Heterogeneous Multi-attribute Large-Scale Group Decision-Making Considering Individual Concerns and Information Credibility

Kaixin Gong (), Weimin Ma (), Hui Zhang () and Mark Goh ()
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Kaixin Gong: Tongji University
Weimin Ma: Tongji University
Hui Zhang: Tongji University
Mark Goh: National University of Singapore

Group Decision and Negotiation, 2023, vol. 32, issue 6, No 3, 1315-1349

Abstract: Abstract Multi-attribute Large-Scale Group Decision-Making (MALSGDM) problems require a plethora of Decision Makers (DMs) with different knowledge structures to evaluate the decision alternatives with respect to the multiple attributes of the problem. To deal with the heterogeneous assessment information provided by the DMs with different concerns, this study develops a heterogeneous MALSGDM method considering individual concerns and information credibility. Under heterogeneous attribute concerns, an approach for fusing individual preference information is presented utilizing Dempster–Shafer theory. A method for determining the weights of each subgroup is given by combining the subgroup size and the credibility of the subgroup preference information. Next, a hybrid consensus measure is proposed to compute the consensus level of the heterogeneous preference information. A feedback mechanism based on the unit adjustment cost is then designed to promote consensus reaching. Finally, an analysis and discussion are performed to validate the value of this research.

Keywords: Multi-attribute large-scale group decision-making; Heterogeneous preference information; Individual concern; Information credibility; Consensus reaching (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10726-023-09845-x

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