Aggregating opinions in non-uniform ordered qualitative scales

García-Lapresta, José Luis; Pérez-Román, David

doi:10.1016/j.asoc.2017.05.064

Cited by 22 publications

(30 citation statements)

References 19 publications

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“…Given a proximity threshold δ ∈ ∆, 6 For instance, the one introduced by García-Lapresta and Pérez-Román [15] in the same setting. Once the new profile is obtained, the degrees of consensus are calculated and the process is re-initiated (see Fig.…”

Section: The Sequential Processmentioning

confidence: 99%

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

García-Lapresta

Pérez-Román

2016

Fuzzy Optim Decis Making

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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.

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Section: The Sequential Processmentioning

confidence: 99%

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

García-Lapresta

Pérez-Román

2016

Fuzzy Optim Decis Making

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“…implementing an appropriate voting system, such as the one introduced and analyzed in García-Lapresta and Pérez-Román [14]; etc.…”

Section: Discussionmentioning

confidence: 99%

Metrizable ordinal proximity measures and their aggregation

García-Lapresta

Pozo

Pérez-Román

2018

Information Sciences

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Ordered qualitative scales formed by linguistic terms are frequently used for evaluating sets of alternatives in different decision-making problems. These scales are usually implicitly considered as uniform in the sense that the psychological proximity between consecutive terms is perceived as identical. However, sometimes agents can perceive different proximities between the linguistic terms of the scale, and an appropriate method is required for aggregating these perceptions. In this paper we introduce the notion of metrizable ordinal proximity measure, discuss some aggregation procedures and propose a method based on metrics for aggregating experts' opinions on proximities between linguistic terms on ordered qualitative scales.

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“…These concepts were recently implemented in some decision-making procedures where alternatives are always assessed through the same OQS. García-Lapresta and Pérez-Román [34] introduce a voting system that ranks the alternatives taking into account the medians of the ordinal degrees of proximity between the obtained individual assessments and the highest linguistic term of the scale. Later, García-Lapresta and González del Pozo [35] presented an ordinal multi-criteria decision-making (MCDM) procedure under uncertainty, extending the previous procedure to a multi-criteria setting, in which agents are allowed to assign two consecutive terms of the OQS to each alternative when they hesitate.…”

Section: Introductionmentioning

confidence: 99%

Using Different Qualitative Scales in a Multi-Criteria Decision-Making Procedure

2020

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Many decision problems manage linguistic information assessed through several ordered qualitative scales. In these contexts, the main problem arising is how to aggregate this qualitative information. In this paper, we present a multi-criteria decision-making procedure that ranks a set of alternatives assessed by means of a specific ordered qualitative scale for each criterion. These ordered qualitative scales can be non-uniform and be formed by a different number of linguistic terms. The proposed procedure follows an ordinal approach by means of the notion of ordinal proximity measure that assigns an ordinal degree of proximity to each pair of linguistic terms of the qualitative scales. To manage the ordinal degree of proximity from different ordered qualitative scales, we provide a homogenization process. We also introduce a stochastic approach to assess the robustness of the conclusions.

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Aggregating opinions in non-uniform ordered qualitative scales

Cited by 22 publications

References 19 publications

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

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

Metrizable ordinal proximity measures and their aggregation

Using Different Qualitative Scales in a Multi-Criteria Decision-Making Procedure

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