What Drives Green Technological Innovation Effectiveness? A Configurational Analysis

To facilitate the successful achievement of the goals outlined in the 2030 Agenda for Sustainable Development, it is imperative to accelerate the advancement of green technological innovation effectiveness (GTIE). This study aims to synthesize three types of drivers and seven concurrent driving factors of green technological innovation effectiveness identified in existing theories, constructing a multiple concurrent mechanism model for such effectiveness. The fuzzy-set Qualitative Comparative Analysis (fsQCA) method is employed to identify the configurational conditions leading to high green technological innovation effectiveness. Furthermore, the robustness of these configurations is verified through panel decomposition, while Necessary Condition Analysis (NCA) is applied to test the necessity of the factors within these configurations and to conduct further examination. The results reveal that high green technological innovation effectiveness is driven by three types of multiple concurrent mechanisms: the “Demand–Pull and Technology–Push and Porter Effect-Driven” configuration type, the “Demand–Pull & Technology–Push-Driven” type, and the “Demand–Pull & Porter Effect-Driven” type. This paper’s contributions are threefold. First, it investigates the configurational drivers of green technological innovation effectiveness. Second, it uses Necessary Condition Analysis (NCA) to identify necessary conditions within these multiple concurrent effects, deepening insight into the drivers. Third, it reveals three patterns driving green innovation in industries and proposes corresponding sustainable manufacturing policy recommendations.