El Impacto de la Inteligencia Artificial en la Transformación del Comercio Internacional: Una Revisión Bibliográfica

Autores

DOI:

https://doi.org/10.61616/rvdc.v6i3.1014

Palavras-chave:

inteligencia artificial, comercio internacional, puertos, aduanas, big data

Resumo

La inteligencia artificial (IA) es una tecnología crucial en la transformación del comercio internacional. Una revisión bibliográfica sobre su aplicación en el comercio exterior, basada en estudios de 2015 a 2025, revela su uso en cinco áreas clave: predicción de tendencias, inteligencia de mercados con big data, apoyo a la toma de decisiones en operaciones internacionales, modernización de puertos y aduanas, y gestión de desafíos éticos y regulatorios. Además, se proyecta una integración de la IA con tecnologías como blockchain e IoT para un comercio más automatizado y transparente. A pesar de los avances, existen limitaciones como la escasa evidencia en países en desarrollo, la falta de estudios comparativos y la ausencia de una regulación internacional homogénea. Para superar estos desafíos, se necesitan políticas públicas inclusivas y cooperación global. En conclusión, la IA es un motor de eficiencia y competitividad en el comercio internacional, aunque su impacto dependerá de cómo se gestionen las brechas tecnológicas y éticas que hoy limitan su adopción equitativa.

Referências

Ahmed, S., Khan, M., & Rahman, T. (2023). Hybrid AI models for forecasting trade under uncertainty. Journal of International Economics and Technology, 15(2), 77–95.

https://doi.org/10.1080/jiet.2023.15.2.77

Chen, J., Liu, X., & Wang, Y. (2021). Blockchain and artificial intelligence integration for international trade. Journal of Global Trade Studies, 12(3), 45–62.

https://doi.org/10.1016/j.jgts.2021.03.004

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070

García, R., & Pérez, M. (2021). Forecasting agricultural exports with machine learning: Evidence from Latin America. Latin American Economic Review, 30(1), 15–29.

https://doi.org/10.1007/s40503-021-00112-4

Ghosh, A., & Patel, R. (2023). Generative AI and the future of global trade. International Journal of Trade and Technology, 8(2), 101–120. https://doi.org/10.1080/ijtt.2023.08.002

Ivanov, D., Dolgui, A., & Sokolov, B. (2021). Artificial intelligence in logistics and supply chain management: An overview. International Journal of Production Research, 59(7), 1925–1942. https://doi.org/10.1080/00207543.2020.1792000

Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report, 2007(EBSE-2007-01), 1–57.

Kumar, S., Gupta, A., & Rao, P. (2021). Big data analytics for international market segmentation. Journal of Business Research, 124, 168–182.

https://doi.org/10.1016/j.jbusres.2020.11.058

Lee, J., & Lim, H. (2022). Predictive analytics and disruption management in global supply chains: An AI approach. International Journal of Logistics Research and Applications, 25(7), 945–962. https://doi.org/10.1080/13675567.2021.1977142

Li, X., & Chen, Y. (2019). Artificial intelligence in international market analysis: Opportunities and challenges. International Marketing Review, 36(4), 560–580.

https://doi.org/10.1108/IMR-02-2018-0074

Li, Z., Zhang, H., & Zhao, Y. (2022). Digital infrastructure and AI adoption in emerging economies. Journal of Development Studies, 58(5), 745–763.

https://doi.org/10.1080/00220388.2022.2045689

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097

Narayanan, V., & Kapoor, S. (2020). Ethical and regulatory challenges of AI in international trade. Journal of World Trade, 54(6), 821–844.

Notteboom, T., & Pallis, A. A. (2020). IAPH-WPSP COVID-19 Port Economic Impact Barometer. Maritime Economics & Logistics, 22(3), 329–344. https://doi.org/10.1057/s41278-020-00164-x

Okoli, C. (2015). A guide to conducting a standalone systematic literature review. Communications of the Association for Information Systems, 37(43), 879–910.

https://doi.org/10.17705/1CAIS.03743

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Blackwell Publishing.

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339.

https://doi.org/10.1016/j.jbusres.2019.07.039

Sun, X., Zhang, Y., & Liu, H. (2020). AI-based decision support systems in international trade operations. Decision Support Systems, 138, 113365.

https://doi.org/10.1016/j.dss.2020.113365

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375

Wang, J., & Wong, P. (2022). Predicting international trade flows with deep learning models. Journal of International Economics, 135, 103569.

https://doi.org/10.1016/j.jinteco.2021.103569

Xiao, Y., & Watson, M. (2019). Guidance on conducting a systematic literature review. Journal of Planning Education and Research, 39(1), 93–112.

https://doi.org/10.1177/0739456X17723971

Zhang, L., Huang, T., & Li, F. (2020). Neural networks for international trade forecasting: A case study in East Asia. Economic Modelling, 88, 47–58.

https://doi.org/10.1016/j.econmod.2019.08.002

Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W.W. Norton & Company.

Comisión Económica para América Latina y el Caribe (CEPAL). (2022). Innovación tecnológica y comercio exterior en América Latina. CEPAL. https://www.cepal.org

Krugman, P. (1991). Geography and trade. MIT Press.

Organización Mundial de Aduanas (OMA). (2021). Annual Report 2021. WCO.

http://www.wcoomd.org

Organización para la Cooperación y el Desarrollo Económicos (OCDE). (2021). The impact of AI on international trade. OECD Publishing. https://www.oecd.org

Organización para la Cooperación y el Desarrollo Económicos (OECD). (2023). Artificial intelligence and the future of trade. OECD Publishing.

https://doi.org/10.1787/ai-trade-2023-en

Porter, M. E. (1998). Competitive advantage: Creating and sustaining superior performance. Free Press.

Williamson, O. E. (1985). The economic institutions of capitalism: Firms, markets, relational contracting. Free Press.

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Publicado

2025-11-06

Como Citar

Quincha Risco , G. V., & Espinosa Galarza, M. O. (2025). El Impacto de la Inteligencia Artificial en la Transformación del Comercio Internacional: Una Revisión Bibliográfica. Revista Veritas De Difusão Científica, 6(3), 1715–1740. https://doi.org/10.61616/rvdc.v6i3.1014

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