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From tariffs to technology policies: the role of regionalism in the digital economy

María Gabriela Ramos Barrera et al.

International Journal of Trade and Global Markets2025https://doi.org/10.1504/ijtgm.2025.150088article
ABDC C
Weight
0.50

What the paper says

This paper explores the evolving role of regionalism in fostering technology transfer within global value chains (GVCs). Combining theoretical and empirical perspectives, we analyse WTO-X provisions in regional trade agreements (RTAs) and assess their capacity to promote knowledge diffusion, innovation, and digital transformation. The findings reveal that: i) while RTAs increasingly include provisions on technology transfer, most lack legally binding mechanisms, limiting their effectiveness in enabling technological upgrading, particularly in developing economies; ii) by examining key indicators such as AI preparedness and regional disparities in knowledge production, the study underscores structural inequalities that constrain inclusive development; and iii) there is an underexplored intersection of regionalism and technology transfer in academic research. The paper concludes by advocating for a stronger regionalism framework with enforceable commitments to innovation policies, education, and industrial cooperation, essential for fostering equitable technology diffusion and sustainable economic integration in the digital era.

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Cite this paper

https://doi.org/https://doi.org/10.1504/ijtgm.2025.150088

Or copy a formatted citation

@article{maría2025,
  title        = {{From tariffs to technology policies: the role of regionalism in the digital economy}},
  author       = {María Gabriela Ramos Barrera et al.},
  journal      = {International Journal of Trade and Global Markets},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijtgm.2025.150088},
}

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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.