Developing a resilient healthcare supply chain to prevent disruption in the wake of emergency health crisis
International Journal of Emerging Markets
; 18(6):1307-1329, 2023.
Artigo
em Inglês
| ProQuest Central | ID: covidwho-20239590
ABSTRACT
PurposeThe study aims to identify and analyse the drivers of resilient healthcare supply chain (HCSC) preparedness in emergency health outbreaks to prevent disruption in healthcare services delivery in the context of India.Design/methodology/approachThe present study has opted for the grey clustering method to identify and analyse the drivers of resilient HCSC preparedness during health outbreaks into high, moderate and low important grey classes based on Grey-Delphi, analytic hierarchy process (AHP) and Shannon's information entropy (IE) theory.FindingsThe drivers of the resilient HCSC are scrutinised using the Grey-Delphi technique. By implementing AHP and Shannon's IE theory and depending upon structure, process and outcome measures of HCSC, eleven drivers of a resilient HCSC preparedness are clustered as highly important, three drivers into moderately important, and two drivers into a low important group.Originality/valueThe analysis and insights developed in the present study would help to plan and execute a viable, resilient emergency HCSC preparedness during the emergence of any health outbreak along with the stakeholders' coordination. The results of the study offer information, rationality, constructiveness, and universality that enable the wider application of AHP-IE/Grey clustering analysis to HCSC resilience in the wake of pandemics.
Business And Economics--International Commerce; The COVID-19 pandemic; Resilient healthcare supply chain (HCSC); Healthcare facilities (HCF); Grey clustering analysis; Analytic hierarchy process (AHP); Supply; Health care; Pandemics; Disruption; Drivers; Medical supplies; Clustering; Entropy; Coronaviruses; Resilience; Coordination; Rationality; COVID-19; China; India
Texto completo:
Disponível
Coleções:
Bases de dados de organismos internacionais
Base de dados:
ProQuest Central
Tipo de estudo:
Estudo prognóstico
Idioma:
Inglês
Revista:
International Journal of Emerging Markets
Ano de publicação:
2023
Tipo de documento:
Artigo
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