Navigating the Ripple Effect: A Risk-Resilient Framework for Supply Chain Optimization
Artificial Intelligence; blockchain; covid-19; global supply chain
Supply chains around worldwide are growing increasingly vulnerable to intricate and interrelated hazards, such as localized disruptions, ie. the COVID-19 pandemic - have repercussions that affect manufacturers, suppliers, and buying habits in other geographical areas. This study offers a risk-resilient paradigm for supply chain optimization that combines cutting-edge risk mitigation and recovery techniques with conventional efficiency-driven tactics. The framework tackles both short-term operational issues and long-term sustainability objectives by fusing lean management, scenario-based stochastic demonstrating, Bayesian network analysis, and digital technologies like blockchain and artificial intelligence. In order to reduce the spread of disruptions and enhance decision-making in the face of uncertainty, this work highlights the significance of supplier collaboration, decentralized planning, and predictive analytics. This paper includes a thorough strategy for managing the ripple effect, improving supply chain adaptation, and guaranteeing continuous value delivery in unstable circumstances using comparative analysis and data from recent literature. 2025 IEEE.
Singh, Nidhi; Arora, Rashmi; Arya, Prabha; Dadwal, Sapna; Upreti, Kamal
2025 World Skills Conference on Universal Data Analytics and Sciences, WorldSUAS 2025;
Institute of Electrical and Electronics Engineers Inc.
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1109/WorldSUAS66815.2025.11199081 https://www.scopus.com/pages/publications/105022288310?origin=resultslist
Singh N., G D Goenka University, Department of Managment, Haryana, India; Arora R., G D Goenka University, Department of Managment, Haryana, India; Arya P., G D Goenka University, Department of Managment, Haryana, India; Dadwal S., DPG Institute of Technology and Management, Department of Managment, Gurugram, India; Upreti K., Christ University Delhi NCR, Department of Computer Science, Ghaziabad, India