Clustering analysis and punishment‐driven consensus‐reaching process for probabilistic linguistic large‐group decision‐making with application to car‐sharing platform selection

2021 ◽  
Author(s):  
Su‐min Yu ◽  
Zhi‐jiao Du ◽  
Xue‐yang Zhang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Clustering Analysis ◽  
Group Decision ◽  
Car Sharing ◽  
Large Group ◽  
Consensus Reaching Process ◽  
Consensus Reaching

Adaptive consensus reaching process with hybrid strategies for large-scale group decision making

2020 ◽  
Vol 282 (3) ◽  
pp. 957-971 ◽  
Author(s):  
Ming Tang ◽  
Huchang Liao ◽  
Jiuping Xu ◽  
Dalia Streimikiene ◽  
Xiaosong Zheng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Large Scale ◽  
Group Decision ◽  
Consensus Reaching Process ◽  
Consensus Reaching

scholarly journals How to determine the consensus threshold in group decision making: a method based on efficiency benchmark using benefit and cost insight

2021 ◽  
Author(s):  
Xiangrui Chao ◽  
Yucheng Dong ◽  
Gang Kou ◽  
Yi Peng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Consensus Methods ◽  
Efficiency Measures ◽  
Degree Of Satisfaction ◽  
Consensus Reaching Process ◽  
The Cost ◽  
Consensus Reaching

AbstractIn the past 10 years, a large number of consensus-reaching approaches for group decision making (GDM) have been proposed. While these methods either focus on the cost of the consensus reaching or the convergency of the consensus process, the consensus efficiency has long been ignored. Meanwhile, the measurements of consensus threshold are often determined by some subjective and intuitive judgements, such as management experience and estimations for the degree of satisfaction, which lack a theoretical foundation. In management applications, how to measure consensus and how to evaluate a consensus reaching method are also ambiguous. To tackle these questions, we introduce efficiency measures into the consensus reaching process of GDM and achieve a comprehensive evaluation of current consensus methods through an efficiency analysis of consensus costs and consensus improvement. From the perspective of efficiency, we propose a benchmark in consensus reaching by data envelopment analysis without explicit input benchmark models, and then present an objective method for consensus threshold determination in GDM. Finally, we use numerical examples to illustrate the usability of our method.

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