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Investigation of carbon emissions due to COVID-19 vaccine inventory

Author

Listed:
  • Nita H. Shah

    (Gujarat University)

  • Ekta Patel

    (Gujarat University)

  • Kavita Rabari

    (Gujarat University)

Abstract

Inventory model for vaccine of COVID-19 pandemic is the subject of analysis in the proposed article. The initial registration for vaccination and vaccination of registered individuals is taken during the period under consideration. The paper considers the utility of vaccine during storage, holding cost, purchase cost, manufacturing cost and inspection cost. A fraction of registered individuals who do not turn up for a vaccination is taken into account. All the actions by the player incur carbon emissions. During the whole procedure of vaccination starting from raw material to end user carbon emissions are observed. Carbon emissions in stocking raw material, during inspection, during purchase activity, during set-up and transportation phase and holding it at point of delivery. Maximum carbon emission of 28% occur during purchase activity followed by 21% during transportation at the point of delivery and stocking it at respective places. To follow green policy, carbon tax is levied. A non-linear formulation of the proposed problem is modelled to compute optimum cycle time without allowing shortages. The convexity of the objective function is established through the numerical data. Analysis of carbon emissions and carbon tax levied is carried out through the data. Research Objective: Carbon Emission is one of a cause for ozone layer depletion. Moreover, it causes many ecological disturbances resulting into several environmental temperature variations. These all problem affect an individual’s health. So, there arise a need to frame a mathematical model to decipher relationship between COVID-19 vaccine inventory and effect of carbon emissions.

Suggested Citation

  • Nita H. Shah & Ekta Patel & Kavita Rabari, 2022. "Investigation of carbon emissions due to COVID-19 vaccine inventory," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 409-420, February.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01285-7
    DOI: 10.1007/s13198-021-01285-7
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    References listed on IDEAS

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    1. Gao Xiang Lou & Hai Yang Xia & Jie Qiong Zhang & Ti Jun Fan, 2015. "Investment Strategy of Emission-Reduction Technology in a Supply Chain," Sustainability, MDPI, vol. 7(8), pages 1-25, August.
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    Cited by:

    1. Julian Vasilev & Tanka Milkova, 2022. "Optimisation Models for Inventory Management with Limited Number of Stock Items," Logistics, MDPI, vol. 6(3), pages 1-12, August.
    2. Yang, Cai & Zhang, Hongwei & Weng, Futian, 2024. "Effects of COVID-19 vaccination programs on EU carbon price forecasts: Evidence from explainable machine learning," International Review of Financial Analysis, Elsevier, vol. 91(C).

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