WHAT DRIVES THE EFFICIENCY OF GREEN TECHNOLOGY INNOVATION IN INDUSTRIAL SECTORS? AN ANALYSIS BASED ON THE TOE FRAMEWORK USING NCA AND FSQCA

Abstract

As the nexus of the "innovation-driven" and "green development" national strategies, green technology innovation resonates with China's dual carbon targets and represents an essential pathway toward achieving high-quality development. Existing literature has seldom employed a holistic framework to investigate the complex causal mechanisms through which technological, organizational, and environmental conditions influence green technology innovation efficiency, thereby largely overlooking the configurational effects among these antecedent conditions. To further advance green technology innovation and enhance its efficiency, this study examines China's industrial sectors. Drawing on the Technology-Organization-Environment (TOE) framework, we utilize both Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) on a sample of 38 industrial sectors above a designated size. The analysis explores how six antecedent conditions across the technological, organizational, and environmental dimensions combine to impact green technology innovation. The findings are threefold. First, no single antecedent condition is necessary for achieving high green technology innovation efficiency, although technological factors exert a relatively strong constraint. Second, three distinct configurational pathways lead to high efficiency: a "technology-led, government-supported" path, a "technology-led, independent-innovation" path, and an "environment-technology-organization synergy" path. Third, in an otherwise favorable market environment, ill-suited environmental regulations can suppress innovation efficiency, a context where even strong market demand fails to be effective, suggesting that the impact of organizational conditions is subject to a threshold.