Potenciando los negocios internacionales con la inteligencia artificial: innovación y desarrollo en la optimización de la cadena de suministros
Palabras clave:
Inteligencia Artificial, Cadena de Suministro Internacional, Optimización, Toma de Decisiones, Sostenibilidad, Desafíos, Riesgos
Resumen
La globalización ha incrementado la competencia y la complejidad en los negocios internacionales, lo que exige a las empresas optimizar sus operaciones y buscar nuevas estrategias para mejorar la eficiencia. La Inteligencia Artificial (IA) se presenta como una herramienta optimizadora que puede transformar la gestión de la cadena de suministro internacional (OCS). El objetivo de este estudio es explorar el efecto de la IA sobre la OCS en los negocios internacionales, para ello se utiliza una metodología cuantitativa basado en un mapeo científico apoyado en técnicas y herramientas bibliográficas. El principal resultado es identificar las principales tendencias que emergen de este tema de investigación. Se concluye que la IA se convierte en un instrumento que permite mejorar la OCS mediante la toma de decisiones, la automatización de procesos, reducción de costos y la mejora en la sostenibilidad de las empresas en el mercado global.
Citas
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Ratten, V., Jones, P., & Braga, V. (2024). Artificial intelligence in international business. Thunderbird International Business Review, 66(2), 127–133. DOI: https://doi.org/10.1002/tie.22373
Sangeetha, M., Hoti, A., Bansal, R., Faez Hasan, M., Gajjar, K., & Srivastava, K. (2022). Facilitating artificial intelligence supply chain analytics through finance management during the pandemic crises. Materials Today: Proceedings, 56, 2092–2095. DOI: https://doi.org/10.1016/j.matpr.2021.11.418
Albarracín Vanoy, R. J. (2023). Logistics 4.0: Exploring Artificial Intelligence trends in efficient supply chain management. Data and Metadata, 2, 145. DOI: https://doi.org/10.56294/dm2023145
Aljazzar, S. M. (2023). Harnessing artificial intelligence for supply chain optimization: Enhanced demand prediction and cost reduction. 2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI), 122, 1–6
Bhanushali, M. M., Bhardwaj, S., Singh, N. K., Vijayalakshmi, P., Mazumdar, N., & Acharjee, P. B. (2024). From automation to optimization: Exploring the effects of Al on supply chain management. En Advances in Logistics, Operations, and Management Science (pp. 77–94). IGI Global
Brevik, E., Lauen, A. Ø., Rolke, M. C. B., Fagerholt, K., & Hansen, J. R. (2020). Optimisation of the broiler production supply chain. International Journal of Production Research, 58(17), 5218–5237. DOI: https://doi.org/10.1080/00207543.2020.1713415
Chidozie, B. C., Ramos, A. L., Ferreira, J. V., & Ferreira, L. P. (2024). Impacts of simulation and digital tools on supply chain in industry 4.0. En Lecture Notes in Networks and Systems (pp. 513–521). Springer Nature Switzerland.
Dutta, P. K., Ghosh, D., & Abotaleb, M. (2024). Harnessing the power of hybrid models for supply chain management and optimization. En Hybrid Information Systems (pp. 407–426). De Gruyter.
Gupta, N., Dutta, G., & Tiwari, M. K. (2018). An integrated decision support system for strategic supply chain optimisation in process industries: the case of a zinc company. International Journal of Production Research, 56(17), 5866–5882. DOI: https://doi.org/10.1080/00207543.2018.1456698
Hasan, R., & Ojala, A. (2024). Managing artificial intelligence in international business: Toward a research agenda on sustainable production and consumption. Thunderbird International Business Review, 66(2), 151–170. DOI: https://doi.org/10.1002/tie.22369
Huerta-Soto, R., Ramirez-Asis, E., Tarazona-Jiménez, J., Nivin-Vargas, L., Norabuena-Figueroa, R., Guzman-Avalos, M., & Reyes-Reyes, C. (2023). Predictable inventory management within dairy supply chain operations. International Journal of Retail & Distribution Management. DOI: https://doi.org/10.1108/ijrdm-01-2023-0051
Ivanovich Vatin, N., John, V., Nangia, R., Kumar, M., & Prasanna, Y. L. (2024). Supply chain optimization in Industry 5.0: An experimental investigation using Al. BIO web of conferences, 86, 01093. https://doi.org/10.1051/bioconf/20248601093
Khaled, A. S. D., Sharma, D. K., Yashwanth, T., Reddy, V. M. K., Doewes, R. I., & Naved, M. (2023). Evaluating the role of robotics, machine learning and artificial intelligence in the field of performance management. En Smart Innovation, Systems and Technologies (pp. 285–293). Springer Nature Singapore.
Li, K., & Zhou, Y. (2023). Automation of financial capital supply chain optimization industry based on time series LSTM algorithm. 2023 16th International Conference on Developments in eSystems Engineering (DeSE), 110–115
Menzies, J., Sabert, B., Hassan, R., & Mensah, P. K. (2024). Artificial intelligence for international business: Its use, challenges, and suggestions for future research and practice. Thunderbird International Business Review, 66(2), 185–200. DOI: https://doi.org/10.1002/tie.22370
Muchenje, C., Mtengwa, E., & Maregere, L. L. (2024). Unleashing entrepreneurial potential: The transformative impact of artificial intelligence. En Advances in Marketing, Customer Relationship Management, and E-Services (pp. 378–405). IGI Global
Ratten, V. (2024). Artificial intelligence, digital trends and globalization: Future research trends. FIIB Business Review, 13(3), 286–293. DOI: https://doi.org/10.1177/23197145231222774
Ratten, V., Hasan, R., Kumar, D., Bustard, J., Ojala, A., & Salamzadeh, Y. (2024). Learning from artificial intelligence researchers about international business implications. Thunderbird International Business Review, 66(2), 211–219. DOI: https://doi.org/10.1002/tie.22374
Ratten, V., Jones, P., & Braga, V. (2024). Artificial intelligence in international business. Thunderbird International Business Review, 66(2), 127–133. DOI: https://doi.org/10.1002/tie.22373
Sangeetha, M., Hoti, A., Bansal, R., Faez Hasan, M., Gajjar, K., & Srivastava, K. (2022). Facilitating artificial intelligence supply chain analytics through finance management during the pandemic crises. Materials Today: Proceedings, 56, 2092–2095. DOI: https://doi.org/10.1016/j.matpr.2021.11.418
Publicado
2025-12-26
Cómo citar
Espinal Piedrahita, J., Cortés Gonzales, J., García Espinosa, J., & Gómez Otálvaro, Ángel. (2025). Potenciando los negocios internacionales con la inteligencia artificial: innovación y desarrollo en la optimización de la cadena de suministros. Revista Sinergia, 1(18), 8-19. Recuperado a partir de http://sinergia.colmayor.edu.co/ojs/index.php/Revistasinergia/article/view/230
