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AbstractResource depletion and environmental pollution have seriously restricted the sustainable development of China's economy in recent years. How to transform the extensive growth mode to the intensive growth mode and realize the green development of economy is a great challenge for China. In this paper, we use the non‐radial and non‐angle Slack‐based Model (SBM) considering the undesired output, combined with the Malmquist–Luenberger productivity index, to measure regional green total factor productivity (GTFP). By constructing the green output density function, the theoretical model of the relationship between regional GTFP and industrial agglomeration is deduced, and the theoretical mechanism of the influence of industrial agglomeration on regional GTFP is analyzed. Based on panel data of 243 cities at the prefecture level in China from 2010 to 2019, this article employs the dynamic spatial panel model to empirically estimate the impact of industrial agglomeration on regional GTFP. The empirical results show that regional GTFP shows significant spatial autocorrelation and spatial clustering characteristics. The manufacturing agglomeration has significant negative impact on regional GTFP and produces negative spatial spillover effect on the surrounding regions, but does not produce congestion effect. The producer services agglomeration significantly improves regional GTFP and produces positive spatial spillover effect on the surrounding regions, and leads to congestion effect. The co‐agglomeration of producer services and manufacturing has significantly promoted the improvement of regional GTFP and produces positive spatial spillover effect on the surrounding regions. Finally, this article puts forward policy suggestions on how to promote regional GTFP and achieve green development from the perspective of industrial agglomeration.

All data supporting this study were collected from the PhD Project: The Use of Surface Texturing for Friction Control. The influence of anisotropically shaped textures on the behaviour of sliding friction and sensitivity to sliding direction was evaluated through experimental methods, and performance of textured surfaces was carefully compared with non-textured surfaces. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 644971.