Leveraging Industry 4.0 technologies for organizational sustainability performance in Chinese firms: an NRBV-mediated model advancing UN SDGs 9 and 12

The rapid integration of Industry 4.0 technologies offers new pathways for Chinese manufacturers to reconcile operational efficiency with environmental stewardship. Grounded in the Natural Resource-Based View (NRBV), this study investigates how digital technologies, Artificial Intelligence/Machine Learning (AIA), Digital Twin Usage (DTU), IoT Integration (IOTI), and Green Technology Adoption (GTA), serve as strategic resources to enhance Sustainable Manufacturing Practices (SMP) and drive Organizational Sustainability Performance (OSP). Analyzing data from 719 firms through structural equation modeling (SEM), the findings reveal significant direct effects of AIA, DTU, GTA, and IOTI on SMP, with SMP fully mediating their impact on OSP. The study advances NRBV by demonstrating how digital technologies function as dynamic capabilities that reconfigure operational practices to achieve sustainability outcomes. Managers should prioritize integrated IoT networks for real‑time monitoring, AI/ML for predictive quality control, digital twins for lifecycle optimization, and green‑technology implementations for energy and material efficiency. While this study does not directly measure SDG-specific indicators, the observed improvements in resource efficiency, emissions reduction, lifecycle optimization, and eco-efficient production practices are conceptually consistent with the objectives of UN Sustainable Development Goals (SDG 9 and 12). Accordingly, SDG alignment should be interpreted as an inferential linkage grounded in firm-level sustainability outcomes rather than as direct evidence of SDG attainment.