Against the backdrop of the United Nations Sustainable Development Goals (SDGs), innovation-driven development serves as the core engine of long-term sustainable economic development, while resource misallocation has emerged as a critical bottleneck constraining sustainable innovation and coordinated regional development. Grounded in the neoclassical theory of factor allocation, this paper incorporates capital misallocation, labor misallocation and the digital economy into a unified analytical framework. Using China’s provincial panel data spanning 2001 to 2024, we systematically investigate the impact effects, underlying transmission mechanisms and regional heterogeneity of resource misallocation and the digital economy on scientific and technological innovation through benchmark regression, robustness tests and heterogeneity analysis. The results show that resource misallocation exerts a significant and robust inhibitory effect on technological innovation, with the inhibitory effect of capital misallocation being more pronounced than that of labor misallocation. The digital economy has a significant positive driving effect on technological innovation, and it can also indirectly boost technological innovation by alleviating resource misallocation, with its mitigating effect on resource misallocation presenting obvious structural differences and a stronger correction effect on capital misallocation than on labor misallocation. Economic growth and technological innovation form a mutually reinforcing “growth-innovation” virtuous cycle. In addition, the innovation effects of both resource misallocation and the digital economy exhibit significant regional heterogeneity, where the digital economy’s innovation-driven effect and misallocation-mitigating effect are notably stronger in eastern China than in the central and western regions. The theoretical contribution of this paper lies in constructing a transmission mechanism framework of “digital economy to resource misallocation to technological innovation”, which enriches the connotations of factor allocation and innovation theories. Its practical value is to provide policymakers with differentiated development paths for the digital economy and optimization strategies for factor allocation, thus facilitating the effective implementation of the innovation-driven development strategy.
Guo et al. (Thu,) studied this question.