Enhancing supply chain resilience through artificial intelligence: Analyzing problem-solving approaches in logistics management

In an increasingly complex and unpredictable global economy, supply chain resilience has emerged as a critical priority for organizations striving to adapt to disruptions and maintain operational continuity. Artificial intelligence (AI) has proven to be a transformative force in addressing the challenges of logistics and supply chain management, offering innovative solutions for forecasting, decision-making, and operational efficiency. This research explores how AI-driven approaches can solve specific supply chain challenges, including demand variability, disruption management, inventory optimization, transportation inefficiencies, and supplier relationship management. The review proposes a comprehensive analysis of AI technologies such as predictive analytics, real-time monitoring systems, optimization algorithms, and autonomous systems, highlighting their contributions to enhancing supply chain resilience. By leveraging AI, organizations can improve their ability to predict disruptions, optimize resource allocation, and respond dynamically to real-time challenges. The research incorporates case studies and real-world applications to illustrate successful implementations of AI in logistics, as well as lessons learned from failed attempts. Additionally, the review examines the benefits of integrating AI into supply chain operations, such as improved risk management, enhanced decision-making, and increased adaptability to uncertainties. However, it also addresses the challenges of AI adoption, including high implementation costs, data privacy concerns, and organizational resistance to change. By presenting actionable insights and recommendations, this research aims to provide a roadmap for organizations seeking to harness AI to strengthen their supply chain resilience. The findings underscore the transformative potential of AI technologies in fostering robust, adaptive, and efficient supply chain systems capable of withstanding future uncertainties and disruptions. Keywords: Supply Chain, Artificial Intelligence, Logistics Management, Review.

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Publication Details

Journal
International Journal of Management & Entrepreneurship Research
Published
2024-12-04
DOI
https://doi.org/10.51594/ijmer.v6i12.1745
Citations
32
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
17.75
Controls
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article

Enhancing supply chain resilience through artificial intelligence: Analyzing problem-solving approaches in logistics management

Obinna Iwuanyanwu, Ifechukwu Gil-Ozoudeh, Baalah Matthew Patrick Garba, Rita Uchenna Attah
32 citations
International Journal of Management & Entrepreneurship Research
Supply Chain Resilience and Risk Management
17.75
article

Enhancing supply chain resilience through artificial intelligence: Analyzing problem-solving approaches in logistics management

Obinna Iwuanyanwu, Ifechukwu Gil-Ozoudeh, Baalah Matthew Patrick Garba, Rita Uchenna Attah
article en
32 citations

Abstract

In an increasingly complex and unpredictable global economy, supply chain resilience has emerged as a critical priority for organizations striving to adapt to disruptions and maintain operational continuity. Artificial intelligence (AI) has proven to be a transformative force in addressing the challenges of logistics and supply chain management, offering innovative solutions for forecasting, decision-making, and operational efficiency. This research explores how AI-driven approaches can solve specific supply chain challenges, including demand variability, disruption management, inventory optimization, transportation inefficiencies, and supplier relationship management. The review proposes a comprehensive analysis of AI technologies such as predictive analytics, real-time monitoring systems, optimization algorithms, and autonomous systems, highlighting their contributions to enhancing supply chain resilience. By leveraging AI, organizations can improve their ability to predict disruptions, optimize resource allocation, and respond dynamically to real-time challenges. The research incorporates case studies and real-world applications to illustrate successful implementations of AI in logistics, as well as lessons learned from failed attempts. Additionally, the review examines the benefits of integrating AI into supply chain operations, such as improved risk management, enhanced decision-making, and increased adaptability to uncertainties. However, it also addresses the challenges of AI adoption, including high implementation costs, data privacy concerns, and organizational resistance to change. By presenting actionable insights and recommendations, this research aims to provide a roadmap for organizations seeking to harness AI to strengthen their supply chain resilience. The findings underscore the transformative potential of AI technologies in fostering robust, adaptive, and efficient supply chain systems capable of withstanding future uncertainties and disruptions. Keywords: Supply Chain, Artificial Intelligence, Logistics Management, Review.

International Journal of Management & Entrepreneurship ResearchVol. 6(12)
Enugu State University of Science and Technology (NG), Delta State University (NG), Bloomfield College (US)
Openalex Percentile: Top 1%
Supply Chain Resilience and Risk Management
17.75
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