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<p>Multi-attribute group decision making (MAGDM) constitutes an important subfield of group decision-making. Most existing studies on MAGDM focus on consensus reaching without considering irrational psychology of decision-makers (DMs), particularly their inequality concern. Meanwhile, research on MAGDM from inequality concern remains rather limited. Motivated by this, we develop a novel fairness-oriented MAGDM approach to alleviate the concern of DMs. First, a weighting model for DMs is developed, which can reflect disparities of the information entropy and fairness concern utility among DMs. Secondly, during the consensus-reaching process, we propose a maximized group consensus model that incorporates fairness concern, which accounts for individual tolerance levels and the consensus principle. Thirdly, we design a fairness-oriented multiplicative data envelopment analysis cross-efficiency (FMDEA) model for selection, with the objective of identifying the optimal alternative. Finally, we apply the approach in a case study involving the upgrade of an electrical system for the highway tunnel, and employ comparative and sensitivity analyses to demonstrate the advantages of the proposed approach.</p>

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Maximum group utility consensus and fairness-oriented cross-efficiency in multi-attribute group decision-making with a focus on inequality concern

  • 期刊论文

  • 发表日期：

    2025年7月30日

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  • Jinpei Liu,
  • Wenqing Xu,
  • Longlong Shao,
  • Feifei Jin,
  • Jiangfeng Hao

摘要

Multi-attribute group decision making (MAGDM) constitutes an important subfield of group decision-making. Most existing studies on MAGDM focus on consensus reaching without considering irrational psychology of decision-makers (DMs), particularly their inequality concern. Meanwhile, research on MAGDM from inequality concern remains rather limited. Motivated by this, we develop a novel fairness-oriented MAGDM approach to alleviate the concern of DMs. First, a weighting model for DMs is developed, which can reflect disparities of the information entropy and fairness concern utility among DMs. Secondly, during the consensus-reaching process, we propose a maximized group consensus model that incorporates fairness concern, which accounts for individual tolerance levels and the consensus principle. Thirdly, we design a fairness-oriented multiplicative data envelopment analysis cross-efficiency (FMDEA) model for selection, with the objective of identifying the optimal alternative. Finally, we apply the approach in a case study involving the upgrade of an electrical system for the highway tunnel, and employ comparative and sensitivity analyses to demonstrate the advantages of the proposed approach.