Year: 2025
Type: article
Abstract: Artificial intelligence (AI) has emerged as a pivotal driver in promoting the efficiency of economic growth. The existing studies have predominantly focused on macro- or cross-industry perspectives, and research targeting manufacturers remains relatively limited. This study, based on data from Chinese manufacturing enterprises, elaborates on the impact of AI on total factor productivity (TFP) to address the role of information disclosure quality (IDQ) in this relationship from a non-technical perspective. The findings indicate that AI significantly promotes TFP in manufacturing, a conclusion that holds through a series of robustness checks. And the underlying mechanisms of such promotion lie in increased R&D investment and enhanced innovation output. Heterogeneity analysis reveals that the positive effect of AI is more pronounced in younger manufacturers and those with lower tax burdens. Further analysis suggests that high-quality information disclosure amplifies the productivity-enhancing effect of AI. These findings provide new empirical evidence for understanding the effectiveness of AI applications in manufacturing in an information context, and offer insights for policy-making aimed at advancing intelligent manufacturing transformation, particularly in countries where manufacturing plays a vital role in the national economy.
DOI: 10.14419/2sbxxt66
Author: Chen Cao
Institution: Xi'an Jiaotong University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4415167486
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