Service efficiency assessment of end-of-life lithium-ion battery recycling centers based on a fuzzy preference correction model

Zhongwei Cheng et al.

Energy and Environment2026https://doi.org/10.1177/0958305x261428676article
ABDC C
Weight
0.50

What the paper says

The end-of-life (EoL) lithium-ion batteries exhibit a dual nature, functioning simultaneously as hazardous waste and as a high-value second resource. In response, this study develops a scientifically grounded evaluation framework to assess the service efficiency of EoL lithium-ion battery Recycling Centers. To address cognitive and behavioral biases in expert judgment, a fuzzy preference correction model based on Prospect Theory is introduced, accounting for irrational psychological tendencies and limited perspectives during information aggregation. Additionally, to manage incomplete knowledge of criterion weights and interdependencies within complex decision environments, a two-stage optimization model is constructed. The framework is further enhanced through the incorporation of bounded rationality using a Fuzzy Analytic Hierarchy Process with group expert participation. The proposed system is validated through sensitivity and comparative analyses, demonstrating its robustness and practical applicability. Future research may further integrate human–machine expert systems to enhance reasoning capabilities and mitigate the cognitive limitations of human evaluators.

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https://doi.org/https://doi.org/10.1177/0958305x261428676

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@article{zhongwei2026,
  title        = {{Service efficiency assessment of end-of-life lithium-ion battery recycling centers based on a fuzzy preference correction model}},
  author       = {Zhongwei Cheng et al.},
  journal      = {Energy and Environment},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/0958305x261428676},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.