Resumo
As cadeias de suprimentos globais têm sido progressivamente pressionadas por um ambiente internacional marcado pela intensificação de tarifas comerciais, embargos econômicos e conflitos geopolíticos, os quais expõem vulnerabilidades estruturais decorrentes de sua elevada interdependência e complexidade operacional. Nesse contexto, este estudo analisa os impactos desses fatores sobre a organização e a estabilidade das cadeias globais de valor, bem como as estratégias adotadas por empresas e blocos econômicos para mitigar riscos e fortalecer a resiliência operacional. A pesquisa utiliza uma abordagem metodológica mista, combinando análise bibliométrica da literatura recente com estudo de caso aplicado à utilização da inteligência artificial na gestão da cadeia de suprimentos. Os resultados evidenciam um crescimento significativo das pesquisas e aplicações práticas de tecnologias digitais, especialmente inteligência artificial, machine learning e analytics preditivo, voltadas à antecipação de disrupções, diversificação de fornecedores, otimização logística e suporte à tomada de decisão estratégica. Conclui-se que a incorporação sistemática dessas tecnologias, aliada a estratégias de gestão de riscos e reconfiguração produtiva, constitui um elemento fundamental para a construção de cadeias de suprimentos mais resilientes, adaptáveis e competitivas, capazes de responder de forma eficaz a choques externos em um cenário global caracterizado por elevada instabilidade geopolítica e econômica.
Referências
Abhulimen, A. O., & Ejike, O. G. (2024). Solving supply chain management issues with AI and Big Data analytics for future operational efficiency. Computer Science & IT Research Journal, 5(8), 1780. https://doi.org/10.51594/csitrj.v5i8.1396
Adewumi, G., Dada, S., Azai, J. S., & Oware, E. (2024). A systematic review of strategies for enhancing pharmaceutical supply chain resilience in the U.S [Review of A systematic review of strategies for enhancing pharmaceutical supply chain resilience in the U.S]. International Medical Science Research Journal, 4(11), 961. Fair East Publishers. https://doi.org/10.51594/imsrj.v4i11.1711
Adewusi, A. O., Komolafe, A. M., Ejairu, E., Aderotoye, I. A., Abiona, O. O., & Oyeniran, O. C. (2024). THE ROLE OF PREDICTIVE ANALYTICS IN OPTIMIZING SUPPLY CHAIN RESILIENCE: A REVIEW OF TECHNIQUES AND CASE STUDIES [Review of THE ROLE OF PREDICTIVE ANALYTICS IN OPTIMIZING SUPPLY CHAIN RESILIENCE: A REVIEW OF TECHNIQUES AND CASE STUDIES]. International Journal of Management & Entrepreneurship Research, 6(3), 815. Fair East Publishers. https://doi.org/10.51594/ijmer.v6i3.938
Akhtar, P., Papadopoulos, T., Khan, H., Ghouri, A. M., Shamim, S., & Ashraf, A. (2026). Risk, generative AI, disinformation control, global supply chains, and social impacts. Technological Forecasting and Social Change, 226, 124609. https://doi.org/10.1016/j.techfore.2026.124609
Arowosegbe, O. B., Olutimehin, D. O., Odunaiya, O. G., & Soyombo, O. T. (2024). Risk Management in Global Supply Chains: Addressing Vulnerabilities in Shipping and Logistics. International Journal of Management & Entrepreneurship Research, 6(3), 910. https://doi.org/10.51594/ijmer.v6i3.962
Atadoga, A., Osasona, F., Amoo, O. O., Farayola, O. A., Ayinla, B. S., & Abrahams, T. O. (2024). THE ROLE OF IT IN ENHANCING SUPPLY CHAIN RESILIENCE: A GLOBAL REVIEW [Review of THE ROLE OF IT IN ENHANCING SUPPLY CHAIN RESILIENCE: A GLOBAL REVIEW]. International Journal of Management & Entrepreneurship Research, 6(2), 336. Fair East Publishers. https://doi.org/10.51594/ijmer.v6i2.774
Attah, R. U., Garba, B. M. P., Gil-Ozoudeh, I., & Iwuanyanwu, O. (2024). Enhancing supply chain resilience through artificial intelligence: Analyzing problem-solving approaches in logistics management. International Journal of Management & Entrepreneurship Research, 6(12), 3883. https://doi.org/10.51594/ijmer.v6i12.1745
Baldwin, R., & Freeman, R. (2022). Risks and Global Supply Chains: What We Know and What We Need to Know. Annual Review of Economics, 14(1), 153. https://doi.org/10.1146/annurev-economics-051420-113737
Caniato, F., Graham, G., Roehrich, J. K., & Vereecke, A. (2023). Impact pathways: a home for insights from relevant and impactful operations and supply chain management research. International Journal of Operations & Production Management, 43(13), 270. https://doi.org/10.1108/ijopm-03-2023-0163
Chakkol, M., Johnson, M. E., Karatzas, A., Papadopoulos, G. C., & Korfiatis, N. (2023). Making supply chains great again: examining structural changes to US manufacturing supply chains. International Journal of Operations & Production Management, 44(5), 1083. https://doi.org/10.1108/ijopm-12-2022-0783
Chen, Y., Li, B., & Huo, B. (2024). Building operational resilience through digitalization: The roles of supply chain network position. Technological Forecasting and Social Change, 211, 123918. https://doi.org/10.1016/j.techfore.2024.123918
Daghar, A., Alinaghian, L., & Turner, N. (2022). The role of cognitive capital in supply chain resilience: an investigation during the COVID-19 pandemic. Supply Chain Management An International Journal, 28(3), 576. https://doi.org/10.1108/scm-09-2021-0457
Dai, J., Geng, R., Xu, D., Shangguan, W., & Shao, J. (2024). Unveiling the impact of the congruence between artificial intelligence and explorative learning on supply chain resilience. International Journal of Operations & Production Management. https://doi.org/10.1108/ijopm-12-2023-0990
Fischer, B. B., Meissner, D., Boschma, R., & Vonortas, N. S. (2024). Global value chains and regional systems of innovation: Towards a critical juncture? Technological Forecasting and Social Change, 201, 123245. https://doi.org/10.1016/j.techfore.2024.123245
Gaudenzi, B., Pellegrino, R., & Confente, I. (2023). Achieving supply chain resilience in an era of disruptions: a configuration approach of capacities and strategies. Supply Chain Management An International Journal, 28(7), 97. https://doi.org/10.1108/scm-09-2022-0383
Grossman, G. M., Helpman, E., & Redding, S. J. (2024). When Tariffs Disrupt Global Supply Chains. American Economic Review, 114(4), 988. https://doi.org/10.1257/aer.20211519
Guo, J., Jia, F., & Chen, L. (2025). How generative AI adoption affects supply chain resilience: An operations and supply chain management perspective. Technological Forecasting and Social Change, 224, 124446. https://doi.org/10.1016/j.techfore.2025.124446
Joel, O. S., Oyewole, A. T., Odunaiya, O. G., & Soyombo, O. T. (2024). LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCED SUPPLY CHAIN OPTIMIZATION: A COMPREHENSIVE REVIEW OF CURRENT PRACTICES AND FUTURE POTENTIALS [Review of LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCED SUPPLY CHAIN OPTIMIZATION: A COMPREHENSIVE REVIEW OF CURRENT PRACTICES AND FUTURE POTENTIALS]. International Journal of Management & Entrepreneurship Research, 6(3), 707. Fair East Publishers. https://doi.org/10.51594/ijmer.v6i3.882
Malik, F. S., & Terzidis, O. (2025). Thriving in turbulence: resilience and strategic adaptation in global business. Review of Managerial Science. https://doi.org/10.1007/s11846-025-00940-8
Matos, S., Schleper, M. C., Hall, J., Baum, C. M., Low, S., & Sovacool, B. K. (2024). Beyond the new normal for sustainability: transformative operations and supply chain management for negative emissions. International Journal of Operations & Production Management, 44(13), 263. https://doi.org/10.1108/ijopm-06-2024-0487
McDougall, N., & Davis, A. M. (2024). The local supply chain during disruption: Establishing resilient networks for the future. Journal of Cleaner Production, 462, 142743. https://doi.org/10.1016/j.jclepro.2024.142743
Mittal, U., & Panchal, D. (2023). AI-based evaluation system for supply chain vulnerabilities and resilience amidst external shocks: An empirical approach. Reports in Mechanical Engineering, 4(1), 276. https://doi.org/10.31181/rme040122112023m
Modgil, S., Singh, R. K., & Hannibal, C. (2021). Artificial intelligence for supply chain resilience: learning from Covid-19. The International Journal of Logistics Management, 33(4), 1246. https://doi.org/10.1108/ijlm-02-2021-0094
Nnaji, U. O., Benjamin, L. B., Eyo-Udo, N. L., & Etukudoh, E. A. (2024). Effective cost management strategies in global supply chains. International Journal of Applied Research in Social Sciences, 6(5), 945. https://doi.org/10.51594/ijarss.v6i5.1146
Ogunjobi, O. A., Eyo-Udo, N. L., Egbokhaebho, B. A., Daraojimba, C., Ikwue, U., & Banso, A. A. (2023). ANALYZING HISTORICAL TRADE DYNAMICS AND CONTEMPORARY IMPACTS OF EMERGING MATERIALS TECHNOLOGIES ON INTERNATIONAL EXCHANGE AND U.S. STRATEGY. Engineering Science & Technology Journal, 4(3), 101. https://doi.org/10.51594/estj.v4i3.554
Olaleye, I. A., Mokogwu, C., Olufemi-Phillips, A. Q., & Adewale, T. T. (2024). Real-time inventory optimization in dynamic supply chains using advanced artificial intelligence. International Journal of Management & Entrepreneurship Research, 6(12), 3830. https://doi.org/10.51594/ijmer.v6i12.1741
Olowonigba, J. K. (2025). Exploring AI-driven supply chain automation to enhance global logistics, reduce operational costs, and ensure resilient business continuity. Engineering Science & Technology Journal, 6(8), 428. https://doi.org/10.51594/estj.v6i8.2021
Oriekhoe, O. I., Adisa, O., & Ilugbusi, B. S. (2024). CLIMATE CHANGE AND FOOD SUPPLY CHAIN ECONOMICS: A COMPREHENSIVE ANALYSIS OF IMPACTS, ADAPTATIONS, AND SUSTAINABILITY. International Journal of Applied Research in Social Sciences, 6(3), 267. https://doi.org/10.51594/ijarss.v6i3.885
Singh, R. K., Modgil, S., & Shore, A. (2023). Building artificial intelligence enabled resilient supply chain: a multi-method approach. Journal of Enterprise Information Management, 37(2), 414. https://doi.org/10.1108/jeim-09-2022-0326
Srai, J. S., Graham, G., Hoek, R. van, Joglekar, N., & Lorentz, H. (2023). Impact pathways: unhooking supply chains from conflict zones—reconfiguration and fragmentation lessons from the Ukraine–Russia war. International Journal of Operations & Production Management, 43(13), 289. https://doi.org/10.1108/ijopm-08-2022-0529
Sun, H., Song, Y., & Zhang, R. (2026). Enhancing supply chain resilience: A fit mechanism between key core technology innovations and digital technology applications. International Journal of Information Management, 88, 103040. https://doi.org/10.1016/j.ijinfomgt.2026.103040
Thủy, N. T. (2023). AN OVERVIEW OF THE FACTORS INFLUENCING THE FLEXIBILITY OF THE SUPPLY CHAIN IN MANUFACTURING ENTERPRISES. International Journal of Management & Entrepreneurship Research, 5(9), 674. https://doi.org/10.51594/ijmer.v5i9.549
Tse, Y. K., Dong, K., Sun, R., & Mason, R. (2024). Recovering from geopolitical risk: An event study of Huawei’s semiconductor supply chain. International Journal of Production Economics, 275, 109347. https://doi.org/10.1016/j.ijpe.2024.109347
Vaio, A. D., Latif, B., Gunarathne, N., Gupta, M., & D’Adamo, I. (2023). Digitalization and artificial knowledge for accountability in SCM: a systematic literature review. Journal of Enterprise Information Management, 37(2), 606. https://doi.org/10.1108/jeim-08-2022-0275
Wang, J., Shi, Y., Jiang, X., & Venkatesh, V. G. (2025). How does artificial intelligence capacity enhance the production system resilience and operational performance? A human-organization-technology fit perspective. International Journal of Information Management, 87, 103023. https://doi.org/10.1016/j.ijinfomgt.2025.103023
Wong, C., Yeung, H. W., Huang, S., Song, J., & Lee, K. (2024). Geopolitics and the changing landscape of global value chains and competition in the global semiconductor industry: Rivalry and catch-up in chip manufacturing in East Asia. Technological Forecasting and Social Change, 209, 123749. https://doi.org/10.1016/j.techfore.2024.123749
Zogaan, W. A., Ajabnoor, N., & Salamai, A. A. (2025). Leveraging deep learning for risk prediction and resilience in supply chains: insights from critical industries. Journal Of Big Data, 12(1). https://doi.org/10.1186/s40537-025-01143-4

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