Large-scale group decision-making (LSGDM) is characterised by a large number of experts
and a complex consensus reaching process. Clustering is used to divide the large group …

This paper develops a new personalized individual semantic (PIS) based consensus
reaching process (CRP) for large-scale group decision making (LSGDM) with probabilistic …

In the consensus reaching process (CRP), experts are not infinitely compromising when
adjusting opinions, and the “compromise limit” is used to reflect the limited compromise …

As digitalization advances and societal patterns evolve, an increasing number of experts are
becoming integral to the decision-making process. The realm of large-scale group decision …

With the rapid development of information technology and social network, the large-scale
group decision-making (LSGDM) has become more and more popular due to the fact that …

Large-scale group decision making, which involves dozens to hundreds of experts, is
attracting increasing attention and has become an important topic in the field of decision …

Large-scale group decision-making (LSGDM) solution is usually based on the clustering
analysis process (CAP) and consensus reaching process (CRP). However, CAP and CRP …

Intelligent decision-making collaborates with big data analytics to navigate the intricate
landscape of the digital economy, orchestrating data-driven strategies to achieve the most …

Consensus reaching process (CRP) is very important for multi-criteria group decision
making (MCGDM). Recently, social network driven CRP methods have been deeply …

Many group decision making (GDM) models enable experts to use only one preference
information representation form. It is natural to allow experts to express preferences in …