Abstract

Digital input, as an important engine for high-quality development, has provided new impetus for green transformation and development of manufacturing enterprises. In this study, unique panel data samples matched from the Global Multi-regional Input-output Database from 2000 to 2014, the Chinese Industrial Enterprise database, and the Chinese Industrial Enterprise Pollution Database are used to estimate the green productivity of Chinese manufacturing enterprises by adopting a non-radial and non-angular SBM model that considers unexpected outputs. Furthermore, a panel Tobit model is adopted to empirically test the impact of digital input on the green productivity of manufacturing enterprises. The research results indicate that: (1) Digital input has a significant positive impact on the green productivity of manufacturing enterprises, and a series of robustness tests have confirmed this conclusion. This research conclusion provides micro evidence and empirical support for empowering the green transformation of manufacturing enterprises with digital economic development. (2) The heterogeneity analysis indicates that, for different enterprises, digital input contributes more significantly to green productivity in foreign-funded enterprises, state-owned enterprises, and larger-scale enterprises. Regarding industry types, digital input positively contributes to green productivity only in labor-intensive and knowledge-technology-intensive manufacturing enterprises. In terms of regions, the contribution of digital input to the green productivity of enterprises in the east and central regions and regions with higher levels of industrial agglomeration is more significant. Heterogeneity analysis from different perspectives can help optimize enterprise choice behavior and green transformation development strategies, thus achieving better digital empowerment. (3) Further mechanism tests reveal that digital input promotes the improvement of green productivity of manufacturing enterprises through the effects of technological progress, factor structure optimization, and innovation, thereby providing a feasible path for relying on digital transformation to promote the improvement of green productivity of manufacturing enterprises.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call