The Effect of Decision Maker Characteristics on Group Decision Making

1989 ◽  
pp. 134-142
Author(s):  
Lori S. Franz ◽  
Gary R. Reeves ◽  
Juan J. Gonzales
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision

FAIR CONSISTENCY EVALUATION FOR RECIPROCAL RELATIONS AND IN GROUP DECISION MAKING

2009 ◽  
Vol 05 (02) ◽  
pp. 407-420 ◽  
Author(s):  
MICHELE FEDRIZZI ◽  
MATTEO BRUNELLI
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Evaluation Method ◽  
Group Decision ◽  
Pairwise Comparison ◽  
Pairwise Comparisons ◽  
Reciprocal Relations ◽  
Decision Making Processes ◽  
Consistency Evaluation

In decision-making processes, it often occurs that the decision maker is asked to pairwise compare alternatives. His/her judgements over a set of pairs of alternatives can be collected into a matrix and some relevant properties, for instance, consistency, can be estimated. Consistency is a desirable property which implies that all the pairwise comparisons respect a principle of transitivity. So far, many indices have been proposed to estimate consistency. Nevertheless, in this paper we argue that most of these indices do not fairly evaluate this property. Then, we introduce a new consistency evaluation method and we propose to use it in group decision making problems in order to fairly weigh the decision maker's preferences according to their consistency. In our analysis, we consider two families of pairwise comparison matrices: additively reciprocal pairwise comparison matrices and multiplicatively reciprocal pairwise comparison matrices.

A Method of Multi-Attribute Group Decision-Making Based on LWD and LOWA Operator

2011 ◽  
Vol 58-60 ◽  
pp. 1130-1135
Author(s):  
Shi Jun Zhang ◽  
Yuan Cai
Keyword(s):  
Decision Making ◽  
Natural Language ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Language Assessment ◽  
New Method ◽  
Group Assessment ◽  
Linguistic Assessment ◽  
Linguistic Assessment Information

A new method was proposed to solve multi-attribute group decision-making problems with natural language assessment information. In this method, firstly the linguistic assessment information given by each decision maker was aggregated by LWD and LOWA operators in order to obtain the group assessment information. Then, the preferred scheme is obtained from the result of aggregation. Finally, a simulation example was given to illustrate the validity of this approach.

scholarly journals An extension of the codas method based on Interval Rough Numbers for multi-criteria group decision making

2021 ◽  
Vol 16 ◽  
pp. 23-43
Author(s):  
Mouna Regaieg Cherif ◽  
◽  
Hela Moalla Frikha ◽  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Sensitivity Analysis ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Multiple Criteria ◽  
Linguistic Terms

This study aims to develop a new Interval Rough COmbinative Distance-based Assessment (IR CODAS) method for handling multiple criteria group decision making problems using linguistic terms. A single decision maker is unable to express his opinions or preferences on multiple criteria decisions, while a Multi-Criteria Group Decision Making MCGDM process ensures successful outcomes when handling greater imprecision and vagueness information. A real-life case study of risk assessment is investigated using our proposed IR-CODAS method to test and validate its application; a sensitivity analysis is also performed. Keywords: Interval Rough Numbers, group decision making, IR-CODAS method, risk assessment.

scholarly journals PENENTUAN BOBOT KEPENTINGAN DECISION MAKER DALAM GROUP DECISION MAKING

2015 ◽  
Vol 4 (2) ◽  
Author(s):  
Dian Eko Hari Purnomo Dan Nur Aini Masruroh
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Research Result ◽  
Regression Method ◽  
Determination Method ◽  
Group Decisions ◽  
Consensus Criterion ◽  
High Competence

Generally, there are two criteria which are widely used to determineDM’s weight of interest, i.e. competenceand consensus. Various studies related to determine DM’s weight of interest based on competence or consensusseparately have been conducted. Each criterion has its own advantages. The advantage of using competence as acriterion is DMs who have high competence based on their consistence on the decisions made will have high of interest weight. Meanwhile, consensus criterion emphasizes a DM/s contribution to a group without consideringthe DM’s ability or competence.Considering the advantages of both criteria, this study developed a model to determine DM’s weight of interestby considering the DM’ competence and consensus in a GDM. This study used2 group decision making cases totaling in 6 groups consisting of 5 people each. Collected data was then processedusing DM’s weight of interest determination method based on competence and consensus. A model was thendesigned using regression method and fuzzy method. Therefore, a model to determine DM’s weight of interest was obtained by considering competence and consensus. DM’s weight of interest from each method was then involvedin group decision making. The research result showed that group decisions made by involving DM’s weight of interest were better decisions. It implies competence and consensus are two criteria which can be used to determineDM’s weight of interest.

Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments

2011 ◽  
Vol 1 (4) ◽  
pp. 47-61 ◽  
Author(s):  
Deng-Feng Li ◽  
Jiang-Xia Nan
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Implementation Process ◽  
Ideal Solution ◽  
Relative Closeness ◽  
Euclidean Distance Measure

This paper extends the technique for order preference by similarity to ideal solution (TOPSIS) for solving multi-attribute group decision making (MAGDM) problems under Atanassov intuitionistic fuzzy set (IFS) environments. In this methodology, weights of attributes and ratings of alternatives on attributes are extracted from fuzziness inherent in decision data and making process and described using Atanassov IFSs. An Euclidean distance measure is developed to calculate the differences between alternatives for each decision maker and an Atanassov IFS positive ideal solution (IFSPIS) as well as an Atanassov IFS negative ideal-solution (IFSNIS). Degrees of relative closeness to the Atanassov IFSPIS for all alternatives with respect to each decision maker in the group are calculated. Then all decision makers in the group may be regarded as “attributes” and a corresponding classical MADM problem is generated and hereby solved by the TOPSIS. The proposed methodology is validated and compared with other similar methods. A numerical example is examined to demonstrate the implementation process of the methodology proposed in this paper.

Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments

2013 ◽  
pp. 241-255
Author(s):  
Deng-Feng Li ◽  
Jiang-Xia Nan
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Ideal Solution ◽  
Euclidean Distance Measure ◽  
Order Preference ◽  
Negative Ideal Solution

This paper extends the technique for order preference by similarity to ideal solution (TOPSIS) for solving multi-attribute group decision making (MAGDM) problems under Atanassov intuitionistic fuzzy set (IFS) environments. In this methodology, weights of attributes and ratings of alternatives on attributes are extracted from fuzziness inherent in decision data and making process and described using Atanassov IFSs. An Euclidean distance measure is developed to calculate the differences between alternatives for each decision maker and an Atanassov IFS positive ideal solution (IFSPIS) as well as an Atanassov IFS negative ideal-solution (IFSNIS). Degrees of relative closeness to the Atanassov IFSPIS for all alternatives with respect to each decision maker in the group are calculated. Then all decision makers in the group may be regarded as “attributes” and a corresponding classical MADM problem is generated and hereby solved by the TOPSIS. The proposed methodology is validated and compared with other similar methods. A numerical example is examined to demonstrate the implementation process of the methodology proposed in this paper.

Doubly Extended Fuzzy TOPSIS Method for Group Decision Making

2019 ◽  
Vol 66 (1) ◽  
pp. 27-50
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Final Decision ◽  
Topsis Method ◽  
Decision Matrix

Multiple Criteria Decision Making methods, such as TOPSIS, have become very popular in recent years and are frequently applied to solve many real-life situations. However, the increasing complexity of the decision problems analysed makes it less feasible to consider all the relevant aspects of the problems by a single decision maker. As a result, many real-life problems are discussed by a group of decision makers. In such a group each decision maker can specialize in a different field and has his/her own unique characteristics, such as knowledge, skills, experience, personality, etc. This implies that each decision maker should have a different degree of influence on the final decision, i.e., the weights of decision makers should be different. The aim of this paper is to extend the fuzzy TOPSIS method to group decision making. The proposed approach uses TOPSIS twice. The first time it is used to determine the weights of decision makers which are then used to calculate the aggregated decision matrix for all the group decision matrices provided by the decision makers. Based on this aggregated matrix, the extended TOPSIS is used again, to rank the alternatives and to select the best one. A numerical example illustrates the proposed approach.

scholarly journals Influence Analysis in Consensus Search — A Multi Criteria Group Decision Making Approach in Environmental Management

2016 ◽  
Vol 15 (04) ◽  
pp. 791-813 ◽  
Author(s):  
Jorge Ivan Romero-Gelvez ◽  
Monica Garcia-Melon
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Similarity Measures ◽  
Decision Makers ◽  
Final Decision ◽  
Analytic Hierarchy ◽  
Decision Making Model ◽  
Environmental Decision

The environmental decision problems often are divisive, even in a technical realm, decision makers with strong personalities influence outcomes. The purpose of this study is to define and quantify the factors that affect the conservation objectives of a national natural park located in Colombia, South America adding the judgments of six decision makers with different knowledge (every decision maker is also a stakeholder representative). This paper uses a hybrid multiple criteria group decision-making model (MCDM), combining the social network analysis (SNA), analytic hierarchy process (AHP) and similarity measures to solve the consensus and anchoring problem among environmental decision makers. The SNA technique is used to build an influential network relation map among decision makers and to obtain their weights for applying a weighted AHP. Then, the final decision matrices for every decision maker are compared between them in order to identify the consensus level of the problem.

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