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A robust data-driven maximum experts consensus modeling approach considering fairness concerns under uncertain contexts

jinpeng wei et al.

European Journal of Operational Research2026https://doi.org/10.1016/j.ejor.2026.01.009article
AJG 4ABDC A*
Weight
0.50

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https://doi.org/https://doi.org/10.1016/j.ejor.2026.01.009

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@article{jinpeng2026,
  title        = {{A robust data-driven maximum experts consensus modeling approach considering fairness concerns under uncertain contexts}},
  author       = {jinpeng wei et al.},
  journal      = {European Journal of Operational Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.ejor.2026.01.009},
}

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A robust data-driven maximum experts consensus modeling approach considering fairness concerns under uncertain contexts

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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

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