Digital Economy, R&D Resource Allocation, and Convergence of Regional Green Economy Efficiency

We looked into the ways in which the digital economy helps to speed up the convergence of environmentally responsible economic efficiency across China’s regions by facilitating the flow and optimization of R&D resources. We measured the mobility of R&D capital and personnel across 30 provinces in China from 2001 to 2022 using a gravity model, assessed the efficiency of green economic using the SBM method, and determined the influence of the digital economy by the use of a fixed-effects model. (1) We identified the σ convergence (the absolute gap between per capita income or per capita economic efficiency levels of different economies gradually decreasing over time) and β convergence (the negative correlation between the rate of economic efficiency increase among various economies or regions and their initial level of economic efficiency) characteristics of green economic efficiency, discovering that the digital economy has sped up the process of convergence of environmentally responsible economic efficiency in regional areas. (2) We found a latecomer advantage in the convergence of China’s green economic efficiency, along with the advancement of the digital economy; that is, the green economic efficiency more quickly converged in less developed regions and regions with fewer resources. (3) The digital economy is able to accelerate the convergence of regional green economy efficiency through the use of internal mechanisms such as the efficient flow of research and development factors and the reasonable allocation of those factors. By identifying the impact of the digital economy on the gaps in regional green economic efficiency from the new perspective of the flow and allocation of R&D elements, this study contributes to the existing body of literature. It also provides new information regarding the ways in which the digital economy is driving the development of China’s green economy. We offer policy suggestions based on our findings to assist regions in achieving a balance between the digital economy and industrial development through the utilization of resources that are specific to the location.