Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

By Nicola Capuano, Francisco Chiclana, Hamido Fujita, Enrique Herrera-Viedma, Vincenzo Loia. IEEE transactions on fuzzy systems, 2018

296 citations recorded by the source corpus.

A promising research area in the field of group decision making (GDM) is the study of interpersonal influence and its impact on the evolution of experts’ opinions. In conventional GDM models, a group of experts express their individual preferences on a finite set of alternatives, then preferences are aggregated and the best alternative, satisfying the majority of experts, is selected. Nevertheless, in real situations, experts form their opinions in a complex interpersonal environment where preferences are liable to change due to social influence. In order to take into account the effects of social influence during the GDM process, we propose a new influence-guided GDM model based on the following assumptions: experts influence each other and the more an expert trusts in another expert, the more his opinion is influenced by that expert. The effects of social influence are especially relevant to cases when, due to domain complexity, limited expertise or pressure to make a decision, an expert is unable to express preferences on some alternatives, i.e., in presence of incomplete information. The proposed model adopts fuzzy rankings to collect both experts’ preferences on available alternatives and trust statements on other experts. Starting from collected information, possibly incomplete, the configuration and the strengths of interpersonal influences are evaluated and represented through a social influence network (SIN). The SIN, in its turn, is used to estimate missing preferences and evolve them by simulating the effects of experts’ interpersonal influence before aggregating them for the selection of the best alternative. The proposed model has been experimented with synthetic data to demonstrate the influence driven evolution of opinions and its convergence properties.

Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/6741a18af7c634aa7b0e1573931b134bcc5b2a93

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Citations in the corpus

A review on trust propagation and opinion dynamics in social networks and group decision making frameworks (2019, background): “On the other hand, trust has been considered as well an important factor to inﬂuence decision making and consensus reaching between multiple users in group decision making (GDM) scenarios [5,33,38,39,41] .”
A novel spherical fuzzy analytic hierarchy process and its renewable energy application (2019, methodology): “The models in this area can be classified as follows: the models dealing with incomplete information (Capuano et al. 2017), the models based on consensus measures (Cabrerizo et al. 2017), and the models based on heterogeneous preference relations (Liu et al. 2017a, b).”