Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.ejor.2013.09.025
Title: Interpreting supply chain dynamics: A quasi-chaos perspective
Authors: Hwarng, H.B. 
Yuan, X.
Keywords: Chaos theory
Lyapunov exponent
Quasi-chaos
Supply chain management
System dynamics
Issue Date: 16-Mar-2014
Citation: Hwarng, H.B., Yuan, X. (2014-03-16). Interpreting supply chain dynamics: A quasi-chaos perspective. European Journal of Operational Research 233 (3) : 566-579. ScholarBank@NUS Repository. https://doi.org/10.1016/j.ejor.2013.09.025
Abstract: Chaotic phenomena, chaos amplification and other interesting nonlinear behaviors have been observed in supply chain systems. Chaos can be defined theoretically if the dynamics under study are produced only by deterministic factors. However, deterministic settings rarely present themselves in reality. In fact, real data are typically unknown. How can the chaos theory and its related methodology be applied in the real world When the demand is stochastic, the interpretation and distribution of the Lyapunov exponents derived from the effective inventory at different supply chain levels are not similar to those under deterministic demand settings. Are the observed dynamics of the effective inventory random, chaotic, or simply quasi-chaos In this study, we investigate a situation whereby the chaos analysis is applied to a time series as if its underlying structure, deterministic or stochastic, is unknown. The result shows clear distinction in chaos characterization between the two categories of demand process, deterministic vs. stochastic. It also highlights the complexity of the interplay between stochastic demand processes and nonlinear dynamics. Therefore, caution should be exercised in interpreting system dynamics when applying chaos analysis to a system of unknown underlying structure. By understanding this delicate interplay, decision makers have the better chance to tackle the problem correctly or more effectively at the demand end or the supply end. © 2013 Elsevier B.V. All rights reserved.
Source Title: European Journal of Operational Research
URI: http://scholarbank.nus.edu.sg/handle/10635/115779
ISSN: 03772217
DOI: 10.1016/j.ejor.2013.09.025
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