A social network analysis trust-consensus based approach to group decision-making problems with interval-valued fuzzy reciprocal preference relations

By Jian Wu, Francisco Chiclana. Knowledge-Based Systems, 2014

312 citations recorded by the source corpus.

Subfields: Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/fc1328422e82c760e2a06558f279b22efec63d34

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In Management Science and Operations Research

Citations in the corpus

Trust based consensus model for social network in an incomplete linguistic information context (2015, methodology): “The interactive consensus model is regarded as an effective method to reach satisfactory consensus level because it implements a feedback mechanism to advice experts on how to change their preferences [5] [19] [23] [24] [53] [56] [63].”
A minimum adjustment cost feedback mechanism based consensus model for group decision making under social network with distributed linguistic trust (2018, methodology): “Consequently, a SNA based methodology could be used to model the concept of trust degree (TD) as well as to make possible its measurement to reflect the actual trust relationships between users in a group [11, 43, 45, 48].”
A visual interaction consensus model for social network group decision making with trust propagation (2017, background): “Therefore, they might wish to keep unaltered their independence [3, 7, 37, 40] or, if possible, to reduce changes cost [6, 8, 10, 11].”
Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence (2018, methodology): “Moreover, by asking experts to place themselves in the defined rankings, we avoid the complication of defining a numerical level representing the susceptibility of each expert to influence (like in [8]) or a numerical level representing interpersonal trust as in [11] and [12].”
Consensus Building for the Heterogeneous Large-Scale GDM With the Individual Concerns and Satisfactions (2018, unknown): “Based on the use of a soft consensus measure, a large number of CRPs have been reported, and they can be mainly classified in to the following types: 1) CRPs under different preference representation structures [5], [8], [16], [27], [31], [37], [50], [54], [56]; 2) CRPs with minimum adjustments or c”
Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors (2016, background): “Based on a “soft” consensus level, different types of CRPs have been proposed: (i) CRPs under different preference representation formats [10,13,15,17,28,35, 55]; (ii) CRPs with minimum adjustments or cost [5,6,12,16,22,23,66, 68,69]; (iii) CRPs based on consistency and consensus measures [18, 20,25”
Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination (2019, background): “Recent LSGDM literature has introduced approaches to studying how social relationships inﬂuence collective decision making processes [34, 35, 36].”
Consensus reaching in social network group decision making: Research paradigms and challenges (2018, methodology): “1 The framework of CRP paradigm based on trust relationships In recent years, the trust relationships among decision makers, described by a social network, are increasingly playing a key role in different phases of CRPs in the SNGDM problem: aggregation [9,75,80,82], incomplete preference values est”