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Knowledge management in turbulent times: time-based scenario analysis of vaccinations against COVID-19

Authors :
MENNINI F.S.
MAGNI M
DANIELE L
M
FAVATO G.
Mennini, F. S.
Magni, D.
Daniele, L. M.
Favato, G.
Magni, M
Daniele, L
M
Publication Year :
2021
Publisher :
EMERALD GROUP PUBLISHING LTD, 2021.

Abstract

Purpose This paper aims to estimate the delay or timely effects of the national vaccination strategy for COVID-19 on Italian gross domestic product (GDP). By adopting a knowledge management lens, the study highlights the importance of “time” for Italian recovery. Indeed, recovering an adequate growth rate is crucial for the future of employment, well-being and management of Italian public debt. Design/methodology/approach This study applies an epidemiological model of a universal access vaccination programme against COVID-19. The economic model is based on the time-shift of available quarterly projections deriving from the expected delay or acceleration of the national vaccination plan against COVID-19. Findings The basic concept underlying the scenario analysis is that the sustainability of the expected recovery of the Italian economy due to the COVID-19 shock, and consequently the growth of the GDP, is time-dependent on the rollout of the national vaccination plan. Research limitations/implications A delay in the vaccination campaign could have a twofold negative impact on the growth of the Italian gross product: it reduces the quarterly growth over the previous year in the short term and it delays the quarterly upwards trend over the next two years. Policymakers and practitioners are called to promptly face new dynamic scenarios due to public and economic policies to fight the COVID-19 crisis. Originality/value To the best of the authors’ knowledge, this is the first attempt of research that focuses attention on the synchrony between the economic time necessary for recovery and the real-time necessary to achieve vaccination coverage for the restart of production activities.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....1ac8a37b56415a25316eaf42c9f8f8a3