The impact of information and communication technology on CO<SUB align="right">2 emissions in the context of environmental sustainability development: a case study of Asian countries

Bui Thi Men et al.

International Journal of Trade and Global Markets2025https://doi.org/10.1504/ijtgm.2025.150079article
ABDC C
Weight
0.50

What the paper says

This study investigates the influence of information and communication technology (ICT) on Asia's greenhouse gas emissions from 2000 to 2023. The findings reveal that ICT development significantly reduces CO2 emissions once it reaches a certain threshold. This paper underscores the vital role of digital infrastructure and technological advancement in promoting environmental sustainability. Additionally, the analysis shows that gross domestic product (GDP) is negatively correlated with greenhouse gas emissions, suggesting that higher economic output may be linked with improved emission efficiency. In contrast, foreign direct investment (FDI), energy consumption, and research and development (R&D) expenditure are associated with increased CO2 emissions. Based on these results, it is recommended that Asian countries accelerate ICT development, encourage environmentally responsible investment, and reform energy policies to achieve a sustainable balance between economic growth and environmental protection.

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https://doi.org/https://doi.org/10.1504/ijtgm.2025.150079

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@article{bui2025,
  title        = {{The impact of information and communication technology on CO<SUB align="right">2 emissions in the context of environmental sustainability development: a case study of Asian countries}},
  author       = {Bui Thi Men et al.},
  journal      = {International Journal of Trade and Global Markets},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijtgm.2025.150079},
}

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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.