IoT platforms assessment methodology for COVID-19 vaccine logistics and transportation: a multi-methods decision making model
Author | Ali, Yasir |
Author | Khan, Habib Ullah |
Available date | 2024-06-27T07:18:25Z |
Publication Date | 2023 |
Publication Name | Scientific Reports |
Resource | Scopus |
Identifier | http://dx.doi.org/10.1038/s41598-023-44966-y |
ISSN | 20452322 |
Abstract | The supply chain management (SCM) of COVID-19 vaccine is the most daunting task for logistics and supply managers due to temperature sensitivity and complex logistics process. Therefore, several technologies have been applied but the complexity of COVID-19 vaccine makes the Internet of Things (IoT) a strong use case due to its multiple features support like excursion notification, data sharing, connectivity management, secure shipping, real-time tracking and monitoring etc. All these features can only feasible through choosing and deploying the right IoT platform. However, selection of right IoT platform is also a major concern due to lack of experience and technical knowledge of supply chain managers and diversified landscape of IoT platforms. Therefore, we introduce a decision making model for evaluation and decision making of IoT platforms that fits for logistics and transportation (L&T) process of COVID-19 vaccine. This study initially identifies the major challenges addressed during the SCM of COVID-19 vaccine and then provides reasonable solution by presenting the assessment model for selection of rational IoT platform. The proposed model applies hybrid Multi Criteria Decision Making (MCDM) approach for evaluation. It also adopts Estimation-Talk-Estimation (ETE) approach for response collection during the survey. As, this is first kind of model so the proposed model is validated and tested by conducting a survey with experts. The results of the proposed decision making model are also verified by Simple Additive Weighting (SAW) technique which indicates higher results accuracy and reliability of the proposed model. Similarly, the proposed model yields the best possible results and it can be judged by the precision, accuracy and recall values i.e. 93%, 93% and 94% respectively. The survey-based testing also suggests that this model can be adopted in practical scenarios to deal with complexities which may arise during the decision making of IoT platform for COVID-19 SCM process. |
Sponsor | This work is supported by Qatar National Library, Doha, Qatar and QU Grant No. 2021-010. |
Language | en |
Publisher | Nature Research |
Subject | SARS-CoV-2 vaccine coronavirus disease 2019 decision making human internet of things reproducibility COVID-19 COVID-19 Vaccines Decision Making Humans Internet of Things Reproducibility of Results |
Type | Article |
Issue Number | 1 |
Volume Number | 13 |
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Accounting & Information Systems [536 items ]
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COVID-19 Research [838 items ]