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Dong, Y., Zhang, G., Hong, W.-C., & Xu, Y. (2010). Consensus models for ahp group decision making under row geometric mean prioritization method. Decision Support Systems, 49, 281–289. 
Added by: Klaus D. Goepel (10 Jun 2019 23:19:16 Asia/Singapore)   
Resource type: Journal Article
DOI: 10.1016/j.dss.2010.03.003
BibTeX citation key: Dong2010
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Categories: AHP/ANP, Decision Making
Keywords: Analytic Hierarchy Process (AHP), consensus, geometric consistency index (GCI), group decision, group decision making, row geometric mean
Creators: Dong, Hong, Xu, Zhang
Publisher: Elsevier
Collection: Decision Support Systems
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The consistency measure is a vital basis for consensus models of group decision making using preference relations, and includes two subproblems: individual consistency measure and consensus measure. In the analytic hierarchy process (AHP), the decision makers express their preferences using judgement matrices (i.e., multiplicative preference relations). Also, the geometric consistency index is suggested to measure the individual consistency of judgement matrices, when using row geometric mean prioritization method (RGMM), one of the most extended AHP prioritization procedures. This paper further defines the consensus indexes to measure consensus degree among judgement matrices (or decision makers) for the AHP group decision making using RGMM. By using Chiclana et al.'s consensus framework, and by extending Xu and Wei's individual consistency improving method, we present two AHP consensus models under RGMM. Simulation experiments show that the proposed two consensus models can improve the consensus indexes of judgement matrices to help AHP decision makers reach consensus. Moreover, our proposal has two desired features: (1) in reaching consensus, the adjusted judgement matrix has a better individual consistency index (i.e., geometric consistency index) than the corresponding original judgement matrix; (2) this proposal satisfies the Pareto principle of social choice theory.
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