Proceedings of the International Conference on Public Organization (ICONPO 2021)

Governmental Management of Big Data to Allocate COVID-19 Vaccines (Post COVID-19) to Make Public Policy in Thailand

Authors
Maneechatchavan Maneesri1, *
1Institute of Development Administration
*Corresponding author. Email: maneechatchavan_pook@hotmail.com
Corresponding Author
Maneechatchavan Maneesri
Available Online 1 March 2022.
DOI
https://doi.org/10.2991/aebmr.k.220209.017How to use a DOI?
Keywords
Management; Governmental Big Data; Policy-Making Process; COVID-19 Vaccines
Abstract

The study “Governmental Management of Big Data to Allocate COVID-19 vaccines (Post COVID-19) to Make Public Policy in Thailand” aims to reflect the important and interesting issue of allocation of vaccines post COVID-19 to Make Public Policy in Thailand. It presents the importance of Big Data, demanding data from the COVID-19 vaccines, management of COVID-19 vaccines, and the Public Policy process related to the allocation of the COVID-19 vaccines and suggestions.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Public Organization (ICONPO 2021)
Series
Advances in Economics, Business and Management Research
Publication Date
1 March 2022
ISBN
978-94-6239-544-2
ISSN
2352-5428
DOI
https://doi.org/10.2991/aebmr.k.220209.017How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Maneechatchavan Maneesri
PY  - 2022
DA  - 2022/03/01
TI  - Governmental Management of Big Data to Allocate COVID-19 Vaccines (Post COVID-19) to Make Public Policy in Thailand
BT  - Proceedings of the International Conference on Public Organization (ICONPO 2021)
PB  - Atlantis Press
SP  - 119
EP  - 125
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220209.017
DO  - https://doi.org/10.2991/aebmr.k.220209.017
ID  - Maneesri2022
ER  -