When does smart manufacturing pay off? a configurational investigation based on necessary condition and fuzzy set qualitative comparative analysis

Smart Manufacturing (SM) represents the transformation of traditional production systems into autonomous, interconnected, and data-driven networks. By leveraging advanced technologies, SM holds the promise of substantial improvements in firms’ operational efficiency. Despite such potential, however, many companies struggle to translate SM adoption into performance gains, with initiatives often stalling before reaching scale. To address this gap, this study employs the Technology–Organisation–Environment (TOE) framework to examine how technological, organisational, and environmental factors should be mobilized to successfully reap the performance benefits tied to SM, focusing on both the necessity-based ordering in which they become binding constraints across performance levels and the specific configurations leading to the highest outcomes. Survey data from 234 firms in the automotive components industry are analysed through a combination of Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The NCA indicates that organisational factors are necessary to secure even minimal performance gains from SM adoption. By contrast, technological factors and environmental support are not necessary on their own. Complementary fsQCA results reveal that the strongest performance improvements reported by respondents stem from multiple, equally effective configurations of TOE factors, each reflecting a different balance among technological, organisational, and environmental elements.