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

• Main Authors: Ruth Banomyong, Apichat Sopadang
• Format: Journal
• Published: 2018
• Subjects: Business, Management and Accounting; Social Sciences
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78349254935&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/50626
• Institution: Chiang Mai University

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.