A consensus reaching process in the context of non-uniform ordered qualitative scales

José Luis García-Lapresta and David Pérez-Román ()
Additional contact information
David Pérez-Román: Universidad de Valladolid

Fuzzy Optimization and Decision Making, 2017, vol. 16, issue 4, No 4, 449-461

Abstract: Abstract In this paper, we consider that a group of agents judge a set of alternatives by means of an ordered qualitative scale. The scale is not assumed to be uniform, i.e., the psychological distance between adjacent linguistic terms is not necessarily always the same. In this setting, we propose how to measure the consensus in each subset of at least two agents over each subset of alternatives. We introduce a consensus reaching process where some agents may be invited to change their assessments over some alternatives in order to increase the consensus. All the steps are managed in a purely ordinal way through ordinal proximity measures.

Keywords: Group decision making; Consensus; Qualitative scales; Ordinal proximity measures (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10700-016-9256-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:fuzodm:v:16:y:2017:i:4:d:10.1007_s10700-016-9256-6

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10700

DOI: 10.1007/s10700-016-9256-6

Access Statistics for this article

Fuzzy Optimization and Decision Making is currently edited by Shu-Cherng Fang and Boading Liu

More articles in Fuzzy Optimization and Decision Making from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().