Unraveling the path to smart manufacturing advancement: insights from necessary condition and fuzzy-set qualitative comparative analyses

Purpose – Smart manufacturing (SM), a key dimension of the Industry 4.0 paradigm, envisions the transformation of traditional production systems into autonomous, interconnected, and data-driven networks. By leveraging advanced technologies, SM promises to enhance firms’ competitiveness and operational efficiency. Despite its strategic relevance, many companies still struggle to achieve high levels of SM advancement. While the operations management literature has identified several technical and social factors crucial for SM advancement, there is little empirical evidence regarding the relevance of each factor in the SM path. Building on socio-technical systems theory, this study aims to understand the specific sequence in which firms need to deploy technical and social factors to advance in SM, and whether specific combinations of factors enable firms to achieve higher levels of SM advancement. Design/methodology/approach – This study combines Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) using survey data from 234 firms in the automotive component industry. Findings – The results of the NCA suggest that technical and social factors must be deployed in a specific sequence to enable SM advancement. Initial stages of SM adoption require a limited set of baseline factors, while advanced stages necessitate a broader array of enablers. Furthermore, the findings show that firms do not need to maximize every factor; instead, they must ensure a minimum presence of critical factors, suggesting the presence of saturation effects. The fsQCA results complement these insights by showing that certain factors, while not strictly necessary on their own, contribute within specific configurations. This highlights how the interplay of sequencing and tailored combinations drives successful SM advancement. Research limitations/implications – This study advances socio-technical systems theory and the SM literature by reframing factor alignment as a dynamic and evolving process that adapts to operational and strategic priorities at different stages of SM advancement. By identifying the technical and social factors critical at each stage, we offer a deeper understanding of how firms can navigate SM complexities to make progress. Moreover, we enrich operations management research by demonstrating how enablers interact within broader systems, emphasizing the importance of tailoring strategies to context-specific requirements and highlighting stage-specific pathways that drive sustainable SM advancement. Practical implications – The findings provide actionable insights for manufacturing executives, helping them strategically allocate resources and adapt configurations to meet the specific needs of their SM transformation. This facilitates a more effective and streamlined progression toward advanced SM capabilities. Originality/value– This study is the first to provide empirical quantitative evidence on both the sequence in which firms need to deploy technical and social factors to reach higher stages of maturity in SM and the presence of specific configurations of factors that enable firms to achieve advanced levels of SM.