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Managing the resource allocation for the COVID-19 pandemic in healthcare institutions: a pluralistic perspective

Manimuthu Arunmozhi (Nanyang Technological University, Singapore, Singapore)
Jinil Persis (Operations and Supply Chain Management Area, National Institute of Industrial Engineering (NITIE), Mumbai, India)
V. Raja Sreedharan (Rabat Business School, International University of Rabat, Sale, Morocco)
Ayon Chakraborty (School of Engineering, IT and Physical Sciences, Federation University, Ballarat, Australia)
Tarik Zouadi (Rabat Business School, International University of Rabat, Sale, Morocco)
Hanane Khamlichi (Faculty of Science and Technology of Tangier, Abdelmalek Essaadi University, Tanger, Morocco)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 5 November 2021

Issue publication date: 17 October 2022




As COVID-19 outbreak has created a global crisis, treating patients with minimum resources and traditional methods has become a hectic task. In this technological era, the rapid growth of coronavirus has affected the countries in lightspeed manner. Therefore, the present study proposes a model to analyse the resource allocation for the COVID-19 pandemic from a pluralistic perspective.


The present study has combined data analytics with the K-mean clustering and probability queueing theory (PQT) and analysed the evolution of COVID-19 all over the world from the data obtained from public repositories. By using K-mean clustering, partitioning of patients’ records along with their status of hospitalization can be mapped and clustered. After K-mean analysis, cluster functions are trained and modelled along with eigen vectors and eigen functions.


After successful iterative training, the model is programmed using R functions and given as input to Bayesian filter for predictive model analysis. Through the proposed model, disposal rate; PPE (personal protective equipment) utilization and recycle rate for different countries were calculated.

Research limitations/implications

Using probabilistic queueing theory and clustering, the study was able to predict the resource allocation for patients. Also, the study has tried to model the failure quotient ratio upon unsuccessful delivery rate in crisis condition.

Practical implications

The study has gathered epidemiological and clinical data from various government websites and research laboratories. Using these data, the study has identified the COVID-19 impact in various countries. Further, effective decision-making for resource allocation in pluralistic setting has being evaluated for the practitioner's reference.


Further, the proposed model is a two-stage approach for vulnerability mapping in a pandemic situation in a healthcare setting for resource allocation and utilization.



Arunmozhi, M., Persis, J., Sreedharan, V.R., Chakraborty, A., Zouadi, T. and Khamlichi, H. (2022), "Managing the resource allocation for the COVID-19 pandemic in healthcare institutions: a pluralistic perspective", International Journal of Quality & Reliability Management, Vol. 39 No. 9, pp. 2184-2204.



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