Abstract:
This study aims to assess the impact of digital transformation (DT) on the green innovation
efficiency of heavy-polluting enterprises (HEGIE), employing the Super-SBM model as the core
methodology. Using panel data spanning from 2012 to 2022, this study investigates the
relationship between DT and HEGIE and its underlying mechanisms. The findings reveal a
positive relationship between DT and HEGIE, highlighting DT as a catalyst for enhancing
environmental sustainability within these enterprises. Heterogeneity analysis implies that firms in
the growth and maturity stages and firms located in the East and Central regions are more likely
to benefit from DT in terms of green innovation efficiency. Mechanism analysis reveals that DT
boosts HEGIE by facilitating the acquisition of knowledge resources, increasing high discretion
slack resources while reducing low discretion slack resources. This study provides empirical
evidence for understanding how DT contributes to green innovation capabilities from the
perspectives of knowledge capital optimization and resource allocation, which inspires heavypolluting
enterprises to focus on maximizing the benefits from DT measures, thereby empowering
their goal toward achieving green transformation.
Keywords: Digital Transformation; Green Innovation Efficiency; Super-SBM Model; Heavypolluting Enterprises; Knowledge Resources; Slack Resources
Abstract: This study aims to assess the impact of digital transformation (DT) on the green innovation efficiency of heavy-polluting enterprises (HEGIE), employing the Super-SBM model as the core methodology. Using panel data spanning from 2012 to 2022, this study investigates the relationship between DT and HEGIE and its underlying mechanisms. The findings reveal a positive relationship between DT and HEGIE, highlighting DT as a catalyst for enhancing environmental sustainability within these enterprises. Heterogeneity analysis implies that firms in the growth and maturity stages and firms located in the East and Central regions are more likely to benefit from DT in terms of green innovation efficiency. Mechanism analysis reveals that DT boosts HEGIE by facilitating the acquisition of knowledge resources, increasing high discretion slack resources while reducing low discretion slack resources. This study provides empirical evidence for understanding how DT contributes to green innovation capabilities from the perspectives of knowledge capital optimization and resource allocation, which inspires heavypolluting enterprises to focus on maximizing the benefits from DT measures, thereby empowering their goal toward achieving green transformation.
Keywords: Digital Transformation; Green Innovation Efficiency; Super-SBM Model; Heavypolluting Enterprises; Knowledge Resources; Slack Resources
JEL codes: Q55; M15; O30
DOI: ...