Abstract for: Analyzing the Frequency Characteristics of Supply Chain Dynamics: An Application of Wavelet Spectral Analysis

Evaluating the frequency characteristics of system dynamics supply chain models is essential for understanding oscillatory phenomena, such as the bullwhip effect; however, conventional eigenvalue-based methods are technically demanding and difficult to apply in practice. This study addresses this challenge by introducing an accessible analytical framework that integrates wavelet spectral (WLS) analysis with frequency response (FR) analysis to characterize oscillatory and nonstationary dynamics. This study enhances traditional system dynamics analytical tools, specifically eigenvalue analysis and FR methods, by incorporating them with WLS analysis. When applied to a semiconductor supply chain model, this enhanced framework broadens conventional capabilities for characterizing oscillatory behavior and nonstationary frequency dynamics. It offers a more rigorous and accessible approach for evaluating the temporal structure of supply chain fluctuations. The application of the proposed methodology to the semiconductor supply chain model demonstrates that the WLS analysis can effectively clarify the fundamental and harmonic oscillatory modes identified through eigenvalue analysis and uncover nonstationary frequency variations. These findings indicate that the integrated WLS–FR framework offers a more comprehensive understanding of dynamic behavior than does eigenvalue analysis alone. The results are consistent with expectations, as the WLS analysis elucidated the oscillatory modes identified by the eigenvalue analysis and uncovered nonstationary frequency dynamics. These findings affirm the utility of integrating WLS with FR analysis. Further extensions, particularly the application of WLS to feedback-loop variables, would offer deeper insights into fluctuation propagation and complex supply-chain behavior.