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Artificial intelligence and green development: Evidence from China on efficiency and equity

Tielong Wu

Energy Economics2026https://doi.org/10.1016/j.eneco.2026.109201article
AJG 3ABDC A*
Weight
0.37

Abstract

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https://doi.org/https://doi.org/10.1016/j.eneco.2026.109201

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@article{tielong2026,
  title        = {{Artificial intelligence and green development: Evidence from China on efficiency and equity}},
  author       = {Tielong Wu},
  journal      = {Energy Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.eneco.2026.109201},
}

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Artificial intelligence and green development: Evidence from China on efficiency and equity

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
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.