Collection and Pricing Decisions in a Closed-Loop Supply Chain for End-of-Life EV Batteries Under a Subjective Retirement Threshold and Dual Nash Bargaining

Existing studies on end-of-life EV battery collection mostly rely on engineering retirement thresholds, overlooking consumers’ subjective retirement behavior and potentially misestimating collection quantity and quality. We develop a dual Nash bargaining model for a closed-loop supply chain that accounts for consumers’ subjective retirement threshold, and analyze collection incentives, pricing, and echelon utilization decisions among a battery manufacturer, an EV manufacturer, and an echelon utilization product manufacturer under four organizational modes. The results show that a higher subjective retirement threshold increases the number of naturally retired batteries and the quality of collected batteries, while optimal collection incentives generally decline and eventually reach zero; bargaining power shapes operational decisions and firms’ cooperation choices by affecting echelon utilization returns, material recycling opportunity costs, and profit allocation within coalitions. The echelon coalition strengthens collection incentives and promotes echelon utilization, whereas the battery coalition must balance material recycling returns against the opportunity cost of echelon utilization; although the full supply chain coalition achieves the highest total supply chain profit, it does not necessarily maximize the EV manufacturer’s profit. These findings provide a basis for EV manufacturers to optimize collection incentives and select cooperation modes, helping promote coordinated development and resource circulation in closed-loop supply chains for end-of-life EV batteries.

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Publication Details

Journal
Systems
Published
2026-11-10
DOI
https://doi.org/10.3390/systems14111438
Primary Topic
Sustainable Supply Chain Management
Type
article
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article

Collection and Pricing Decisions in a Closed-Loop Supply Chain for End-of-Life EV Batteries Under a Subjective Retirement Threshold and Dual Nash Bargaining

Di Wu, 陈菊红, Liao Wenjing, Chenyu Ouyang et al.
Systems
Sustainable Supply Chain Management
article

Collection and Pricing Decisions in a Closed-Loop Supply Chain for End-of-Life EV Batteries Under a Subjective Retirement Threshold and Dual Nash Bargaining

Di Wu, 陈菊红, Liao Wenjing, Chenyu Ouyang, Chen Jiang, Hao Wang
article en

Abstract

Existing studies on end-of-life EV battery collection mostly rely on engineering retirement thresholds, overlooking consumers’ subjective retirement behavior and potentially misestimating collection quantity and quality. We develop a dual Nash bargaining model for a closed-loop supply chain that accounts for consumers’ subjective retirement threshold, and analyze collection incentives, pricing, and echelon utilization decisions among a battery manufacturer, an EV manufacturer, and an echelon utilization product manufacturer under four organizational modes. The results show that a higher subjective retirement threshold increases the number of naturally retired batteries and the quality of collected batteries, while optimal collection incentives generally decline and eventually reach zero; bargaining power shapes operational decisions and firms’ cooperation choices by affecting echelon utilization returns, material recycling opportunity costs, and profit allocation within coalitions. The echelon coalition strengthens collection incentives and promotes echelon utilization, whereas the battery coalition must balance material recycling returns against the opportunity cost of echelon utilization; although the full supply chain coalition achieves the highest total supply chain profit, it does not necessarily maximize the EV manufacturer’s profit. These findings provide a basis for EV manufacturers to optimize collection incentives and select cooperation modes, helping promote coordinated development and resource circulation in closed-loop supply chains for end-of-life EV batteries.

SystemsVol. 14(11)
Xi'an University of Technology (CN)
Sustainable Supply Chain Management
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