1. On dynamic consensus processes in group decision making problems
- Author
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Ignacio Javier Pérez, Yucheng Dong, Sergio Alonso, Francisco Chiclana, Francisco Javier Cabrerizo, and Enrique Herrera-Viedma
- Subjects
multi period decision making ,0209 industrial biotechnology ,Information Systems and Management ,Process modeling ,Operations research ,Computer science ,Process (engineering) ,media_common.quotation_subject ,02 engineering and technology ,Theoretical Computer Science ,Group decision making ,dynamic decision support systems ,consensus process ,020901 industrial engineering & automation ,Artificial Intelligence ,Order (exchange) ,0202 electrical engineering, electronic engineering, information engineering ,media_common ,Iterative and incremental development ,Deliberation ,Computer Science Applications ,Group decision-making ,Negotiation ,Systematic review ,Control and Systems Engineering ,020201 artificial intelligence & image processing ,adaptive consensus models ,Software - Abstract
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Consensus in group decision making requires discussion and deliberation between the group members with the aim to reach a decision that reflects the opinions of every group member in order for it to be acceptable by everyone. Traditionally, the consensus reaching problem is theoretically modelled as a multi stage negotiation process, i.e. an iterative process with a number of negotiation rounds, which ends when the consensus level achieved reaches a minimum required threshold value. In real world decision situations, both the consensus process environment and specific parameters of the theoretical model can change during the negotiation period. Consequently, there is a need for developing dynamic consensus process models to represent effectively and realistically the dynamic nature of the group decision making problem. Indeed, over the past few years, static consensus models have given way to new dynamic approaches in order to manage parameter variability or to adapt to environment changes. This paper presents a systematic literature review on the recent evolution of consensus reaching models under dynamic environments and critically analyse their advantages and limitations.
- Published
- 2018