An alternative calculation of the consensus degree in group decision making problems

In a problem of group decision-making it is desirable to obtain a solution with the highest possible degree of agreement – consensus- among the participants. For this aim, it is necessary to have tools that facilitate the calculation of the degree of consensus in a reliable way. This study proposes a consensus index based on a statistical measure of variability of the preferences expressed by the experts in a group decision-making process and performs a specific comparative study between this index and several known consensus measures. The analysis shows that in this specific situation the proposed measure behaves in a similar way to the previous ones and it could play their role in a process of decision making in group.European Commission TIN2016-75850-

Information Technology and Quantitative Management (ITQM 2017): An alternative calculation of the consensus degree in group decision making problems

In a problem of group decision-making it is desirable to obtain a solution with the highest possible degree of agreement – consensus- among the participants. For this aim, it is necessary to have tools that facilitate the calculation of the degree of consensus in a reliable way. This study proposes a consensus index based on a statistical measure of variability of the preferences expressed by the experts in a group decision-making process and performs a specific comparative study between this index and several known consensus measures. The analysis shows that in this specific situation the proposed measure behaves in a similar way to the previous ones and it could play their role in a process of decision making in group.The authors would like to acknowledge FEDER financial support from the Project TIN2016-75850-R

A Variance-Based Consensus Degree in Group Decision Making Problems

The variance is a well-known statistical measure and is frequently used for the calculation of variability. This concept can be used to obtain the degree of agreement in groups that have to make decisions. In this study, we propose the use of a variance derivative as an alternative for the calculation of the degree of consensus for Group Decision Making problems with fuzzy preference relations. As revealed by a subsequent comparative study, the values obtained by this new method are comparable to the values obtained by means of frequently used methods that employ distance functions and aggregation operators, while it turns out to be a simpler application method

A variance-based consensus degree in group decision making problems

The variance is a well-known statistical measure and is frequently used for the calculation of variability. This concept can be used to obtain the degree of agreement in groups that have to make decisions. In this study, we propose the use of a variance derivative as an alternative for the calculation of the degree of consensus for Group Decision Making problems with fuzzy preference relations. As revealed by a subsequent comparative study, the values obtained by this new method are comparable to the values obtained by means of frequently used methods that employ distance functions and aggregation operators, while it turns out to be a simpler application method

A comparative analysis between two statistical deviation–based consensus measures in group decision making problems

The mean absolute deviation and the standard deviation, two statistical measures commonly used in quantifying variability, may become an interesting tool when defining consensus measures. Two consensus indexes which obtain the level of consensus in some problems of Group Decision Making are introduced in this paper by expanding the aforementioned statistical concepts. A comparative analysis reveals that the levels of consensus derived from these indexes are close to those obtained employing distance functions when a fuzzy preference relations frame is considered, so they turn out to be a useful tool in this context. In addition, these indexes are different from each other and with the distance functions considered. Thus, they are applicable tools in the calculation of consensus in our context and are different from those commonly used

Algorithms to Detect and Rectify Multiplicative and Ordinal Inconsistencies of Fuzzy Preference Relations

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.Consistency, multiplicative and ordinal, of fuzzy preference relations (FPRs) is investigated. The geometric consistency index (GCI) approximated thresholds are extended to measure the degree of consistency for an FPR. For inconsistent FPRs, two algorithms are devised (1) to find the multiplicative inconsistent elements, and (2) to detect the ordinal inconsistent elements. An integrated algorithm is proposed to improve simultaneously the ordinal and multiplicative consistencies. Some examples, comparative analysis, and simulation experiments are provided to demonstrate the effectiveness of the proposed methods

An approach for estimating measurement uncertainty in medical laboratories using data from long-term quality control and external quality assessment schemes

The present study was prompted by the ISO 15189 requirements that medical laboratories should estimate measurement uncertainty (MU)

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered