@article{Kumar_V-2025_193656,
title = {Artificial intelligence applications in healthcare supply chain networks under disaster conditions},
author = {Kumar, V. and Goodarzian, F. and Ghasemi, P. and Chan, F. and Gupta, N.},
month = {jan},
year = {2025},
abstract = {Disasters disrupt the normal functioning of society, leading to significant financial and human losses. Effective disaster management relies heavily on robust logistics, which ensures efficient supply and support chains. A key strategy for maintaining operational continuity in healthcare systems during disruptions is to improve the resilience of supply chains and adapt to unpredictable events. The COVID-19 pandemic highlighted the need for adaptable healthcare supply chains, exemplified by factories pivoting to produce essential personal protective equipment. Despite the critical importance of quantitative models in healthcare supply chain management, their application has a noticeable gap. Artificial Intelligence (AI) has emerged as a transformative tool to address these complexities, offering solutions for diagnostics, chronic disease management, and logistics optimisation. AI technologies enhance patient care and improve healthcare logistics, proving invaluable in disaster scenarios. This special issue aims to explore innovative AI-based approaches to tackle the challenges faced by healthcare supply chains, especially in the context of recent disruptions like the COVID-19 pandemic, which exacerbated shortages of essential medicines and increased patient demand. We are inviting papers that focus on integrating AI methods to enhance the efficiency and effectiveness of healthcare supply chains. This Editorial summarises these studies, emphasising possibilities for future research pathways.},
pages = {395-403},
volume = {63},
issue = {2},
journal = {International Journal of Production Research},
publisher = {Taylor and Francis},
url = {https://doi.org/10.1080/00207543.2024.2444150},
}
