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Challenges For Improving Consensus Reaching Process In Collective Decisions

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Author Info

  • L. MARTÍNEZ

    ()
    (Department of Computer Sciences, University of Jaén, 23071 - Jaén, Spain)

  • J. MONTERO

    ()
    (Faculty of Mathematics, Complutense University, 28040 - Madrid, Spain)

Abstract

The majority rule is frequently presented as a cornerstone of any democratic society, guiding many group decision-making processes where final decision requires the agreement of more than half the people involved. But sometimes, some key decisions require a higher level of agreement. In such cases, an added value would be to reach some consensus about the decision-making problem. Decision making under consensus drives to decisions which are better accepted and appreciated. But it also implies a greater complexity and time consuming process to reach a final decision, and it may even lead to a deadlock or unsuccessful results, whenever the searched agreement is not achieved. Meanwhile, these problems arise because the requirements to achieve the consensus are too strong, and different processes have softened their requirements. In particular, soft consensus is one of the most widespread consensus reaching processes that uses fuzzy logic to soften the consensus requirements. However, several problems still persist despite the softening of the requirements.In this paper, we are going to make a brief revision of the different concepts about consensus and about different consensus reaching processes, both in the crisp and fuzzy environment. We shall then analyze how to overcome their lacks, indicating the challenges facing these processes in order to obtain successful results in those group decision problems in which they are required to make a decision under consensus.

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Bibliographic Info

Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal New Mathematics and Natural Computation.

Volume (Year): 03 (2007)
Issue (Month): 02 ()
Pages: 203-217

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Handle: RePEc:wsi:nmncxx:v:03:y:2007:i:02:p:203-217

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Related research

Keywords: Group decision making; consensus; fuzzy sets;

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