# The Non-Linear Impact of Industry 4.0 on Carbon Emissions in China's Logistics Sector
## 3 Results
### Mediation Analysis  
Mediation analysis was then conducted to provide deeper insights into the mechanisms through which Industry 4.0 influenced carbon emissions. Three primary mediators were identified as the following: production efficiency, business output scale, and information integration capabilities (Table 3). * Production Efficiency--The adoption of advanced Industry 4.0 technologies significantly enhanced production efficiency within the logistics sector. The findings showed that an improvement in efficiency was directly proportional to a decrease in carbon emissions, as logistics functions became more streamlined and consumed less power. Such effectiveness means a lot for controlling the initial increase in emissions demonstrated during the early stages of Industry 4.0 adoption [18]. * Business Output Scale--The scale of logistics operations expanded as firms adopted Industry 4.0 technologies, which came to help achieve higher outflows without wasting more resources. This study also revealed that this scalability affected the per-unit carbon emissions as large-scale operations could leverage economies of scale, which in turn enhanced the efficiency of resource use [19]. * Information Integration Capabilities--Among the strong outcomes of Industry 4.0 was the possibility to connect and analyze data across the whole logistics supply chain. Enhanced information integration works for better decision-making, an appropriate and optimized way of delivering the goods, and the management of inventory; so, it contributes to the mitigation of carbon emissions. This research also proved that data integration serves as a strong mediator, helping logistics enterprises to reach great enhancements in environmental quality due to change in their operational approach [20]. The mediation analysis revealed that production efficiency was a critical mediator in the relationship between Industry 4.0 adoption and carbon emissions. Specifically, a one-unit increase in the Industry 4.0 index was associated with a 0.8-unit reduction in emissions through improved production efficiency (\(p<0.05\)). Similarly, business output scale and information integration capabilities contributed to reducing carbon emissions, but their effects were less pronounced compared to production efficiency (Table 3). These findings suggest that enhancing production efficiency should be a priority in strategies aimed at reducing emissions in the logistics sector. The non-linear impact of Industry 4.0 on carbon emissions is influenced by human factors such as user adaptability and organizational readiness. In the initial stages, the adoption of new technologies can lead to inefficiencies and higher emissions due to insufficient training and suboptimal integration. As users become more adept and systems are finetuned, these negative effects diminish, and the benefits of increased operational efficiency and reduced resource consumption become more pronounced. This underscores the importance of strategic workforce development and adaptive management practices in realizing the full potential of Industry 4.0 for sustainable development. Human factors such as organizational culture and employee skill levels play a critical role in determining the effectiveness of Industry 4.0 technologies. Studies by [PERSON] et al. (2024) demonstrated that human behavior significantly influenced the adoption and integration of digital tools in logistics [19; 20]. Proactive workforce training and engagement can mitigate resistance to technological changes and enhance the positive environmental outcomes of Industry 4.0. Thus, aligning human resources with technological advancements is essential for achieving sustainable logistics operations. The mediation analysis revealed that production efficiency served as a primary mediator by streamlining logistics operations and reducing energy consumption. Business output scale further influenced emissions by leveraging economies of scale.