Using Monte Carlo simulation to refine emergency logistics response models: A case study

Purpose: The purpose of this paper is to provide a framework for the development of emergency logistics response models. The proposition of a conceptual framework is in itself not sufficient and simulation models are further needed in order to help emergency logistics decision makers in refining the...

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Main Authors: Banomyong R., Sopadang A.
Format: Journal
Published: 2017
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78349254935&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43238
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-432382017-09-28T06:52:41Z Using Monte Carlo simulation to refine emergency logistics response models: A case study Banomyong R. Sopadang A. Purpose: The purpose of this paper is to provide a framework for the development of emergency logistics response models. The proposition of a conceptual framework is in itself not sufficient and simulation models are further needed in order to help emergency logistics decision makers in refining their preparedness planning process. Design/methodology/approach: The paper presents a framework proposition with illustrative case study. Findings: The use of simulation modelling can help enhance the reliability and validity of developed emergency response model. Research limitations/implications: The emergency response model outcomes are still based on simulated outputs and would still need to be validated in a real-life environment. Proposing a new or revised emergency logistics response model is not sufficient. Developed logistics response models need to be further validated and simulation modelling can help enhance validity. Practical implications: Emergency logistics decision makers can make better informed decisions based on simulation model output and can further refine their decision-making capability. Originality/value: The paper posits the contribution of simulation modelling as part of the framework for developing and refining emergency logistics response. © Emerald Group Publishing Limited. 2017-09-28T06:52:41Z 2017-09-28T06:52:41Z 2010-09-01 Journal 09600035 2-s2.0-78349254935 10.1108/09600031011079346 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78349254935&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/43238
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description Purpose: The purpose of this paper is to provide a framework for the development of emergency logistics response models. The proposition of a conceptual framework is in itself not sufficient and simulation models are further needed in order to help emergency logistics decision makers in refining their preparedness planning process. Design/methodology/approach: The paper presents a framework proposition with illustrative case study. Findings: The use of simulation modelling can help enhance the reliability and validity of developed emergency response model. Research limitations/implications: The emergency response model outcomes are still based on simulated outputs and would still need to be validated in a real-life environment. Proposing a new or revised emergency logistics response model is not sufficient. Developed logistics response models need to be further validated and simulation modelling can help enhance validity. Practical implications: Emergency logistics decision makers can make better informed decisions based on simulation model output and can further refine their decision-making capability. Originality/value: The paper posits the contribution of simulation modelling as part of the framework for developing and refining emergency logistics response. © Emerald Group Publishing Limited.
format Journal
author Banomyong R.
Sopadang A.
spellingShingle Banomyong R.
Sopadang A.
Using Monte Carlo simulation to refine emergency logistics response models: A case study
author_facet Banomyong R.
Sopadang A.
author_sort Banomyong R.
title Using Monte Carlo simulation to refine emergency logistics response models: A case study
title_short Using Monte Carlo simulation to refine emergency logistics response models: A case study
title_full Using Monte Carlo simulation to refine emergency logistics response models: A case study
title_fullStr Using Monte Carlo simulation to refine emergency logistics response models: A case study
title_full_unstemmed Using Monte Carlo simulation to refine emergency logistics response models: A case study
title_sort using monte carlo simulation to refine emergency logistics response models: a case study
publishDate 2017
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78349254935&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/43238
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