Enhancing enterprises’ green and low-carbon innovation through digital technology embeddedness: From passive response to active innovation
Promoting green and low-carbon innovation (GCI) with digitalization is important to achieve carbon peaking and neutrality goals and would accelerate low-carbon transformation. Digital technology embeddedness (DTE) disrupts traditional business innovation patterns, but its ability to steer innovation toward low-carbon-biased technologies is debated. Based on enterprises’ innovation motivation from passive response to active change, this study explores the impact mechanism and network spillover effect of DTE on GCI by combining data of green and low-carbon patent and technical knowledge complexity in China. The study finds that (1) DTE positively impacts GCI and increases its technical knowledge complexity. This effect is particularly evident in enterprises with weak technology accumulation, large-scale, better ESG performance and heavily polluted enterprises. (2) Through the moderating effect of passive response channels, DTE forces enterprises to choose GCI under external environmental pressure from government environmental regulation, public environmental awareness and market innovation transformation ability. (3) Active innovation mechanisms show DTE stimulates enterprises to seek low-carbon-biased technologies by improving their market information acquisition, knowledge-sharing and absorption, and collaborative innovation abilities, thus improving GCI. (4) Peer spillover and supply chain spillovers strengthen the positive impact of DTE on GCI, resulting in green and low-carbon transformation via improved GCI scale and quality within the industry and supply chain. Hence, a novel governance pattern could be established by using digital technology as a core strategy, with participation of multiple agents (government, enterprises and the public) and creation of a green and intelligent innovative supply chain system.
Authors
- Nanxu Chen (ORCID: https://orcid.org/0000-0003-1604-9135)
- Lianbang Wang (ORCID: https://orcid.org/0000-0002-6595-1670)
- Yuling Hu (ORCID: https://orcid.org/0000-0003-3155-2038)
Publication Details
- Journal
- Journal of Innovation & Knowledge
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1016/j.jik.2025.100801
- Citations
- 6
- Primary Topic
- Innovation Diffusion and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 12.64
Funders
- National Planning Office of Philosophy and Social Science
- Fundamental Research Funds for the Central Universities
- National Social Science Fund of China