Influence of intelligent manufacturing on innovation efficiency based on machine learning: A mechanism analysis of government subsidies and intellectual capital

Abstract

Intelligent manufacturing (IM) is an advanced model that integrates traditional manufacturing with artificial intelligence to achieve automation, intelligence, and flexibility throughout the production process. Chinese enterprises exhibit a relatively low overall innovation efficiency, with a central focus on IM as a powerhouse strategy. The developmental status of IM is pivotal, as it directly affects the quality standards of China's manufacturing industry. This study employed machine learning techniques to examine whether IM can enhance the innovation efficiency of Chinese enterprises while also exploring the roles of government subsidies and intellectual capital in this process. The empirical findings are as follows. (1) Among Chinese listed companies, a higher level of IM significantly improved innovation efficiency, a result confirmed by robustness tests. (2) Mechanism analysis revealed that IM enhanced innovation efficiency primarily by securing government resource support and fostering intellectual capital. (3) Moderation analysis indicated that the positive correlation between IM and innovation efficiency weakened as the level of financial development increased, whereas intensified market competition strengthened this correlation. This study could provide valuable insights for Chinese manufacturing enterprises aiming to enhance their intelligence levels and promote innovation transformation and upgrading.