Abstract: Recently, the world faces the economic challenges triggered by the shocks in the industrial sectors. The resilience of the industrial system after shocks, is a complex process. This work examine the role of dynamic patterns on industrial ecosystem resilience and collapse. Using the dynamic mode decomposition approach and the data of input-output for industrial transaction of OECD countries from 1995-2015 were simulated and the results unveiled. The empirical outcomes show that the amount of transaction between industrial sectors, dominant industries and transaction growth rate are the potential parameters that drive the system economy towards growth (resilience) or collapse, furthermore, the US followed by China is the most resilient country while South Africa, Brazil and Spain experience the least industrial ecosystem resilience. The study provides a good direction for policy making in industrial growth and economy as well.
Keywords: Industrial ecosystem resilience, economic collapse, Dynamic patterns, Dynamic Mode Decomposition.
Title: Dynamic patterns towards industrial ecosystem resilience and collapse: Dynamic Mode Decomposition Approach
Author: Sherehe Semba, Huijie Yang
International Journal of Social Science and Humanities Research
ISSN 2348-3156 (Print), ISSN 2348-3164 (online)
Vol. 11, Issue 3, July 2023 - September 2023
Page No: 109-118
Research Publish Journals
Website: www.researchpublish.com
Published Date: 12-August-2023
