Purpose While extensive research examines the environmental impact of green intellectual capital (GIC), the mechanisms enabling compliance with mandatory sustainability reporting standards remain underexplored. This study conceptualises green accounting capability (GAC) as a dynamic intervening mechanism that translates GIC into sustainability reporting compliance (SRC). Design/methodology/approach We analysed data from 279 sustainability managers at Indonesian manufacturing firms. Our multi-method approach uniquely combines three techniques: (1) partial least squares structural equation modelling (PLS-SEM) to test the measurement model and hypotheses; (2) necessary condition analysis (NCA) to examine bottlenecks; and (3) fuzzy-set qualitative comparative analysis (fsQCA) to reveal equifinal pathways. Findings We found that GAC mediates the relationship between green structural capital (GSC) and SRC, whilst intervening in the relationships between green human capital (GHC) and SRC, and between green relational capital (GRC) and SRC. GRC exhibited the most substantial total effect. NCA reveals evolving bottlenecks, whilst fsQCA identifies five equifinal pathways. The externally validated systems route (GSC•GRC) proved the most prevalent. Practical implications Firms can achieve high SRC through five distinct pathways, enabling resource-optimised strategies rather than universal best practices. The bottleneck analysis provides a 12-month implementation roadmap addressing sequential constraints. Policymakers should recognise pathway plurality rather than mandating uniform compliance approaches. Originality/value This paper makes four theoretical advances: (1) it conceptualises GAC as a dynamic capability distinct from structural capital; (2) it demonstrates configurational equifinality in GIC deployment, challenging universal best-practice assumptions; (3) it reveals sequential bottlenecks, suggesting staged capability development; and (4) it provides the first empirical evidence combining three complementary analytical methods for intellectual capital research.
Wahyuni et al. (Fri,) studied this question.