Big data technology application and carbon emission efficiency of manufacturing enterprises.

With the application and popularization of artificial intelligence, the Internet of Things and other technologies, the role of big data technology in the production and operation processes of enterprises is becoming more and more important. Exploring the mechanism of the influence of big data technology application (BDTA) on carbon emission efficiency (CEE) of manufacturing enterprises can provide a new pathway to promote the realization of the dual-carbon goal. We theoretically analyze the role channels of BDTA in influencing CEE of manufacturing enterprises from the perspectives of green innovation and internal control quality, and empirically test it with the listed companies in China's manufacturing industry from 2010 to 2023 as the research subject. The study reveals that BDTA can improve CEE of manufacturing enterprises, and the regression results are still robust after a series of robustness tests and endogeneity tests. BDTA improves CEE of manufacturing enterprises by fostering green innovation and enhancing internal control quality. The results of the heterogeneity analysis indicate that BDTA has a more significant effect on improving CEE in non-state-owned enterprises, high-tech enterprises, and enterprises with low market concentration.