Effect of digital transformation on enterprises' green innovation: Empirical evidence from listed companies in China

Maogang Tang, Yinlin Liu, Fengxia Hu and Baijun Wu

Energy Economics, 2023, vol. 128, issue C

Abstract: Digital transformation could potentially promote enterprises' green innovation through optimizing resource allocation, innovation, and network effects. However, few empirical studies explore the mechanism of the promotion effect of digital transformation on enterprises' green innovation. In this context, this study explores this mechanism based on technological innovation effects, the learning-by-doing effect, innovation cooperation networks, and financial constraint alleviation. Based on microdata from Chinese A-share listed companies for a time period ranging from 2011 to 2020, this study adopts a multidimensional fixed effects model to conduct empirical analyses. The benchmark results suggest that digital transformation significantly promotes enterprises' green innovation. The findings remain robust after a series of robustness tests and an endogeneity test. Mechanism analysis confirms that digital transformation can facilitate enterprises' green innovation by promoting innovation effects, the learning-by-doing mechanism and spillover effects, innovation cooperation network formation, and financial constraint alleviation. Finally, we suggest that the government should implement a series of support policies, establish collaborative innovation platforms and organizations, explore the application scenarios of digital technologies in green innovation, and increase the construction of and investment in digital infrastructure to promote enterprises' green innovation.

Keywords: Digital transformation; Green innovation; Learning-by-doing; Innovation cooperation network; China (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:128:y:2023:i:c:s0140988323006333

DOI: 10.1016/j.eneco.2023.107135

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