE in CE business models (CEBM) but lacks a systematic map of the associations between specific business model configurations and rebound mechanisms (i.e., the economic and behavioral causal chains that lead to RE). This research addresses this gap by developing and applying an interpretation-based semantic network analysis linking CEBM patterns to rebound mechanisms via triggers and drivers. The three primary contributions are: (1) a first semantic network of the associations between CEBM patterns and rebound mechanisms, offering important structural insights; (2) a clear positioning of triggers and drivers as the essential, actionable links between CEBM and RE; and (3) an operational causal ontology and complementary analytical procedures to support RE analysis within sustainability transitions. The ontology, semantic network and complementary analytical procedures provide a foundational framework for further explanatory studies in the field and for designing reboundless business models. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s44498-026-00110-3.