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COVID-19 vaccine distribution: exploring strategic alternatives for the greater good

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  • Arben Asllani

    (University of Tennessee at Chattanooga)

  • Silvana Trimi

    (University of Nebraska-Lincoln)

Abstract

The dire state of the COVID-19 pandemic crisis symbolized the urgency for efficient distribution and administration of vaccines to combat the virus as the most urgent public health service. This paper presents a prototype multi-criteria decision support model based on goal programming that can effectively support vaccination plans for the greater good of society. The optimization goals of the model include minimizing the number of fatalities and risk of spreading the disease, while complying with government health agency’s priority guidelines for vaccination. This study applied the model to a real-world dataset to demonstrate how it can be effectively applied as a decision support tool for vaccine distribution plans and manage future pandemics.

Suggested Citation

  • Arben Asllani & Silvana Trimi, 2022. "COVID-19 vaccine distribution: exploring strategic alternatives for the greater good," Service Business, Springer;Pan-Pacific Business Association, vol. 16(3), pages 601-619, September.
    • Handle: RePEc:spr:svcbiz:v:16:y:2022:i:3:d:10.1007_s11628-022-00497-6
    DOI: 10.1007/s11628-022-00497-6
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    References listed on IDEAS

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    Cited by:

    1. Chengyu Liu & Yan Li & Mingjie Fang & Feng Liu, 2023. "Using machine learning to explore the determinants of service satisfaction with online healthcare platforms during the COVID-19 pandemic," Service Business, Springer;Pan-Pacific Business Association, vol. 17(2), pages 449-476, June.

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