Artificial Intelligence in Hospital Procurement: Advancing supply chain resilience and efficiency in Singapore
Ikechukwu Torti et al.
What the paper says
The COVID-19 pandemic exposed critical vulnerabilities in hospital supply chains across the Asia-Pacific region, emphasizing the need for more resilient and agile procurement systems. This study examines how artificial intelligence (AI) is being leveraged to optimize hospital procurement processes in Singapore, a country known for its advanced digital infrastructure and strong public health governance. Using a qualitative research approach based on secondary data, literature analysis, and relevant case studies, the paper explores the application of AI technologies such as predictive analytics, demand forecasting, and supplier risk assessment in Singapore’s healthcare procurement ecosystem. The findings reveal that AI integration has improved procurement responsiveness, minimized supply chain disruptions, and enhanced crisis preparedness. A conceptual model is proposed to illustrate how AI supports both operational efficiency and supply chain resilience within resource-optimized yet high-demand health systems. The study also identifies regulatory, workforce, and organizational challenges that influence the pace of AI adoption. The insights from this research offer practical guidance for policymakers, hospital administrators, and supply chain professionals seeking to strengthen procurement systems through AI-driven strategies in digitally mature healthcare environments.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.