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International comparisons of COVID-19 pandemic management : what can be learned from activity analysis techniques?
Giménez, Víctor (Universitat Autònoma de Barcelona. Departament d'Empresa)
Prior Jiménez, Diego (Universitat Autònoma de Barcelona. Departament d'Empresa)
Thieme, Claudio (Universidad Diego Portales)
Emili, Tortosa-Ausina (Universitat Jaume I)

Publicación: Elsevier, 2023
Descripción: 41 pàg.
Resumen: The global spread of COVID-19 since early 2020 has resulted in significant humanitarian costs. The pandemic has affected most countries to varying degrees, and governments have implemented diverse policies to minimise the impact on public health. However, these policies have varied across regions and even within countries. This study proposes a nonparametric activity analysis methodology to assess how different countries have managed the pandemic. Specifically, we assess the effectiveness of 61 countries nine months into the pandemic using a robust directional Benefit of Doubt (BoD) model according to expert opinion and conditional on country contextual factors. We then estimate the marginal impact of structural and discretionary contextual variables on effectiveness using nonparametric regression analysis, which shows that effectiveness is strongly influenced by socioeconomic and cultural factors. The results reveal three main groups of countries according to their level of effectiveness in pandemic management, suggesting that an accurate assessment of countries' management of the pandemic benefits greatly from operations research methods, as we obtain benchmarks and find out how these benchmarks (or best practices) vary when contextual factors are included in the analysis.
Ayudas: Agència de Gestió d'Ajuts Universitaris i de Recerca 2021SGR00719
Ministerio de Ciencia e Innovación PID 2020-115450GB-I00
Nota: Altres ajuts: Universitat Jaume I (UJI-B2020-27)
Derechos: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Lengua: Anglès
Documento: Article ; recerca ; Versió acceptada per publicar
Materia: Data envelopment analysis ; COVID-19 ; Composite indicators ; Assurance region ; Robust conditional convex frontier models ; SDG 3 - Good Health and Well-being
Publicado en: Omega, The International Journal of Management Science, 122 (2024), ISSN 0305-0483

DOI: 10.1016/j.omega.2023.102966


Disponible a partir de: 2026-01-30
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