ArticleComputers & industrial engineering2023
Vaccine supply chain coordination using blockchain and artificial intelligence technologies.
Article in Computers & industrial engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A review of artificial intelligence in healthcare supply chains: untapped potential?BMC health services research · 2026Pooled it
- Literature review: Current trends and future prospects of digital vaccine supply chain support technology.Human vaccines & immunotherapeutics · 2025Pooled it
- Privacy-preserving vaccine supply chain management leveraging blockchain and self-sovereign identity.Scientific reports · 2026Article
- The adaptive large language models for vaccine prediction: A novel approach to vaccine demand prediction with engineered deviation prompts.PLOS digital health · 2026Article
- Management of drug supply chain information based on "artificial intelligence + vendor managed inventory" in China: perspective based on a case study.Frontiers in pharmacology · 2024Article
- System dynamics model for an agile pharmaceutical supply chain during COVID‑19 pandemic in Iran.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Currently, the global spread of COVID-19 is taking a heavy toll on the lives of the global population. There is an urgent need to improve and strengthen the coordination of vaccine supply chains in response to this severe pandemic. In this study, we consider a vaccine supply chain based on a combination of artificial intelligence and blockchain technologies and model the supply chain as a two-player dynamic game with inventory level as the dynamic equation of the system. The study focuses on the applicability and effectiveness of the two technologies in the vaccine supply chain and provides management insights. The impact of the application of the technologies on environmental performance is also considered in the model. We also examine factors such as the number of people vaccinated, positive and side effects of vaccines, vaccine decay rate, revenue-sharing/cost-sharing ratio, and commission ratio. The results are as follows: the correlation between the difficulty in obtaining certified vaccines and the profit of a vaccine manufacturer is not monotonous; the vaccine manufacturer is more sensitive to changes in the vaccine attenuation rate. The study's major conclusions are as follows: First, the vaccine supply chain should estimate the level of consumers' difficulty in obtaining a certified vaccine source and the magnitude of the production planning and demand forecasting error terms before adopting the two technologies. Second, the application of artificial intelligence (AI) technology is meaningful in the vaccine supply chain when the error terms satisfy a particular interval condition.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.