Author(s)

Linda Tan, Michael Chan^*

Affiliation(s)

Department of Information Systems, Singapore Management University, 188065, Singapore.

Corresponding Author

Michael Chan

ABSTRACT

The integration of artificial intelligence in supply chain management and logistics has fundamentally transformed traditional operational paradigms, ushering in an era of unprecedented efficiency and innovation. This comprehensive review synthesizes the latest research and practical implementations from 2019 to 2024, examining the multifaceted impact of AI technologies across the supply chain spectrum. Through systematic analysis of academic literature, industry implementations, and emerging trends, this paper presents a thorough examination of how AI is reshaping supply chain operations, decision-making processes, and strategic planning. Our findings indicate a significant shift toward autonomous and intelligent supply chain systems, with particular emphasis on real-time optimization, predictive analytics, and adaptive learning mechanisms that are revolutionizing the industry landscape.

KEYWORDS

Artificial intelligence; Machine learning; Supply chain

CITE THIS PAPER

Linda Tan, Michael Chan. Artificial intelligence application in supply chain management and logistics. Innovation and Technology Studies. 2024, 1(1): 10-16. DOI: https://doi.org/10.61784/its3004.

REFERENCES

[1] Toorajipour R, Sohrabpour V, Nazarpour A, et al. Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 2021, 122: 502-517.

[2] Li J, Fan L, Wang X, et al. Product Demand Prediction with Spatial Graph Neural Networks. Applied Sciences, 2024, 14(16): 6989.

[3] Sharma R, Shishodia A, Gunasekaran A, et al. The role of artificial intelligence in supply chain management: mapping the territory. International Journal of Production Research, 2022, 60(24): 7527-7550.

[4] Wang X, Wu Y C, Ma Z. Blockchain in the courtroom: exploring its evidentiary significance and procedural implications in US judicial processes. Frontiers in Blockchain, 2024, 7: 1306058.

[5] Pournader M, Ghaderi H, Hassanzadegan A, et al. Artificial intelligence applications in supply chain management. International Journal of Production Economics, 2021, 241: 108250.

[6] Chen J, Cui Y, Zhang X, et al. Temporal Convolutional Network for Carbon Tax Projection: A Data-Driven Approach. Applied Sciences, 2024, 14(20): 9213.

[7] Culot G, Podrecca M, Nassimbeni G. Artificial intelligence in supply chain management: A systematic literature review of empirical studies and research directions. Computers in Industry, 2024, 162: 104132.

[8] Zuo Z, Niu Y, Li J, et al. Machine learning for advanced emission monitoring and reduction strategies in fossil fuel power plants. Applied Sciences, 2024, 14(18): 8442.

[9] Wang X, Zhang X, Hoo V, et al. LegalReasoner: A Multi-Stage Framework for Legal Judgment Prediction via Large Language Models and Knowledge Integration. IEEE Access, 2024.

[10] Dash R, McMurtrey M, Rebman C, et al. Application of artificial intelligence in automation of supply chain management. Journal of Strategic Innovation and Sustainability, 2019, 14(3).

[11] Ma Z, Chen X, Sun T, et al. Blockchain-Based Zero-Trust Supply Chain Security Integrated with Deep Reinforcement Learning for Inventory Optimization. Future Internet, 2024, 16(5): 163.

[12] Hellingrath B, Lechtenberg S. Applications of artificial intelligence in supply chain management and logistics: focusing onto recognition for supply chain execution. The Art of Structuring: Bridging the Gap Between Information Systems Research and Practice, 2019: 283-296.

[13] Liu M, Ma Z, Li J, et al. Deep-Learning-Based Pre-training and Refined Tuning for Web Summarization Software. IEEE Access, 2024.

[14] Baryannis G, Validi S, Dani S, et al. Supply chain risk management and artificial intelligence: state of the art and future research directions. International journal of production research, 2019, 57(7): 2179-2202.

[15] Khatua A, Khatua A, Chi X, et al. Artificial intelligence, social media and supply chain management: The way forward. Electronics, 2021, 10(19): 2348.

[16] Wang X, Wu Y C, Zhou M, et al. Beyond surveillance: privacy, ethics, and regulations in face recognition technology. Frontiers in big data, 2024, 7: 1337465.

[17] Boute R N, Udenio M. AI in logistics and supply chain management. In Global logistics and supply chain strategies for the 2020s: Vital skills for the next generation . Cham: Springer International Publishing, 2022: 49-65.

[18] Chen X, Liu M, Niu Y, et al. Deep-Learning-Based Lithium Battery Defect Detection via Cross-Domain Generalization. IEEE Access, 2024.

[19] Abaku E A, Edunjobi T E, Odimarha A C. Theoretical approaches to AI in supply chain optimization: Pathways to efficiency and resilience. International Journal of Science and Technology Research Archive, 2024, 6(1): 092-107.

[20] Tirkolaee E B, Sadeghi S, Mooseloo F M, et al. Application of machine learning in supply chain management: a comprehensive overview of the main areas. Mathematical problems in engineering, 2021(1), 1476043.

[21] Wang X, Wu Y C. Balancing innovation and Regulation in the age of geneRative artificial intelligence. Journal of Information Policy, 2024, 14.

[22] Hendriksen C. Artificial intelligence for supply chain management: Disruptive innovation or innovative disruption?. Journal of Supply Chain Management, 2023, 59(3): 65-76.

[23] Sun T, Yang J, Li J, et al. Enhancing Auto Insurance Risk Evaluation with Transformer and SHAP. IEEE Access, 2024.

[24] Adenekan O A, Solomon N O, Simpa P, et al. Enhancing manufacturing productivity: A review of AI-Driven supply chain management optimization and ERP systems integration. International Journal of Management & Entrepreneurship Research, 2024, 6(5): 1607-1624.

[25] Wang X, Wu Y C, Ji X, et al. Algorithmic discrimination: examining its types and regulatory measures with emphasis on US legal practices. Frontiers in Artificial Intelligence, 2024, 7: 1320277.

[26] Richey Jr R G, Chowdhury S, Davis‐Sramek B, et al. Artificial intelligence in logistics and supply chain management: A primer and roadmap for research. Journal of Business Logistics, 2023, 44(4): 532-549.