eISSN: 2791-173X editor@grpublishing.org
All Journals
Submit your article

Global Multidisciplinary Journal

Open Access Peer Review International
Open Access

Artificial Intelligence–Driven Hierarchical Supply Chain Planning: Toward a Unified Framework for Visibility, Demand Forecasting, and Sustainable Optimization

DOI
PDF
Dr. Arjun Mehta 1 ,
4 Department of Industrial Engineering, Global Institute of Technology and Management

Abstract

The rapid evolution of Artificial Intelligence (AI) has profoundly reshaped how supply chains are conceptualized, managed, and optimized. This paper synthesizes extant literature to propose a unified, hierarchical framework for AI-driven supply chain planning that integrates demand forecasting, real‑time visibility, inventory and logistics optimization, and sustainability considerations. Drawing on empirical and conceptual studies—including hierarchical neural‑network planning, supply‑chain visibility models, and systematic reviews of AI adoption—the framework aims to address critical research gaps in current practices. Through a detailed, structured literature review, this study examines how AI techniques such as artificial neural networks (ANNs), machine learning (ML), and advanced analytics contribute to base‑level outcomes (e.g., demand forecasting, inventory control), mid‑level orchestration (e.g., logistics routing, replenishment scheduling), and high-level strategic objectives (e.g., sustainability, resilience, service-level optimization). Key findings reveal that AI-driven supply chain management (SCM) enhances responsiveness, reduces waste, and improves resource utilization, but also faces barriers including data quality, system interoperability, organizational readiness, and social considerations. The discussion explores theoretical implications, practical challenges, and future research directions—highlighting the need for longitudinal empirical validation, hybrid human–AI decision processes, and standardization of performance metrics. This paper contributes to supply chain theory by offering a comprehensive, multi-layered conceptual model that bridges short-term operational gains and long-term strategic sustainability goals via AI adoption.

Keywords

Artificial Intelligence, Supply Chain Management, Neural Networks, Supply Chain Visibility, Demand Forecasting, Hierarchical Planning

References

📄 Rohde, Jens. “Hierarchical Supply Chain Planning Using Artificial Neural Networks to Anticipate Base‑Level Outcomes.” OR Spectrum, vol. 26, no. 4, pp. 471–92, 2004.
📄 Selyukh, Alina. “Optimized Prime: How AI And Anticipation Power Amazon’s 1-Hour Deliveries.” NPR, 21 Nov. 2018.
📄 Sharma, Rohit, et al. “The Role of Artificial Intelligence in Supply Chain Management: Mapping the Territory.” International Journal of Production Research, vol. 60, no. 24, Feb. 2022, pp. 7527–50.
📄 Silva, Nathalie, et al. “Improving Supply Chain Visibility With Artificial Neural Networks.” Procedia Manufacturing, vol. 11, 2017, pp. 2083–90.
📄 Gayam, S.R. “AI for Supply Chain Visibility in E-Commerce: Techniques for Real-Time Tracking, Inventory Management, and Demand Forecasting.” Distributed Learning and Broad Applications in Science Research, vol. 5, 2019, pp. 218–251.
📄 Sanders, N.R., Boone, T., Ganeshan, R., Wood, J.D. “Sustainable Supply Chains in the Age of AI and Digitization: Research Challenges and Opportunities.” Journal of Business Logistics, vol. 40, 2019, pp. 229–240.
📄 Kollia, I., Stevenson, J., Kollias, S. “AI‑enabled Efficient and Safe Food Supply Chain.” Electronics, vol. 10, 2021, p. 1223.
📄 Culot, G., Podrecca, M., Nassimbeni, G. “Artificial Intelligence in Supply Chain Management: A Systematic Literature Review of Empirical Studies and Research Directions.” Computers & Industry, vol. 162, 2024, article 104132.
📄 Sony, M., Naik, S. “Key Ingredients for Evaluating Industry 4.0 Readiness for Organizations: A Literature Review.” Benchmarking: An International Journal, vol. 27, 2020, pp. 2213–2232.
📄 Min, H. “Artificial Intelligence in Supply Chain Management: Theory and Applications.” International Journal of Logistics Research and Applications, vol. 13, 2010, pp. 13–39.
📄 Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., Fischl, M. “Artificial Intelligence in Supply Chain Management: A Systematic Literature Review.” Journal of Business Research, vol. 122, 2021, pp. 502–517.
📄 Riahi, Y., Saikouk, T., Gunasekaran, A., Badraoui, I. “Artificial Intelligence Applications in Supply Chain: A Descriptive Bibliometric Analysis and Future Research Directions.” Expert Systems with Applications, vol. 173, 2021, article 114702.
📄 Chowdhury, W. A. “Optimizing Supply Chain Logistics Through AI & ML: Lessons from NYX.” International Journal of Data Science and Machine Learning, vol. 5, no. 1, 2025, pp. 49–53.
📄 Shahzadi, G., Jia, F., Chen, L., John, A. “AI Adoption in Supply Chain Management: A Systematic Literature Review.” Journal of Manufacturing Technology Management, vol. 35, 2024, pp. 1125–1150.
📄 Cannas, V.G., Ciano, M.P., Saltalamacchia, M., Secchi, R. “Artificial Intelligence in Supply Chain and Operations Management: A Multiple Case Study Research.” International Journal of Production Research, vol. 62, 2024, pp. 3333–3360.
📄 Hangl, J., Behrens, V.J., Krause, S. “Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study.” Logistics, vol. 6, 2022, p. 63.
📄 Hendriksen, C. “Artificial Intelligence for Supply Chain Management: Disruptive Innovation or Innovative Disruption?” Journal of Supply Chain Management, vol. 59, 2023, pp. 65–76.
📄 Eyo-Udo, N. “Leveraging Artificial Intelligence for Enhanced Supply Chain Optimization.” Open Access Research Journal of Multidisciplinary Studies, vol. 7, 2024, pp. 1–15.

How to Cite

Dr. Arjun Mehta. (2025). Artificial Intelligence–Driven Hierarchical Supply Chain Planning: Toward a Unified Framework for Visibility, Demand Forecasting, and Sustainable Optimization. Global Multidisciplinary Journal, 4(05), 8-16. https://www.grpublishing.org/journals/index.php/gmj/article/view/235

Most read articles by the same author(s)

<< < 2 3 4 5 6 7 8 9 10 11 > >> 

Similar Articles

1-10 of 87

You may also start an advanced similarity search for this article.