Unlocking emission-growth synergy in China's manufacturing: The nonlinear role of intelligent transformation and factor reallocation.

To examine how intelligent transformation enables emission-growth synergy in manufacturing, this study develops a nonlinear factor-biased allocation intensity model. This issue is critical for global low-carbon development. The framework decomposes the multiple reallocation effects triggered by intelligent inputs into changes in economic output and carbon emissions. Carbon productivity serves as a composite indicator for evaluating synergy performance. Empirical analysis further verifies and extends theoretical conclusions from both industrial and firm-level perspectives. The findings indicate a significant inverted U-shaped relationship between the level of intelligent inputs and synergy performance. Specifically, intelligent transformation induces three distinct effects: factor substitution, allocation optimization, and rebound effects. Each effect demonstrates differentiated nonlinear dynamics as the intelligent input level varies. When the intelligent input level lies within a specific threshold, an optimal interval for emission-growth synergy emerges. Within this range, intelligent transformation enhances synergy performance by substituting non-energy factors for energy, correcting resource mismatch, and dampening the rebound effect. Furthermore, the direction and magnitude of these effects exhibit considerable heterogeneity across manufacturing sub-sectors and individual firms.