Abstract
Data symmetry and asymmetry might cause difficulties in various areas including criteria weighting approaches. Preference elicitation is an integral part of the multicriteria decision-making process. Weighting approaches differ in terms of accuracy, ease of use, complexity, and theoretical foundations. When the opinions of the wider audience are needed, electronic surveys with the matrix questions consisting of the visual analogue scales (VAS) might be employed as the easily understandable data collection tool. The novel criteria weighting technique VASMA weighting (VAS Matrix for the criteria weighting) is presented in this paper. It respects the psychometric features of the VAS scales and analyzes the uncertainties caused by the survey-based preference elicitation. VASMA weighting integrates WASPAS-SVNS for the determination of the subjective weights and Shannon entropy for the calculation of the objective weights. Numerical example analyzing the importance of the criteria that affect parents’ decisions regarding the choice of the kindergarten institution was performed as the practical application. Comparison of the VASMA weighting and the direct rating (DR) methodologies was done. It revealed that VASMA weighting is able to overcome the main disadvantages of the DR technique—the high biases of the collected data and the low variation of the criteria weights.
Highlights
Criteria weighting is an integral part of the multicriteria decision making (MCDM) models, that are widely applied in economics [1], service quality [2], talent identification process [3], robotics [4], healthcare [5], social studies [6], and other areas
Due to the nature of the pairwise comparison, responses, where at least one criterion is not weighed, should be omitted. Such a data cleaning procedure drastically reduces the number of responses; it might be an important disadvantage of its exploitation for the survey-based criteria weighting
The uncertainty caused by the psychometric features of the visual analogue scales (VAS) scales is going to be reduced, employing the Weighted Aggregated Sum Product Assessment extended by single-valued neutrosophic sets (WASPAS-SVNS)
Summary
Criteria weighting is an integral part of the multicriteria decision making (MCDM) models, that are widely applied in economics [1], service quality [2], talent identification process [3], robotics [4], healthcare [5], social studies [6], and other areas. Differences in the preference elicitations methodologies, transparency of the evaluation process, diversity of the opinions, and the competence of the decision-makers (DM) are the important factors affecting the final values of the criteria weights [7]. People participating in the decision-making processes tend to have a different understanding of the problem addressed and to the factors associated with it. Symmetry 2020, 12, 1641 the public opinion might cause inaccuracies in the preference elicitation results and the repulsive reactions to the decisions based on them. In these circumstances, the increased interest in the criteria weighting approaches that respect opinions of the wider audience was recently observed
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