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Firm complexity and carbon emissions: Evidence from textual analysis

Chih‐Wei Wang et al.

Journal of Economic Behavior and Organization2026https://doi.org/10.1016/j.jebo.2026.107454article
AJG 3ABDC A*
Weight
0.50

Abstract

Utilizing a novel measure of firm complexity derived from textual analysis by Loughran and McDonald (2024), we examine the relationship between firm complexity and carbon emissions in the United States from 2005 to 2021, considering the roles of AI investment levels and firm leverage as mediating factors. We find that more complex firms are inclined to invest in AI technologies associated with increased carbon emissions. Additionally, these firms tend to have higher leverage, further amplifying their carbon emissions. Our results indicate that this relationship is more pronounced when oil price uncertainty is low and in manufacturing and high-tech industries. The relationship is also stronger among smaller firms, as they face more significant challenges in adopting ESG policies. Finally, firms with higher returns on assets, long-term debt, and gross profit demonstrate a more substantial positive relation between complexity and carbon emissions.

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https://doi.org/https://doi.org/10.1016/j.jebo.2026.107454

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@article{chih‐wei2026,
  title        = {{Firm complexity and carbon emissions: Evidence from textual analysis}},
  author       = {Chih‐Wei Wang et al.},
  journal      = {Journal of Economic Behavior and Organization},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.jebo.2026.107454},
}

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Firm complexity and carbon emissions: Evidence from textual analysis

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.