Multiple paths for green technology innovation in high-pollution firms driven by heterogeneous regulatory pressure and intrinsic traits: an integrated study of NCA and fsQCA

Purpose Drawing on the resource-based view and institutional theory, this study aims to explore the synergistic effects of internal and external causal conditions on green technology innovation (GTI) in high-pollution firms and advances targeted governance strategies accordingly. Design/methodology/approach This study develops a configurational analysis framework of “heterogeneous regulatory pressure - intrinsic traits”. Based on data from 366 high-pollution listed firms in China, it uses fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) to explore the configurational effects of multiple causal conditions on GTI. Findings The findings reveal that: no individual causal condition is necessary for achieving high or non-high levels of GTI in high-pollution firms; firm size (FS) serves as a core condition across all configurations leading to high GTI, while low FS and low public concern are core conditions in all configurations leading to non-high GTI; three configurations produce high GTI and correspond to three distinct types: reputation-driven-scale advantage supported mode, proactive response mode further driven by informal regulation and proactive response mode further driven by formal regulation; four configurations yield non-high GTI, exhibiting a pronounced asymmetry with the configurations for high GTI. Originality/value This study develops a tailored configurational analysis framework for GTI in high-pollution firms. The framework conceptualizes internal conditions as a systematic influence chain of “strategic guidance-foundational support-dynamic resource assurance”, and integrates both formal and informal regulatory pressures as external conditions. Furthermore, by combining fsQCA and NCA, this study enables a comprehensive analysis of both positive and negative outcome configurations, facilitating an in-depth exploration of the complex mechanisms underlying GTI.