Intelligent Manufacturing, Digital Finance and Green Technology Innovation in Manufacturing

This study selects 30 provinces in China as research samples for the period from 2013 to 2022(Hong Kong, Macao, Taiwan and Xizang province were excluded). Utilizing the Bartik instrumental variable method and the entropy method, this paper quantifies the robot installation density and Internet development index of each province respectively. Subsequently, it evaluates the development level of intelligent manufacturing from two dimensions: intelligent manufacturing application and intelligent manufacturing conditions. The sample is divided into three groups by robot installation density: high, medium, and low. This study employed panel benchmark regression model and mediating effect model to investigate how intelligent manufacturing affects green technology innovation, and the role of digital finance in the transmission channel. The whole sample analysis revealed that both components of intelligent manufacturing promote green technology innovation with digital finance contributing to the beneficial intermediation effect. Group-specific findings indicate diverse effects. In areas with high-level intelligent manufacturing, robot installation density significantly enhances green innovation; digital finance provides a positive mediation effect; and the Internet development index has no influence. In regions with medium-level intelligent manufacturing capabilities, both dimensions significantly improve green innovation while digital finance has a positive regulatory effect. Conversely, in low-level areas, intelligent manufacturing inhibits green technology innovation, and digital finances’ positive intermediary regulatory impact is lost. Furthermore, the mechanism test reveals that the structure of human capital and the level of low-carbon development serve as critical pathways through which intelligent manufacturing influences green technological innovation. Based on these findings, it is recommended that efforts be intensified to optimize the composition of human capital and accelerate low-carbon development, thereby enhancing the efficacy of intelligent manufacturing in promoting green technological innovation.