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Inventory pooling decisions under demand scenarios in times of COVID-19
Governments have been challenged to provide timely medical care to face the COVID-19 pandemic. The aim of this research is to propose a novel inventory pooling model to help determine order sizes and safety inventories in local hospital warehouses. The current study attempts to portray the availabil...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423939/ https://www.ncbi.nlm.nih.gov/pubmed/34511709 http://dx.doi.org/10.1016/j.cie.2021.107591 |
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author | Rojas, Fernando Wanke, Peter Bravo, Fernando Tan, Yong |
author_facet | Rojas, Fernando Wanke, Peter Bravo, Fernando Tan, Yong |
author_sort | Rojas, Fernando |
collection | PubMed |
description | Governments have been challenged to provide timely medical care to face the COVID-19 pandemic. The aim of this research is to propose a novel inventory pooling model to help determine order sizes and safety inventories in local hospital warehouses. The current study attempts to portray the availability of pharmaceutical items in public hospitals facing COVID-19 challenges. Different from previous studies, this research builds upon the consecrated theory of inventory pooling, extending it to pandemic circumstances where the intractability of kurtosis and skewness in inventory models are critical issues for making sure that medicines have high availability at a low cost. These effects on the total cost of inventory are explored and compared to a supply system with no consolidation. A continuous-review model is assumed with allocation rules for centralization and regular transshipment given different skewness and kurtosis structures for the demand, describing them by the copula method. This method models a multivariate demand considering that the marginal distributions of the demand can be specified by the Generalized Additive Model for Location, Scale and Shape, which offers advantages to model demands considering virtually any marginal statistical distribution. Numerical simulations and an illustrative example show that distributions of demands with more negative skewness and high kurtosis favor to a greater extent obtaining lower total costs with regular supply transshipment systems. Our study points out important considerations for supply chain decision makers when having demands with skewness and kurtosis patterns. |
format | Online Article Text |
id | pubmed-8423939 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84239392021-09-08 Inventory pooling decisions under demand scenarios in times of COVID-19 Rojas, Fernando Wanke, Peter Bravo, Fernando Tan, Yong Comput Ind Eng Article Governments have been challenged to provide timely medical care to face the COVID-19 pandemic. The aim of this research is to propose a novel inventory pooling model to help determine order sizes and safety inventories in local hospital warehouses. The current study attempts to portray the availability of pharmaceutical items in public hospitals facing COVID-19 challenges. Different from previous studies, this research builds upon the consecrated theory of inventory pooling, extending it to pandemic circumstances where the intractability of kurtosis and skewness in inventory models are critical issues for making sure that medicines have high availability at a low cost. These effects on the total cost of inventory are explored and compared to a supply system with no consolidation. A continuous-review model is assumed with allocation rules for centralization and regular transshipment given different skewness and kurtosis structures for the demand, describing them by the copula method. This method models a multivariate demand considering that the marginal distributions of the demand can be specified by the Generalized Additive Model for Location, Scale and Shape, which offers advantages to model demands considering virtually any marginal statistical distribution. Numerical simulations and an illustrative example show that distributions of demands with more negative skewness and high kurtosis favor to a greater extent obtaining lower total costs with regular supply transshipment systems. Our study points out important considerations for supply chain decision makers when having demands with skewness and kurtosis patterns. Elsevier Ltd. 2021-11 2021-08-09 /pmc/articles/PMC8423939/ /pubmed/34511709 http://dx.doi.org/10.1016/j.cie.2021.107591 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Rojas, Fernando Wanke, Peter Bravo, Fernando Tan, Yong Inventory pooling decisions under demand scenarios in times of COVID-19 |
title | Inventory pooling decisions under demand scenarios in times of COVID-19 |
title_full | Inventory pooling decisions under demand scenarios in times of COVID-19 |
title_fullStr | Inventory pooling decisions under demand scenarios in times of COVID-19 |
title_full_unstemmed | Inventory pooling decisions under demand scenarios in times of COVID-19 |
title_short | Inventory pooling decisions under demand scenarios in times of COVID-19 |
title_sort | inventory pooling decisions under demand scenarios in times of covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8423939/ https://www.ncbi.nlm.nih.gov/pubmed/34511709 http://dx.doi.org/10.1016/j.cie.2021.107591 |
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