Can Industrial Robot Adoption Improve the Green Total Factor Productivity in Chinese Cities? - Siying Chen; Siying Mu; Yedong Feng; Zhixiong Tan (Systems)
Industrial robot adoption significantly affects economic growth and environmental protection, serving as a critical driver of green development. This paper empirically investigates the effects of industrial robot adoption on green total factor productivity from the perspectives of knowledge flow and spatial spillover using the Chinese cities panel dataset. The findings demonstrate that industrial robot adoption improves local green total factor productivity while generating positive spillover effects on neighboring regions, mediated by strengthened knowledge agglomeration and diffusion capacities. Central cities within urban clusters exhibit significantly stronger impacts on knowledge aggregation and diffusion capabilities than peripheral cities. Furthermore, cities with higher human capital, better transportation infrastructure, and stronger support for the AI industry show a more significant positive effect of industrial robot adoption on knowledge agglomeration and diffusion capabilities. This, in turn, facilitates the flow of knowledge between cities and improves green total factor productivity, thereby contributing to green development. This study provides city-level empirical evidence highlighting how industrial robot adoption drives green development through spatial spillovers and knowledge flow mechanisms.