Author
Listed:
- Chen, Jie
- Yang, Lisha
- Su, Huahuang
Abstract
Artificial intelligence (AI) drives disruptive technological breakthroughs and fosters paradigm shifts in firms' green innovation (GI). This study constructs a Green Citation Disruption Index based on green patent citation networks to measure disruptive green innovation (DGI) in Chinese listed manufacturing firms. The results show that about 12.43 % of firms have achieved DGI. In our empirical analysis, we decompose firms' DGI into two dimensions: the probability of achieving DGI and the innovation capability of firms that have already achieved it. The results show that a one-unit increase in AI level raises the probability of a firm achieving DGI by about 4.33 percentage points and enhances its DGI capability by about 9.71 percentage points, after controlling for firm and year fixed effects as well as other covariates. The mechanism analysis reveals that AI facilitates disruptive breakthroughs in green technologies through capability enhancement and capability compensation. The capability enhancement effect operates as AI attracts patient capital and overcomes organizational inertia, thereby strengthening firms' intrinsic ability to undertake DGI. The capability compensation effect arises as AI reinforces inter-firm collaboration, enabling firms to draw on external capabilities and resources. Moreover, we find evidence of a gradual deepening pattern in AI-enabled collaboration: AI first strengthens relationship-based collaboration formed through managerial interlocks, and subsequently enhances capital-based collaboration via shared ownership ties over a longer horizon, providing increasingly substantive external support for DGI. Heterogeneity analyses suggest that AI more strongly enhances the DGI capability of firms located in regions with environmental tribunals. The effect is also more pronounced for high-pollution firms. Moreover, state-owned firms exhibit both a higher probability of achieving DGI and stronger improvements in their innovation capability through AI. This study extends the measurement framework for DGI, clarifies the mechanisms through which AI enables such innovation, and provides new empirical evidence on how AI drives firms' engagement in it.
Suggested Citation
Chen, Jie & Yang, Lisha & Su, Huahuang, 2026.
"Green transformation in the era of intelligence: How artificial intelligence affects disruptive green innovation in firms,"
Energy Economics, Elsevier, vol. 153(C).
Handle:
RePEc:eee:eneeco:v:153:y:2026:i:c:s0140988325009235
DOI: 10.1016/j.eneco.2025.109093
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