Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/50626
Full metadata record
DC FieldValueLanguage
dc.contributor.authorRuth Banomyongen_US
dc.contributor.authorApichat Sopadangen_US
dc.date.accessioned2018-09-04T04:43:06Z-
dc.date.available2018-09-04T04:43:06Z-
dc.date.issued2010-09-01en_US
dc.identifier.issn09600035en_US
dc.identifier.other2-s2.0-78349254935en_US
dc.identifier.other10.1108/09600031011079346en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78349254935&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/50626-
dc.description.abstractPurpose: 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.en_US
dc.subjectBusiness, Management and Accountingen_US
dc.subjectSocial Sciencesen_US
dc.titleUsing Monte Carlo simulation to refine emergency logistics response models: A case studyen_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of Physical Distribution and Logistics Managementen_US
article.volume40en_US
article.stream.affiliationsThammasat Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.