Complexity analysis of a closed-loop supply chain for power battery recycling under government subsidies.

Considering government subsidies for new energy electric vehicle manufacturers, the study will construct a static game model to analyze the optimal strategies of decision-makers from the perspectives of manufacturers and retailers. It will analysis the impact of key model parameters such as governme...

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Bibliographic Details
Main Authors: Abudureheman Kadeer, Xiaobin Wang, Huanying He, Lei Dai
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0322888
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Summary:Considering government subsidies for new energy electric vehicle manufacturers, the study will construct a static game model to analyze the optimal strategies of decision-makers from the perspectives of manufacturers and retailers. It will analysis the impact of key model parameters such as government subsidy criteria, the fund returns rate and market size on optimal strategy selection. Additionally, a dynamic game model will be developed to investigate the complex behavior characteristics of decision-makers, as well as the influence of different behaviors on their complex benefits. The research results show: First, government subsidy criteria, the fund return rate and market size importantly influence the optimal pricing strategies and recycling services. Second, the stability region of the equilibrium strategy is given. Moreover, when the decision-makers 's price adjustment speed exceeds a certain threshold, the equilibrium strategy undergoes complex behaviors such as bifurcation and chaos. The time-delay feedback control method is adopted to regulate the chaos. Ultimately, based on the findings, a series of targeted management insights and recommendations are proposed, indicating that while short-term government subsidies can lead to increased profits for members, excessive subsidies in the long run can result in system chaos and profit decline.
ISSN:1932-6203